The potential of advanced approaches for accurate ... · The potential of advanced approaches for accurate genotyping in grapevines N. ŠTAJNER 1, L. BITZ 2, B ŠKRLJ 1, J. JAKŠE

The potential of advanced approaches for accurate genotyping in grapevines

N. ŠTAJNER1, L. BITZ2, B ŠKRLJ1, J. JAKŠE1, R. BACILIERI3 and B. JAVORNIK11 University Of Ljubljana, Biotechnical Faculty, Agronomy Department, Slovenia

2 Natural Resources Institute Finland, Alimentum – Myllytie 1, 31600 Jokioinen, Finland3 UMR AGAP, Equipe Diversité Et Adaptation De La Vigne Et Des Espèces Méditerranéennes, INRA, Montpellier, France

Objective: GenotypingVariety identification

• grape growers • winemakers • regulatory authorities • consumers• germplasm collections

AREA Conference - Belgrade, 18-20 April 2016

• ampelography• chemical and

biochemical methods• molecular methods

• RFLP• RAPD• AFLP• SNP• SSR

Microsatellite markers• highly abundant in the genome, • distributed throughout the genome• highly polymorphic (replication slippage once per

1,000 generations)


TATATATATA

GTCGTCGTCGTCGTC

High throughput analysis of grape genetic diversity

•Laucou et al., 2011, TAG• 4,370 accessions (Vitis vinifera subsp. sativa (3,727), V. vinifera subsp. sylvestris (80),

interspecific hybrids (364), and rootstocks (199) - INRA collection)• 20 SSR markers•→ 2,836 SSR unique genotypes


Cipriani et al., 2010, TAG

• 1,148 accessions (from the Italian national repositories)• genotyped at 34 microsatellite loci→745 unique genotypes

Emanuelli et al. 2013, BMC Plant Biology

• 2,273 accessions (from the collection San Michaele all'Adige in Italy )• 22 microsatellites and 384 SNPs→ 1,085 unique genotypes

Towards the preservation of autochthonous grapevine

varieties in WBC

COLLECTION of autochthonous varieties

• National grapevine collections • Local vineyards• Nursuries or individual farms


Sampling in WBC

• Slovenia (3 locat, 52 sampl)• BIH (9 locat, 80 sampl.) • Montenegro (8 locat, 24 sampl) • Serbia (1 locat, 62 sampl) • Macedonia (7 locat,15 sampl)


233 grapevine samples


autochthonous/local grapevines

MATERIAL

Main agronomic features


Photo 1: Bagrina

Photo 2: Bakator beli

Photo 2: BelaDinka

Photo 4: Medenac beli

•ampelographic descriptors:•grape berry / bunch / leaf


•ampelographic descriptors:•grape berry / bunch / leaf


AIM OF THE PROJECT

MOLECULAR CHARACTERIZATION

• Establish microsatellite profiles• Identify genotypes• Determine synonyms and homonyms• Evaluate genetic relationships• Revealed genetic structuring


Comparative analysis (intra- and inter-group)

Intra-group analysis22 microsatellites


233 samples / 147 uniqueUNIQUE (63%)

• Misnomers (planting mistakes) (6%)• Synonyms (8%)• Associations of duplicates/clones (23%)

REDUNDANCY (37%)

Same name, same genotype, different locationDuplicates (23%)

Belo Zimsko MAK = Belo Zimsko SRBBena I BIH = Bena IX BIHBlatina I BIH = Blatina SRBDobrogostina I BIH = Dobrogostina IX BIHKambuša I = Kambuša IXKratošija I MNE = Kratošija II MNE = Kratošija IV MNEKratošija MAK = Kratošija SRBKrkošija I = Krkošija IXPlavka I BIH = Plavka IX BIHPlavka IV BIH = Plavka VI BIHProkupac IX BIH = Prokupac III MNE = Prokupac IV MNERadovača II BIH = Radovača III BIHRefošk SLO = Star Refošk SLO = Refošk Istra SLO = Refošk Teranovka SLOSmederevka BIH = Smederevka MAK = Smederevka SRBVranac I BIH = Vranac SRB = Vranac MAKVranac V MNE = Vranac VI MNEŽilavka VIIBIH =Žilavka VIII BIH = Žilavka MAK = Žilavka IX MNE = Žilavka SRBŽlozder I BIH = Žlozder IX BIHŽupljanka I BIH = Župljanka SRB


Same name, different genotype, different location

Misnomers –planting/naming mistakes (6%)


Bena III BIH ≠ (Bena I BIH = Bena IX BIH)

Blatina IX BIH ≠ (Blatina I BIH = Blatina SRB)Krkošija III BIH = (Krkošija IX BIH = Krkošija SRB)

Menigovka I BIH ≠ Menigovka II BIH

Podbil I BIH ≠ Podbil IX BIH

Prokupac SRB ≠ (Prokupac III MNE = Prokupac IV MNE = Prokupac IX BIH)

Radovača IX BIH ≠ (Radovača II BIH = Radovača III BIH)

Razaklija IX BIH ≠ (Rezaklija V BIH = Rezaklija VI MNE)

