HUMAN EVOLUTION 30 OcTObEr - 1 NOVEMbEr 2019

ABST

RACT

BO

OK

1

Name:

Human Evolution 2019

Wellcome Genome Campus Conference Centre, Hinxton, Cambridge, UK

30 October – 1 November 2019

Scientific Programme Committee:

Marta Mirazon Lahr

University of Cambridge, UK

Lluis Quintana-Murci Institut Pasteur and Collège de France, France

Michael Westaway

The University of Queensland, Australia

Yali Xue

Wellcome Sanger Institute, UK

Tweet about it: #HumanEvol19

@ACSCevents /ACSCevents /c/WellcomeGenomeCampusCoursesandConferences

2

Wellcome Genome Campus Scientific Conferences Team:

Rebecca Twells

Head of Advanced Courses and

Scientific Conferences

Treasa Creavin

Scientific Programme

Manager

Nicole Schatlowski

Scientific Programme

Officer

Jemma Beard

Conference and Events

Organiser

Lucy Criddle

Conference and Events

Organiser

Sarah Heatherson

Conference and Events

Administrator

Zoey Willard

Conference and Events

Organiser

Laura Wyatt

Conference and Events

Manager

3

Dear colleague,

I would like to offer you a warm welcome to the Wellcome Genome Campus Advanced Courses and

Scientific Conferences: Human Evolution 2019. I hope you will find the talks interesting and

stimulating, and find opportunities for networking throughout the schedule.

The Wellcome Genome Campus Advanced Courses and Scientific Conferences programme is run on a

not-for-profit basis, heavily subsidised by the Wellcome Trust.

We organise around 50 events a year on the latest biomedical science for research, diagnostics and

therapeutic applications for human and animal health, with world-renowned scientists and clinicians

involved as scientific programme committees, speakers and instructors.

We offer a range of conferences and laboratory-, IT- and discussion-based courses, which enable the

dissemination of knowledge and discussion in an intimate setting. We also organise invitation-only

retreats for high-level discussion on emerging science, technologies and strategic direction for select

groups and policy makers. If you have any suggestions for events, please contact me at the email

address below.

The Wellcome Genome Campus Scientific Conferences team are here to help this meeting run

smoothly, and at least one member will be at the registration desk between sessions, so please do

come and ask us if you have any queries. We also appreciate your feedback and look forward to your

comments to continually improve the programme.

Best wishes,

Dr Rebecca Twells Head of Advanced Courses and Scientific Conferences rebecca.twells@wellcomegenomecampus.org

4

General Information

Conference Badges

Please wear your name badge at all times to promote networking and to assist staff in identifying you.

Scientific Session Protocol

Photography, audio or video recording of the scientific sessions, including poster session is not

permitted.

Social Media Policy

To encourage the open communication of science, we would like to support the use of social media at

this year’s conference. Please use the conference hashtag # HumanEvol19. You will be notified at the

start of a talk if a speaker does not wish their talk to be open. For posters, please check with the

presenter to obtain permission.

Internet Access

Wifi access instructions:

Join the ‘ConferenceGuest’ network

Enter your name and email address to register

Click ‘continue’ – this will provide a few minutes of wifi access and send an email to the

registered email address

Open the registration email, follow the link ‘click here’ and confirm the address is valid

Enjoy seven days’ free internet access!

Repeat these steps on up to 5 devices to link them to your registered email address

Presentations

Please provide an electronic copy of your talk to a member of the AV team who will be based in the

meeting room.

Poster Sessions

Posters will be displayed throughout the conference. Please display your poster in the Conference

Centre on arrival. There will be two poster sessions during the conference.

Odd number poster assignments will be presenting in poster session 1, which takes place on

Wednesday, 30 October 2019, at 18:00-19:30.

Even number poster assignments will be presenting in poster session 2, which takes place on

Thursday, 31 October 2019, at 18:00-19:30.

The page number of your abstract in the abstract book indicates your assigned poster board

number. An index of poster numbers appears in the back of this book.

Conference Meals and Social Events

Lunch and dinner will be served in the Hall, apart from on Wednesday, 30 October, lunch will be

served in the Conference Centre. Please refer to the conference programme in this book as times will

vary based on the daily scientific presentations. Please note there are no lunch or dinner facilities

available outside of the conference times.

All conference meals and social events are for registered delegates. Please inform the conference

organiser if you are unable to attend the conference dinner.

The Hall Bar (cash bar) will be open from 19:00 – 23:00 each day.

5

Dietary Requirements

If you have advised us of any dietary requirements, you will find a coloured dot on your badge.

Please make yourself known to the catering team and they will assist you with your meal request.

If you have a gluten or nut allergy, we are unable to guarantee the non-presence of gluten or nuts in

dishes, even if they are not used as a direct ingredient. This is due to gluten and nut ingredients being

used in the kitchen.

For Wellcome Genome Campus Conference Centre Guests

Check in If you are staying on site at the Wellcome Genome Campus Conference Centre, you may

check into your bedroom from 14:00. The Conference Centre reception is open 24 hours.

Breakfast Your breakfast will be served in the Hall restaurant from 07:30 – 09:00.

Telephone If you are staying on-site and would like to use the telephone in your room, you will need

to contact the Reception desk (Ext. 5000) to have your phone line activated – they will require your

credit card details to do so.

Departures You must vacate your room by 10:00 on the day of your departure. Please ask at

reception for assistance with luggage storage in the Conference Centre.

Taxis

Please find a list of local taxi numbers on our website. The conference centre reception will also be

happy to book a taxi on your behalf.

Return Ground Transport

Complimentary departure transport from the Conference Centre has been arranged on Friday, 1

November at the times shown below. Please allow a 30-40 minute journey time to both Cambridge

and Stansted Airport, and two and a half hours to Heathrow.

12:30 to Stansted and Heathrow airports.

12:45 to Cambridge train station and city centre (Downing Street).

A sign-up sheet will be available at the conference registration desk from 15:30 on Wednesday, 30

October. Places are limited so you are advised to book early.

Messages and Miscellaneous

Lockers are located outside the Conference Centre toilets and are free of charge.

All messages will be available for collection from the registration desk in the Conference Centre.

A variety of toiletry and stationery items are available for purchase at the Conference Centre

reception. Cards for our self-service laundry are also available.

Certificate of Attendance

A certificate of attendance can be provided. Please request one from the conference organiser

based at the registration desk.

Contact numbers

Wellcome Genome Campus Conference Centre – 01223 495000 (or Ext. 5000)

Wellcome Genome Campus Conference Organiser (Jemma) – 07771 666665

If you have any queries or comments, please do not hesitate to contact a member of staff who will

be pleased to help you.

6

Conference Summary

Wednesday, 30 October

11:30 – 12:45 Registration with Buffet Lunch

12:45 – 13:00 Welcome and Introduction

13:00 – 14:00 Keynote Lecture: Robert Foley

14:00 – 15:30 Session 1: Inferring human demography from genomic data

15:30 – 16:00 Afternoon Tea

16:00 – 17:30 Session 2: Ancient and modern genetic admixture

17:30 – 18:00 Lightning Talks

18:00 – 19:30 Poster Session 1 (odd numbers) with drinks reception

19:30 Buffet Dinner

Thursday, 31 October

09:00 – 10:30 Session 3: Searching for signals of local adaptation

10:30 – 11:00 Morning Coffee

11:00 – 12:30 Session 4: Insights from paleoanthropology

12:30 – 14:00 Lunch

14:00 – 15:30 Session 5: Insights from Chronology

15:30 – 16:00 Afternoon Tea

16:00 – 17:30 Session 6: Languages, culture and history

17:30 – 18:00 Lightning Talks

18:00 – 19:30 Poster Session 2 (even numbers) with drinks reception

19:30 Silver Service Conference Dinner

Friday, 1 November

09:00 – 10:30 Session 7: Human diversity and dispersals

10:30 – 11:00 Morning Coffee

11:00 – 12:00 Keynote Lecture: Chris Tyler-Smith

12:00 – 12:15 Closing Remarks

12:15 – 12:30 Lunch

12:30 Coach departs to London Heathrow airport via London Stansted airport

12:45 Coach departs to Cambridge train station and city centre (Downing Street)

7

Human Evolution 2019

Wellcome Genome Campus Conference Centre,

Hinxton, Cambridge

30 October – 1 November 2019

Lectures to be held in the Francis Crick Auditorium

Lunch and dinner to be held in the Hall Restaurant

Poster sessions to be held in the Conference Centre

Spoken presentations - If you are an invited speaker, or your abstract has been selected for a

spoken presentation, please give an electronic version of your talk to the AV technician.

Poster presentations – If your abstract has been selected for a poster, please display this in the

Conference Centre on arrival.

Conference programme

Wednesday, 30 October

11:30-12:45 Registration with lunch

12:45-13:00 Welcome and Introductions

Michael Westaway and Yali Xue

13:00-14:00 Keynote Lecture:

A change of climate: the impact of recent research on our understanding of

human evolution

Robert Foley

University of Cambridge, UK

14:00-15:30 Session 1: Inferring human demography from genomic data

Chair: Lluis Quintana-Murci

14:00 Walking backwards into the future: The evolution of Pacific genomes

and the implications for the health of Pacific peoples

Lisa Matisoo-Smith

University of Otago, New Zealand

14:30 Genomic Evolution and Adaptation in Africa

Sarah Tishkoff

University of Pennsylvania, USA

15:00 The genomic history of Near and Remote Oceania

Jeremy Choin

Institut Pasteur, France

8

15:15 Generation time differences among non-African human populations

inferred from sizes of introgressed archaic fragments and accumulation

and spectrum of new mutations

Moisès Coll Macià

BiRC, Aarhus University, Denmark

15:30-16:00 Afternoon Tea

16:00-17:30 Session 2: Ancient and modern genetic admixture

Chair: Yali Xue

16:00 Exploring admixture and ancestry using genome-wide DNA

Garret Hellenthal

University College London, UK

16:30 Ancient DNA and the evolution of complex traits

Iain Mathieson

University of Pennsylvania, USA

17:00 Recovering signals of ghost archaic introgression in African populations

Arun Durvasula

UCLA, USA

17:15 Reconstructing spatio-temporal patterns of admixture in human

history using present-day and ancient genomes

Manjusha Chintalapati

UC, Berkeley, USA

17:30-18:00 Lightning Talks

18:00-19:30 Poster Session 1 (odd numbers) with drinks reception

19:30 Buffet Dinner

19:30 Cash Bar

Thursday, 31 October

09:00-10:30 Session 3: Searching for signals of local adaptation

Chair: Lluis Quintana-Murci

09:00 Excavating archaic hominin DNA from the genomes of modern

humans

Joshua Akey

Lewis-Sigler Institute for Integrative Genomics, USA

09.30 Toward a genetic and molecular dissection of Tibetan adaptations to

hypoxia

Anna Di Rienzo

University of Chicago, USA

9

10:00 Investigating human-pathogen evolution using ancient genomics and

proteomics

Christiana Scheib

University of Tartu, Estonia

10:15 Direct Identification of Neanderthal Introgressed Genetic Variation

Affecting Gene Expression in Modern Human Immune Cell Lines

Evelyn Jagoda

Harvard University, USA

10:30-11:00 Morning Coffee

11:00-12:30 Session 4: Insights from paleoanthropology

Chair: Michael Westaway

11:00 Stasis and Innovation in the evolution of human and non-human

primate technology

Susana Carvalho

University of Oxford, UK

11:30 Hominin variability in the Middle to Late Pleistocene Asia. New fossils

and evolutionary interpretations

Maria Martinon Torres CENIEH, Spain

12:00 Human Evolution during the Middle Pleistocene in Eurasia

Chris Stringer

Natural History Museum, UK

12:15 The nature of Neanderthal introgression revealed by 27,566 Icelandic

genomes

Laurits Skov

Max Planck institute for evolutionary anthropology, Germany

12:30-14:00 Lunch

14:00-15:30 Session 5: Insights from Chronology

Chair: Marta Mirazon Lahr

14:00 Direct dating of human fossils and the ever changing story of human

evolution

Rainer Grün

Griffith University, Australia

14:30 Timing is everything;

Narrowing the gulf between the physical and genetic evidence for

human dispersal in Asia

Kira Westaway

Macquarie University, Australia

15:00 A 12,000-year Genetic History of Rome and the Italian Peninsula

Hannah Moots

Stanford University, USA

10

15:15 Sedimentary DNA Analysis from FAY-NE1 Jebel Faya, UAE

Simon Underdown

Oxford Brookes University, UK

15:30-16:00 Afternoon Tea

16:00-17:30 Session 6: Languages, culture and history

Chair: Michael Westaway

16:00 Layers of history and layers of evidence: genes, languages and complex

histories in the Pacific

Russell Gray

Max Planck Institute for the Science of Human History, Germany

16:30 What language tells is about a possible evolutionary trade-off between

olfaction and vision

Asifa Majid

The University of York, UK

17.00 Genomic structure of Siberians and the expansion of Altaic languages

Oleg Balanovsky

Vavilov Institute of Genetics, Russian Federation

17:15 The genetic landscape of North African human populations

David Comas

Universitat Pompeu Fabra, Spain

17:30-18:00 Lightning Talks

18:00-19:30 Poster Session 2 (even numbers) with drinks reception

19:30 Silver Service Conference Dinner

19:30 Cash Bar

Friday, 1 November

09:00-10:30 Session 7: Human diversity and dispersals

Chair: Marta Mirazon Lahr

09:00 The genetic history of Africa based on modern and ancient DNA

Carina Schlebusch

Uppsala University, Sweden

09:30 The Implications of New Discoveries in Southeast Asia and Sahul for

the Out of Africa Story

Chris Clarkson University of Queensland, Australia

11

10:00 Population Structure, Stratification and Introgression of Human

Structural Variation

Mohamed Almarri

Wellcome Sanger Institute, UK

10.15 Ancestry-related assortative mating and sex bias driven by social

stratification in admixing American populations

Alex Mas-Sandoval

Imperial College of London, UK

10:30-11:00 Morning Coffee

11:00-12:00 Keynote Lecture:

Human evolutionary studies: technical triumphs, current challenges and future

choices

Chris Tyler Smith

Wellcome Sanger Institute, UK

12:00-12:15 Closing Remarks

Marta Mirazon Lahr and Lluis Quintana-Murci

12:15-12:30 Lunch

12:30 Coaches depart to Stansted Airport via Heathrow Airport

12:45 Coaches depart to Cambridge City Centre and Train Station

12

These abstracts should not be cited in bibliographies. Materials contained herein

should be treated as personal communication and should be cited as such only

with consent of the author.

S1

Spoken Presentations

A change of climate: the impact of recent research on our understanding of human evolution Robert A Foley Leverhulme Centre for Human Evolutionary Studies, Department of Archaeology, University of Cambridge, UK It is now more than 30 years since the famous “Cann et al 1987” paper launched the ‘recent out of Africa model’ of modern human origins. Despite early criticism and prolonged controversy, the name and heart of the model has survived. We are all ‘out of Africanists’ now. But what exactly does the model represent in 2019? For most proponents, 'Out of Africa' in the 1980s and 1990s meant a recent origin of modern humans, probably in a small population, followed by rapid dispersal across the world and replacement of archaic hominins in Europe. It implied a sharp contrast in the nature and abilities of modern humans and creatures such as Neanderthals, and placed great emphasis on the origins of the Upper Palaeolithic as a signal of modernity. The ‘human revolution’, rather than human evolution. How much of this has stood the test of time, or more importantly, the test of new evidence? While much of that evidence has come from the rise of genomics, and the impact of ancient DNA technologies in particular, changes in chronology as well as new discoveries of fossils and archaeological remains have also played an important part. In this talk, I will explore what I now consider to be the most appropriate model of modern human origins. Four major changes have occurred that shape this exploration. First, all lines of evidence indicate a much more extended chronology for the totality of events and processes that have underlain the evolution of modern humans. Second, although the ‘end-product’ remains the unique survivorship of Homo sapiens, the evidence for demographic entanglement is now strong, as is the range of taxa with which our ancestral populations may have interacted. Third, rather than there being a single or limited horizon of change, the process is one of asynchrony across the different biological and behavioural domains. And fourth, the African and Eurasian climatic and environmental context in which these events all occurred is now much clearer. Is this a substantial change of the ‘out of Africa’ model? Or just a tinkering of the details? I will argue that the evidence accrued in the past two decades indeed requires a re-formulation of some of the basic principles and theory behind modern human origins.

S2

Notes

S3

Walking backwards into the future: The evolution of Pacific genomes and the implications for the health of Pacific peoples

Lisa Matisoo-Smith, Anna Gosling, Tony Merriman

University of Otago, New Zealand

The Pacific region is an ideal place for studying human evolution, variation and adaptation. It has a complex history of both ancient and recent human migrations, variable levels of population interactions and a range of potential source populations. There are an array of different physical environments and associated pathogen loads which may have shaped Pacific genomes. Pacific communities have distinct histories and impacts of European contact, including introductions of new infectious diseases and differing levels of population integration. Pacific peoples therefore likely adapted (both genetically and culturally) in unique ways. Despite these differences, some Pacific populations share a propensity for unusually high rates of metabolic disease - including type 2 diabetes, obesity, gout, heart and renal disease. We are undertaking the first Pacific-wide, inter-disciplinary study, applying an evolutionary approach to understand what factors shaped Pacific genomes contributing to the high rates of metabolic disease we see in Pacific peoples today.

S4

Notes

S5

Genomic Evolution and Adaptation in Africa Sarah A. Tishkoff Departments of Genetics and Biology, University of Pennsylvania, Philadelphia, PA, USA Africa is thought to be the ancestral homeland of all modern human populations. It is also a region of tremendous cultural, environmental and genetic diversity. Differences in diet, climate, and exposure to pathogens among ethnically and geographically diverse African populations have produced divergent selection pressures, resulting in local genetic adaptations, including some that play a role in disease susceptibility. A number of common complex diseases (including hypertension, diabetes, and chronic kidney disease) occur at higher frequency in people of African descent and are rapidly on the rise in urban regions of Africa. And yet, most human genomic studies have focused on non-African populations. The under-representation of ethnically diverse populations impedes our ability to fully understand the genetic and environmental factors influencing complex traits and may exacerbate health inequalities. A comprehensive knowledge of patterns of variation in African genomes is critical for a deeper understanding of human genomic diversity, the identification of functionally important genetic variation, the genetic basis of adaptation to diverse environments and diets, and the origins of modern humans. We use an integrative and functional genomics approach to characterize patterns of genomic variation, ancestry, and local adaptation across ethnically and geographically diverse African populations, leading to identification of novel genetic variants that play a role in immune response, metabolism, and skin pigmentation.

