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Multi-omics approach in plant characterization, domestication and breeding in a food safety context. Dr. Gustavo H.F. Klabunde [email protected] Agronomist - Post-Doc Research Fellow – UFSC, Brasil Regional Seminar “Advanced research on promissory edible plants in La6n America: tools to improve Food Security in the region” Dec 4th, 2017

Multi-omics approach in plant characterization

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Page 1: Multi-omics approach in plant characterization

Multi-omics approach in plant characterization, domestication and breeding in a food safety context.

Dr. Gustavo H.F. Klabunde

[email protected] Agronomist - Post-Doc Research Fellow – UFSC, Brasil

RegionalSeminar“AdvancedresearchonpromissoryedibleplantsinLa6nAmerica:toolstoimproveFoodSecurityintheregion”

Dec4th,2017

Page 2: Multi-omics approach in plant characterization

Multi-omics approach in plant characterization, domestication and breeding in a food safety context. OutlineOmicsdefini6on–BriefhistoryandconceptOmicstoolsusedbyourresearchgrouponedibleplants.

Genomecharacteriza6on–MarkerdevelopmentandusePhylogeography–Araucariaangus+foliaChloroplastgenomics–Na6veMyrtaceaespeciesTranscriptomics–Acaurariaangus+foliaPhenomics–AccasellowianaMetagenomics–Bambusoideaespecies

Page 3: Multi-omics approach in plant characterization

Gene(Johannsen1909)–Evolvingconcept+Chromosome(Waldeyer-Hartz1888)“I propose the Genome expression for the set of haploidchromosomes, which together with their respec6veprotoplastspecifiesthefoundingmaterialofthespecies”Winkler,H.1920.VerbreitungundUrsachederParthenogenesisimPflanzen-undTierreiche.VerlagFischer,Jena.

Genome (Winkler 1920) Hybrid term - Fusion of affixes

ISSN:0888-7543

Genomics1:1-2(1987)

GenomicsTermcreatedin1987First“Omics”NewdisciplineNewpeer-reviewedjournal

Page 4: Multi-omics approach in plant characterization

Genomics Evolu3onStructure Func3on/Varia3on

Training–“capacitybuilding”

Page 5: Multi-omics approach in plant characterization

Omics

Bioinforma6cs Bioinforma6cs

Page 6: Multi-omics approach in plant characterization

Short Tandem Repeats – STR or Microsatellite - SSR

Molecular Marker Development

Acca sellowiana and Campomanesia xanthocarpa (Native Myrtaceae)

Page 7: Multi-omics approach in plant characterization

• DevelopmentofspecificnuclearandcpDNAmolecularmarkersforpoorlycharacterizedtreespecies

• RequiresclassicalLibraryconstruc6on(bacterialtransforma6on)ORasinglelowthroughputNGSrun(onlytoiden6fyrepe66vemofits)

• Requiressamplesfromatleast4distantpopula6onstomaximizetheprobabilityofvariant(alleles)finding

• RequiresaccesstoDNAgenotypingplagorms(C.E.orP.A.G.E.)•  Timetodevelopandvalidatemarkers:from6to12months• Whenready,STRmarkersareabletoaccessgene6cdiversityfromundercharacterizedtreespecies

Short Tandem Repeats Development STR or SSR – Microsatellite

Page 8: Multi-omics approach in plant characterization

Accasellowiana–Feijoa-Na6veMyrtaceaeFruitswithuniqueflavourandtexture–HighMarketacceptanceIndomes6ca6onandbreedingprocessGene6cdiversity–Unknownformostpopula6ons(Lackofmoleculartools)

Samplescollectedformarkervalita6on

Page 9: Multi-omics approach in plant characterization

Newmarkers

Allelesrevealed

Short Tandem Repeats Development STR or SSR – Microsatellite

HighPolimorphysmInforma6onContent(PIC)

Page 10: Multi-omics approach in plant characterization

Short Tandem Repeats Development STR or SSR – Microsatellite

ABI3500XLDNASequencer

*Mul6plexgenotypingPanels(un6l24lociperrun)*96plantsgenotypedinlessthan120minutes

Laboratoryphase2AutomatedgenotypingCappilaryElectrophoresisE.C.