Ružica V MNE ≠ Ružica VI MNE ≠ Ružica SRB

(Kratošija I MNE = Kratošija II MNE = Kratošija IV) ≠ (Kratošija MAK = Kratošija SRB)

(Vranac I BIH = Vranac SRB = Vranac MAK) ≠ (Vranac V MNE = Vranac VI MNE)

Different name, same genotypeSynonyms (8%)


Begljerka Bela MAK = Bele Kozije Sise SRB = Bijela Prošip I BIH = Drenak Beli SRBBela Zgodnja SLO = Petrovka IX BIHBena III BIH = Krkošija I BIH = Krkošija IX BIH = Krkošija SRBBlatina I BIH = Stara Blatina I BIH = Stara Blatina VII = Stara Blatina VIIIBlatina VII BIH = Blatina VIII BIH = Plavka I BIH = Plavka IX BIHBlatina IX = Krkošija III BIH=Žilavka BIH I=Žilavka II= Žilavka III= Žilavka V= Žilavka VII= Žilavka VIII= Žilavka MAK =Žuta Žilavka I BIHCrljenak IX BIH = Kratošija I MNE = Kratošija II MNE = Kratošija IV MNE = Vranac III MNE = Vranac IV MNECrna Prošip I BIH = Dobrogostina I BIH = Dobrogostina IX BIHČauš MAK = Čauš Crveni SRBDalmatinka VI BIH = Kambuša I BIH = Kambuša IX BIH = Podbil IX BIHFrankovka SRB = Sura Lisičina SRBKadarun II BIH = Kadarun IV BIH = Podbil I BIH = Surac IV BIHKadarun Bijeli BIH = Smederevka BIH= Smederevka MAK = Smederevka SRBMala Blatina I BIH = Prošip I BIHMala Blatina VII BIH = Mala Blatina VIII BIH= Vranac I BIH = Vranec MAK = Vranac SRBOhridsko Crno MAK = Stanušina MAKPlavka IV BIH = Plavka VI BIHProkupac IX BIH = Prokupac III MNE = Prokupac IV MNE = Surac VIRezaklija VI MNE = Rezaklija V BIHRužica IV MNE = Slankamenka Crvena SRB

SYNONYMSe.g. Smederevka SRB = Kadarun Bijeli BIHe.g. Stanušina = Ohridsko crno MKde.g. Žilavka BIH = Žuta Žilavka BIH

TRUE-TO-TYPEe.g. Smederevka SRB = Smederevka MNE = Smederevka BIHe.g. Žilavka BIH = Žilavka MKD = Žilavka SRB

32 groups of SYNONYMS

HOMONYMSe.g. Prokupac SRB ≠ Prokupac SRB ≠ Prokupac (DVC)

3 groups of HOMONYMS

MISTAKESe.g. Krkošija III BIH ≠ (Krkošija IX BIH = Krkošija SRB)e.g. Menigovka I BIH ≠ Menigovka II BIH

10 groups of MISNOMERS

70 groups of TRU-TO-TYPE

147 UNIQUE GENOTYPES AREA Conference - Belgrade, 18-20 April

2016

ANANLYSIS OF GENETIC RELATEDNESS

Nei genetic distance:• the highest genetic distance

between SLO and MAK cultivars • the lowest between SLO and SRB

cultivars. AREA Conference - Belgrade, 18-20 April

2016

I GROUP

II GROUP

III GROUP

IV GROUP

V GROUP

VI GROUP

VII GROUP

VIII GROUP

IX GROUP

Proportion of shared alleles among Balkan cultivars = 35 %

Genotypes clustered into nine groups:

MAK grapevines ≠ groups I, II, IV, VIII, IXEuropean cultivars (group IV) ≠ MAK, MNE

BIH, SRB, SLO cultivars equally dispersed among all nine clusters

MNE, MAK cultivars = separated gene pool

RUPESTRIS

Core collection –entire allelic richness (242 alleles)

• 63 genotypes outof 147 (43%)

•• 50% genotypes

from each country


STRUCTURE • assigned to a cluster when 85% or more of their

inferred genome belonged to the cluster groups• identified according to the classification of Negrul:• 1) representatives from 4 countries, excluding Slovenia• 2) group lack Macedonian and Montenegrin genotypes • 3) grapevines from Montenegro, Macedonia and BiH• 4) representatives from Western Europe and Slovenia


Pontica Balcanica Pontica Occidentalis GallicaOrientalis Caspica

Inter- comparative analysis

• to standardize allele scoring by defining reference alleles

• well-known reference cultivars• Barbera, Cabernet Sauvignon, Chardonnay, Merlot, Pinot Noir, Sultanine, and Touriga National

• Compared only some of micorsatellite markers(VVS2, VVMD5, VVMD7, VVMD27, ssrVrZAG62, ssrVrZAG79)


Standardization

Inter-group analysis


Bojanka MAK = Garnacho (or Morrastel-Bouschet) = Grand Noir (University of California Davis collection) Crven Valandovski Drenok = Geisstutte (Sefc et al., 2000) = Cornichon Violet (Davis) Frankovka SRB = Sura Lisičina SRB =Franconia (Grando, 2000) = Limberger (Davis) (Galet,