S6

Notes

S7

The genomic history of Near and Remote Oceania

Jeremy Choin1,2, Javier Mendoza-Revilla1, Lara R Arauna1, Christine Harmant1, Olivier Cassar3, Maximilian Larena4, Jean-François Deleuze5, Mattias Jakobsson4, Mark Stoneking6, Antoine Gessain3, Laurent Excoffier7, Etienne Patin1 & Lluis Quintana-Murci1,8

1.Human Evolutionary Genetics Unit, Institut Pasteur, UMR 2000, CNRS, Paris 75015, France 2.Université Paris Diderot, Sorbonne Paris Cité, Paris 75013, France 3.Unité d'Epidémiologie et Physiopathologie des Virus Oncogènes, Institut Pasteur, CNRS, UMR 3569, Paris 75015, France 4.Human Evolution, Department of Organismal Biology, Uppsala University, Uppsala 752 36, Sweden 5.Centre National de Recherche en Génomique Humaine (CNRGH), Institut de Biologie François Jacob, CEA, Université Paris-Saclay, Evry 91057, France 6.Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, Leipzig 04103, Germany 7.Institute of Ecology and Evolution, University of Bern, Bern 3012, Switzerland 8.Chair Human Genomics and Evolution, Collège de France, Paris 75005, France

Pacific islanders descend from two ancestral groups believed to originate from the early out-of-Africa migration and the late Austronesian expansion ~4,000 ya, i.e., the most recent human dispersal into empty territories. Furthermore, Oceanian genomes carry the highest degree of combined Neanderthal and Denisovan ancestry of all human groups. However, a detailed demographic model of the peopling history of Near and Remote Oceania and an unbiased assessment, based on whole genome sequences, of the levels of archaic introgression in the region, are missing. We thus generated high-coverage genomes for 317 individuals from Oceanian islands and archipelagos that represent different sources of genetic ancestry, including Taiwan, the Philippines, the Solomon Islands, Santa Cruz, Vanuatu as well as Polynesian outliers.

Using a composite likelihood method, we find that Near Oceanians diverged from Eurasians ~55,000 years ago (ya) and that the settlement of the region was accompanied by a founder event ~5x stronger than in Eurasia. We estimate deep divergence times among Near Oceanians in the Late Pleistocene (~20,000-40,000 ya), with Papuans separating first from peoples of the Bismarck Archipelago and the Solomon Islands. Our simulations also indicate that the Papuan ancestry of Remote Oceanians came from the Bismarck Archipelago ~3,500 ya, consistent with recent ancient DNA data. Furthermore, the Asian ancestry detected in Polynesian outliers appeared to have diverged from Taiwanese ~15,000-20,000 ya, questioning the origin of Polynesians and their relationship to the Austronesian expansion. Focusing on archaic introgression, while the levels of Neanderthal ancestry are relatively homogeneous across populations (~2.2 to 2.9%), those of Denisova ancestry vary markedly (0 to ~3.1%). Denisova ancestry is highly correlated with Papuan-like ancestry (r²~0.8), with the exception of the Agta hunter-gatherers from the Philippines. To identify high-confident archaic haplotypes, we next implemented a two-step process that uses the intersection of two statistics. These haplotype-based analyses confirm a signal of two distinct Denisova lineages in all populations presenting strong Papuan ancestry. Intringuingly, our results reveal that the majority of archaic segments detected in the Agta are exclusive to this population, suggesting the presence of an additional, yet unknown, Denisova lineage in Asia. Lastly, we find strong signals of adaptive introgression, particularly in genes impacting immune-related functions, indicating that archaic-inherited segments contributed to the adaptation of modern humans to the insular environments of the Pacific.

S8

Notes

S9

Generation time differences among non-African human populations inferred from sizes of introgressed archaic fragments and accumulation and spectrum of new mutations

Moisès Coll Macià1, Laurits Skov1&2, Benjamin Peter2, Mikkel Heide Schierup1

1. Bioinformatics Research Centre, Aarhus University, Denmark 2. MPI Evolutionary Anthropology, Leipzig, Germany

Recombination breaks down introgressed Neanderthal fragments into smaller and smaller

pieces. Therefore, the Neanderthal fragment length (NFL) distribution measures the time in

generations since the admixture event. Another measure of time can be derived from the

accumulation and spectrum of derived alleles in individual genomes. We investigate both

processes assessing non-African populations in the Simons Genome Diversity Project

(SGDP) dataset. We started comparing the NFL distribution and find that it notably differs

among non-Africans. East Asians, for instance, have longer NFL (mean = 82 kb, SE = 0.41

kb) than West Eurasians (mean = 73 kb, SE = 0.39 kb). This is also observed if only shared

fragments between the two populations (≈ 80% of all fragments) are compared. We show

that this pattern can be better explained by West Eurasians having shorter generation times

than East Asians than other demographic scenarios through simulations. Moreover, ancient

European-related samples (Lochbour, 8 kya; Stuttgart, 7 kya) have longer NFL than West

Europeans, but similar or shorter than East Asians. This implies that the difference in

generation time between these two populations must have been of 8-7 kya of recombination

(300 generations approx). Next, we analysed the number and spectrum of derived alleles

accumulated since the Out-of-Africa and outside regions with evidence of Neanderthal

admixture. East Asians show a reduced accumulation of derived alleles - thus, lower

mutation rate per year caused by longer generation times - (mean = 31083, SE = 82.2) than

West Eurasians (mean = 31425, SE = 62.9). Then, for each individual and each mutation

type (depending on the ancestral and derived allele nucleotides), we correlated the mutation

fraction with the mean NFL. Surprisingly, we obtained similar correlations to the de novo

mutation (DNM) spectrum correlations with parental age (Jónssons et al 2017). This

suggests that both NFL and allele mutation spectrum covary with generation time and that

historic generation times must have been different among non-African up to 20%.

Furthermore, we find that each population shifted the overall generation time changing the

paternal to maternal age ratio by comparing the sex specific mutation signatures such as

X/A ratio and C>G enrichment in cDNM. This differences in generation time and paternal-to-

maternal age-ratio might reflect cultural changes, probably by transitioning from a nomad to

sedentary lifestyle and food-source availability, during the last 60-50 kya of human evolution.

S10

Notes

S11

Exploring admixture and ancestry using genome-wide DNA Garret Hellenthal University College London, UK I describe statistical techniques to identify, describe and date genetic admixture events using genome-wide autosomal data. In particular the approaches exploit correlations among neighboring genetic markers (i.e. haplotype information) to increase precision over commonly-used software. I describe results from applying these haplotype-based methods to the genomes of present-day individuals sampled from multiple world-wide populations, as well as how to incorporate high-coverage DNA from ancient human remains. I highlight how genetics-based approaches can contribute new insights into human history by: (1) helping to resolve controversies in the literature based on findings from other disciplines, (2) inferring the genetic impact of well-attested historical events, and (3) unearthing previously unknown interactions among the ancestors of different groups. I illustrate how different types of analyses can be used to shed light on the processes that have led to genetic differences among peoples. I also discuss the current limitations of our approaches, providing examples where signals are unclear or inconclusive. Nonetheless, overall these findings point towards a large number of recent genetic links among geographically separated humans.

S12

Notes

S13

Ancient DNA and the evolution of complex traits Iain Mathieson University of Pennsylvania, USA In the 45,000 years that modern humans have been present in Europe, they have experienced–and adapted to–dramatic changes in environment and selective pressures. Ancient DNA allows us to directly observe the genetic changes associated with those adaptation. We use data from approximately 1200 ancient Europeans to investigate the landscape of natural selection over this time. We identify loci under recent positive selection associated with diet, skin pigmentation, and anthropometric traits. Looking more carefully at these loci, we show that patterns of adaptation are more complex than often assumed. In particular, loci that appear to be involved in adaptation to agriculture were not selected until long after the agricultural transition. Moving to more complex traits, we show that selection for light skin pigmentation–a classically adaptive trait– persisted for tens of thousands of years but that, overall, the frequencies of loci underlying skin pigmentation are actually driven as much by demographic history as well as selection. Finally, we show that polygenic predictions of anthropometric traits like height body proportions and bone morphology closely match phenotypes measured from ancient skeletons, and that deviations from these predictions likely indicate the effect of environment. Combining ancient DNA with anthropological and archaeological information, allows us to paint a much richer and complete picture of human evolution than by looking at any single aspect.

S14

Notes

S15

Recovering signals of ghost archaic introgression in African populations

Arun Durvasula, Sriram Sankararaman

Department of Human Genetics, University of California, Los Angeles, USA

While introgression from Neanderthals and Denisovans has been well-documented in

modern humans outside Africa, the contribution of archaic hominins to the genetic variation

of present-day Africans remains poorly understood. Using 405 whole-genome sequences

from four sub-Saharan African populations, we provide complementary lines of evidence for

introgression into these populations from an as-yet-uncharacterized archaic population. We

analyzed the conditional site frequency spectrum (CSFS), the site frequency spectrum in a

present-day African population conditioned on observing a derived allele in the Neanderthal.

This summary statistic is sensitive to ancestral structure and introgression, but is robust to

details of recent demographic history in both the African as well as the Neanderthal

populations. Population genetic theory predicts that the CSFS is expected to be uniform

under a model where the ancestors of Neanderthals and present-day Africans diverged with

no subsequent admixture. Instead, we observe a U-shaped CSFS in each of the sub-

Saharan African populations, suggestive of departures from panmixia in the history of these

populations. Technical artifacts like sequencing and genotyping errors as well as ancestral

state misidentification cannot explain the shape of the CSFS. Comprehensive simulations

indicate that current demographic models that relate archaic and present-day humans do not

explain the CSFS. Systematically exploring models of deep population structure as well as

archaic introgression in the history of African populations, we document that these

populations derive 2-19% of their genetic ancestry from an archaic population that diverged

prior to the split of Neanderthals and modern humans. Joint analyses of the CSFS in African

(Yoruba) and European (CEU) populations indicates that the archaic ancestry in African

populations is shared, in part, with out-of-African populations. Using a method that can

identify segments of archaic ancestry without the need for reference archaic genomes, we

built genome-wide maps of archaic ancestry in the Yoruba and the Mende populations that

recover about 482 and 502 Megabases of archaic sequence, respectively. Analyses of these

maps reveal segments of archaic ancestry at high frequency in these populations (33 loci in

the Yoruba and 37 in the Mende at a frequency >50%) that represent potential targets of

adaptive introgression. Our results reveal the substantial contribution of archaic ancestry in

shaping the gene pool of present-day African populations.

S16

Notes

S17

Reconstructing spatio-temporal patterns of admixture in human history using present-day and ancient genomes

Manjusha Chintalapati, Nick Patterson, Neel Alex, Priya Moorjani

Department of Molecular and Cell Biology, Center for Computational Biology, University of California, Berkeley, CA, USA Broad Institute of Harvard and MIT, Cambridge, MA, USA Department of Electrical Engineering and Computer Science, University of California, Berkeley, CA, USA Department of Molecular and Cell Biology, Center for Computational Biology, University of California, Berkeley, CA, USA

Recent studies have shown that gene flow or admixture has been pervasive throughout

human history and impacts most contemporary and ancient human populations.

Understanding the timing and signatures of admixture is important for studying the genomic,

evolutionary and functional impact of admixture, as well as uncovering the historical context

in which the mixture occurred. With the availability of a large number of present-day and

ancient genomes, it is now possible to characterize demographic changes and their timing

with unprecedented resolution. While a number of methods exist for characterizing

population mixture in contemporary populations, they are not applicable to sparse data

available from ancient DNA specimens (that have low coverage and large proportion of

missing variants). Here we introduce a new method, DATES (Distribution of Ancestry Tracts

of Evolutionary Signals) which leverages ancestry covariance patterns to infer mixture

proportions as well as timing of admixture, applicable to a single sample. By performing

simulations, we show that DATES provides reliable results under a range of scenarios,

including for cases when there is only a single admixed individual is available or samples

have low coverage or large amounts of missing data. To illustrate the method, we applied

DATES to reconstruct the timing of population admixture using published data with over

5,000 present-day and 2,000 ancient human genomes. This analysis helped to reconstruct

the timing of numerous admixture events in human history, including the spread of Arab

slave trade, the formation of the Western and Caucasus hunter-gatherers, expansion of

Neolithic farming and Indo-European languages to Europe and South Asia, and the

Australasian admixture into the Americans. These analyses highlight the ubiquity and

genetic legacy of population mixture in human history and prehistory and provide a fine-

grained map of human migrations over the past 10,000 years.

S18

Notes

S19

Excavating archaic hominin DNA from the genomes of modern humans Joshua Akey Lewis-Sigler Institute for Integrative Genomics, USA Genetic data has revealed that hybridization between anatomically modern humans and archaic hominins occurred multiple times and with multiple hominin lineages. We have developed a number of statistical methods to identify sequences inherited from archaic hominin ancestors that persist in the DNA of modern individuals, and applied it to whole-genome sequences from over 1,500 geographically diverse individuals. The catalog of surviving Neandertal and Denisovan sequences identified provides insight into admixture dynamics, selective pressures acting on introgressed sequences, and the functional and phenotypic consequences of hybridization. Moreover, new methodological advances reveal significantly more Neandertal ancestry among African individuals than previously appreciated. We show this observation has important implications for interpreting contemporary patterns of Neandertal sequences in both African and non-African populations. The continued excavation of archaic hominin lineages from the genomes of geographically diverse humans will clarify hominin evolutionary history and the genetic substrates of uniquely modern traits.

S20

Notes

S21

Toward a genetic and molecular dissection of Tibetan adaptations to hypoxia Anna Di Rienzo University of Chicago, USA Because the physiological impact of hypobaric hypoxia, indigenous high altitude populations provide a rare opportunity to observe human evolution in action and have emerged as an ideal system to study the genetic architecture of adaptive traits. These populations have phenotypes distinct from those of lowlanders at high altitude and from each other, such as the unelevated hemoglobin concentration in Tibetans. Strong selective sweep signals have previously been detected in Tibetans at the EGLN1 and EPAS1 loci, with alleles that are common in Tibetans but rare elsewhere being associated with lower Hb. We used data from physiological and fertility traits in Tibetans from Nepal in an attempt to characterize human adaptation for its whole set of components, i.e. selective pressure, adaptive traits, genetic background and realized fitness differential. To this end, we conduct GWAS of these traits and test for selective events that took place in the past using approaches that can detect selective sweeps and polygenic adaptations, as well as for ongoing events, through the direct approach of mapping measures of reproductive success. We replicated the strong selective sweep signals at EPAS1 and EGLN1, while finding surprisingly little evidence for polygenic adaptation toward lower Hb. We are now testing the hypothesis that the Tibetan EPAS1 haplotype has pleiotropic effects by altering the function of enhancers active in different tissues. The results of our work have implications with regard to the identity of the adaptive trait.

S22

Notes

S23

Investigating human-pathogen evolution using ancient genomics and proteomics

Christiana L. Scheib1, Meriam Guellil1, Richard Hagan, Marcel Keller1, Sarah A. Inskip, Craig Cessford3,, Ruoyun Hui3, Eugenia D’Atanasio, Jenna Dittmar3, Alice Rose3, Bram Mulder3, Piers Mitchell, Tamsin C. O’Connell6, Alexander Herbig, Mait Metspalu1, Johannes Krause7, Tina Warinner7,, Toomas Kivisild5, John E. Robb6

1 Institute of Genomics, University of Tartu, Tartu, Estonia; 2 Department of Archaeology, University of York, York, UK; 3 McDonald Institute for Archaeological Research, University of Cambridge, Cambridge, UK; 4 Cambridge Archaeological Unit, University of Cambridge, Cambridge, UK; 5 Department of Human Genetics, Katholieke Universiteit Leuven, Leuven, Belgium; 6 Department of Archaeology, University of Cambridge, Cambridge, UK; 7 Max Planck Institute for the Science of Human History, Jena, Germany; 8 Department of Anthropology, Harvard University, Cambridge, Massachusetts, USA

Communicable disease has likely been a selective pressure on human populations;

however, it is difficult to pinpoint exactly which diseases have had the greatest impact and

the magnitude of the selective force. A number of factors influence a person's susceptibility

to and manifestation of infectious disease including: inherited genes, diet, age, microbiome

composition, and the virulence of the pathogen itself. Teasing apart these factors is

especially difficult when there is missing data. In modern populations it is impossible and

highly unethical to recreate the experimental conditions necessary to test the impact of each

of these factors on survival rates and host-pathogen evolution. In archaeogenomic studies,

the focus is usually on the phylogeography of the people or the pathogen itself, though

recently a few studies have incorporated some functional and/or immune-gene analysis.

Ancient cemeteries and their skeletal remains can provide a much improved experimental

landscape, especially if they cover time periods of epidemic disease and thus have a general

population of both victims and survivors. By layering multiple bioanthropological and

geochemical techniques (aDNA, proteomics, lipids, isotopes, radiocarbon dating, histology,

morphology, and osteology) per individual on a population-scale, we can attempt to

reconstruct a "health landscape" for that population through time and test the relationship

between factors and manifestation of disease. For example: are dairy consumers more likely

to show tuberculosis lesions? Are plague victims more likely to be related? Does periodontal

disease predict susceptibility to viral infection?

I will present preliminary results and the workflow we established for the After the Plague

Project (Wellcome Trust) with our collaborators to develop new laboratory and bioinformatic

methods as well as novel applications of standard methods to analyse hundreds of ancient

individuals. We use shotgun genomic data to combine human demography, kinship,

phenotype prediction, oral microbiome diversity, and pathogen presence/strain analysis. We

incorporate a method for efficient co-extraction of proteins and DNA (endogenous and

exogenous) allowing us to study the diet, pathogen-specific proteins and immune response

to infection, whether chronic (e.g. periodontal disease) or acute (e.g. Plague). This

framework has allowed us to detect unexpected bacterial and viral infections and to start to

elucidate the complex interactions between diet, environment, hereditary traits and disease,

which have and continue to shape our evolution as a species.

S24

Notes

S25

Direct Identification of Neanderthal Introgressed Genetic Variation Affecting Gene Expression in Modern Human Immune Cell Lines

Evelyn Jagoda, Evelyn Jagoda, James Xue, Steven Reilly, Michael Dannemann, Fernando Racimo, Emilia Huerta-Sanchez, Sriram Sankararaman, Janet Kelso, Luca Pagani, Pardis Sabeti, Terence D. Capellini

Evelyn Jagoda: Department of Human Evolutionary Biology, Harvard University, Cambridge, Massachusetts 02138, USA; James Xue: Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA; Steven Reilly: Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA; Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; Michael Dannemann: Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology Leipzig, Germany; Fernando Racimo: Lundbeck GeoGenetics Centre, The Globe Institute, University of Copenhagen; Emilia Huerta-Sanchez: Department of Ecology and Evolutionary Biology and Center for Computational Molecular Biology, Brown University; Sriram Sankararaman: Department of Computer Science, Department of Human Genetics, UCLA; Janet Kelso: Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology Leipzig, Germany; Luca Pagani: Estonian Biocentre, Institute of Genomics, University of Tartu, Estonia; Department of Biology, University of Padova, Italy; Pardis Sabeti: FAS Center for Systems Biology, Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA; Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA; Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA 02120, USA; Howard Hughes Medical Institute, Chevy Chase, MD 20815, USA; Terence D. Capellini: Department of Human Evolutionary Biology, Harvard University, Cambridge, Massachusetts 02138, USA.

