Ecological and Evolutionary Systems biology:Conceptual and molecular tools for analysis

Justin BorevitzEcology & Evolution

University of Chicagohttp://naturalvariation.org/

Ecological and Evolutionary Systems biology:Conceptual and molecular tools for analysis

Justin BorevitzEcology & Evolution

University of Chicagohttp://naturalvariation.org/

Deer mouse burrow

Finch (large beaked)Sitting in a cotton wood Hemicordate

Sea anemoneStickleback

Aquilegia, Arabidopsis, Mimulus? Indiana Dunes National Lakeshore

Developing Model Organisms - Community

• Critical mass of labs, hands/eyes/minds• Coordinated collaboration

– webinar lab meetings– Open chat/ focus problems/ big picture meetings

• United by questions– Development: novelty/plasticity– Adaptation: abiotic/biotic

• United by organism– Shared tools: genomic/ genetic/ methods

• United by ecoregion – field study site– Soil/ water testing, weather monitoring,

development/behavioral real time recording

Developing Model Organisms - Tools

• High throughput Phenotyping– Physiological dissection of 1000s correlated traits– Biological Variation

• Multi species ecological interactions– “extended phenotype”

• Environmental Interaction (GxE)– Local adaptation

• Epistasis (GxG)– Magnify minor QTL in local backgrounds

• Multiple genes under major QTL– High Density markers – Linkage Drag

Functional Genomics•Microarrays •SNPs•Induced deletions

Talk OutlineTalk Outline• Genetic Diversity

– Population structure, Haplotype Mapping set

• Phenotyping in multiple environments– Seasonal Variation in the Lab

• SNP/Tiling microarrays– Splicing

– Methylation

– Very High Density Markers SFPs

– Bulk Mapping

– Deletions

• Genetic Diversity– Population structure, Haplotype Mapping set

• Phenotyping in multiple environments– Seasonal Variation in the Lab

• SNP/Tiling microarrays– Splicing

– Methylation

– Very High Density Markers SFPs

– Bulk Mapping

– Deletions

Global and Local Population Structure

Olivier Loudet

Local adaptation

under strong

selection

Seasonal Variation

Matt Horton

Megan Dunning

144 Non singleton SNPs >2000 accessions

Global, Midwest, and UK

common haplotypes

Local Population Structure

Megan Dunning, Yan Li

80 Major Haplotypes

Diversity within and between populations

17 Major Haplotypes

80 Major Haplotypes

Diversity within and between populations

Variation within a field http://naturalvariation.org/hapmapVariation within a field http://naturalvariation.org/hapmap

Begin with regions spanning the Native Geographic range

Nordborg et al PLoS Biology 2005Li et al PLoS ONE 2007

Tossa Del MarSpain

LundSweden

Seasons in the Growth Chamber

• Changing Day length• Cycle Light Intensity• Cycle Light Colors• Cycle Temperature

Sweden Spain

Seasons in the Growth Chamber

• Changing Day length

• Cycle Light Intensity

• Cycle Light Colors

• Cycle Temperature

GenevaScientific/ Percival

Day Length

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standard

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Kurt Spokas

Version 2.0a June 2006

USDA-ARS Website Midwest Area (Morris,MN)http://www.ars.usda.gov/mwa/ncscrl

Flowering time QTL, Kas/Col RILsFlowering time QTL, Kas/Col RILs

Genomic Breeding Path

QTL geneConfirmation

MarkerIdentificationGenotyping

Genomics path

Experimental DesignMapping population PhenotypingQTL AnalysisFine Mapping

Candidate genePolymorphismsgene expressionloss of function

QTL gene

Confirmation

Experimental Design

Mapping population

Phenotyping

QTL Analysis

Fine Mapping

Borevitz and Chory, COPB 2003

Which arrays should be used?

cDNA array

Long oligo array

BAC array

Which arrays should be used?

Gene array

Exon array

Tiling array35bp tile, 25mers 10bp gaps

Which arrays should be used?

Tiling/SNP array 2007 250k SNPs, 1.6M tiling probes

SNP array

Ressequencing array

How about multiple species? Microbial communities?