2000) Kadarka Bela SRB = Kadarka Byala BU, Slankamenka Crvena SRB = Pamid BU in

Smederevka = Dimyat BU (Bulgarian cultivars genotyped by Dhambazova et al. (2009) Furmint SRB= Knipperle (Davis) = Ortlieber (Sefc et al., 2000). Alicante Bouchet = Kambuša/Dalmatinka = Alicante Henri Bouchet (Lopes et al., 2006),

Garnacha Tinta (de Mattia et al., 2009) = Garnacha Tintorea (Sefc et al., 2000; Ibanez et al., 2003). Menigovka = Italia = Perd’e Sali (Zecca et al. (2010) Kratošija = Zinfandel in Primitivo (Davis) (Calo et al. (2008). Muskat Krokan SRB = Muscat Fleur d’Oranger (Gianenetto et al. (2010) Plemenka Nova SRB = Pirovano 2 = Angelo Pirovano Portugizac SRB = Portugais Bleu (Davis) Plavka BIH = Plavina HR (Maletić et al., 1999) = Brajdica = Plavina Crna (Davis) Tamjanika Crna SRB = Muškat Ruža Porečki (Maletić et al., 1999) = Moscato Rosa (Crespan

et al., 1999)

Variety

Country

Prime name DNA reference Putative synonymes

Bela Zgodnja SLO Perla von Csaba Sefc et al. 1998, Ibanez et al. 2009, Santana et al. 2010, UCD

Cilibarka SRB CilibarkaGrk BIH ?, distinct from Grk in

Pejic et al. (2000) and in CVD

NN BIH Sljiva IX (below), except in VVMD28NPS1 BIH Diretta Bianca (Carimi et al. 2010)Prosip Bijela BIH Vela Pergolla Maletic et al. 1999 ; Sefc et

al. 2001Volovnik (Stajner et al. 2008)

Radovaca MNE Afus Ali Dattier de Beyrouth (UCD) ; Mennavacca (Zulini et al. 2002); Regina (Crespan et al. 1999)

Ruzica VI MNE Pamid Dzhambazova et al. 2009 ; BD

Slankamenka (below)

Ruzica V MNE Garvan Dzhambazova et al. 2009SlankamenkaCrvena

SRB Pamid Dzhambazova et al. 2009 ; BD

Ruzica VI (above)??????.. . .

147 UNIQUE GENOTYPES

“NEW” IDENTITY

TRUE-TO-TYPEHOMONYMS

DISCOVERIES OF IDENTITY

“NEW” IDENTITY

DISCOVERY OF MISTAKES

110 UNIQUE GENOTYPES


Ruzica VI MNE

Which is RUZICA ???

Ruzica SRB

Ruzica IV MNE

Slankamenka Crvena SRB

Gavran (SRB)

Pamid (BNC)

Garvan (BNC)

Unique Genotype

≠≠

=≠

Some new questions …


and answers ….

Linking of two sets of SSR data


1,130 grapevine genotypes held at the INRA Vassal,

France

14 SSR markers

110 uniquegenotypes fromWestern Balkan

region

Laucou et al., 2011, TAGLacombe et al., 2013, TAGBacilieri et al., 2013, BMC Plant Biol.

Synonyms/counterpartsBalkan sample INRA sample (LACOMBE et al. 2013)‘Bela Zgodnja’ (SVN) ‘Perle de Csaba’ (#1069) (HUN)‘Čauš Bel’ (MKD) ‘Chaouch rose’ (#1674) (TUR)‘Drenak’ (BIH) ‘Rosa menna di vacca’ (#1662) (ROU)‘Drenak Beli’ (SRB) ‘Coarna alba’ (#749) (ROU)‘Drenak Crni’ (SRB) ‘Darkaia noir’ (#728) (MAR)‘Elezovka’ (BIH) ‘Chaouch blanc’ (#1673) (TUR)‘Furmint’ (SRB) ‘Knipperle’ (#283) (FRA)‘Gnjet’ (SVN) ‘Piccola nera’ (#2387) (ITA)‘Harslevelu’ (SRB) ‘Harslevelu’ (#1609) (HUN)‘Kratosija’ (MNE, MKD) ‘Primitivo’ = ‘Zinfandel’ (#1277) (ITA)‘Marburger’ (SVN) ‘Neuburger’ (#2172) (AUT)‘Menigovka’ (BIH) ‘Italia’ = ‘Pirovano’ 65 (#926) (ITA)‘Muskat Ruza’ (SRB) ‘Muscat rouge de Madère’ = ‘Moscato violetto’ (#576) (ITA)‘Plavka’ (BIH) ‘Plavina crna’ (#1843) (HRV)‘Prokupac’ (BIH) ‘Prokupac’ (#1630) (SCG)‘Radovaca’ (MNE) ‘Dattier de Beyrouth’=’Afuz Ali’ (#634) (TUR)‘Refosk’ (SVN) ‘Terrano’ (#1293) (ITA)‘Rezaklija’ (BIH) ‘Razachie rosie’ (#1887) (ROU)‘Ruzica’ (SRB) ‘Kovidinka’ (#1578) (YUG)‘Šipon’ (SVN) ‘Furmint’ (#25) (HUN)‘Smederevka’ (SRB) ‘Dimiat’ (#1666) (BGR)‘Srem Zelenika’ (SRB) ‘Szeremi zöld’ (#1623) (HUN)‘Trbljan Beli’ (SRB) ‘Mostosa = ‘Empibotte bianco’ (#2054) (ITA)‘Žilavka’ (BIH) ‘Zilavka’ (#1637) (BIH)