Since the sequencing of the first Neanderthal genome, revealing evidence for Neanderthal-

human interbreeding, researchers have wondered what, if any, adaptive impact introgression

may have had in the modern human gene pool. Studies have identified a few putative cases

of adaptive introgression (AI). However, broader functional characterization of AI regions

across the genome has been limited as most variants reside in largely uncharacterized non-

coding portions of the genome. This challenge is compounded by the fact that AI regions in

present-day genomes often span tens-to-hundreds of kilobases and consist of many linked

genetic variants, further obscuring discovery of the true driver variant(s) underlying each

positive selection signal. Identifying such driver variants in introgressed portions of the

genome is paramount to understanding the phenotypic and, potentially, adaptive

consequences of interbreeding with archaic hominins.

Adaptation through changes in gene expression may explain why positive selection targeted

non-coding AI variation. Because testing thousands of AI variants individually is time- and

cost-prohibitive, we used the Massively Parallel Reporter Assay (MPRA) system to

simultaneously test ~6,000 introgressed Neanderthal variants and their non-introgressed

orthologs for their ability to modulate gene expression. We selected Neanderthal AI variants

from geographically diverse human populations (1000 Genomes Project, the Simons

Diversity Project, and the Estonian Biocentre Human Genome Diversity Panel) and tested

them in two human immune cell lines. Out of all tested variants, ~5% significantly modulated

gene expression, and notably, these candidate adaptively introgressed variants were more

likely to be in regulatory regions than frequency- and location-matched controls. We further

investigated the set of candidate driver variants and found their activity to be functionally

enriched in certain immune pathways, particularly in the signaling pathways of certain

Interleukins. We are continuing to investigate the most promising of these potential driver

variants using other in vitro assays. Overall, this research identifies some of the most likely

driver variants of adaptive introgressed signals in the human immune system and illustrates

the ability of next generation laboratory methods to contribute to the study of human

adaptation from introgression.

S26

Notes

S27

Stasis and Innovation in the evolution of human and non-human primate technology Susana Carvalho University of Oxford, UK Abstract not available at the time of printing.

S28

Notes

S29

Hominin variability in the Middle to Late Pleistocene Asia. New fossils and evolutionary interpretations. María Martinón-Torres1,2

1CENIEH (National Research Center on Human Evolution), Burgos, Spain 2UCL Anthropology, London, UK Recent studies and new fossil findings reveal that the variability of the Asian hominin fossil record from the Middle to Late Pleistocene may have been oversimplified under the blanket term of H. erectus. The re-analysis of classic fossil samples like those from Zhoukoudian, Hexian and Yiyuan has allowed us to refine the morphological definition of classic H. erectus, warning that not all hominin populations found in Asia should be classified under this name (Xing et al., 2017). The identification of a “non-erectus” Middle Pleistocene group is parallel to the paleogenetic identification of a type of extinct hominin, distinct from Neanderthals and modern humans, that the scientific community has coined as “Denisovans” (Krause et al., 2019) and whose fossil record is limited to a few isolated teeth from the Denisova cave (Altai Mountains, Siberia) and a mandible from Xiahe (Tibet), the first Denisovan to be found outside the Denisova and identified by means of paleoproteomics analysis (Chen et al., 2019). In addition, growing evidence in favour of an earlier presence of H. sapiens outside the African continent is increasing the time of possible overlap among modern humans and other extinct hominins (Martinón-Torres et al., 2017). Here we present an overview of the hominin fossil record from the Middle to Late Pleistocene of Asia, particularly of hominin samples of unclear taxonomic assignment such as Xujiayao, Tongzi, Hualong, Panxian Dadong and Penghu and discuss their possible evolutionary interpretation in the light of Denisovans and H. sapiens presence in the Asian continent.

Chen, F., Welker, F., Shen, C.-C. , Bailey, S.E:, Bergmann, I. Davis, S., Xia, H., Wang, H. Fischer, R., Freidline, S.E., Yu, T.L., Skinner, M.M., Stelzer, S., Dong, G., Fu, Q., Dong, G., Wang, J. Zhang, D., Hublin, J.-J. 2019. A lte Middle Pleistocene Denisovan mandible from the Tibetan Plateau. Nature 569, 409-412. Krause, J., Qiaomei, F., Good, J.M., Viola, B., Shunkov, M., Derevianko, A., Pääbo, S. 2010. The complete mitochondrial DNA genome of an unknown hominin from southern Siberia. Nature, 464 894–97. Martinón-Torres, M., Wu, X., Bermúdez de Castro, J.M., Xing, S., Liu, W. 2017. Homo sapiens in the Eastern Asian Late Pleistocene. Current Anthropology 58, 434-448. Xing, S., Martinón-Torres, M. Bermúdez de Castro, J.M. 2018. The fossil teeth of the Peking Man. Scientific Reports 8. Xing, S., Martinón-Torres, M. Bermúdez de Castro, J.M. 2018. The fossil teeth of the Peking Man. Scientific Reports 8.

S30

Notes

S31

Human Evolution during the Middle Pleistocene in Eurasia

Chris Stringer

Natural History Museum, London, UK

I have recently changed my views on the nature of the last common ancestor of H. sapiens

and H. neanderthalensis, and I now think that ancestor had a facial morphology more like

that of H. antecessor (and H. sapiens) than the large individuals I assign to H.

heidelbergensis, such as Petralona and Broken Hill. In my view, who that ancestor was, and

when and where it lived are all currently unknown. By about 400 ka, material like Ceprano

(Italy), Aroeira (Portugal), and Balanica (Serbia) extends anatomical variation in middle

Pleistocene humans beyond that known at Swanscombe and Atapuerca-Sima, and

increases the apparent overlap of 'pre-Neanderthal' and Neanderthal-like morphologies in

Europe. From genetic data, the Denisovan lineage had also emerged by this time, but its

geographical extent around 400 ka cannot yet be mapped. Nevertheless, it probably

overlapped chronologically with late H. erectus populations in eastern Eurasia.

Towards the end of the Middle Pleistocene, it is now claimed from study of a partial skull

found in Apidima Cave (Greece) in 1978 that early modern humans were living there at least

210,000 years ago. If these analyses are correct, H. sapiens entered Europe over 150,000

years earlier than previous records suggested, raising a whole new range of questions and

possibilities, including where they came from, what happened to them, and what were their

interactions with early Neanderthal populations? If we have interpreted the Apidima evidence

correctly, behavioural evidence of these early H. sapiens must also be present in the

European record.

S32

Notes

S33

The nature of Neanderthal introgression revealed by 27,566 Icelandic genomes

Laurits Skov, Moisès Coll Macià 1, Garðar Sveinbjörnsson 2, Fabrizio Mafessoni 3, Elise A. Lucotte 1, Margret S. Einarsdóttir 2, Hakon Jonsson 2, Bjarni Halldorsson 2,6, Daniel F Gudbjartsson 2, Agnar Helgason 2,4, Mikkel Heide Schierup 1, Kari Stefansson 2,5

1 Bioinformatics Research Centre, Aarhus University, Dk-8000 Aarhus C., Denmark 2 deCODE genetics/Amgen Inc., 101 Reykjavik, Iceland 3 Max Planck Institute for Evolutionary Anthropology, Deutscher Pl. 6, 04103 Leipzig, Germany 4 Department of Anthropology, University of Iceland, 101 Reykjavik, Iceland 5 Faculty of Medicine, School of Health Sciences, University of Iceland, 101 Reykjavik, Iceland 6 School of Science and Engineering, Reykjavik University, 101 Reykjavik, Iceland

Human evolutionary history is rich with interbreeding of divergent populations. The impact of

one such event can still be seen in non-Africans, who trace about 2% of their genomes to

introgression from Neanderthals 50-60 thousand years ago. The impact of Neanderthals on

modern humans is of considerable interest. Here, we shed light on it using 14.4 million

putative archaic chromosome fragments detected in fully phased whole genome sequences

from 27,566 Icelanders. They correspond to a range of 56,388-111,616 unique archaic

fragments that cover 38.0-48.2% of the callable genome. Based on similarity with known

archaic genomes, we assign 84.5% of fragments an Altai or Vindija Neanderthal origin, 3.3%

a Denisovan origin and 12.2% an unknown origin. We propose that the introgressing archaic

group was closely related to the Vindija Neanderthal with an ancient contribution from

another archaic group distantly related to the Altaian Denisovans. A paired comparison of

archaic fragments with homologous non-archaic fragments revealed that while the overall

rate of mutation was similar in humans and Neanderthals during the 500 thousand years

their lineages were separate, there were differences in the relative frequencies of mutation

types - perhaps due to different generation intervals for males and females. Finally, we

assessed 271 phenotypes, report five associations driven by variants in archaic fragments

and show that the majority of previously reported associations are better explained by non-

archaic variants.

S34

Notes

S35

Direct dating of human fossils and the ever changing story of human evolution

Rainer Grün, Mathieu Duval

Australian Research Centre for Human Evolution, Griffith University, Nathan, Australia

The development of nearly non-destructive dating has given us access to many human

fossils. The results have contributed to some major revisions of the chronology of modern

human evolution. The dating of Irhoud pushed back the age of the earliest Homo sapiens to

around 300,000 years ago. Direct dating also demonstrated that anatomical associations, for

example for Homo floresiensis or Homo naledi, may lead to erroneous age assessments.

This presentation will give an overview of the results published in the last three years,

showing that the phylogenetic tree of humans has gained considerable complexity. It can be

expected that new discoveries in geographical areas that have not yet seen systematic

investigations will further contribute to the complex and exciting story of human evolution.

S36

Notes

S37

Timing is everything; Narrowing the gulf between the physical and genetic evidence for human dispersal in Asia Kira Westaway Department of Earth and Environmental Sciences, Macquarie University, Sydney, Australia Human dispersal across the globe is arguably one of the greatest accomplishments of our species and is paramount to understanding the human journey through time. We know that modern Homo sapiens travelled from Africa through Asia en route to Australia, but the timing and nature of these dispersals has been heavily contested; from the exit/s out of Africa, to the timing of arrival in Asia, Southeast Asia, island SEA and Australia. This uncertainty relates to the paucity of well-dated, secure physical evidence of these dispersals. Genetic studies using ancient DNA can also be used to reconstruct and date human dispersals. However, the variability in the genetic clock caused by calibration issues can create large uncertainties. Therefore, the lack of well-dated evidence and the genetic uncertainties means that the physical evidence found on the ground is often at odds with the genetic evidence, as seen in Australia (e.g., Clarkson et al 2017; Malaspinas et al., 2017). How do we narrow this apparent gulf? The paucity of secure physical evidence is often not related to a lack of evidence but rather a lack of confidence in the analysis. Issues such as; uncertain provenance; reliance on only one dating technique; poor association between the evidence and dating material; and uncertainty over identification have led to doubt and criticisms, and have prevented the evidence being incorporated into models of dispersal. How do we establish a solid foundation of reliable physical evidence to compare against the genetic evidence? In this talk, I will outline a minimum acceptable strategy for the analysis and presentation of human dispersal evidence, using highly developed sedimentary and fossil contexts that are securely dated, replicated and modelled. I will use examples from Lida Ajer cave in Sumatra and Tam Pa Ling Cave in northern Laos that have been used to securely establish modern human arrival in island and mainland Southeast Asia, and will touch on the application of this approach to new research in Java and Southern China.

S38

Notes

S39

A 12,000-year Genetic History of Rome and the Italian Peninsula

Hannah M. Moots, Margaret L. Antonio2, Ziyue Gao3,4, Michaela Lucci5, Francesca Candilio6,7, Susanna Sawyer8, Victoria Oberreiter8, Diego Calderon2, Katharina Devitofranceschi8, Rachael C. Aikens2, Serena Aneli9, Fulvio Bartoli10, Alessandro Bedini11, Olivia Cheronet8, Daniel J. Cotter3, Daniel M. Fernandes8,12, Gabriella Gasperetti13, Renata Grifoni14, Alessandro Guidi15, Francesco La Pastina7, Ersilia Loreti16, Daniele Manacorda17, Giuseppe Matullo9, Simona Morretta18, Alessia Nava5,19, Vincenzo Fiocchi Nicolai20, Federico Nomi15, Carlo Pavolini21, Massimo Pentiricci22, Philippe Pergola23, Marina Piranomonte24, Ryan Schmidt25, Giandomenico Spinola26, Alessandra Sperduti27,28, Mauro Rubini29,30, Luca Bondioli27, Alfredo Coppa7, Ron Pinhasi8, Jonathan K. Pritchard3,4,31

1 Stanford University, Department of Anthropology, Stanford, CA, USA. 2 Program in Biomedical Informatics, Stanford University, Stanford, CA, USA; 3 Howard Hughes Medical Institute, Stanford University, Stanford, CA, USA; 4 Department of Genetics, Stanford University, Stanford, CA, USA; 5 DANTE Laboratory for the study of Diet and Ancient Technology, Sapienza Università di Roma, Rome, Italy; 6 School of Archaeology, University College Dublin, Dublin, Ireland; 7 Dipartimento di Biologia Ambientale, Sapienza Università di Roma, Rome, Italy; 8 Department of Evolutionary Anthropology, University of Vienna, Vienna, Austria; 9 Dipartimento di Scienze Mediche, Università di Torino, Torino, Italy; 10 Dipartimento di Biologia, Università di Pisa, Pisa, Italy. 11 Ministero dei Beni e delle Attività Culturali (retired), Rome, Italy; 12 CIAS, Department of Life Sciences, University of Coimbra, Coimbra, Portugal; 13 Soprintendenza Archeologia, belle arti e paesaggio per le province di Sassari e Nuoro, Sassari, Italy; 14 Dipartimento di Civiltà e Forme del Sapere, Università di Pisa, Pisa, Italy. 15 Dipartimento di Studi Umanistici, Università degli Studi di Roma Tre, Rome, Italy; 16 Curatore Beni Culturali presso Comune di Roma, Rome, Italy; 17 Dipartimento di Archeologia, Università degli Studi di Roma Tre, Rome, Italy; 18 Soprintendenza Speciale Archeologia Belle Arti e Paesaggio di Roma, Rome, Italy; 19 Servizio di Bioarcheologia, Museo delle Civiltà, Rome, Italy; 20 Christian and Medieval Archaeology, University of Rome Tor Vergata, Rome, Italy; 21 Università della Tuscia, DISUCOM Dipartimento di Scienze Umanistiche, della Comunicazione e del Turismo, Viterbo, Italy; 22 Ufficio Coordinamento Progetti Speciali e intersettoriali, Rome Italy; 23 Aix-Marseille University, Marseille, France; 24 Soprintendenza speciale Archeologia Belle arti e paesaggio di Roma, Rome, Italy; 25 University College Dublin; 26 Musei Vaticani, Reparto Antichità Greche e Romane, Vatican City; 27 Servizio di Bioarcheologia, Museo delle Civiltà, Rome, Italy; 28 Università L’Orientale Napoli, Naples, Italy; 29 Dipartimento di Archeologia, Università di Foggia, Foggia, Italy; 30 SABAP-LAZ Ministero dei Beni e delle Attività Culturali, Rome, Italy; 31 Department of Biology, Stanford University, Stanford, CA, USA.

Ancient DNA has become a powerful tool for studying the human past. This talk highlights our

team's multidisciplinary approach to analyzing new genomic evidence from Rome and the Italian

Peninsula in the context of the extensive archaeological and historical record of the region. We

have built a time series of 127 ancient genomes that spans the last 12,000 years, from the Upper

Paleolithic to the present, allowing us to present a contextually-situated discussion of genomic

changes through time. This approach allows us to study changes ranging from population-level

ancestry shifts to individual traits of interest, such as those related to health and disease. We

observe two major prehistoric ancestry shifts, one at the Neolithic Transition with the introduction

of farming into Italy and the second coinciding with increased movement and admixture of people

across the Mediterranean following technological developments in seafaring and horse-drawn

transport in the Bronze Age and Iron Ages. By the time of the founding of Rome, the genetic

composition of the region began to approximate modern Mediterranean populations and to

exhibit high levels of ancestry diversity. We see evidence that as Rome grew from a small city to

an empire encompassing the entirety of the Mediterranean - or Mare Nostrum, 'our sea', as the

Romans called it - and beyond, the city became a mosaic of inhabitants from across the empire

and remained so even after the fragmentation of the Western Roman Empire. Furthermore, we

find that gene flow between Rome and surrounding regions closely mirrors Rome's geopolitical

interactions. I will explore these general trends and discuss case studies, such as the site of Isola

Sacra, the necropolis of Rome's primary trading port, in which contextualizing archaeological and

textual evidence have been instrumental in understanding the genetic structure of the Roman

population in our study.

S40

Notes

S41

Sedimentary DNA Analysis from FAY-NE1 Jebel Faya, UAE

Simon Underdown 1,2, Riaan F. Rifkin 1,2, Ash Parton 1, Adrian Parker 1, Kira Dahling 1, Christiana L. Scheib 3, Knut Bretzke 4

1 Human Origins and Palæo-Environments Research Group, Oxford Brookes University, UK 2 Centre for Microbial Ecology and Genomics, University of Pretoria, South Africa 3 Institute of Genomics, University of Tartu, Estonia 4 Department of Early Prehistory and Quaternary Ecology at the University of Tübingen, Germany

The Jebel Faya rock-shelter (FAY-NE1) is one of the most important archaeological sites in

Arabia and the oldest stratified site in Southeast Arabia, comprising a 5m deep sequence of

archaeological levels from the Palaeolithic to the Iron Age. The work of Armitage et al.

(2011) and Bretzke et al. (2013) indicate that FAY-NE1 occupation was linked to periods of

increased freshwater availability punctuated by a lack of occupation during dry periods.

Wetter periods were characterised by increased resource availability and biogeographical

connectivity with adjacent regions, however, little is known about the way in which plant and

animal communities responded to climatic changes. The application of sedimentary DNA

analysis, therefore, promises to dramatically increase our understanding of human

occupation of FAY-NE1 and Southern Arabia. Ancient sediments can yield aDNA from

eukaryotes, prokaryotes and viruses and as such, can provide a wide range of data about

human ecology and have the potential to greatly enhance our understanding of human-

environment interactions. Here we report on the first sedimentary ancient DNA analysis from

Jebel Faya.

The Neolithic levels comprise approximately 1m of sediment and are sealed from the

Palaeolithic layers by a dense sand layer. Neolithic occupation has been dated to 9,500 BP

and contains a rich archaeological assemblage, representing the first reoccupation of the

site following the 'Assemblage A' Palaeolithic layers, which are dated to c. 40 Kyr. In 2018

sediment samples were taken from the Neolithic levels of FAY-NE1. Two sets of samples

were collected for analysis: set one was taken from the Eastern section of Trench 4 and set

two was taken from the Southern section of Trench 37. Samples were collected horizontally

across the sections and control samples from the exposed surface of the shelter and

additional controls derived from the archaeological layers directly above and below the

targeted Neolithic levels. To minimise the risk of contamination by modern DNA a custom

developed sample contamination prevention protocol was followed during sampling

activities. Sediments were processed in the dedicated ancient DNA laboratory at the Institute

of Genomics at the University of Tartu following published protocols of Slon et al (2017) and

Rohland et al (2018) and shotgun sequenced. We find a segregation by microbial

communities between sample set one (Neolithic), set two (Palaeolithic) and the controls

along with evidence of the ancient presence of plants and animals, providing insight to the

past environment during human occupation of the site.