Laboratoryphase1PolymorphismscreeningPolyacrylamideGelElectrophoresisP.A.G.E.Costeffec6ve

Page 11: Multi-omics approach in plant characterization

Short Tandem Repeats Development STR or SSR – Microsatellite

Locus Primersequences(5'-3') Repeatmo3f

Allelesize(bp)

Ta(°C) 5´Dye GenBank

accessionno.

Cxant22 F:GCTTGGTGGTGCCTCTCTC (TCCA)3 209 55 VIC MG557627

R:GCTCTTCCCTTTGCCTCTCT Cxant26 F:ATGCAAAATCCCTACGTGCT (ATCG)3 162 57 NED MG557629

R:ATGACACATTTCGGCTGTGA Cxant36 F:TTCCCGCCTAACCCTAATG (AAG)4 323 57 PET MG557631

R:GTCAAATCTCGCTCCTCCAA Cxant50 F:CGCACAACCAGCACAAAAC (CTTT)3 477 66 6FAM MG557634

R:CTATCACCGAGGGAGGCAAG Cxant59 F:GAGGGACTTTCAGTTTGTGTGTC (GA)10 230 55 NED MG557635

R:GACCGTTTCCAACATTTCCA Cxant66 F:GCGAGACCATAAGCCACTAC (AGA)4 211 57 NED MG557636

R:TGAGAAGGAGACACACACAAAT Cxant69 F:CCCAACACTCTCCACAATCC (GA)7 294 55 6FAM MG557637

R:TCCTTCCCTCTTCTCTCCATC Cxant76 F:ATGTTTTTGTGCGTTCTGG (AAG)6 336 57 VIC MG557638

R:TTGACCTTTGTTCCTCTTCCT

Guabi05 F:TTCTCGTGATTTGTATCCAAGG (T)10 201 66 PETMG557633

R:TGCTTCAATCTTTCCTATCGAA Guabi11 F:TTGATTCAGGGAACAAATTCAA (ATTA)4 225 55 6FAM MG557632

R:TGGCTAGTGTGGTTCATTCAG

ChloroplastGenome

NucleargenomeIlluminarun

12Puta3vemo3fsdetected

77Puta3vemo3fsdetected

Polymorphismscreening4na3vepops.

2PolymorphicCpSSR

8PolymorphicCpSSR

Campomanesiaxanthocarpa(Myrtaceae)“guabiroba”Gene6cdiversity–Unknown(Lackofmoleculartools)Medicinalproper6es–FruitsCul6va6onop6on

Page 12: Multi-omics approach in plant characterization

Genetic characterization of wild populations of Araucaria angustifolia (Native conifer)

Short Tandem Repeats – STR

Molecular Marker Characterization

Page 13: Multi-omics approach in plant characterization

Short Tandem Repeats Characterization

• RequirespreviousmarkerDevelopmentandValida6on•  STRsmarkersrevealpresentgene6cdiversityandgeneflowindexes•  Insomecases,STRdatamaybeincorporedtoPhylogeographycanalysis

•  STRAnalysisrevealsseveralPopula6onGene6csques6ons,suchasderivedfrom:

•  Inbreeding/Ma6ngsystems•  Migra6on/HabitatFragmenta6onEffects•  RandomGene6cDrim•  NaturalorAr6ficialSelec6on

Page 14: Multi-omics approach in plant characterization

Frequencedistribu6onofobserveddistancedispersaleventsof(a)pollenand(b)seed

dispersal,determinedbySTRparentageanalysis

Spa6algene6cStructureMul3plepurposestudy:Toaccessgene6cdiversityofFederalConserva6onAreasandevaluateits“efficiencyinconservategene6cresources”.Todetermineseedandpollendispersalranges.Increasingconcernaboutthehighlevelofforestfragmenta6onandassociatedlossofdiversity.