ParentagesOffspring First candidate Second candidate

Trio loci compared

‘Dobrogostina’ (BIH) = ‘Stara Žilavka’ (BIH)

‘Krkošija’ (BIH) ‘Rosenmuskat ‘(#3550) (DEU) 14

‘Godominka’ (SRB) ‘Muscat Ottonel’ (#280) (FRA)‘Smederevka’ (SRB)=’Dimiat’ (#1666) (BGR)

14

‘Gročanka’ (SRB)‘Bela Zgodnja’ (SVN)= ‘Perle de Csaba’ (#1069) (HUN)

‘Radovaca’ (MNE)=‘Dattier de Beyrouth’=Afuz Ali’ (#634) (TUR)

15

‘Krivaja’ (SRB)‘Drenak (BIH)=‘Rosa menna di vacca’ (#1662) (ROU)

Rezaklija’ (BIH)=’Razachie rosie’ (#1887) (ROU)

14

‘Manastirsko Belo’ (MKD)‘Drenak (BIH)=‘Rosa menna di vacca’ (#1662) (ROU)

‘Heptakilo’ (#743) (GRC) 14

‘Polšakica’ (SVN) ‘Malvasia del Chianti’ (#1352) (ITA) ‘Prošip Bijela’ (BIH) 14

‘Prokupac’ (SRB)‘Prokupac’ (BIH)=‘Prokupac’ (#1630) (SRB)

‘Refošk’ (SVN)=’Terrano’ (#1293) (ITA)

14

‘Šljiva’ (BIH)‘Drenak Beli’ (SRB)=‘Coarna alba’ (#749) (ROU)

‘Heptakilo’ (#743) (GRC) 14

‘Žilavka’ (BIH) ‘Albaimputotato’ (#44) (ROU) ‘Dobrogostina’ (BIH) 14

‘Bagrina’ (SRB) ‘Beli Medenac’ (SRB) ‘Braghina=Dinkavoros’ (#1670) (HUN) 13

‘Kreaca’ (SRB)‘Drenak Beli’ (SRB)=‘Coarna alba’ (#749) (ROU) ‘Plavac Mali’ (#3144) (HRV) 14

‘Prošip’ (BIH)‘Drenak Beli’ (SRB)=‘Coarna alba’ (#749) (ROU) ‘Gouaisblanc’=’Heunischweiss’(#211) (FRA) 14



Origin/group 1 2 3 4AFG 100,0 0,0 0,0 0,0ARG 26,7 0,0 73,3 0,0ARM 62,5 0,0 37,5 0,0AUS 27,3 9,1 54,5 9,1AUT 23,1 38,5 7,7 30,8AZE 0,0 0,0 100,0 0,0BEL 0,0 20,0 80,0 0,0BGR 18,8 25,0 56,3 0,0BIH 19,0 76,2 4,8 0,0CHE 0,0 0,0 0,0 100,0CYP 50,0 0,0 50,0 0,0CZE 0,0 0,0 50,0 50,0DEU 3,6 9,1 9,1 78,2DZA 85,7 0,0 14,3 0,0ESP 63,2 0,0 21,1 15,8FRA 18,8 24,1 11,9 45,2GBR 0,0 0,0 100,0 0,0GEO 50,0 50,0 0,0 0,0GRC 36,4 27,3 36,4 0,0HRV 40,0 50,0 10,0 0,0HUN 8,2 58,8 28,2 4,7IRN 42,9 0,0 42,9 14,3ISR 10,0 10,0 80,0 0,0ITA 20,8 24,0 49,0 6,3LBN 0,0 0,0 100,0 0,0MAR 57,1 0,0 28,6 14,3MDA 0,0 50,0 50,0 0,0MEX 100,0 0,0 0,0 0,0MKD 0,0 75,0 25,0 0,0MNE 0,0 100,0 0,0 0,0nd 43,8 6,3 37,5 12,5NLD 0,0 0,0 100,0 0,0PER 0,0 0,0 100,0 0,0PRT 53,4 2,7 21,9 21,9ROU 11,1 44,4 40,7 3,7RUS 42,9 50,0 7,1 0,0SCG 0,0 25,0 75,0 0,0SRB 5,6 72,2 16,7 5,6SVN 9,1 81,8 9,1 0,0SYR 60,0 0,0 40,0 0,0TCH 0,0 33,3 0,0 66,7TJK 100,0 0,0 0,0 0,0TKM 100,0 0,0 0,0 0,0TUN 50,0 12,5 37,5 0,0TUR 20,0 60,0 20,0 0,0UKR 40,0 33,3 20,0 6,7URS 16,7 25,0 50,0 8,3USA 31,8 0,0 63,6 4,5UZB 63,6 0,0 36,4 0,0YUG 0,0 100,0 0,0 0,0ZAF 8,3 0,0 75,0 16,7


MNE 100

SVN 82

BIH 76

MKD 75

SRB 72

YUG 100

TUR 60

HUN 59

RUS 50

HRV 50

Characterization of the STRUCTURE groups according to Geography And Use.Bacilieri Et Al. BMC Plant Biology 2013 13:25


Principal Component Analysis (PCA)


Far- and Middle-East

Western and Central Europe

Balkan and East Europe

Principal Component Analysis (PCA)









Ruzica VI MNE

Is this true-to-type RUZICA ???