S42

Notes

S43

Layers of history and layers of evidence: genes, languages and complex histories in the Pacific Russell Gray Max Planck Institute for the Science of Human History, Germany The Austronesian languages of Vanuatu are notable for both their sheer number and their marked deviation from most other Oceanic languages. Their aberrant features include non-decimal numeral systems, rounded labial phonemes, dually articulated labial-velar phonemes, bilabial trills, dual exclusion of p and c phonemes, and serial verb constructions. Blust (2008) has argued that the presence of these linguistic features can only be explained by a wave of Papuan expansion into Remote Oceania that quickly followed the initial Austronesian “Lapita” expansion (around 3000 BP). In this paper I will outline how a combination of modern and ancient genomic data can be used to test Blust's hypothesis. I will present genome-wide data from 19 ancient and 27 contemporary ni-Vanuatu that demonstrate an almost complete replacement of Lapita-Austronesian by Papuan ancestry. Despite this massive demographic change, incoming Papuan languages did not replace Oceanic languages. Population replacement with language continuity is extremely rare – if not unprecedented – in human history. Our analyses show that rather than one large-scale event, the process was incremental and complex, comprising repeated migrations and sex-biased interactions with peoples from the Bismarck Archipelago.

S44

Notes

S45

What language tells is about a possible evolutionary trade-off between olfaction and vision Asifa Majid The University of York, UK It has been claimed that vision supplanted olfaction as humans became upright. Anatomical changes associated with the convergence of the orbits accompanying stereoscopic vision led to changes in olfactory physiology. Similarly, the genetic change that led to trichromatic colour vision was accompanied by many olfactory receptor genes becoming pseudogenes. Finally, there is a negative correlation between olfactory and visual brain structures. Taken together this suggests olfactory cognition may have been downgraded in favour of visual cognition. Evidence from language seems to support this scenario. People refer to vision far more frequently than olfaction—be it in academic texts or everyday conversation. There are also more terms for visual than for olfactory phenomena. And when tested under experimental conditions, even familiar odors are rarely named correctly by people. In sum, it seems as if humans really are microsomatic. I will present results from a range of resent cross-cultural studies that challenge this view. We find that there are communities with large lexicons for smell. There are even languages that have grammatical resources for smell—something previously thought impossible. Moreover, smell talk is more frequent in some cultures than in the west. In addition, under experimental conditions, some people (especially hunter-gatherer communities) can name smells as easily as visual phenomena. Taken together, these results question the wide-spread view that olfaction is unimportant for modern humans.

S46

Notes

S47

Genomic structure of Siberians and the expansion of Altaic languages

Oleg Balanovsky, Yuri Bogunov, Elena Lukyanova, Anna Dybo, Irina Alborova, Valery Zaporozhchenko, Anastasiya Agdzhoyan, Kharis Mustafin, Yali Xue, Chris Tyler-Smith, Elena Balanovska

Vavilov Institute for General Genetics, Moscow, Russia; Research Centre of Medical Genetics, Moscow, Russia; Biobank of North Eurasia, Moscow, Russia; Institute of linguistics, Moscow, Russia; Moscow Institute of Physics and Technology, Moscow, Russia; The Wellcome Sanger Institute, Hinxton, Cambridgeshire, UK

To study the genetic structure of the Siberian populations, we sampled 26 ethnic groups

from the region. Most of them speak Altaic languages, though there are also many other

language families - presumable more autochtonous and thus often called Paleo-Siberian.

We genotyped 700 samples by the Illumina genome-wide arrays and 2,000 samples by the

Y-chromosomal markers, including those we discovered by resequencing the pan-Asian

haplogroup C.

The dataset revealed that admixture clines between West and East Eurasians occupy most

of Siberia, while populations in the easternmost area have minimal or no West Eurasian

component. Within this area we found a tripartite genetic structure: cluster of populations

from Amur basin, East Siberian cluster, and Beringian cluster. The populations of these

clusters were deeply divergent from one another, with the average pairwise FST (0.04)

approaching differences between subcontinental gene pools of West Eurasia (e.g., between

Europeans and Indians).

This high interpopulation variation was coupled with the lowest (in Eurasia) intrapopulation

variation (heterozygosity) and resulted from a pronounced genetic drift in these scarcely

populated areas where the farming was never adopted.

Ancient DNA data demonstrated that the tripartite genetic structure was stable for at least

last five thousand years. Amur basin populations did not experience much genetic changes

when comparing with ancient DNA from the same region dated 7 ky BP. Similarly, modern

Beringian populations still keep the Paleo-Eskimo-related ancestry dated 5 ky BP. In

contrast, modelling the East Siberian cluster demanded an additional gene flow from inland

Siberia.

Thus, the overall genetic structure of Siberians reflects geography well, but purely correlates

with linguistics. This might be because this structure preceded the emergence of the local

language families, or because many populations recently switched to Altaic (Tungusic,

Turkic, and Mongolic) languages.

To investigate the genetic-linguistic correlations in more details, we updated the Swadesh

lists for the 114 languages and dialects and reconstructed the detailed tree of Altaic

languages. The particularly intensive branching occurred twice: in Manchuria 1,5 - 2 kyBP

(Tungusic languages) and around West Mongolia 1 - 1,5 ky BP (Turkic languages). The

detailed phylogeographic analysis of the haplogroup C, predominating in these populations,

revealed intensive branching of the phylogenetic tree in the same areas and periods. We

identified the rapid, recent, and simultaneous expansions of many branches within

haplogroup C, which coincided in time and space with the expansions of Tungusic and

Turkic languages.

S48

Notes

S49

The genetic landscape of North African human populations

David Comas

Institut de Biologia Evolutiva (CSIC-UPF), Departament de Ciències Experimentals i de la Salut, Universitat Pompeu Fabra, Barcelona, Spain

Despite being part of the African continent, the population history of North Africa has shown

its own demographic characteristics. The region has been populated since Paleolithic times

although posterior gene flow from West Eurasia and sub-Saharan Africa has been extensive.

There has been a vivid debate about the continuity of the first inhabitants in the region and

the extant groups of North Africa. The genetic composition of North Africans is an amalgam

of West Eurasian and sub-Saharan components, including an autochthonous component

found exclusively in North Africa. This admixture of components has been shown by the

analysis of classical genetic and uniparental markers, as well as recent genome-wide data.

Ancient genetic data and new complete genomes provide new insights into the population

history of the region, suggesting that there is genetic evidence of population continuity in

North Africans despite the major genetic replacement that took place during the Neolithic

and the minor influence of historical events such as the Arabization. No correlation between

major linguistic groups (Arabs and Berbers) and genetics is found in North Africa, but

gradients of ancestral components are found in the region, suggesting a heterogeneous

genetic landscape, which can be correlated with demographic events.

S50

Notes

S51

The genetic history of Africa based on modern and ancient DNA Carina M. Schlebusch Human Evolution, Department of Organismal Biology, Uppsala University, Sweden Genetics helped to establish Africa as the birthplace of anatomically modern humans. However, the history of human populations in Africa is complex and includes various demographic events that influenced patterns of genetic variation across the continent. Through genetic studies of modern-day, and most recently, ancient African genetic variation, it became evident that deep African history is captured by connections among African hunter-gatherers, and that the deepest population divergence date to around 300,000 years before present. Furthermore, it was shown that agriculture had a large influence on the distribution of current-day Africans. These later population movements disrupted pre-existing population distributions and complicate inferences regarding deep human history. With the increased availability of full genomic data from diverse sets of modern-day and prehistoric Africans we have more power to infer human demography and the next few years will be exciting for investigating our species deep genetic history, rooted in Africa.

S52

Notes

S53

The Implications of New Discoveries in Southeast Asia and Sahul for the Out of Africa Story Chris Clarkson University of Queensland, Australia The recent finding of human occupation in northern Australia by 65 ± 6 thousand years ago necessitates a fresh look at current models of modern human dispersals out of Africa. This includes the archaeological signature of dispersal, the question of behavioural complexity and flexibility, and the apparent complex distribution of modern humans and archaic hominin species, and their hybrid forms, across Eurasia, Southeast Asia and Sahul during MIS 5-3. The new finds at Madjedbebe indicate modern humans had reached Southeast Asia and Sahul by at least 65 ka, bringing a diverse and highly adaptive economy and technology with identifiable roots in the Middle Stone Age of Africa. This colonising technology underwent bottlenecks and incorporated new innovations as populations spread east, made frequent water crossings and entered new and unfamiliar habitats. The Sahul evidence indicates that the first colonists made use of prepared centripetal core technology, multicomponent hafted technologies such as the oldest known edge ground axes in the world, invasively flaked stone points, and a broad diet including use of some of the earliest known plant processing technologies outside of Africa. Evidence now also exists for the production of figurative art, burial of the dead, and personal adornment among the first colonists to reach Southeast Asia and Sahul. This record indicates that innovation and behavioural flexibility were key characteristics of early modern human groups in the region. The important implications of new finds across Southeast Asia and Sahul are explored here in terms of genetics, fossil evidence, early modern human technology and economy, behavioural adaptation to new regions, and more esoteric phenomena such as symbolic expression.

S54

Notes

S55

Population Structure, Stratification and Introgression of Human Structural Variation

Mohamed Almarri1, Anders Bergström1,2, Javier Prado-Martinez1, Alistair S. Dunham1,3, Yuan Chen1, Chris Tyler-Smith1, Yali Xue1

1. Wellcome Sanger Institute, Hinxton, CB10 1SA, UK 2. Francis Crick Institute, London, NW1 1AT, UK 3. EMBL-EBI, Hinxton, CB10 1SD, UK

Structural variants contribute substantially to genetic diversity and are important

evolutionarily and medically, yet are still understudied. Here, we present a comprehensive

analysis of deletions, duplications, inversions and non-reference unique insertions in the

Human Genome Diversity Project (HGDP-CEPH) panel, a high-coverage dataset of 910

samples from 54 diverse worldwide populations. We identify in total 61,801 structural

variants, of which 61% are novel. Some reach high frequency and are private to continental

groups or even individual populations, including a deletion in the maltase-glucoamylase

gene MGAM, involved in starch digestion, in the South American Karitiana and a deletion in

the Central African Mbuti in SIGLEC5, potentially increasing susceptibility to autoimmune

diseases. We discover a dynamic range of copy number expansions and find cases of

regionally-restricted runaway duplications, for example, 18 copies near the olfactory receptor

OR7D2 in East Asia and in the clinically-relevant HCAR2 in Central Asia. We identify highly-

stratified putatively introgressed variants from Neanderthals or Denisovans, some of which,

like a deletion within AQR in Papuans, are almost fixed in individual populations. Finally, by

de novo assembly of 25 genomes using linked-read sequencing we discover 1631

breakpoint-resolved unique insertions, in aggregate accounting for 1.9 Mb of sequence

absent from the GRCh38 reference. These insertions show population structure and some

reside in functional regions, illustrating the limitation of a single human reference and the

need for high-quality genomes from diverse populations to fully discover and understand

human genetic variation.

S56

Notes

S57

Ancestry-related assortative mating and sex bias driven by social stratification in admixing American populations

Alex Mas-Sandoval, Matteo Fumagalli

Department of Life Sciences, Imperial College London, Ascot, UK

Beyond geography, the cultural and socioeconomic framework of each society, such as the

stratification of the distribution of wealth and power, have historically shifted the human

mating pattern from random mating. Therefore, the genetic structure of human populations is

shaped by assortative mating. However, the effect of non-random mating within admixed

populations has been underestimated and disregarded in most population genetics studies.

In recently admixed populations, ancestry-related assortative mating and sex bias are the

main drivers that modulate their population structure. The European colonization of America

and the subsequent Atlantic slave trade gave rise to contemporaneous admixing societies

and complex urban population structures, where three main ancestral components are

admixed in different proportions: The Native American, the European and the sub-Saharan

African.

In this study, we aimed to analyze the footprint on the genome of changing mating patterns

in the admixing populations across the Americas, driven by the cultural and social contexts

at each time period. To solve these questions, we derive a mechanistic model of ancestry-

related assortative mating and sex bias and generate simulations of various complex

admixture scenarios. We then implement and train an artificial neural network to infer the

changing mating parameters since the admixture process began from genomic data of

admixing American populations.

Results point to a persistence of ancestry-related assortative mating in admixing American

populations through time. The admixture dates and the admixture source ratios might be

misinterpreted if assortative mating and sex bias are not carefully analyzed. We highlight the

need of a fine analysis of complex admixture events to be able to discern between

confounding scenarios. In addition, the accurate assessment of the demographic model is

key to allow the detection of genomic regions under selection.

Herein we present a novel computational strategy to address a pressing question at the

interface between anthropology and population genetics through a machine learning

approach. Our work stresses the importance of considering the cultural and socioeconomical

context for understanding the evolutionary processes that accompanied human populations

in their genetic history.

S58

Notes

S59

Human evolutionary studies: technical triumphs, current challenges and future choices Chris Tyler-Smith Wellcome Sanger Institute, UK My brief is to review the main turning points in the study and understanding of human evolutionary genetics, and provide some thoughts on the major questions that lie ahead. 2019 is a perfect time to do this, because 100 years ago Hirschfeld and Hirschfeld published their paper comparing blood group frequencies in different human populations, marking the beginning of human population genetics, while almost 200 years ago the Red Lady of Paviland was recognised as an ancient human skeleton suitable for scientific investigation. I will provide a personal choice of key advances in theory and data generation that have led to the presentations we will hear about at this meeting, and also some of the ethical challenges encountered. I will also consider major unanswered questions in the field and speculate on some of the diverse ways, utopian or dystopian, in which our area might develop in the future.

S60

Notes

P1

Poster Presentations

The genetic landscape of Finno-Ugric populations: the autosomal and Y-chromosomal projections

Anastasia Agdzhoyan1,2, Oleg Balanovsky1,2, Valery Zaporozhchenko2,1, Zhaneta Kagazezheva1,2, Elena Lukianova1, Elena Balanovska2

1 Vavilov Institute for General Genetics, Moscow, Russia; 2 Research Centre for Medical Genetics, Moscow, Russia.

The populations speaking Finno-Ugric languages live from Fennoscandia to Western

Siberia, connecting the northern strip of Europe with Siberia. Finno-Ugric languages spread

into Europe from the east long before the Baltic-Slavic and Turkic, but the question of

genetic traces and dating of this expansion is still actively studied [Illumae et al., 2016;

Tambets et al., 2018; Lamnidis et al., 2018; Post et al., 2019; Saag et al., 2019].

We conducted the detailed sampling of most Finno-Ugric populations, including small ethnic

groups and regional subpopulations (Vod, Izhora, Saami, Karelians, Veps, Moksha and

Erzya Mordovians, Udmurts, Besermyan, Mari, Komi, Khanty, Mansi). We performed

genome-wide and Y-chromosome genotyping and analyzed the data in the North Eurasian

context.

Finno-Ugric populations demonstrated large (compared with their area) genetic diversity.

Analysis of both, autosomal and Y-chromosome markers revealed the same local clusters -

North European, the Volga-Uralic and West Siberian. Each cluster includes Finno-Ugric

peoples and their non-Finno-Ugric-speaking neighbors. This pattern can be explained by the

language shift in some previously Finno-Ugric populations to Turkic (Tatars, Chuvashs,

Bashkirs in the Volga-Ural region) or to Slavic (Russians in Northeastern Europe).

Differentiation of the studied populations by the Y-chromosome has been shaped by various

proportions of haplogroup N3 branches. The geography of these (N2, N3a1, N3a3, N3a4)

correlates with the patterns of distribution of IBD segments shared with different Finno-Ugric

groups (Mansi, Udmurts, Karelians). The ages of these IBD segments correspond to a

period of 700-2800 years which covers the time of haplogroup N branches expansion.

Differentiation of the studied populations by autosomal markers is associated with the

contribution of two contrasting ancient genetic components: Eastern Hunter-Gatherers

(EHG), and the second component most pronounced in the modern population of Western

Siberia. The spread of the West Siberian component to Europe in the Iron Age has been

recently identified by ancient DNA analysis from various regions, including the Baltic coast

and the Kola Peninsula.

The expansion of West Siberian genetic component into Europe (according to ancient DNA,

no earlier than 3,500 ya and no later than 2,500 ya) corresponds with the linguistic patterns

of the dissemination of Finno-Ugric languages. The ongoing studies of Y-chromosomal

subbranches (their ages, homelands, and present-day areas), ancient DNA, as well as

renewed linguistic dating help to draw a synthetic model of Finno-Ugric migrations and

following demographic history.

P2

What makes us human? - Investigating de novo gene evolution in the human lineage

Katrin Berk, Daniel Dowling and Erich Bornberg-Bauer

Institute for Evolution and Biodiversity, University Münster

What sets humans apart from other primates? At the genetic level, human-specific genes

may play a major role in influencing our specific appearance and abilities. Such human-

specific genes can arise from the duplication and divergence, through mutation, of pre-

existing genes and may lead to evolutionary novelty. However, gene duplication and

mutations do not explain all cases of so-called orphan genes - genes that do not have

detectable homologs outside the focal species or clade. Recently, researchers have

proposed other mechanisms, such as de novo gene emergence from previously non-coding

DNA. De novo gene emergence starts with the formation of an open reading frame (ORF)

and its transcription, followed by translation into protein. De novo genes are not necessarily

functional upon emergence, but may gain function over time. Since de novo genes are

known to play an important role in speciation, a deeper look into the origin of de novo genes

may further our understanding of the molecular evolution of the human genome and human

evolution more generally.

Previous comparisons between Neanderthal and modern human genomes suggest past

interbreeding between Neanderthals and our own ancestors. Published introgression maps

show which regions in the modern human genome are highly probable to have been

introgressed from Neanderthals. Such introgressed DNA has been associated with adaptive

benefits, e.g. high altitude adaptation and immune defence. However, the impact of

introgression of Neanderthal and other archaic hominins on the emergence of de novo

genes in modern human genomes is unknown. Therefore, we investigate the possible

transfer of de novo genes from ancient hominins to modern humans. We used about 5000

short transcribed human-specific ORFs, which putatively code for de novo proteins, and

compared these ORFs with introgression maps, showing genomic regions likely to have

been introgressed from Neanderthals. We find that some of the 5000 ORFs are located

within these introgressed genomic regions. Nevertheless, none of the ORFs can be found

within introgressed regions of the sex chromosomes. Between all autosomes, the number of

introgressed de novo ORFs is spread unevenly. Novel genes, including de novo genes, may

have helped ancient hominins to adapt to changes in their environment. Therefore we aim to

distinguish between possible cases of adaptive introgression of beneficial de novo genes

and introgression of neutral or deleterious de novo genes, which may be maintained in the

genome due to linkage to beneficial genes.