Page 15: Multi-omics approach in plant characterization

Chloroplast Genomics Plastome Campomanesiaxanthocarpa

Eugeniauniflora

Pliniaaureana

Wholeplastomesequenceprovides:

Dataforevolu3onarystudies Filogeny Ecology

Sourceofnewmolecularmarkers(SSR,SNPandintergenicspacers)

Gene3cdiversity Phylogeography

Page 16: Multi-omics approach in plant characterization

Tree Phylogeography Araucaria angustifolia

•  Studyofprincipalsandprocessesgoverningthegeographicaldistribu6onofindividuals

• UseofChloroplastDNA(cpDNA)varia6ontoreconstructhistoricaleventsduetoitslowmuta6onrates

•  Extensivefieldsamplingwork(wholedistribu6onrange)andDNAsequencing(SangerSequencing1stgen.)•  Searchforbarriers,historicalgeneflowtendencies,glacialrefugiaandactualgenediversitystatusforconserva6onpurposes

JohnC.Avise

Page 17: Multi-omics approach in plant characterization

Sampling area x Range distribution 40 natural populations (n=594 trees)

Page 18: Multi-omics approach in plant characterization

SeveralChloroplastIntergenicSpacers–Sangersequencing

Chloroplast Variation

Page 19: Multi-omics approach in plant characterization

Laboratory workflow Extensive lab work

Page 20: Multi-omics approach in plant characterization

Forward / - Reverse AlignmentBioinformatics BidirecionalsequencingFinalConsensussequence

VariableSites29variablesitesin2.492bp

Page 21: Multi-omics approach in plant characterization

Araucaria angustifolia – Phylogeography Haplotypenetwork

Demographicscenarios–ABCanalysis

Mismatchdistribu6onfor3lineages

24dis3nctChloroplastforms

Page 22: Multi-omics approach in plant characterization

Central group

North group

South group

Admixture Zone (High gene flow)

BarrierNorthernhaplotypesarenotsharedwithCentralandSouthernVariantsHighGene6cdifferen6a6onbetweennaturalpopula6onsMul6pleGlacialRefugia

Speciesdistribu6onmodelingofA.angus+folia

Araucaria angustifolia – Phylogeography

Page 23: Multi-omics approach in plant characterization
Page 24: Multi-omics approach in plant characterization

Transcriptome Sequencing •  AnalysisofallmRNAexpressedinagiven6ssueandcondi6on•  Geneexpressioncompleteprofiles(includingmiRNAandotherRNAs)•  Highlydinamicprofileanddependentonphysiologicalandenvironmentalcondi6ons,cells,6ssues,age,methodofsampling,stabiliza6onandstorage

•  UseofNextGenera6onSequencing(NGS)Plagormsfordeepsequencing•  Alterna6vewhenthegenomeofthespeciesofinterestisnotavailable(Crea6onofagenecatalogbasedontranscripts)

•  Requiresextensivebioinforma6ctrainingandanalysis•  Excellenttoolforthecharacteriza6onofdiversityandsearchforgenesofinterestforbreeding

Page 25: Multi-omics approach in plant characterization

RNA-Seq Workflow From field samples to complete transcriptomes

Page 26: Multi-omics approach in plant characterization

Field samples – Species Natural Environment

Leaf

Stem

Pollen

Leaf

Araucariaangus3folia

Podocarpuslamber3i

Page 27: Multi-omics approach in plant characterization

Transcriptomics *100Millionsofrawreadsper6ssue*ReadLength=80pbto(IonProton)*DenovoandRefferencebasedassembly(Piceaabies)*SeveralNGSplagormsavailable

Page 28: Multi-omics approach in plant characterization

Annotatedgenes

Annota3onEfficiency

GOlvl2 GOlvl3

P.lamber3iLeaf 4.649 28,43% CC:9 CC:17

MF:8 MF:12PB:15 PB:42

A.angus3foliaLeaf 4.354 29,25% CC:9 CC:17

MF:8 MF:12PB:15 PB:42

A.angus3foliaStem 3.643 28,43% CC:9 CC:17

MF:8 MF:12PB:15 PB:42

A.angus3foliaPollen 9.354 33,45% CC:12 CC:40

MF:13 MF:71PB:22 PB:196

Complete gene sequences from RNA-Seq data

Page 29: Multi-omics approach in plant characterization

Transcriptomics Functional annotation

Page 30: Multi-omics approach in plant characterization

Phenomics

•  Largescalephenotypecharacteriza6on•  Integra6onbetweenfactors

environmental,gene6c,epigene6cHowgene6cdiversityaffectsthephenotypes?