Ruzica SRB

Ruzica IV MNE

Slankamenka Crvena SRB

Pamid (BNC)

Garvan (BNC)

Unique Genotype

≠≠

=WHO IS RUZICA ?!

XKovidinka (#1578)

NO!AREA Conference - Belgrade, 18-20 April

2016

≠

What about Gavran (SRB)



Conclusions• 233 WB cultivars 57 unique

• 40 accessions (83%) are structured within group of Balkan and Eastern genotypes.

• valuable for conservation, • future investigations and • breeding purposes.


8%9%

83%

A3-Western Europe group

B3-Far- and Middle-East group

C3-Balkan and Eastern Europe

CONCLUSION


High-throughput sequencingtechnology

NGS-SSR-genotyping protocol

• using Ion Proton or Ion PGM sequencers or MiniSeqsystem of Illumina1) Library preparation2) Sequencing (Ion Plus Fragment Library kit)3) Mapping of the reads to loci specific sequences; 4) Trimming of primers to obtain full length sequences of

microsatellite amplicons, 5) Counting of repeats, 6) Analysis of the frequency of the discovered

microsatellites to determine true alleles of the genotypes.


Locus VVS2


Output – Ion PGMChardonnay_sample Counts PercentagesTotal reads raw 286.214 100%Total nucleotides 44.624.468 100%Total trimmed reads 269.756 94.25%Total trimmed nucleotides 42.649.743 95.57%Mapped reads 269.150 94.04% (of total)Not mapped reads 606 0.21% (of total)


LociDe-novo assembly

Reference/Loci name

Reference length

Mapped reads

Non-perfect matches

Average coverage

Total nucleotides in

data setAllele1 length Allele1 count

Allele2 length Allele2 count

VVS2 137 27.079 18255 19.740.32 2.754.490 144 3995 138 2274

VVMD5 227 9.887 9874 8.451.77 1.999.474 233 5054

VVMD7 246 35.960 30730 26.393.76 6.371.400 242 2967 238 8864

VVMD25 241 33.369 23615 22.921.37 5.623.129 241 801 239 1500

VVMD27 180 16.291 14069 11.068.31 2.054.445 186 983 180 665

VVMD32 271 52.179 40658 28.917.14 8.689.772 250 25

VrZAG62 214 34.700 25025 15.907.08 3.423.149 196 3004 186 887

VrZAG79 258 26.461 26248 17.798.42 4.623.334 242 4315


Microsatellite stuttering

Frequency of occurence


Validation tests - CE vs. NGS


P values generated using a Chi-square test to compare the CE peak height ratios to the NGS sequence count ratios

VVMD 32

High-throughput sequencingtechnology

• The maximum output of the Ion PGM sequencer (~5 M) enable us to analyze simultaneously

• 96 genotypes at 15 loci with an average length of 250 bp

• resulting in coverage of 4 000 x for each locus specific sequence


Genotyping-by-Sequencing(GBS)

Sequences are used simultaneously to detect and score SNPs

Genotyping-by-Sequencing

• the next generation of molecular markers

• reduced representation sequencing method

• A shift from uniplex to multiplex assays that allow

the simultaneous analysis of multiple markers

• variant discovery (SNPs, microsatellites, etc.)• By-passing the entire classical marker assay

development stage

Applications

• GWAS• MAS• Genetic mapping• Genomic Selection – Breeding applications• Conservation• QTL analyses• diversity studies

Genotyping by sequencing (GBS) in any large genomespecies requires reduction of genome complexity

I. – restriction site(Technically less challenging)

• no prior seq data about genome

• no prior identified polymorphisms, SNP

• with RE reduce the complexity of the genome

• identification of markers ‚de novo‘

II. – target enrichment(AmpliSeq approach)

• known data about genome, transcriptomes etc.

• the polymorphism were identified

• design of primers in targetregions of polymorphic sites

• up to 6000 loci can beamplified simultaneusly

Poland et al., 2012

Approach I: Restriction

1) restriction with RE

2) ligation of universal adapters

3) amplification and sequencing

By choosing appropriate REs, repetitive regions of genomes can be avoided, and lower copy regions can be targeted with two to three fold higher efficiency

Approach II - Target enrichment

Transcriptoms of fewgenotypes:Celeia WyeTargetAppolo Nugget TaurusMagnum Merkur Tettnanger

Detect Polymorphic sites among mapped reads

CLC Genomics workbench

Tool 1

Tool 2

reference genome

Appropriate variable sites

ResultsCeleia-T Celeia-V WyeTarget Taurus Appolo Nugget Magnum Merkur Tettnanger

Technology Illumina PE 100 Illumina 50 bp Illumina 50 bp Illumina PE100Illumina PE100

Illumina PE 100 IlluminaPE100 454 454

Cleaned Reads 304,410,220 414,356,977 403,695,640 108,900,006 53,495,846 23,468,860 18,515,373 296,487 210,129