P3

Reshaping the Hexagone: the genetic landscape of modern France

Francesc Calafell1, Simone Andrea Biagini1, Ángel Carracedo2,3,4, David Comas1

1. Departament de Ciències Experimentals i de la Salut, Institute of Evolutionary Biology (CSIC-UPF), Universitat Pompeu Fabra, Barcelona, Catalonia, Spain. 2. Forensic Genetics Unit, Institute of Forensic Sciences, University of Santiago de Compostela, Spain 3. Grupo de Medicina Xenómica (GMX), Faculty of Medicine, University of Santiago de Compostela, Spain 4. Center of Excellence in Genomic Medicine Research, King Abdulaziz University, Jeddah, Saudi Arabia

Unlike other European countries, Metropolitan France is surprisingly understudied. We have

combined newly genotyped samples from various zones in France with publicly available

data and applied both allele frequency and haplotype-based methods in order to describe

the internal structure of this country, taking advantage of the Human Origins SNP array,

specifically designed for human population genetics studies. We found out that French

Basques are genetically distinct from all other populations in the Hexagone and that the

populations from southwest France (namely the Franco-Cantabrian region) are intermediate

between Basques and other populations. Moreover, Bretons slightly separated from the rest

of the groups and a link with the historical gene flow from the British Isles has been found.

Results from the allele frequency analyses point to a general background that appears to be

a mixture of two components, one closer to Southern Italy and the other to Ireland. This

combination may be the result of a contact that happened in two different moments: in the

Early Neolithic, and then Ireland would be a proxy for the continental pathway for the

Neolithic wave of advance and South Italy for the coastal penetration, or the Iron Age, when

the Celtic and the Mediterranean worlds met in France. On the other hand, results from the

haplotype-based methods describe a more structured landscape, highlighting the presence

of areas characterized by differential links with the neighboring populations, possibly

reflecting a more recent history.

P4

Identifying signals of positive selection in Peruvian populations

Rocio Caro-Consuegra1, Maria A. Nieves-Colón2,3, Andrés Moreno-Estrada2, Elena Bosch1

1 Institute of Evolutionary Biology (UPF-CSIC), Department of Experimental and Health Sciences, Pompeu Fabra University, Barcelona, Catalonia, Spain 2 Laboratorio Nacional de Genómica para la Biodiversidad, Unidad de Genómica Avanzada (LANGEBIO-CINESTAV), Irapuato, Guanajuato, Mexico 3 School of Human Evolution and Social Change, Arizona State University, Tempe, Arizona

Since our origin in Africa, humans have colonised very diverse environments and confronted

distinctive selective pressures that have left traceable signatures across the human genome.

Perú is an extremely diverse country, hosting three main ecologically differentiated regions

or ecozones: the desert Pacific coast, the Andean highlands and the Amazonian jungle. Our

goal is to elucidate novel insights into the adaptive allelic variants and phenotypes that

favoured adaptation to the different environments of the three Peruvian ecozones. To do so,

we count on a geographically extensive dataset that includes 155 samples from 23 Peruvian

populations genotyped with Illumina Infinium® Multi-Ethnic Global Array (MEGA; 1,779,819

SNPs).

Global ancestry analyses, including principal component and admixture analyses, were

performed to infer population structure and individual ancestry fractions. Broadly, the Native

American ancestry component predominantes in all Peruvian populations but especially in

the highland ones. On the contrary, only a small fraction of European ancestry component is

present mostly in the Amazonian and coastal populations, where some African ancestry

component can be appreciated. Signals of positive selection according to the hard sweep

model were investigated using tests based on population differentiation (Fixation index [Fst]

and Population Branch Statistic [PBS]) and on linkage disequilibrium (integrated Haplotype

Score [iHS] and cross-population Extended Haplotype Homozygosity [XP-EHH]). As for

signals of polygenic selection, we computed SUMSTAT to check whether particular

pathways and gene sets show stronger selection signals than randomly generated gene

sets. Preliminary results of tests comparing highland to lowland populations (including the

coast and jungle ecozones) confirm previously described candidate genes for adaptation to

hypoxia, such as NOS2, BRINP3, EPAS1, FADS2, TGFA and ULBP1. Similarly, several

pathways (REACTOME, KEGG) and GO terms associated to cardiovascular health were

confirmed to be involved in high-altitude adaptation. Currently, we are investigating the

selection signals specific to the Amazonian jungle and desert Pacific coast ecozone.

P5

Adaptive gene flow in recent human evolutionary history

Sebastian Cuadros Espinoza, Guillaume Laval, Lluis Quintana-Murci, Etienne Patin

1. Human Evolutionary Genetics, Institut Pasteur, 75015 Paris, France 2. Centre National de la Recherche Scientifique UMR 2000, 75015 Paris, France 3. Center of Bioinformatics, Biostatistics, and Integrative Biology, Institut Pasteur, 75015 Paris, France 4. Sorbonne Université, 75006 Paris, France (lead author only)

Gene flow is a potential source - understudied in humans - of beneficial genetic variation.

Unlike classical models of positive selection where beneficial variants occur de novo,

adaptive gene flow introduces such variants directly, allowing populations to adapt faster to

new environments. This evolutionary process has been described in several plant and

animal species including humans, although examples for the later have been mostly

confined to gene flow from archaic hominins. Indeed, studies of recent adaptive gene flow

among modern humans have been limited to few populations, and the power of the methods

used, which were originally developed to detect loci evolving through classic models of

positive selection (i.e., selective sweeps), has yet to be determined. Here, we used forward

simulations to evaluate the power of classic selection statistics in the context of adaptive

gene flow, while incorporating confounding factors such as background selection. We show

that iHS and FST perform poorly, because they detect positive selection at variants that

were selected in the donor but not in the recipient population. To account for this scenario,

we devised an allele frequency-based statistic (adapted from Reynold's distance), which

specifically detects selection posterior to gene flow. We show that this statistic performs on

par with deviations of local ancestry, even in scenarios where the parental allele frequencies

are poorly estimated. We then apply these statistics to real data from different modern

human populations across the globe. We replicate previously described signals suggesting

that lactose tolerance and malaria resistance have been acquired by sub-Saharan Africans

and South Asians through gene flow, respectively, and have since been advantageous. We

also report new candidate regions for adaptive gene flow in East Indonesian populations,

noticeably ADH1B and TNFAIP3, which have been reported to evolve through positive

selection in East Asians and Papuans, respectively. Our study provides new evidence that

adaptive gene flow has been pervasive in the evolution of modern humans, whose genetic

history is characterized by periods of isolation and spatial expansions resulting in increased

gene flow.

P6

Making the invisible visible: hidden native contribution in the Uruguayan population

Maria Ines Fariello, Hugo Naya, Mónica Sans, Gabriel Illanes, Lucía Spangenberg

Universidad de la República, Instituto Pasteur Montevideo, Uruguay

Uruguay is one of the smallest countries in Latin America: it has neither mountains, nor

forest, and it has no tropical weather.. And there are no living native groups among its

population. The "Charrúas", that lived in the country before the European invasion, were

exterminated in 1831 (almost all males), so the popular saying is that Uruguay is a country of

European immigrants. Natives were almost erased from the Uruguayan population and

history, and according to the 2011 National Census only 4.9% of the population admit to

have at least one native ancestor.

To retrieve the native information of Uruguay, we collected samples from 10 Charrúa

descendants (according to thorough anthropological studies) and did high coverage whole

genome sequencing. We were able to determine global and local ancestries, obtaining a

relative high native signal within those genomes. Many of them, had more native ancestry

than self-declared. Participants declared to have at least one native great grandparent (or

great great grandparent) on one family side, but in several cases genomic studies showed

that the native contribution was on both sides, matrilineal and patrilineal. To explore about

the ancestors of each individual, we implemented a test to infer how many generations ago

lived the most recent "complete" native ancestor.

Additionally, we sampled 30 individuals from the general population. We observed that there

is a cline from south to north, where the native signal increases (from 0 to 60%) the northern

we go on the map..

Using only the native tracts of those genomes we found that most of the native signal comes

from the same population as the first 10 individuals, hence probably also Charrúas.

Additionally, we were able to determine similarities with other South American tribes. We

found selection traits among those genomes; some of them were old ones (conserved in

other natives) associated with two different genes very relevant in the immune system. Other

selection traits, were only present in the Uruguayan natives (and not in other natives),

indicating a newer private signature.

In the present work we retrieved for the first time, from whole genome sequencing, native

genomic DNA fragments to get some insight into the long lost "Charrúa" genome. This is

only the beginning; Ancient Charrúas and other native genomes from the region could

definitely refine our results.

P7

European Roma: from admixture footprints and demography to genetic distribution of coding variation

David Comas, Neus Font-Porterias(1), Lara R Arauna(1,2), Alaitz Poveda(3), Erica Bianco(1), Esther Rebato(4), Maria Joao Prata(5), Francesc Calafell(1)

(1) Institute of Evolutionary Biology (UPF-CSIC), Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona, Spain (2) Unit of Human Evolutionary Genetics, Institut Pasteur, Paris, France (3) Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Lund University, Malmo¨, Sweden (4) Department of Genetics, Physical Anthropology and Animal Physiology, University of the Basque Country UPV/EHU, Leioa, Spain (5) Instituto de Investigaca~o e Inovaca~o em Saude/Institute of Molecular Pathology and Immunology of the University of Porto, Porto, Portugal; Faculty of Sciences, University of Porto, Porto, Portugal

The Roma population, also known with the misnomer "Gypsies", is recognized as the largest transnational ethnic minority in Europe, characterized by a linguistic and cultural heterogeneity. Previous linguistic, anthropological, and genetic data have claimed a South Asian origin of the Roma followed by a diaspora towards the European continent with extensive admixture with non-Roma West Eurasian groups. Their demographic history together with their endogamous social practices has contributed to a different spectrum of genetic disorders in relation to other neighboring European populations. However, their South Asian source and West Eurasian components have not been deeply characterized and the impact of their demographic history on the mutational load has not been approached yet. Here, we analyze previously published genome- wide data of 152 European Roma at a haplotype-based level and whole exome sequences of 80 Iberian Roma samples. Our results suggest that the original genetic composition of the proto-Roma involves a Punjabi group with low levels of West Eurasian ancestry. In addition, we have identified a complex West Eurasian component in the Roma: all Roma groups present a Balkan genetic footprint, suggesting a single arrival to Europe; and Northern and Southwestern Roma groups present additional Baltic and Iberian components, respectively. Finally, Roma population shows a flatter site-frequency spectrum compared to other populations, pointing to a depletion of exon rare variants as a result of a bottleneck without population expansion. In sum, our analyses unravel at fine-scale the genetic components of the Roma groups, dissecting the original South Asian, ancestral West Eurasian, and recent European components and suggest that their demography and ancestry backgrounds might have influenced the genetic distribution of functional variants in their genomes.

P8

Ancient DNA and isotopic analysis of archaeological remains from Guam

M George B Foody1, Peter W. Ditchfield2, S.H. Ambrose3, Joanne Eakin4, Lynda B. Aguon5, Raymond F.Y. Blas5, Rosalind L. Hunter-Anderson6, Maria Pala1, Martin B. Richards1, Ceiridwen J. Edwards1

1.University of Huddersfield, Applied Sciences, Queensgate, Huddersfield HD1 3DH, England 2.University of Oxford, School of Archaeology, 1 South Parks Road, Oxford OX1 3TG, England 3.University of Illinois, Department of Anthropology, 607 S Mathews Avenue, Urbana, IL 61801, Illinois, United States 4.1005 Headingly NW, Albuquerque, New Mexico, United States 5.Department of Parks and Recreation, Guam Historic Resources Division, 490 Chalan Palasyo, Agana Heights, Guam 96910, Guam 6.1513 Wellesley Drive NE, Albuquerque, NM 87106, United States

Guam, located in the tropical north-western Pacific, is the largest island in Micronesia and

the most southerly of the Mariana Islands. While linguistic and modern DNA studies have

inferred that the ancestors of the indigenous Chamorros were south-east Asian migrants

who arrived as early as 2,000 BC, geology and archaeology indicate that the first human

groups arrived 500 years later.

Marianas prehistory is divided by archaeologists into two main periods: Pre-Latte (c. 1,500

BC to AD 1000) and Latte (AD 1000-1521). For the first thousand years of the Pre-Latte

Period, human interment was not practiced. The Naton Beach Site, on Guam's leeward west

coast, represents the earliest dated burial and permanent settlement.

Stable isotopic analyses on bone collagen carbon and nitrogen, and tooth enamel oxygen,

carbon and strontium, have been completed on seven ancient individuals from the Naton

Beach Site. One of these individuals has been radiocarbon dated to the late Pre-Latte

period, 774-509 cal. BC; a time associated with a distinctive pottery style that disappeared

from the archaeological record around 900 years later. After a "transitional" era of several

centuries, the Latte Period began, characterised by different ceramics, uniquely shaped

stone pillar house foundations, and the cultivation of rice - all cultural traits that were not

found elsewhere in Oceania at that time.

Genome-wide analysis has been attempted for two individuals from the Naton Beach

cemetery. The resulting data will be the first ancient DNA from Guam's oldest burial site.

Both uni-parental and autosomal genetic information will be used to assess possible

migration routes of the first settlers of Guam.

P9

Admixture and selection in the ancient Near East

Marc Haber, Joyce Nassar, Christiana L. Scheib, Lehti Saag, Tina Saupe, Samuel J. Griffith, Julien Chanteau, Muntaha Saghieh Beidoun, Yali Xue, Chris Tyler-Smith

Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, CB10 1SA, UK. Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, B15 2TT, UK Institut français du Proche-Orient (lfpo), Beirut, Lebanon Université de Bordeaux, CNRS, MCC, UMR 5199 PACEA, 33615 Pessac Cedex, France Estonian Biocentre, Institute of Genomics, University of Tartu, 23b Riia Street, Tartu 51010, Estonia. Université Libanaise, Rectorat BP: 14-6573, Place du Musée Beyrouth, Lebanon

The Near East remains under-represented in ancient DNA (aDNA) studies because of the

difficulty of obtaining aDNA from samples buried in warm regions. Here, we sequenced the

whole-genomes from 20 individuals who lived in Lebanon in the city of Beirut between 1000

BC and 500 AD. These new data, together with our previously generated datasets from the

Bronze Age and the Medieval periods, present a genetic transect of the Levant region

between 4,000 years ago and the present. This allows us to observe the genetic changes in

this region directly as they were occurring and understand how they led to the genetic

diversity observed today in the modern population. We investigated the decrease in genetic

distance between the Near Easterners and Europeans after the Bronze Age, refining our

previous models of how the Steppe ancestry penetrated the Levant region. Additionally, we

performed the first scan for selection using ancient DNA in the Near East by analysing

samples before and after the adaptation events and found selection on variants in genes

involved in development and metabolism. Our results highlight the importance of using

ancient DNA to understand how admixture and selection have shaped the genetics of

modern populations.

P10

Human male lineages outside Africa originated via a massive expansion beginning in East Asia 50,000-55,000 years ago followed by replacement of West Eurasian lineages

Pille Hallast1,2, Yali Xue1, Chris Tyler-Smith1

1 Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, CB10 1SA, UK; 2 Institute of Biomedicine and Translational Medicine, University of Tartu, Tartu, 50411, Estonia

The genomes of human populations outside Africa originated almost entirely from a single

major migration out around 50,000-60,000 years ago, followed closely by mixture with

Neanderthals contributing ~2% to the genomes of all non-Africans. However, the details of

this initial migration remain poorly understood because no ancient DNA analyses have been

reported so far from this key time period, and present-day autosomal data carry limited

information due to subsequent population movements and reshaping. One locus, however,

does retain information from this early period: the Y chromosome, where a detailed

calibrated phylogeny has been constructed. Three present-day Y lineages were carried by

the initial migration: the rare haplogroup D, the moderately rare C, and the very common FT

lineage which dominates most non-African populations. We show that phylogenetic analyses

of haplogroup C, D and FT sequences, including very rare deep-rooting lineages, together

with phylogeographic analyses of available ancient and present-day non-African Y

chromosomes, all point to East or South-east Asia as the origin 50,000-55,000 years ago of

all extant non-African male lineages. This implies that the initial Y lineages in populations

between Africa and East Asia have been entirely replaced by lineages from the east,

contrasting with the expectations of the serial founder model, and thus informs and

constrains models of the initial expansion.

P11

Assessing the Performance of qpAdm: A Statistical Tool for Studying Population Admixture

Eadaoin Harney, John Wakeley

Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, 02138, USA The Max Planck-Harvard Research Center for the Archaeoscience of the Ancient Mediterranean, Cambridge, MA, 02138, USA and Jena, D-07745, Germany

A major drawback of many population genetic tools for modeling the ancestry of admixed

populations is the requirement for the user to have a complete understanding of the

population histories of all other groups included in the model. qpAdm-a statistical tool for

modeling the ancestry of admixed (or un-admixed) populations-circumvents this problem by

eliminating the need for users to specify the underlying relationships of all other populations

in the model. Although qpAdm is growing in popularity (particularly in the field of ancient

DNA), relatively little has been done to assess its performance under both simple and

complex scenarios. We performed a simulation-based study to assess the behavior of

qpAdm under various scenarios in order to identify areas of potential weakness and

establish recommended best practices for use.

P12

Wavelet analysis of African and European recombination rates

Clare Horscroft, Reuben Pengelly, Andy Collins

University of Southampton, UK

Recombination is the process in which pairs of homologous chromosomes cross-over during

meiosis. These cross-over events are beneficial as they stop negative mutations building up

along one haplotype by breaking down linkage between alleles. Recombination rates are

known to be variable across the genome, with events clustering in hotspots. In the study of

evolution and natural selection, it is important to understand the underlying recombination

map for the population being analysed. The aim of this work is to calculate recombination

rates in African and European populations and use wavelet analysis to investigate the

differences on multiple scales.

Recombination rates were estimated using the widely implemented LDhat software for four

human genomic datasets: two European and two African. The resulting recombination maps

were then analysed using wavelets. Wavelet analysis allowed the recombination maps to be

analysed at multiple scales simultaneously, rather than using a fixed window size, from the

fine scale (2 Kb) through to the wide scale (16 Mb). This meant it could be ascertained

whether the variance in the original scale was contained in short-term trends, or in longer

ranging changes. Wavelet coherence analysis also allowed the comparison of the

correlations of recombination rate changes between pairs of datasets, both globally and

locally along the region.

The highest proportion of variance in the recombination rates was found at around the 16-64

Kb range across all the datasets, accounting for around a third of the total variance. The

correlations between the recombination rate changes increased with scale over all pairs of

datasets. The differences between African and European recombination rate changes were

greatest at the fine scale. The recombination rate changes were found to be non-uniform

across the region analysed, regardless of scale.

This work provides evidence that a recombination map built from one human population will

not be representative of all other populations, especially at the fine scale. This has

implications for methods designed to find evidence of natural selection in the genome that

rely on linkage disequilibrium calculations.