“P=G+E”

Borsuk,2015

Page 31: Multi-omics approach in plant characterization

Acca sellowiana - Phenomics Tree analysis - Field

Variables - Beggining of budding -  Beggining of flowering (10% open) -  End of flowering (90% fallen) -  Beggining of harvest -  End of harvest -  Flower index -  Fruit index

-  Daily climate data

N= 235 genotypes

Evalua6onperiod-10years

Page 32: Multi-omics approach in plant characterization

Acca sellowiana - Phenomics Fruit analysis - Lab

Variables • Fruit diameter (cm), • Fruit length (cm), • Fruit weight (g), • Peel weight (g), • Pulp weight (g), • Pulp yield (%), • Peel thickness (cm), • Brix - Bxº • pH

N= 235 genotypes

Evalua6onperiod-10years

Page 33: Multi-omics approach in plant characterization

7 8 9 10 11 120.00

0.05

0.10

0.15

0.20 Inicio de Brotação - Inicio de Floração

Cv = 0.0033902 (Tb)^2 - 0.0526979 (Tb) + 0.3008925 R 2=0.9753 Tb=7,77°C

Temp. Base

CV

7 8 9 10 11 120.08

0.09

0.10

0.11

0.12 Inicio e Fim de Floração

Cv = 7.490e-04 (Tb)^2 - 1.143e-02 (Tb) + 1.261e-01 R 2=0.986 Tb=7,63°C

Temp. Base

CV

5 6 7 8 9 10 11 12 13 14 150.05

0.06

0.07

0.08

0.09

0.10Fim Floração - Inicio de Colheita

Tb=13,5°C

Temp. Base

CV

9 10 11 12 130.0

0.2

0.4

0.6

0.8 Inicio e Fim de Colheita

Cv = 0.05216 (Tb)^2 - 1.052549 (Tb) + 5.479667 R 2=0.9745 Tb=10,09°C

Temp. Base

CV

5 6 7 8 9 10 11 12 13 14 150.00

0.05

0.10

0.15

0.20Inicio de Brotação - Inicio de colheita

Tb=11,0°C

Temp. Base

CV

5 6 7 8 9 10 11 12 13 140.00

0.05

0.10

0.15Inicio de Brotação - Fim de colheita

Tb=11,0°C

Temp. Base

CV

Acca sellowiana - Phenomics

225

212

246

241

216

218

208

209

196

218

221

210

195

188

1069.61GD

1081.36GD

1058.41GD

1077.15GD

1083.93GD

1116.23GD

1058.43GD

1151.19GD

1105.52GD

1145.21GD

1159.58GD

1132.51GD

1091.73GD

1072.92GD

Dias

Page 34: Multi-omics approach in plant characterization

Acca sellowiana - Phenomics

L210

C10

20

L2

12C

L44.

38

L2

03C

212

L210

C10

17

L208

C34

1

Non

ante

L207

C29

1

L201

C53

B7

L202

C11

8

L210

C10

18

L214

C39

7

L204

C33

2

L214

C90

3

L210

C34

4

L309

C718

L201

C50-

2

L202

C103

L203

C242

L204

C301

L207

C152-

12

L205

C453

L215

C422

L204

C331

L213

C86

L305

CB24.27

L309

CB22.32

L206

C812

L310C719

L208C342

L206C511

L214C398

L203C240

L204C276

Helena

L207C358 L210C235 L207C138-2 L209C393 L208C339 L206C755 L210Cv1017 L210C535 L203C249 L212CB27.18 L301CB05.36 L304CB10.37

L207C712 L209C1010

L204C260

Mattos

L208C805

L214C382

L207CL33.11

L303CB25.01

L202C124

L208C716

L214C411

L214C381

L205C501

L213C21

L216C129

L206C522

L210CL44.29

L212CL54.02

L206C735

L216C80

L213C150

L302CB11.06

L202C135

L206C508

L202C138A

L210C259

L214C380

L207C392

L206C521B

L209C1004

L204C277

L215C389

L215C418

L209C1003

L310CB02.38

L218C831

L208C260

L215C350

L215C97

L210C1015

L215C15

L213C352

Alcantara L213C

128

L204C294 L210C1013 L210C533 L218C629 L209C629 L301CB08.30 L215C348 L213C722

L215C214 L209C1005

L215C720 L208C101

L302CB12.03

L204C373

L212CB10.04

L202C148

L217C432

L210C127

L213C14

L215C412

L213C20

L213C7

L205C504

L202C138

L203C159-27

L206C707

L206C509

L208C366

L210C333

L210C345

L212CB24.21

L306CB28.12

L209C902

L302CB15.16

L210C534

L213C806

L217C429

L306CB18.34

L207C520

L214C414

L306CB30.20

L305CB13.01

L214C415

L204C321

L212

CB2

5.29

L201

C50

2

L2

09C

502-

2

L2

02C

117

L208

C14

8

L2

05C

379

L204

C33

7

L2

07C

110

Alca

ntar

a (2

07)

L212

CB2

9.23

L203

C23

1

L2

12C

L49.