No. of bases 29,582,070,478 20,717,848,850 20,184,782,000 10,998,900,606 5,403,080,446 2,370,354,860 1,870,052,673 84,603,345 56,456,211Mapped reads 161,119,954 227,880,067 160,481,003 70,319,435 37,343,753 16,689,802 13,023,120 149,763 210,129

No. of bases 15599356755 11,394,003,350 8,024,050,150 7,102,262,9353,771,719,053 1,685,670,002 1,315,335,120 40,620,826 56,456,211

Percentage of all 52.93% 55.00% 39.75% 64.57% 69.81% 71.11% 70.34% 50.51% 49.77%Not mapped 143290266 186,476,910 243,214,637 38,580,571 16,152,093 6,779,058 5,492,253 146,724 190807Percentage of all 47.07% 45.00% 60.25% 35.43% 30.19% 28.89% 29.66% 49.49% 47.60%Reads in pairs 83569798 / / 53,469,574 28,706,978 12,658,482 10,153,922 / /

Broken paired reads 74958798 / / 15,039,022 7,695,499 3,587,412 2,527,208 / /

Variants 265,712 246,086 191,236 152,132 80,201 29,030 21,392 534 1012variants without N 264118 220781 183227 151990 80104 29030 21373 532 1010Ns 1594 25305 8009 142 97 0 19 2 2Homozygous 126886 121357 90503 52414 42304 12149 8928 236 595Heterozygous 137232 99424 92724 99576 37800 16881 12445 296 415Unique references 12385 14804 13708 10502/10495 7923/7921 4128 3240/3238 158 276

different polymorphisms within

different genotypes

Cross-section of polymorphisms

• Highly polymorphic markers– with high quality– high coverage– good allelic ratio

Two conditions

1. polymorphism present in all genotypes

2. heterozygous SNP = for mapping studies

1992 of heterozygous SNPs/variations

referenca identifikator Polimorf. Apollo Celeia NuggetMagnum Taurus WyeTarget

LD151021.1 10005 SNV Heterozygous Homo Heterozygous Heterozygous /

LD157464.1 10016 SNV Heterozygous / Heterozygous Heterozygous Heterozygous

LD163320.1 10025 SNV Heterozygous Homo Homo Homo Homo

LD133157.1 10064 SNV Heterozygous / / / /

LD154264.1 10065 SNV Heterozygous Heterozygous Heterozygous Heterozygous Heterozygous





LD170702.1 10078 Insertion Heterozygous Heterozygous Heterozygous Heterozygous Heterozygous











Determination of target/flankingregions

Preliminary testing with Sanger sequencing

1) Primerjs hetero (5 genotypes – heterozyg. SNPs)LD132484-F CGAAATTCCACCAAATCTGCLD132484-R GTACCTGCTGCCAATGGAACLD132578-F TCACCACAGCCCAATTAACALD132578-R GGAGGAGATATTCCCGAACCLD132627-F GCCCTGTTGACTTGCTTGATLD132627-R GCAATTAGCAAACACGAGGALD132933-F AAGGAGCCAAAGCATTCTCALD132933-R CAAGGGGTAACATCCCCATALD133023-F AATAGGAACCAGGAGCAGCALD133023-R GAACCAGCCCATGTGTTGTALD133025-F GGAGGTAAAAGCGCATAGCALD133025-R CCAGCCAGGGTATCTATTGCLD133146-F GCTTTCTCAATTGTCCCCTGTLD133146-R TGTTCCAGGAAACACAACTGALD133184-F TCATCAGGCTCCTCAGTACGLD133184-R AGGTGTTAAGCACGGCTTTTLD133310-F TGAAAGTTGAAGCCAAATAAGGLD133310-R TTTATATATTTCTCTAAAATGGCTGGALD133373-F CCTGTCATGACCTCCACCTTLD133373-R GCCAATGGGTCTGATGACTT

2) Primers SNPs in Celei a and WTcontig3-2732-F GACTGCGTGAAGATGGTGAAcontig3-2732-R TCAAGTAGGGACGGGTTACGcontig5-4227-F GGTGCCAAGATTTGATAGGGcontig5-4227-R CCTGGTGTCCAACAGGTTTAGLD132744-F CCACCTGAGTTCTACACCTTCCLD132744-R ATTGATCGGTTGAACCCTGALD132791-F TCAAGGTGGACTTTGGATCTTTLD132791-R TCACAAAGGATTCCAGCTCALD132865-F CCGACGAAGACTGATGCTCLD132865-R TACCTTCGAGCTCTGGCAACLD133125-F TCCCAAGGAGAAAGCTGAGALD133125-R CCTTGTTTTGAGCCGAGAATLD133184_CeWy 2-F TCCGGATATCAACACCATCALD133184_CeWy 2-R TCTCAGCAATTGCAGCTAACTCLD134063-F TTCAGAGAAGATAGAGAGAAAGTGAAALD134063-R TCAACTTCAATAAACACTATTCAATCALD134219-F GCACGGGTTTCTTCTTTTGALD134219-R GGGTTTGGGTTTGGATTCATLD134913-F ATAAACCGGATTGGTGTGGALD134913-R CAGCTGTGAGTCTGATGTGTGALD135083-F AACTAAGATTAAAACCCATAATTGAAALD135083-R GCCTCTCAAGTGTTTGTTGG