P13

A time transect of life around Cambridge through 5,000 years

Ruoyun Hui (1), Christiana L. Scheib (2), Eugenia D’Atanasio (3), Sarah A. Inskip (1), Craig Cessford (4), John E. Robb (5), Toomas Kivisild (2,3)

1 McDonald Institute for Archaeological Research, University of Cambridge, Cambridge, UK; 2 Institute of Genomics, University of Tartu, Tartu, Estonia; 3 Department of Human Genetics, Katholieke Universiteit Leuven, Leuven, Belgium; 4 Cambridge Archaeological Unit, University of Cambridge, Cambridge, UK; 5 Department of Archaeology, University of Cambridge, Cambridge, UK

Population genetics and ancient DNA research have contributed enormously to revealing

prehistoric large-scale migrations, yet relatively less work has been dedicated on the study

of genetic differences at local scale. As part of an interdisciplinary project "After the Plague:

Health and History in Medieval Cambridge", we have sequenced skeletal remains from over

394 individuals that once lived in or around the current city of Cambridge. Our study sites

span in time from Neolithic, Iron Age, to Roman, Anglo-Saxon, Medieval and post-Medieval

periods. For the Medieval and post-Medieval period, we have comparatively examined

burials from different social groups such as urban parish, rural parish, the urban poor, and

various religious groups. After the Neolithic period, all burial groups exhibit the highest

affinity to present-day western and northern Europeans. Intriguingly, we find significant

genetic differentiation between two Anglo-Saxon sites, which could reflect the co-existence

of groups of different genetic ancestry in the region in the second half of the first millennium.

We also observed a decline in close kinship within sites in the Medieval and post-Medieval

period, especially in urban sites. Greater geographical as well as social mobility have been

suggested as a consequence of the Black Death pandemic. However, we do not detect

evidence for major cross-regional gene flow in later burials. As the majority of our samples

has low coverage (0.05-1x), we tailored a pipeline to maximize accurate imputation of

common variants from our data using a modern reference panel. We observed no significant

(p<0.01) allele frequency changes in individual genetic markers related to the phenotypic

appearance, health, and diet. While evaluating polygenic risk score predictions from imputed

genomes we observed a strong (r2>0.4) positive correlation between the risk scores for

height and stature estimated from long bone lengths in a pilot test. We plan to incorporate

other anthropometric and health-related traits in the future towards a synthesis with evidence

from osteoarchaeology, paleopathology, stable isotope analysis and morphometrics.

P14

Evaluating Neandertal admixture time estimates

Leonardo Iasi, Benjamin Peter

Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany.

An emergent finding in evolutionary genetics is that gene flow between distinct populations is

much more common than previously thought. A question of great interest is when this

admixture happened, particularly in the case of gene flow between Neandertals and modern

humans. The most-widely used approaches are based on a recombination clock, i.e. they

measure the decay of the length of introgressed fragments over time. Most models make

fairly strong assumptions about the data, such as that the recombination rate is known, and

that gene flow happened over a very short period of time. Here we present a simulation

study where we test the effect of some of these assumptions, to evaluate our knowledge of

when Neandertal gene flow happened, based on present-day genetic data.

To allow for ongoing gene flow, we introduce a model where migration times follow a gamma

distribution, in which case the admixture tract length distribution has a closed form. However,

we find that even if migration persists over thousands of generations, the effect on admixture

time inference is small, suggesting an inherent limit to the accuracy that can be obtained

when estimating the time of gene flow. Moreover, we find that particularly the accuracy of the

recombination map has by far the highest impact on inferred admixture times. Even small

deviations can lead to an underestimate of admixture times up to 60%.

Based on these results, we find that most attempts to estimate the timing of gene flow from

present-day data are likely seriously underpowered. Analyses incorporating ancient DNA

(both to calibrate the recombination clock and to have more recent admixture times), will be

required to resolve this issue.

P15

A graph theoretical approach to depicting sex-biased dispersal and coevolution in ancient populations: mitochondrial DNA vs. Y-chromosome variation

Pierre Justeau 1, Olivier Dameron 2, Simão Moreira Rodrigues 1, Ceiridwen Edwards 1, Maria Pala 1, Martin B. Richards 1

1. Department of Biological and Geographical Sciences, School of Applied Sciences, University of Huddersfield, Huddersfield, HD1 3DH, UK, 2. Institut de Recherche en Informatique et Système Aléatoire, 263 Avenue Général Leclerc, 35000 Rennes, France

Since the advent of next-generation sequencing, the quality and quantity of ancient DNA

data have allowed us to depict human movements through time, and in particular the

contribution of different sexes to these dispersals. One of the most striking examples is the

male-biased migration during the Bronze Age from the Eurasian steppe to western Europe.

This sex-biased dispersal led to an important genetic turnover by virtually replacing the

previous Neolithic Y-chromosome diversity with haplogroup R1b-M269 in many parts of the

continent. A network approach that combines information from the maternal and paternal

haploid marker systems, as well as geographical, chronological and cultural evidence, could

illuminate sex-specific patterns or coevolution. Here, we begin to develop such an approach

using graph theory, combining Y-chromosome and mtDNA haplotype data with

archaeological and geographical information, in order to better understand sex-specific

patterns of dispersal and coevolution between the male and female lines of descent. Our aim

is to portray graphically the social structure within and between prehistoric human

populations, and throw new light on ancient dispersal patterns in relation to patrilocal versus

matrilocal residence systems.

P16

Extensive ethnolinguistic diversity in Vietnam reflects multiple sources of genetic diversity

Dang Liu1, Nguyen Thuy Duong2, Nguyen Dang Ton2, Nguyen Van Phong2, Brigitte Pakendorf3, Nong Van Hai2 and Mark Stoneking1

1. Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany 2. Institute of Genome Research, Vietnam Academy of Science and Technology, Hanoi, Vietnam 3. Laboratoire Dynamique du Langage, UMR5596, CNRS & Université de Lyon

Vietnam features extensive ethnolinguistic diversity and occupies a key position in Mainland

Southeast Asia (MSEA). Yet, the genetic diversity of Vietnam remains relatively unexplored,

especially in genome-wide data, because previous studies have focused mainly on the

majority Kinh group. Here we analyze newly-generated genome-wide SNP data for the Kinh

and 21 additional ethnic groups in Vietnam, encompassing all five major language families in

MSEA. In addition to analyzing the allele and haplotype sharing within the Vietnamese

groups, we incorporate published data from both nearby modern populations and ancient

samples for comparison. We find that the Vietnamese ethnolinguistic groups harbor multiple

sources of genetic diversity associated with heterogeneous ancestry sharing profiles in each

language family from different time periods. However, linguistic diversity does not completely

match genetic diversity; there have been extensive interactions between the Hmong-Mien

and Tai-Kadai groups, and a likely case of cultural diffusion in which some Austro-Asiatic

groups shifted to Austronesian languages. Overall, our results highlight the importance of

genome-wide data from dense sampling of ethnolinguistic groups in providing new insights

into the genetic diversity and history of an ethnolinguistically-diverse region, such as

Vietnam.

P17

Partial polygenic scores for individuals of mixed ancestries

Davide Marnetto, Katri Pärna, Kristi Läll, Ludovica Molinaro, Francesco Montinaro, Toomas Haller, Mait Metspalu, Reedik Mägi, Krista Fischer, Luca Pagani

Institute of Genomics, University of Tartu, Tartu, Estonia. Department of Epidemiology, University of Groningen, UMCG, Groningen, Netherlands Institute of Mathematics and Statistics, University of Tartu, Tartu, Estonia. Department of Biology, University of Padova, Padova, Italy

Polygenic Scores (PS) describe the genetic component of an individual's quantitative

phenotype for their susceptibility to diseases with a genetic basis. PS rely on population-

dependent contributions of many associated alleles, with limited applicability to populations

other than the training one and recently admixed individuals.

Here we introduce a novel combination of local ancestry deconvolution and partial PS

computation to account for the population-specific nature of the association signals in

admixed individuals.

We show that PS distributions of admixed populations can be seen as linear combinations of

the original PS tendencies pertaining to the ancestral populations, but that the local pattern

of admixture needs to be taken into account when evaluating each individual's PS. We

demonstrate partial PS to be a good proxy for the total PS and that even a small portion of

the genome is enough to improve susceptibility predictions for the four traits we tested,

namely: Type 2 Diabetes, height, BMI and breast cancer. Our results show that the newly

introduced partial PS can be used to predict phenotypes in individuals of mixed ancestry or

where part of the genetic information is missing, such as ancient genomes.

These promising results may extend the applicability of PS to subjects that are left aside of

the personalized medicine revolution due to their complex history of admixture.

P18

Removing reference bias in ancient DNA data analysis by mapping to a sequence variation graph Martiniano R* [1], Garrison E* [2,3], Jones ER [4], Manica A [4], Durbin R [1,2]. 1. Department of Genetics, University of Cambridge, Cambridge CB3 0DH, UK 2. Wellcome Sanger Institute, Cambridge CB10 1SA, UK 3. Genomics Institute, University of California, Santa Cruz, CA 95064, USA 4. Department of Zoology, University of Cambridge, Cambridge CB2 3EJ, UK *Equal contributions During the last decade, the analysis of ancient DNA (aDNA) sequence has become a powerful tool for the study of past human populations. However, the degraded nature of aDNA means that aDNA sequencing reads are short, single-ended and frequently mutated by post-mortem chemical modifications. All these features decrease read mapping accuracy and increase reference bias, in which reads containing non-reference alleles are less likely to be mapped than those containing reference alleles. Recently, alternative approaches for read mapping and genetic variation analysis have been developed that replace the linear reference by a variation graph which includes all the alternative variants at each genetic locus. Here, we evaluate the use of variation graph software vg to avoid reference bias for ancient DNA. We used vg to align multiple previously published aDNA samples to a variation graph containing 1000 Genome Project variants, and compared these with the same data aligned with bwa to the human linear reference genome. We show that use of vg leads to a much more balanced allelic representation at polymorphic sites and better variant detection in comparison with bwa, especially in the presence of post-mortem changes, effectively removing reference bias. A recently published approach that filters bwa alignments using modified reads also removes bias, but has lower sensitivity than vg. Our findings demonstrate that aligning aDNA sequences to variation graphs allows recovering a higher fraction of non-reference variation and effectively mitigates the impact of reference bias in population genetics analyses using aDNA, while retaining mapping sensitivity.

P19

Adaptive introgression as a driver of local adaptation in Southwest Pacific human populations

Javier Mendoza-Revilla1,2, Jeremy Choin1,2,3, Lara R Arauna1,2, Christine Harmant1,2, Olivier Cassar4, Maximilian Larena5, Jean-François Deleuze6, Mattias Jakobsson5, Mark Stoneking7, Antoine Gessain4, Laurent Excoffier8, Etienne Patin1,2 & Lluis Quintana-Murci1,2

1 Human Evolutionary Genetics Unit, Institut Pasteur, UMR 2000, CNRS, Paris 75015, France; 2 Human Genomics and Evolution, Collège de France, Paris 75005, France; 3 Université Paris Diderot, Sorbonne Paris Cité, Paris 75013, France; 4 Unité d'Epidémiologie et Physiopathologie des Virus Oncogènes, Institut Pasteur, CNRS, UMR 3569, Paris 75015, France; 5 Human Evolution, Department of Organismal Biology, Uppsala University, Uppsala 752 36, Sweden; 6 Centre National de Recherche en Génomique Humaine (CNRGH), Institut de Biologie François Jacob, CEA, Université Paris-Saclay, Evry 91057, France; 7 Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, Leipzig 04103, Germany; 8 Institute of Ecology and Evolution, University of Bern, Bern 3012, Switzerland

Genomic analyses of sequence data from archaic and modern humans have shown that

these groups interbred. While most of the introgressing haplotypes were removed by

purifying selection, there is increasing evidence to suggest that in some cases archaic

haplotypes provided some selective advantage to modern humans, and increase in

frequency through a process known as adaptive introgression (AI). Nonetheless, the degree

and potential adaptive nature of archaic introgression in populations harboring both

Neanderthal and Denisovan ancestry remain largely unexplored. In this context, Southwest

Pacific populations represent an ideal setting in which to study how AI has contributed to

human adaptation, as these populations carry the highest levels of combined archaic

ancestry worldwide. Here, we generated more than 300 high-coverage (~40×) WGS from 20

Pacific populations from Taiwan, the Philippines, and Near and Remote Oceania (Solomon

Islands, Santa Cruz and the Vanuatu archipelago), and used the number and allele

frequencies of sites that are uniquely shared between archaic hominins and humans to

evaluate AI.

We found strong signs of AI at several reported genes, including pigmentation-, metabolic-

and immune-related genes related to Neanderthal ancestry, and immune-related genes to

Denisovan ancestry. Yet, we detect a number of novel hits; for example, the CD33 gene,

which is part of the immunoglobulin superfamily, presents the strongest signal of Denisovan

AI in all populations from Remote Oceania. This genomic region contains 6 uniquely shared

alleles with Denisova, 2 of which have a frequency >65%, suggesting an old AI event in the

ancestor of all Remote Oceanians. We also detected a strong Denisovan AI signal in the

Agta hunter-gatherers from the Philippines within the IRF4 gene, a transcription factor

involved in immunity. This region includes 7 uniquely shared alleles with Denisova, 6 of

which have a frequency >60%. Notably, one of these sites, SNP rs376970869, is a

promoter-flanking region that is active only in B and CD4 immune cells. Finally, enrichment

analyses of the top AI genomic regions revealed the strongest enrichment of Denisovan AI in

several categories related to immunity, a pattern that is not observed for Neanderthal AI.

This suggests a greater contribution of Denisovan segments to pathogen-driven human

adaptation.

Overall, our analyses reveal that the introgression of Neanderthal and Denisovan genetic

material into the genomes of modern populations from the Pacific facilitated their local

adaptation, targeting primarily immune-related functions and thus, pinpointing pathogens as

one of the main selective pressures in this region.

P20

Post-Roman Iberia: A Genetic Journey There and Back Again

Gonzalo Oteo-Garcia (1), Marina Silva(1), George Foody(1), Alessandro Fichera(1), Bobby Yau(1), Marisa Rovira(2), Vicente Palomar(3) Albert Ribera i Lacomba(4), Maria Pala(1), Ceiridwen Edwards(1), Martin B. Richards(1)

1) Department of Biological and Geographical Sciences, School of Applied Sciences, University of Huddersfield, Queensgate, Huddersfield HD1 3DH, UK 2) Museu Arqueològic Municipal, La Vall d'Uixó 12600, Spain 3) Museo Municipal de Arqueología y Etnología, Segorbe 12400, Spain 4) Servicio de Investigacion Arqueologica Municipal, Ayuntamiento de Valencia, Valencia 46002, Spain

The post-Roman period in Iberia is yet to be studied in depth using ancient DNA. Our

research focuses on understanding population genetic changes during this time in the

Iberian Levante. This Mediterranean region is interesting because it became a cultural

crossroads after intense Romanization, followed by a decline during the Visigothic era, a

Byzantine invasion and later becoming a jewel of Islamic agriculture. The main focus of the

research is on the Medieval Islamic period. During the five centuries of Islamic rule, and

according to historical records, many Arab and North African settlers were attracted to Xarq

Al-Andalus. We sequenced 13 early to late Medieval genomes with coverages ranging from

0.3X to 2.3X from the Valencian region in eastern Spain and discovered widespread North

African admixture and foreign uniparental markers in the Andalusian Islamic rural society.

These results are the more striking when compared to the modern Spanish population,

which displays little surviving genomic evidence for this relatively recent admixture episode.

We identify one major historical event in the 17th century, potentially responsible for the

disappearance of the North African ancestry in eastern Spain. On the other hand, we did not

find a clear Arab genetic contribution, consistent with the view that Arabs were a minority

ruling elite. However, the genomic results of two samples dated to the 6th-7th century

moment of the Byzantine invasion suggest that the admixture trend may have started earlier,

during late Roman times. These two samples are father and daughter, found in a borderland

territory between Visigothic and Byzantine rule, and display a significant degree of Near

Eastern ancestry but with clear Iberian affinities. In conclusion, we see evidence that the

Spanish Levante suffered two genetic transformations in a relatively short period of time - a

few centuries - within the last thousand years. This dual genomic transformation saw the

arrival of North African ancestry to eastern Iberia in high proportions only to later disappear

almost completely. However, the North African genetic legacy in Spain survived in some

ways until our days, mostly in the form of paternal lineages E1b and maternal lineages U6a

which we clearly identified being introduced for the first time during the Islamic period.

P21

Estimation of relatedness in ancient populations

Divyaratan Popli, Stephane Peyregne, Laurits Skov, Leonardo Iasi, Steffi Grote, Matthias Meyer, David López Herráez, Mateja Hajdinjak, Viviane Slon, Janet Kelso, Svante Pääbo, Benjamin Peter

Max Planck Institute for Evolutionary Anthropology

Identifying related individuals is one of the key applications of genetics, as related individuals

need to be removed for many analyses, and we may learn about social and cultural

practices. In ancient DNA studies, this is often difficult because the genotypes determined

from ancient individuals are typically sparse, suffer from ascertainment bias and may partly

derive from present-day DNA contaminating the experiments.

Most current approaches to estimate relatedness between individuals are allele-frequency

based, and have significant drawbacks for the analysis of ancient DNA in that they require

intermediate or high (>1x) coverage, large reference panels from related populations or large

number of diploid called sites. Here, we present a method to infer relatedness from low-

coverage data. Our method models the fact that every genome is a mosaic of fragments

inherited from various ancestors, and closely related individuals will share large chunks of

their chromosomes identical by descent (IBD). We develop a Hidden Markov Model to

identify IBD fragments shared between pairs of ancient samples, and use this model to infer

their degree and nature of relatedness. We evaluate this method on simulations and apply it

to 31 DNA libraries prepared from 15 Neandertal specimens. These libraries have been

used to capture 713,000 informative sites; the coverage per specimen ranges from 0.01 to

1.58. Preliminary results suggest that three of the specimens come from the same individual,

and that one specimen is closely related to four other specimens. Although further work is

required to elucidate the exact relatedness among these individuals, we show that

relatedness inference is feasible even for data with coverage significantly less than 1x.

P22

Archaeogenetics and Palaeogenetics of Southeast and Eastern Europe

Simão Rodrigues (1), Pierre Justeau (1), George Foody (1), Rita Monteiro (1), Francesca Gandini (1), Bobby Yau (1), Gonzalo Oteo-Garcia (1), Alessandro Fichera (1), Marina Silva (1), Katharina Dulias (1), Gheorghe Stefanescu (2), Luminita Bejenaru (3), Pedro Soares (4), Ceiridwen Edwards (1), Martin B. Richards (1) and Maria Pala (1)

1: Department of Biological and Geographical Sciences, School of Applied Sciences, University of Huddersfield, Queensgate, Huddersfield HD1 3DH, United Kingdom 2: Institutul de Cercetari Biologice, Iasi 700505, Romania 3: Faculty of Biology, Alexandru Ioan Cuza University of Iasi, Iasi 700505, Romania 4: CBMA (Centre of Molecular and Environmental Biology), Department of Biology, University of Minho, 4710- 057, Braga, Portugal

Thanks to its geographic position in the south-east of Europe, the Balkan region has

functioned as a bridge area connecting the Near East and Asia to Europe. This role has led

to unusually high levels of genetic, linguistic and cultural heterogeneity characterising the

entire region[1,2]. The genetic diversity was most likely shaped by four events: (1) the arrival

of anatomically modern humans (AMH) in Europe; (2) Late Glacial recolonization from

refuge areas; (3) the Neolithic revolution; and (4) the Yamnaya migrations from the Pontic-

Caspian steppe[3-5]. However, which one of these event/s played the leading role, at what

time depth, to what extent earlier episodes were overwritten, and whether other minor actors

were involved, is still debated. In order to shed some light on this issue, we are generating

mitochondrial and genome-wide sequence data for both modern and ancient samples from

the area. The aim is to better comprehend the origin of the genetic diversity and quantify the

impact of ancient and more recent events in shaping the current genetic variability. By doing

so, we also hope to illuminate the population dynamics that ultimately shaped the genetic

variation more widely across the European peninsula.