03

L302

CL5

1.02

L210

C53

6

L214

C458

L303

CL51

.02

L207

C228

L215

C347

L214

C519

L215

C320

L202

C119

L209

C53

L209

C721

L201

C79

L209

C1007

L201

C66

L205

C377

L205C401

L207C526

L216C427

L206C521A

L207C250

L208C91

L206C804

L303CB24.16

L307C336

L303CB22.32

L303CB27.16

L212CB12.03

L303CB10.37

L215C425

L217C522

L304CB23.16 L307C129 Distancia euclidiana pelo metodo UPGMA

Correlação cofenetica, r=0,6906

Primeiroranqueamento:L307C336,L301CB08.30,L209C629,L217C522,L303CB24.16,L303CB10.37,L310C719,L208C716,L206C812e,L215C425.Segundoranqueamento:L210C534,L217C522,L303CB10.37,L213C806,L215C425,L307C336,L303CB27.16,L212CB12.03,L203C249e,L304CB23.16.

Clones Group Alcantara 1 Helena 1 Mattos 1 Nonante 1 Outros 163 acessos 1 L204C294 2 L210C1013 2 L210C533 2 L218C629 2 L209C629 2 L301CB08.30 2 L215C348 3 L213C722 3 L215C214 3 L209C1005 3 L215C720 3

Com a ACP e CLUSTER Com o IS Método dos Ranks

Page 35: Multi-omics approach in plant characterization

Phenomics + Genomics AllPhenotypicallyevaluatedcul6vars/accessionsarebeingsequencedandgenotypedExtensivesetofinforma6onsforplantbreedersandresearchersLess6metoreleasenewandadaptedcul6vars

Page 36: Multi-omics approach in plant characterization

Metagenomics Associated genomes

• Applica6onofgenomictechniquesforthestudyofmicrobialcommuni6esdirectlyfromen6resamples;

• Dispensingtheneedofclassicmicrobiologictechniques;

Completegenomesor Metabarcode16S/ITS

Page 37: Multi-omics approach in plant characterization

Associated genomes metagenome

?

?

Page 38: Multi-omics approach in plant characterization

Associated genomes metabarcode workflow

-80°C

MS medium

30 days

Total DNA isolation and QC

In vivo: 10 nodal segments/tube

In vitro: 10 nodal segments

Type Region FragmentArquea 16S V4Bacteria 16S V3-V4Fungi ITS ITS2

PCR

NGS - Illumina MiSeq

NGS Data processing and OTU characterization

Page 39: Multi-omics approach in plant characterization

Associated genomes metagenome Bacterial preliminary results

44,3% 37,9% 17,9%

25,8% 72% 2,3%

36,3% 60,3% 3,4%

A

C

B

51,9 55,1

13,2 9,2

13,2 12,2

11,6 13,3

3,1 4,12,3 2,0

0102030405060708090100

SegmentoNodal Meiodecultura

Rela6veabun

dance(%

)

Spirochaetes

Planctomycetes

FBP

Cyanobacteria

Arma6monadetes

[Thermi]

OutrosemBactériaAcidobacteria

Page 40: Multi-omics approach in plant characterization

Laboratório de Fisiologia do Desenvolvimento e Genética Vegetal - LFDGV

Rgv.ufsc.brLfdgv.paginas.ufsc.br

Thankyouforyouraven6on

Page 41: Multi-omics approach in plant characterization

Multi-omics approach in plant characterization, domestication and breeding in a food safety context.

Dr. Gustavo H.F. Klabunde

[email protected] Agronomist - Post-Doc Research Fellow – UFSC, Brasil

RegionalSeminar“AdvancedresearchonpromissoryedibleplantsinLa6nAmerica:toolstoimproveFoodSecurityintheregion”

Dec4th,2017