3) Primers-controlLD151021-F GTTGCTGAGGCTTCTGGATTLD151021-R GCGCTGAGTGCTCCATTAAGLD157464-F CCCTCTTCAGTCTGGTCGAGLD157464-R GATGGTCCTGCTCCATCTTGLD134176-F GAGGAGGTATCCACGCCTTCLD134176-R GCGACGCCGTTAGAATAATA

Case 1

Polymorphism at 4 cultivars -

all SNPs are heterozygous

(TC)

Case 2Mappingfamiliy

WT x 2/1(GA x AA)

in7 križancev F1

(GA ali AA)

Take home message• Microsatellites are considered as a gold standard in the

field but there is still scope for the improvement in terms of speed and accuracy

• Given the amount of coverage it would be possible to sequence around 1000 PCR-amplified loci x 100 samples in one Ion Proton sequencing run.

• The current prices (and the time needed) are approx. half lower in comparison to Sanger sequencing and fragment analysis approach (CE)

• Looking forward, high-density markers from NGS systems (like GBS) will soon be applied to almost every genomic question as they are getting more robust and economical each year


Acknowledgments

• SEE-ERA.NET Plus project• Slovenian Research Agency• FA COST Action FA1003


University of Ljubljana, Biotechnical faculty Center for

plant breeding and genetics

Thank you!



višek …

N. ŠTAJNER1, L. BITZ1,3, R. BACILIERI2, B. JAVORNIK1 et al.1 University Of Ljubljana, Biotechnical Faculty, Agronomy Department, Slovenia

2 UMR AGAP, Equipe Diversité Et Adaptation De La Vigne Et Des Espèces Méditerranéennes, INRA, Montpellier, France 3 Natural Resources Institute Finland, Alimentum – Myllytie 1, 31600 Jokioinen, Finland

STRUCTURE No. 1

• 112 ‘Balkan’ genotypes, • the hierarchical levels of structure clusters

could hardly be recognized. • Clusters of admixed origin and usage (wine vs.

table)


Long term impacts and practical implications

• Story of Žilavka – can it become successful outside borders?

Important for economy of Balkan countries? (particluarly BIH?)If well characterized might become a local brend.

We obtained: • truenes-to-genotype & truenes-to-type; • intravarietal genetic polimorphism (AFLP); • analysis of putative clonal variability (AFLP + SSR); • we established close genetic relatedness with other local cultivars (Dobrogostina; Crna Prosip

& Stara Žilavka) and strong differentiation from other cultivars clones or siblings? evidence of local breeding efforts?

• Is Žilavke bred in Herzegovina? • Parentageship is finally elucidated: Žilavka = Albaimputotato (Romania) × Dobrogostina (BIH)


Activities and objectives

• Molecular characterization and evaluation of genetic relationships– Microsatellite genotyping (22 loci) and data analysis

• Determination of synonyms and homonyms and establishment of SSR database– Comparative analysis (intra- and inter-group)


How to solve Synonyms ?• Grapevine scions were shared all over the world by different travelers having

diverse intention for use and were obtaining local names often compeltely different from what is called prime name.

• World database with standardized gentic profiles prooved excellent tool in solving these complicated puzzles generated over times.

• VIVC is updating almost daily in 2015• therefore our results might change accordingly

Accession OriginPrime name given in VIVC

Pending prime name DNA reference

Country of collection

Berry color Comment

Begljerka Crna Macedonia Begljerka Crna WBVD; Zulj Mihaljevicet al. 2013 MAK

Noir Confirmed by curator Beleski Klime

Bela Dinka Serbia Bela Dinka Dzhambazova et al.2012; WBVD SRB

Blanc Unique genotype

Dolgi Grozdi Slovenia Pelena Stajner et al. 2014;WBVD; Crespan et al.2011 SLO

Blanc Synonym

Kolana Slovenia KOLANA not found SLO Unique genotype

Krivaja ? ? KRIVAJA Present paper SRB Blanc Unique genotype

Kujundžuša ? ? KUJUNDZUSA Present paper BIH Blanc Unique genotype

Stara Blatina Bosnia andHerzegovina

Blatina Present paper; ZuljMihaljevic et al. 2013;Tomic et al. 2012 BIH

Noir Synonym


microsatellite markers• individual fingerprinting, • revealing identities• analyzing population structures• parental and kinship analysis• detection of genetic diversity• Linkage mapping• Geographical Origin - predominance of

certain alleles


What are Duplicates telling us?

• In case of not-standardized traditional varieties

• duplicates having an identical allelic profile are able to confirm

• that the cultivar is true-to-type. •


How to solve Synonyms ?• Grapevine material were shared all over the

world• obtaining local names often compeltely

different from what is called prime name

•World database- VIVC with standardized gentic profiles

prooved excellent tool in solving these complicated puzzles


locus VrZAG62


AmpliSeq™

• ‚Custom design‘ – limit to 6144 primers or 3072 amplicons in one PCR reaction.