1. Bosch, E. et al. Paternal and maternal lineages in the Balkans show a homogeneous

landscape over linguistic barriers, except for the isolated Aromuns. Ann. Hum. Genet. 70,

459-487 (2006).

2. Kovacevic, L. et al. Standing at the gateway to Europe - The genetic structure of western

Balkan populations based on autosomal and haploid markers. PLoS One 9, e105090 (2014).

3. Soares, P. et al. The archaeogenetics of Europe. Curr. Biol. 20, 174-183 (2010).

4. Pinhasi, R., Thomas, M. G., Hofreiter, M., Currat, M. & Burger, J. The genetic history of

Europeans. Trends Genet. 28, 496-505 (2012).

5. Mathieson, I. et al. The genomic history of southeastern Europe. Nature 555, 197-203

(2018).

P23

Genome-wide analyses of Ni-Vanuatu populations reveal diverse ancestries and temporal differences in admixture patterns

Lara Rubio Arauna, Jeremy Choin, Javier Mendoza-Revilla, Christine Harmant, Laure Lemee, Olivier Cassar, Antoine Gessain, Etienne Patin, Lluis Quintana-Murci

Institut Pasteur, Paris, France

The Vanuatu archipelago was peopled during the last human migration at the worldwide

scale ~3,000 years ago, concomitantly with the expansion of Austronesian languages and

Lapita assemblies. Although languages spoken in Vanuatu are of Austronesian origin, recent

evidence suggests a predominantly Papuan-like genetic ancestry in some Vanuatu islands.

Recent ancient DNA studies support the arrival of Papuan-like ancestry soon after

Austronesian expansions, likely from the Bismarck Archipelago. Yet, genetic studies of

modern populations from Vanuatu -the country with the highest number of languages per

capita and spreading through 65 islands- remain scarce. Furthermore, the temporal peopling

of this archipelago, and the sources and extent of admixture processes in the region remain

uncharacterized.

Here, we generated genome-wide SNP data from more than 1,000 Ni-Vanuatu DNA

samples, originating from 30 islands. Despite their high cultural diversity, our data revealed

an overall degree of genetic homogeneity, suggesting a common peopling process for the

archipelago. When using haplotype-based methods (ChromoPainter, fineSTRUCTURE),

however, we observed fine patterns of genetic structure that mirror geography. We found a

Papuan-like component that is present at overall high proportions (~80%) but that varies

according to geography, revealing differences in admixture proportions across islands. Using

GLOBETROTTER, we estimated the admixture events between the Papuan-like and

Austronesian ancestry components to have occurred between 2,000 and 500 years ago,

depending on the different islands. Notably, our analyses revealed more complex patterns of

ancestry sources than previously appreciated, with different Austronesian sources

contributing to the current patterns of diversity of Ni-Vanuatu. Finally, although a high degree

of relatedness was generally observed within islands, supporting the sea as a general barrier

to gene flow, we found that the northern Torres Islands show similar numbers of related

individuals within and between islands, supporting a history of cultural exogamy.

In conclusion, our analyses revealed that the various populations inhabiting today the

Vanuatu archipelago descend from different ancestry components, which vary today in

intensity across islands, that have admixed to different extents since the early peopling of

the region. Moreover, the fine-scale genetic structure of the region has also been shaped by

geographic barriers and by different mating patterns. Together, this study sheds new light

onto the complex peopling and admixture history of this largely neglected region of the

world.

P24

Ancient genomes from Fatyanovo culture, a Corded Ware subgroup in Western Russia

Lehti Saag 1, Sergey V. Vasilyev 2, Liivi Varul 3, Natalia V. Kosorukova 4, Dmitri V. Gerasimov 2, Kristiina Tambets 1, Christiana Lyn Scheib 1, Aivar Kriiska 1, Mait Metspalu 1

1 University of Tartu, Estonia; 2 Russian Academy of Sciences, Russia; 3 Tallinn University, Estonia; 4 Cherepovets State University, Russia

Western Russia is a region which has so far been genetically very poorly studied. Here we

present, to our knowledge, the first genetic results from Fatyanovo culture, futhermore

accompanied by new Mesolithic data from the region.

Fatyanovo culture is a prominent Eastern European Corded Ware subgroup, that was

spread over a large area in Western Russia. So far, only 14 radiocarbon dates have been

published for Fatyanovo culture, placing it to 2,750-2,500 (2,300) calBC. The burial customs

related to the culture included placing the dead in an earthen grave, flexed and on their side

- men mostly on the right and women on the left side, both often facing south - and shaft-

hole stone axes, flint tools and corded ware etc. as grave goods.

This study aims firstly, to add 30 new radiocarbon dates from Fatyanovo culture and

secondly, to characterize the genetic affinities of the individuals associated with the culture.

To that end, we have extracted DNA from 52 individuals and present genome-wide data

from 3 (Sub-)Mesolithic individuals from Central and Northwestern Russia, 27 from

Fatyanovo culture and 1 from Estonian Corded Ware culture. We have sequenced these

individuals to an average genomic coverage of 0.12x.

The first results of the study show that the Mesolithic individuals were most similar to

Eastern hunter-gatherers while the Fatyanovo individuals together with the Estonian Corded

Ware individual were most similar to other European individuals with steppe ancestry,

including other Corded Ware culture individuals.

P25

New insights into the genetic history of the Chalcolithic/Bronze Age transition in Italy Tina Saupe, Francesco Montinaro 1, Cinzia Scaggion, Nicola Carrara, Toomas 1 2 3 4, Kivisild 5, Ophelie Lebrasseur 6 7, Greger Larson 7, Luca Alessandri 8, Flavio De Angelis 9, Mario Federico Rolfo 10, Robin Skeates, Letizia Silvestri 8, Jessica Beckett, Mait Metspalu 11 12 1, Sahra Talamo 13, Monica Miari 14, Stefano Benazzi, Cristian Capelli, Luca Pagani 1, Christiana L. Scheib 15 16 17 1 1 Estonian Biocentre, Institute of Genomics, University of Tartu, Estonia; 2 Department of Evolutionary Biology, Institute of Cell and Molecular Biology, University of Tartu, Estonia; 3 Department of Geosciences, University of Padova, Italy 4 Museum of Anthropology, University of Padova, Italy; 5 Department of Human Genetics, KU Leuven, Belgium; 6 Department of Archaeology, Classics and Egyptology, University of Liverpool, UK; 7 Palaeogenomics & Bio-Archaeology Research Network, School of Archaeology, University of Oxford, UK; 8 Groningen Institute of Archaeology, University of Groningen, Netherlands; 9 Centre of Molecular Anthropology for Ancient DNA Studies, University of Rome “Tor Vergata”, Italy; 10 Department of History, Culture and Society, University of Rome “Tor Vergata”, Italy; 11 Department of Archaeology, Durham University, UK; 12 Independent scholar, Cagliari, Italy; 13 Department of Chemistry "Giacomo Ciamician", University of Bologna, Italy; 14 Superintendency of Archeology, Fine Arts and Landscape for the metropolitan city of Bologna and the provinces of Modena, Reggio Emilia and Ferrara, University of Bologna, Italy; 15 Laboratory of Osteoarchaeology and Paleoanthropology, University of Bologna, Ravenna, Italy; 16 Department of Zoology, University of Oxford, UK; 17 Department of Biology, University of Padova, Italy The Chalcolithic Age in Europe is defined as the transition from the Neolithic to the Bronze Age and is characterized by the use of copper to produce metallic tools. From the genetic point of view, it marks a period in which many demographic changes occurred. In fact, influence from the Pontic-Caspian Steppe and Greater Caucasus has been reported for Central and Southern Europe, respectively. However, it is not clear if some of these events may have impacted some southern regions, such as Italy, before the Bronze Age. In this study, we generated new shotgun sequences of 46 samples from four archaeological sites (Grotte del Broion n=26, Necropoli di Gattolino n=4, Grotta Regina Margherita n=3, Grotta La Sassa n=13) geographically located in Northern and Central Italy, which are archaeologically dated to the Chalcolithic and Middle Bronze Age. We extracted DNA from teeth (n = 37) and petrous bone (n = 9) in the dedicated ancient DNA laboratory at the Institute of Genomics, University of Tartu leading to 16 individuals covered from 0.05 - 1.06x for population genomic analysis. We find high genetic relatedness of some ancient samples to Sardinian and Early European Chalcolithic populations, confirming the high impact of the Chalcolithic expansion on the whole peninsula. All individuals from Grotta Regina Margherita archaeologically dated to the Middle Bronze Age and five Broion individuals cluster with present-day Northern and Southern Italian individuals. We find close patrilineal kinship groups within sites conforming to PCA cluster but not between them and a shift in Y chromosome lineages through time. We also find each site has differential affinities to the three main waves of European ancestry, granting the first insights into local genetic dynamics in the Italian Peninsula during the transition from the Chalcolithic to the Bronze Age.

P26

The Evolutionary Significance of Healthcare Provisioning

Penny Spikins, Calvin Dytham

Department of Archaeology, University of York and Department of Biology, University of York, UK

The existence of skeletal evidence indicating that certain individual hominins who suffered

illness or injuries in the distant past received care from others has been recognised for some

time. However both a lack of primate models for extended care behaviours and a tendency

to see care practices as cultural traits, alongside symbolism or mortuary practices, have

constrained appreciation of the evolutionary implications of care practices. As a result

evidence for care has been seen as an interesting indication of some "spark of humanity"

rather than of evolutionary significance.

Here we aim to demonstrate that healthcare provisioning has played a far more significant

role in human evolution than has previously been recognised. We present an analysis of the

emergence and patterning of healthcare provisioning in the evolutionary past, and describe

both the evolutionary advantages of such care and its potential impacts on human ecology

and demography. As part of this analysis we present an agent-based simulation model of the

effects of healthcare provisioning on capacities to move into new ecological niches, as well

as implications of care for demographic patterns. We argue that a full understanding of key

social and biological transitions in human origins demands an understanding of how care

practices influenced human evolution.

P27

Modelling human adaptations in mice

Michal Szpak, Yali Xue, Qasim Ayub, Valerie E. Vancollie, Nicola Griggs, David Lafont, Neil J. Ingham, Morag A. Lewis, Mark Campbell, Sergio Rodriguez-Cuenca, Toomas Kivisild, Antonio Vidal-Puig, Karen P. Steel, Christopher J. Lelliott, Chris Tyler-Smith

Wellcome Sanger Institute; Wolfson Centre for Age-Related Diseases, King's College London; Metabolic Research Laboratories, University of Cambridge; Department of Archaeology and Anthropology, University of Cambridge; School of Science, Monash University Malaysia

Following the out-of-Africa expansion, humans have adapted to a diverse range of new

environments and selective pressures. Scanning genomes for population-genetic signatures

of such adaptations yields vast lists of thousands of genetic candidates. Their functional

validation and investigation of their biological consequences is a current roadblock in the

field, limiting both our understanding of the selected phenotypes and more generally the

importance of positive selection. Successful examples show that in-depth follow-up studies

of putatively-selected variation using genome editing and model organisms constitute a

suitable tool to uncover the underlying biology. However, modelling of non-pathological

human variation has received limited attention to date. We therefore developed a tool for

pinpointing and prioritisation of candidate selected variants for functional follow-up studies

(FineMAV). After compiling lists of ~100 high-priority candidates across different continental

populations, we have begun investigating several of them using CRISPR/Cas9 technology to

generate 8 mouse knock-outs, and 21 knock-ins carrying the human selected allele. Knock-

outs of Herc1 and Prss53 reveal diverse phenotypes and a single hair-related phenotype,

respectively. Mouse knock-in of a CPT1A allele selected in Siberians recapitulated some

aspects of the human metabolic phenotype expected, while the PCDH15 allele selected in

East Asia confers a detectable hearing phenotype, although it is a progressive decrease in

high-frequency hearing sensitivity, which is unexpected. Linking mouse phenotype to fitness

in humans is thus complex; nevertheless, animal models provide one of the few ways to test

hypotheses regarding recent human evolution and need large-scale evaluation.

P28

The population structure of Medieval Estonia

Kristiina Tambets1, Lehti Saag1, Martin Malve2, Kadri Irdt1, 3, Christiana Lyn Scheib1, Alena Kushniarevich1, Lauri Saag1, Anu Solnik1, 2, Tuuli Reisberg1, Toomas Kivisild1, 4, Heiki Valk2, Mait Metspalu1

1Institute of Genomics, University of Tartu, Tartu, Estonia; 2Institute of History and Archaeology, University of Tartu, Tartu, Estonia; 3Institute of Cell and Molecular Biology, Tartu, Estonia; 4 Dept. of Human Genetics, KU Leuven, Leuven, Belgium

This interdisciplinary project is part of multiple studies of temporal population dynamics of

the eastern coast of the Baltic Sea, in the territory of present-day Estonia. We have used the

skeletal material from Estonian archaeological collections to characterize the genetic

structure of the population in time series starting from the earliest layers of lithic cultures to

the contemporary population. The results of these studies have revealed several population

shifts during the prehistory of the region and show that since the Early Iron Age the local

population has not changed much. The Medieval time layer is rich in well-preserved

osteological material and a wealth of historical records, yet the genetic structure of the

population has not been studied in depth.

The Medieval period started in the eastern Baltic region in the 13th century AD, much later

than in Central Europe or in Scandinavia when the crusades and conquest brought along

vast social, economic and cultural changes. These processes presumably also changed the

structure of the local population. Our sample set consists of skeletal remains of 107

individuals from different regional subgroups, as well as from Medieval rural and town

cemeteries, representing the local and elite communities respectively. The latter are often

associated with the new wave of people who arrived mostly from Western Europe via the

economic, cultural and political networks. The samples in our dataset are mostly from the

13th - 15th cc AD.

We produced low-coverage (up to 0,9x) whole-genome shotgun sequencing data on Illumina

platform. The resulting data was analyzed in the context of modern Estonian and European

genetic variation. Although the diversity of the Medieval time layer is very similar to that of

present-day populations, our pilot study shows a clear difference between the genome-wide

data of individuals belonging to different subgroups. Interestingly, the urban elite individuals

cluster genetically with modern West Europeans but the rural individuals with modern

Estonians which mirrors the economic and social structure of the time. We did find a few

individuals of mixed genetic ancestry, indicating that these social groups were not

completely endogamous, but the overall admixture between them was presumably limited.

Our purpose is to build a high density pre-modern database next to this of the Estonian

Biobank to understand the recent evolutionary processes in human evolution that have had

an impact on the health and structure of the population.

P29

The role of geomagnetic field intensity in late Quaternary human evolution

*J.E.T. Channell, **L. Vigliotti

* Department of Geological Sciences, University of Florida, Gainesville, FL 32611, USA ** Istituto di Scienze Marine, ISMAR-CNR, Via P. Gobetti 101, 40129 Bologna, Italy

It has long been speculated that biological evolution has been influenced by ultraviolet

radiation (UVR) reaching the Earth's surface, despite imprecise knowledge of the timing of

both UVR flux and evolutionary events. The past strength of Earth's dipole field provides a

proxy for UVR flux because of its role in maintaining stratospheric ozone. Over the last ~200

kyr, phylogeny based on mtDNA and Y-chromosomes in modern humans yields nodes and

bifurcations in evolution that can be linked to minima in geomagnetic field strength, implying

a long-term role for UVR in human evolution. Phylogeography demonstrates that when

migration occurs from one region to another, new mutations unique to that region

accumulate. Local adaption to different habitats, including changes in exposure to mutagenic

solar radiation, partially controlled by the magnetic field, are potential sources of

phenotypical divergence. As UVR is a known driver of numerous biological processes it is

possible that the migration to new environments alters selection pressures on the human

genome, and genetic studies have identified certain loci that were likely targets of this

selection. Relative paleointensity (RPI) records indicate several prominent low geomagnetic

intensity episodes implying enhanced UVR flux at Earth's surface at 190 ka (Iceland Basin

excursion), 100-120 ka (Blake excursions) and 41 ka (Laschamp excursion) that correspond

to key events in human evolution. Dated fossil finds of early AMH (Homo Kibish) and the

Time to the Most Recent Common Ancestor (TMRCA) based on both mtDNA and Y-

chromosomes imply branching in human phylogeny corresponding with the Iceland Basin

excursion at ~190 ka. The subsequent minimum during the Blake excursion (100-120ka)

coincides with another key step in human evolution coincident with marine isotope stage

(MIS) 5. The demise of Neanderthals at ~41 ka is now closely tied to the Laschamp

excursion. AMH survival at the 41-kyr barrier may be attributed to a variant (Val381) of the

aryl hydrocarbon receptor (AhR), an intracellular chemosensor that has a key role in the

evolutionary response to UVR flux. Neanderthals, Denisovan and non-human primates

encode the ancestral Ala381 variant that weakened their defense against mithocondrial

disfunction. Future improvement in the RPI chronology, further documentation of mammalian

extinction events, understanding the role of geomagnetic field in UVR flux and the role of Ahr

in modulating the deleterious effects of UVR in mammals, as well as improvements in

human phylogeny from mtDNA and Y-chromosomes, will clarify the role of the geomagnetic

field in mammalian evolution.

P30

French-style genetics v. 2.0: The “e-CohortE” project

Vogt Guillaume, Henri-Corto Stoekle´1,2,3, Marc Bollet*4,5, Aure´lie Cobat*6,7, Philippe Charlier*8,9, Oudy Ch. Bloch*4,10, Je´ro^me Flatot11, Cle´ment Draghi4, Vale´rie Tolyan4, Christian Herve´12, Pierre Desvaux13,14, Laurent Uzan15, Michae¨l Grynberg16, Alexandre Alcai¨s+6,7,17, Alain Tole´dano+4,5, Guillaume VogtO1,2,3,18

1 Neglected Human Genetics Laboratory, CNRGH-CEA, Evry, France 2 Centre National de Recherche en Ge´nomique Humaine (CNRGH), Direction de la recherche fondamentale, CEA, Institut de biologie Franc¸ois Jacob, Universite´ Paris Saclay, Evry, France 3 Institut Sapiens, Paris, France 4 Institut Rafae¨l, Maison de l'apre`s cancer, Levallois-Perret, France NA>> 5 Institut de Radiothe´rapie et de Radiochirurgie, H Hartmann, Levallois-Perret, France 6 Sorbonne Paris Cite´, Imagine Institute, Paris Descartes University, Paris, France 7 Laboratory of Human Genetics of Infectious Diseases, INSERM UMR 1163, Necker Branch, Paris, France 8 De´partement de la Recherche et de l'Enseignement, Muse´e du Quai Branly - Jacques Chirac, Paris, France 9 UVSQ (Laboratoire DANTE - EA 4498), Montigny-le-Bretonneux, France 10 Attorney, Paris, France 11 Socie´te Flatot, Paris, France 12 International Academy of Ethics, Medicine and Public Health, Paris Descartes University, Paris, France 13 Department of Urology, Cochin hospital, Paris, France 14 Paris Descartes University, Sorbonne Paris Cite´, Paris, France 15 Institut Coeur Effort Sante´, Paris, France 16 Service de Me´decine de la Reproduction & Pre´servation de la Fertilite´, Ho^pital Antoine Be´cle`re, Clamart, France 17 French National Reference Center for Primary Immune Deficiencies (CEREDIH), Necker-Enfants Malades University Hospital, Assistance Publique-Ho^pitaux de Paris, Paris, France 18 Neglected Human Genetics Laboratory, INSERM, Universite´ Paris Descartes, Paris, France

In the digital age, a genetics cohort has become much more than a simple means of

determining the cause of a disease. Two-sided markets, of which 23andMe, Ancestry DNA

and MyHeritage are the best known, have showed this perfectly over the last few years: a

cohort has become a means of producing massive amounts of data for medical, scientific

and commercial exploitation, and for genetic use in particular. French law does not currently

allow these foreign private companies to develop on French national terri- tory and also

forbids the creation of similar entities in France. However, at least in the- ory, this same law

does not preclude the creation of new types of cohorts in France inspired by the success of

two-sided markets but retaining features specific to the French healthcare management

system. We propose an optimal solution for France, for genomic studies associated with

multi-subject questionnaires, still purely theoretical for the moment: the development, with no

need for any change in the law, of France's own version of "Genetics v.2.0": "e-CohortE."