• we can perform two PCR reaction and join them subsequently

• panel for human exome – amplification of 25.000 amplicons in one reaction

Analysis

MappingReference Position Type Length Reference Allele Zygosity Count Coverage Frequency

Average quality Unique_references

LD132478.1 mapping 9147 MNV 2 TC AA Homozygous 47 48 97,9166667 36,69767 LD132478.1 mappingLD132478.1 mapping 10151 SNV 1 T N Heterozygous 29 92 31,5217391 37,65517 LD132480.1 mappingLD132478.1 mapping 18308 SNV 1 C T Homozygous 45 45 100 39,28889 LD132481.1 mappingLD132478.1 mapping 18592 SNV 1 A G Homozygous 82 85 96,4705882 37,86585 LD132482.1 mappingLD132478.1 mapping 19198 SNV 1 T G Homozygous 77 77 100 39,01299 LD132483.1 mappingLD132478.1 mapping 19919 SNV 1 C T Homozygous 75 85 88,2352941 39,14667 LD132484.1 mappingLD132478.1 mapping 19939 SNV 1 C T Homozygous 102 102 100 37,98039 LD132485.1 mappingLD132478.1 mapping 22634 SNV 1 A G Homozygous 154 154 100 38,38961 LD132486.1 mappingLD132478.1 mapping 22649 Replacement 2 GT A Homozygous 25 41 60,9756098 38,36 LD132487.1 mappingLD132478.1 mapping 23320 SNV 1 C T Homozygous 83 84 98,8095238 39,38554 LD132488.1 mappingLD132478.1 mapping 23339 Insertion 3 - GAT Heterozygous 23 48 47,9166667 38,97101 LD132489.1 mappingLD132478.1 mapping 23559 Deletion 1 A - Homozygous 32 43 74,4186047 33,53125 LD132490.1 mappingLD132478.1 mapping 24361 SNV 1 G A Homozygous 153 153 100 38,94771 LD132491.1 mappingLD132478.1 mapping 24373 SNV 1 C T Homozygous 114 114 100 38,59649 LD132493.1 mappingLD132478.1 mapping 24548 Deletion 1 T - Homozygous 39 46 84,7826087 37,61538 LD132494.1 mappingLD132478.1 mapping 26627 SNV 1 T G Heterozygous 161 342 47,0760234 36,86335 LD132509.1 mapping

WyeTarget

Illumina 50 bp

403,695,640

20,184,782,000160,481,003

Variants191,236

1832278009

905039272413708

Case 2 – predicted polymorphism wasNOT confirmed

Inappropriate variable sites

Ion AmpliSeq Designer

Custom reference

LD132478 9147 9148LD132478 10151 10152LD132478 18308 18309LD132478 18592 18593LD132478 19198 19199LD132478 19919 19920LD132478 19939 19940

Add target regions with predicted polymorphisms

Result

384Well_PlateID

384Well_Row

384Well_Col Amplicon_ID

Ion_AmpliSeq_Fwd_Primer

Ion_AmpliSeq_Rev_Primer Name Chr

Amplicon_Start

Insert_Start Insert_Stop

Amplicon_Stop

IAD88342_1_A A 1 AMPL1029338AATGGTGAACAGAATTGTGCTATTGC

AAGGCCAGAGCAATACTTACCC SNP1 LD132478 8961 8987 9213 9235

IAD88342_1_A A 2 Blank . .

IAD88342_1_A A 3 AMPL1029339GAACAGCTTGTCGAAGCATCAC

CCAAGCCCAGCAAATGAATTGAC SNP2 LD132478 9933 9955 10184 10207

IAD88342_1_A A 4 Blank . .

IAD88342_1_A A 5 AMPL1029340CATTTTCTTCATGTTGTGTCATTTGTTGTG

CTGTACAAACGCAGCAGACACAAAG SNP3 LD132478 18075 18105 18324 18349

IAD88342_1_A A 6 Blank . .

IAD88342_1_A A 7 AMPL1029341TGATGTAGTCAATGTAGATGGATGGTATGT

CGCTCAAGTATTTTAACACATTTTGGAAGA SNP4 LD132478 18359 18389 18603 18633

IAD88342_1_A A 8 Blank . .

IAD88342_1_A A 9 AMPL1029342GCAATGAGGGCTCTTCAGTATTTTC

CTTACAAGAGCAAGGGCTTCAAAG SNP5 LD132478 18959 18984 19209 19233

IAD88342_1_A A 10 Blank . .

IAD88342_1_A A 11 AMPL1029343TGTTAATTAGGCATGTGGGATTAAGACTG

ACTTACCAACCCAAGATATCGAATGTTT SNP6

SNP7 LD132478 19704 19733 19950 19978

8%

9%

83%

A3-Western Europe group

B3-Far- and Middle-East group

C3-Balkan and Eastern Europe


Microsatellite stuttering – NGS approach


Hop – Humulus lupulus L.

• In the past AFLPs, SSRs, SNPs … clustered together

• ESTs – good dispersion throughout genome

• Transcriptomic part of the genome

Documents

The potential of advanced approaches for accurate ... · The potential of advanced approaches for accurate genotyping in grapevines N. ŠTAJNER 1, L. BITZ 2, B ŠKRLJ 1, J. JAKŠE