P31

Identifying positively selected genetic variants in whole-genome sequenced Chinese, Malay and Indian population datasets

Fadilla Ramadhani Wahyudi (1), Jasbir Kaur Dhaliwal (2), Farhang Aghakhanian (3), Sadequr Rahman (1), Teo Yik Ying (4), Michal Szpak (5), Yali Xue (5), Chris Tyler-Smith (5), Qasim Ayub (1,3)

(1) School of Science, Monash University Malaysia, 47500 Bandar Sunway, Selangor Darul Ehsan, Malaysia. (2) School of Information Technology, Monash University Malaysia, 47500 Bandar Sunway, Selangor Darul Ehsan, Malaysia. (3) Monash University Malaysia Genomics Facility, Tropical Medicine and Biology Multidisciplinary Platform, 47500 Bandar Sunway, Selangor Darul Ehsan, Malaysia. (4) Saw Swee Hock School of Public Health, National University of Singapore, Singapore. (5) Wellcome Sanger Institute, Hinxton, CB10 1SA, United Kingdom.

Whole genome sequencing projects have contributed towards the unbiased detection of

genomic variation in human populations. Detecting these genetic variants aids in the

understanding of human evolutionary adaptation and provides insight into how humans

interact with pathogens, the climate and their diet. This study leverages on three publicly

available high-coverage sequencing projects from Han Chinese (n = 90), Singaporean Malay

(n = 96) and Singaporean Indian (n = 35) population groups and uses Fine-Mapping of

Adaptation Variation (FineMAV), a statistical method that highlights population-specific

candidate variants underlying positive selection signal in these datasets using Combined

Annotation Dependent Depletion (CADD) scores. CADD is a tool that integrates various

functional annotations and condenses it into a single score which can predict the

deleteriousness of single nucleotide variants.

FineMAV was able to discriminate well-established positively selected variants in three

genes in the Han Chinese and Singapore Malay that were previously identified in the 1000

Genomes Project East Asian dataset. These included variants in the ectodysplasin A

receptor (EDAR; rs3827760), serine protease 53 (PRSS53; rs11150606) and the melanoma-

associated antigen E2 (MAGEE2; rs1343879). It also picked up the high frequency derived

variant (rs201075024) in the Singapore Indian population, which was the only outlier

identified in the 1000 Genomes Project South Asian populations. Although the Singaporean

Malays are genetically distinct from East and South Asian populations, they share

substantial genetic history with the Han Chinese, which resulted in fewer population-specific

signals in these populations, because FineMAV penalises allele sharing between

populations.

We are also developing a user-friendly interface to allow researchers to import variant files

from their populations of interest in order to determine and display genome-wide FineMAV

scores for their datasets. This will permit users to visualize the FineMAV scores graphically

using the University of California, Santa Cruz (UCSC) Human Genome Browser annotation

to enable the identification of functional positively selected candidate loci for experimental

follow-up.

P32

Denisovans in Sunda, Wallacea and Sahul but where are the fossils? Michael C Westaway The University of Queensland, Australia Genomic research now indicates that the first hominins to cross from Sunda (the continental shelf of Southeast Asia) into Wallacea and into northern Sahul (the continental landmass incorporating Papua New Guinea and Australia) were the Denisovans. Archaeological and fossil evidence for earlier hominins in Sahul is non-existent. This is not, however, the case for Wallacea where it has already been demonstrated that the small bodied archaic hominins, Homo floresiensis and Homo luzonensis, were able to cross large bodies of water. While some geneticists have argued that these small bodied hominins may represent the Denisovans, this idea has been dismissed by palaeoanthropologists. Interestingly two hominin hybridisation zones between Homo sapiens and Denisovans have now been identified in Sunda and Wallacea/Sahul. The most obvious contender for the Denisovans is in the late Pleistocene hominin record from the Solo River, Java, and I will provide here a reassessment of the morphology of these hominins in light of what we now know from a) the genomic record of past introgression events from Sunda, Wallaces and Sahul and b) morphological evidence for hybridisation from the primate record.

P33

Notes

P34

Notes

P35

Notes

Speaker & Delegate List

Sandra Ackerman

American Scientist Magazine

sandrajackerman@nc.rr.com

Anastasia Agdzhoyan

VIGG RAS

aagdzhoyan@gmail.com

Joshua Akey

Princeton University

jakey@princeton.edu

John Albert

Institute of Continuing Education

jsajalbones@aol.com

Mohamed Almarri

Sanger Institute

ma17@sanger.ac.uk

Isabel Alves

l'institut du thorax

isabel.alves@univ-nantes.fr

Kat Arney

First Create the Media

kat@firstcreatethemedia.com

Qasim Ayub

Monash University Malaysia

qa1@sanger.ac.uk

Oleg Balanovsky

Vavilov Institute of Genetics

balanovsky@inbox.ru

Katrin Berk

Westfalian Wilhelms University Muenster

k.berk@uni-muenster.de

Marilou Boddé

University of Cambridge

mmb52@cam.ac.uk

Alvis Brazma

EMBL - EBI

lorraine@ebi.ac.uk

Francesc Calafell

IBE (CSIC-UPF)

francesc.calafell@upf.edu

Rocio Caro Consuegra

Institute of Evolutionary Biology

rocio.caro@upf.edu

Susana Carvalho

University of Oxford

susana.carvalho@anthro.ox.ac.uk

Manjusha Chintalapati

UC, Berkeley

m_chintalapati@berkeley.edu

Jeremy Choin

Institut Pasteur

jeremy.choin@pasteur.fr

Chris Clarkson

University of Queensland

C.clarkson@uq.edu.au

Moisès Coll Macià

BiRC, Aarhus University

moicoll@birc.au.dk

David Comas

Universitat Pompeu Fabra

david.comas@upf.edu

Sebastian Cuadros Espinoza

Institut Pasteur

scuadros@pasteur.fr

Chiara De Rienzo

Private attendee

chiara.derienzo@gmail.com

Bianca De Sanctis

University of Cambridge

bddesanctis@gmail.com

Anna Di Rienzo

University of Chicago

dirienzo@uchicago.edu

Vera Domingues

Nature Ecology & Evolution

vera.domingues@nature.com

Arun Durvasula

UCLA

arun.durvasula@gmail.com

Anders Eriksson

University of Tartu

aeriksson75@gmail.com

Maria Ines Fariello

Universidad de la Republica

fariello@fing.edu.uy

Rosienne Farrugia

University of Malta

rosienne.farrugia@um.edu.mt

Robert Foley

University of Cambridge

raf10@cam.ac.uk

Neus Font Porterias

Universitat Pompeu Fabra

neus.font@upf.edu

George Foody

University of Huddersfield

george.foody@hud.ac.uk

Erik Gjesfjeld

University of Cambridge

eg540@cam.ac.uk

Russell Gray

Max Planck Institute for the Science of Human

History

gray@shh.mpg.de

Rainer Grün

Griffith University

rainer.grun@griffith.edu.au

Marc Haber

Wellcome Trust Sanger Institute

mh25@sanger.ac.uk

Pille Hallast

The Wellcome Trust Sanger Institute

ph8@sanger.ac.uk

Eadaoin Harney

Harvard University

harney@g.harvard.edu

Garrett Hellenthal

University College London

g.hellenthal@ucl.ac.uk

John Hooper

Oakleigh

johnhooper@videotron.ca

Clare Horscroft

University of Southampton

c.horscroft@soton.ac.uk

Ruoyun Hui

University of Cambridge

rh627@cam.ac.uk

Leonardo Iasi

MPI forEvolutionary Anthropology

leonardo_iasi@eva.mpg.de

Evelyn Jagoda

Harvard University

ejagoda@g.harvard.edu

Pierre Justeau

University of Huddersfield

pierre.justeau@hud.ac.uk

Toomas Kivisild

KU Leuven

toomas.kivisild@kuleuven.be

Jerry Lanchbury

Jerry Lanchbury

jerrylanchbury@btinternet.com

Maximilian Larena

Uppsala University

maximilian.larena@ebc.uu.se

Graham Lawton

New Scientist

graham.lawton@newscientist.com

Dang Liu

Max Planck Institute for Evolutionary

Anthropology

dang_liu@eva.mpg.de

Liisa Loog

University of Manchester/ University of

Oxford

liisaloog@gmail.com

Asifa Majid

University of York

asifa.majid@york.ac.uk

Nina Marchi

University of Bern (IEE)

nina.marchi@iee.unibe.ch

Davide Marnetto

University of Tartu

davide.marnetto@ut.ee

Rui Martiniano

University of Cambridge

rm890@cam.ac.uk

Maria Martinon Torres

CENIEH, Burgos, Spain

maria.martinon@cenieh.es

Alex Mas Sandoval

Imperial College of London

a.mas-sandoval@imperial.ac.uk

Iain Mathieson

University of Pennsylvania

mathi@pennmedicine.upenn.edu

Lisa Matisoo Smith

University of Otago

matisoo-smith@otago.ac.nz

Javier Mendoza Revilla

Institut Pasteur

javier.mendoza-revilla@pasteur.fr

Mait Metspalu

University of Tartu

mait.metspalu@ut.ee

Marta Mirazon Lahr

University of Cambridge

mbml1@cam.ac.uk

Hannah Moots

Stanford University

hmoots@stanford.edu

Gonzalo Oteo Garcia

University of Huddersfield

gonzalo.oteo-garcia@hud.ac.uk

Luca Pagani

Institute of Genomics, Uni Tartu

lp.lucapagani@gmail.com

Divya Ratan Popli

Max Planck Institute for Evolutionary

Anthropology

divyaratan_popli@eva.mpg.de

Javier Prado Martinez

Wellcome Trust Sanger Institute

jpm@sanger.ac.uk

Lluis Quintana Murci

Institut Pasteur - Collège de France

quintana@pasteur.fr

Simao Rodrigues

University of Huddersfield

u1775383@pgr.hud.ac.uk

Lara RUBIO ARAUNA

Institut Pasteur

lara.rubio-arauna@pasteur.fr

Adam Rutherford

BBC/UCL

adam.rutherford@gmail.com

Lehti Saag

University of Tartu

lehti.saag@ut.ee

Naruya Saitou

National Institute of Genetics

saitounr@nig.ac.jp

Tina Saupe

University of Tartu

tina.saupe@ut.ee; tsaupe@live.de

Christiana Scheib

University of Tartu

cls83@ut.ee

Carina Schlebusch

Uppsala University

carina.schlebusch@ebc.uu.se

Laure Segurel

CNRS (Musée de l'Homme)

lsegurel@mnhn.fr

Laurits Skov

Max Planck institute for evolutionary

anthropology

lauritsskov2@gmail.com

Penny Spikins

University of York

penny.spikins@york.ac.uk

Henri Corto Stoeklé

CEA

henri-corto.stoekle@cea.fr

Chris Stringer

Natural History Museum

c.stringer@nhm.ac.uk

Andrew Sugden

AAAS Science International

asugden@science-int.co.uk

Michal Szpak

Wellcome Trust Sanger Institute

ms30@sanger.ac.uk

Kristiina Tambets

University of Tartu

kristiina.tambets@ut.ee

Sarah Tishkoff

University of Pennsylvania

tishkoff@pennmedicine.upenn.edu

Chris Tyler Smith

The Wellcome Sanger Institute

cts@sanger.ac.uk

Simon Underdown

Oxford Brookes University

sunderdown@brookes.ac.uk

Luigi Vigliotti

CNR

luigi.vigliotti@bo.ismar.cnr.it

Guillaume Vogt

Inserm

guillaume.vogt@inserm.fr

Fadilla Ramadhani Wahyudi

Monash University Malaysia

fadilla.wahyudi@monash.edu

Kira Westaway

Macquarie University

kira.westaway@mq.edu.au

Michael Westaway

The University of Queensland

m.westaway@uq.edu.au

Yali Xue

Wellcome Sanger Institute

ylx@sanger.ac.uk

2019/20 CONFERENCES

Evolution and Ecology of Cancer NEW17-19 JulyCRISPR and Beyond: perturbations at scale to understand genomes NEW2-4 SeptemberRNA Informatics9-11 SeptemberOptimising Multistudy Integrative Research NEW18-20 SeptemberMechanisms and Evolution of Intergenerational Change NEW 24-26 SeptemberWorld Congress on Genetic Counselling2-4 OctoberPlant Genomes in a Changing Environment16-18 OctoberExploring Human Host-Microbiome Interactions in Health and Disease23-25 OctoberHuman Evolution30 October-1 NovemberEpigenomics of Common Diseases6-8 NovemberMitochondrial Medicine11-13 DecemberEvolutionary Systems Biology12-14 FebruaryOptimmunize: Improving the beneficial effects of vaccines NEW 19-21 FebruarySingle Cell Biology11-13 MarchGenomics of Brain Disorders18-20 MarchGenomics of Rare Diseases25-27 MarchProteomics in Cell Biology and Disease Mechanisms30 March-1 AprilLongitudinal Studies20-22 AprilNursing, Genomics and Healthcare NEW27-29 April

Antimicrobial Resistance – Genomes, Big Data and Emerging Technologies6-8 MayCurating the Clinical Genome20-22 MayHealthy Ageing27-29 May

COURSES LABORATORY COURSES

Train the Trainer: Capacity building for genomic surveillance of AMR in low- and middle-income countries NEW 6-11 OctoberMolecular Pathology and Diagnosis of Cancer17-22 NovemberDerivation and Culture of Human Induced Pluripotent Stem Cells9-13 DecemberGenomics and Clinical Microbiology19-24 JanuaryGenomics and Clinical Virology23-28 FebruaryGenetic Engineering of Mammalian Stem Cells15-27 MarchNext Generation Sequencing20-27 AprilLow Input Epigenomics NEW 8-15 May

COMPUTATIONAL COURSESGenetic Analysis of Population-based Association Studies23-27 SeptemberNext Generation Sequencing Bioinformatics1-7 DecemberMathematical Models for Infectious Disease Dynamics24 February-6 MarchFungal Pathogen Genomics10-15 May

LECTURE/DISCUSSION COURSESScience Policy: Improving the Uptake of Research into UK Policy19-21 August

@ACSCeventswellcomegenomecampus.org/coursesandconferences

Molecular Neurodegeneration2-6 DecemberClinical Genomics: Scientific Fundamentals and Future Directions29-31 JanuaryGenomic Practice for Genetic Counselling3-5 FebruaryPractical Aspects of Small Molecule Drug Discovery21-26 June

OVERSEAS COURSESNGS Analysis for Genetic Diseases5-6 November (Philippines) Working with Protozoan Parasite Database Resources10-15 November (Uruguay)Next Generation Sequencing Bioinformatics19-24 January (Chile)Next Generation Sequencing Bioinformatics9-14 February (Malaysia) Molecular Approaches to Clinical Microbiology in Africa21-27 March (The Gambia)

ONLINE COURSESBacterial Genomes: Disease Outbreaks and Antimicrobial ResistanceBacterial Genomes: From DNA to Protein Function Using BioinformaticsBacterial Genomes: Accessing and Analysing Microbial Genome Data Bacterial Genomes: Comparative Genomics using Artemis Comparison Tool (ACT) NEWWhat is Genetic Counselling? NEW

Please see our website for more details and scheduling of online courses

Index

Agdzhoyan, A P1 Majid, A S45

Akey, J S19 Marnetto, D P17

Almarri, M S55 Martiniano, R P18

Martinon-Torres, M S29

Balanovsky, O S47 Mas-Sandoval, A S57

Berk, K P2 Mathieson, I S13

Matisoo-Smith, L S3

Calafell, F P3 Mendoza Revilla, J P19

Caro Consuegra, R P4 Moots, H S39

Carvalho, S S27

Chintalapati, M S17 Oteo Garcia, G P20

Choin, J S7

Clarkson, C S53 Popli, D R P21

Coll Macià, M S9

Comas, D S49 Rodrigues, S P22

Cuadros Espinoza, S P5 Rubio Arauna, L P23

Di Rienzo, A S21 Saag, L P24

Durvasula, A S15 Saupe, T P25

Scheib, C S23

Fariello, M I P6 Schlebusch, C S51

Foley, R S1 Skov, L S33

Font Porterias, N P7 Spikins, P P26

Foody, G P8 Stringer, C S31

Szpak, M P27

Gray,R S43

Grün, R S35 Tambets, K P28

Tishkoff, S S5

Haber, M P9 Tyler Smith, C S59

Hallast, P P10

Harney, E P11 Underdown, S S41

Hellenthal, G S11

Horscroft, C P12 Vigliotti, L P29

Hui, R P13 Vogt, G P30

Iasi, L P14 Wahyudi, F R P31

Westaway, K S37

Jagoda, E S25 Westaway, M P32

Justeau, P P15

Liu, D P16

A

Hinxton Hall

B

C

Hinxton HallPompeiian RoomLibrary RoomGreen RoomRestaurantLounges/BarBedrooms 362-367/407-410

Conference CentreReception

Francis Crick AuditoriumJames Watson Pavilion

Rosalind Franklin PavilionLoft Room 1 and 2

Willow Court (A&B)B = 230-243

330-343A = 244-259

344-361

Tennis CourtTraining Suite

Mulberry Court (C)201-229301-329401-406

Fire Assembly Point

Designated Smoking Area

To Hinxton Village(Vehicle access via main exit to site)

Disabled

The SulstonLaboratories

EMBL - EBI

WestPavilion

RSF

The DataCentre

Wet Labs

The

Mo

rgan

Bu

ildin

g

EBI South

Reception

The CairnsPavilion

Conference Centre

@ACSCevents Wellcome Genome Campus Courses and Conferenceswellcomegenomecampus.org /coursesandconferences