Pst,Psm,Psy,Psx, Agro, Xanthomonas, H parasitica, 15 virus,

SNP SFP MMMMM MSFP

SFP

MMMMM M

Chromosome (bp)

con

serv

atio

n

SNP

ORFa

start AAAAA

Tra

nsc

ripto

me

Atla

s

ORFb

deletion

Improved Genome Annotation

RNA DNA

Universal Whole Genome Array

Transcriptome AtlasExpression levelsTissues specificity

Transcriptome AtlasExpression levelsTissues specificity

Gene/Exon DiscoveryGene model correctionNon-coding/ micro-RNA

Gene/Exon DiscoveryGene model correctionNon-coding/ micro-RNA

Alternative SplicingAlternative Splicing

Comparative GenomeHybridization (CGH)

Insertion/DeletionsCopy Number Polymorphisms

Comparative GenomeHybridization (CGH)

Insertion/DeletionsCopy Number Polymorphisms

MethylationMethylation

ChromatinImmunoprecipitation

ChIP chip

ChromatinImmunoprecipitation

ChIP chip

Polymorphism SFPsDiscovery/Genotyping

Polymorphism SFPsDiscovery/Genotyping

Control for hybridization/genetic polymorphismsto understand TRUE expression variation

RNA ImmunoprecipitationRIP chip

RNA ImmunoprecipitationRIP chip

Antisense transcription

Allele Specific Expression

AT1G07350

AT1G29120

AT1G51350

AT1G53560

AT1G76170

D E

Additive, Dominant, Maternal, Genotype Variation

FDR for selection 3%

Total exons tested

86,349

Total exons 69

Tested exons 5

confirmed 5

Alternative spliced exons

- verification

ColVan

v v v c c c v c RT-PCR gDNA PCR

Col

Col

Van

Van

Col

Van

Van

Col

Genomic DNA RNA

No significant

allele specific expression

cis regulatory variation

(Van allele)

Paternal Imprinting Maternal Imprinting

cis regulatory variation

(Col allele)

RNA

RNA

RNA

RNA

GlobalAllele Specific

Expression

Zhang, X., Richards, E., Borevitz, J. Current Opinion in Plant Biology (2007)

65,000 SNPsTranscribedAccession Pairs12,000 genes

>= 1 SNP6,000 >= 2 SNPs

Potential Deletions

SFPs and CC*GG Methylome

Extract genomic 100ng DNA (single leaf)

Digest with either msp1 or hpa2 CC*GG

Label with biotinRandom primers

Hybridize to array

HpaII digestion

Random labeling

Random labeling

MspI digestion

* * *

* * *

* * *

A)

B)

Hpa msp

Inte

nsit

y

*

*

Col

Col

Hpa msp

Col

Col

Hpa mspV

an

Van

mSFP

Hpa msp

Van

Van

SFP

Delta p0 FALSE Called FDR

1.00 0.95 18865 160145 11.2%

1.25 0.95 10477 132390 7.5%

1.50 0.95 6545 115042 5.4%

1.75 0.95 4484 102385 4.2%

2.00 0.95 3298 92027 3.4%

SFP detection on tiling arrays

Chip genotyping of a Recombinant Inbred Line

29kb interval

Map bibb100 bibb mutant plants100 wt mutant plants

bibb mapping

ChipMapAS1

Bulk segregantMapping usingChip hybridization

bibb maps toChromosome2 near ASYMETRIC LEAVES1

BIBB = ASYMETRIC LEAVES1

Sequenced AS1 coding region from bib-1 …found g -> a change that would introduce a stop codon in the MYB domain

bibb as1-101

MYB

bib-1W49*

as-101Q107*

as1bibb

AS1 (ASYMMETRIC LEAVES1) =MYB closely related toPHANTASTICA located at 64cM

Array Mapping

Hazen et al Plant Physiology (2005)

chr1 chr2 chr3 chr4 chr5

eXtreme Array Mapping

Histogram of Kas/Col RILs Red light

hypocotyl length (mm)

cou

nts

6 8 10 12 14

02

46

81

01

2

15 tallest RILs pooled vs15 shortest RILs pooled

LOD

eXtreme Array Mapping

Allele frequencies determined by SFP genotyping. Thresholds set by simulations

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D

Composite Interval Mapping

RED2 QTL

Chromosome 2

RED2 QTL 12cM

Red light QTL RED2 from 100 Kas/ Col RILs (Wolyn et al Genetics 2004)

eXtreme Array Mapping BurC F2

XAMLz x Col

F2

QTLLz x Ler

F2

(Werner et al Genetics 2006)

XRED2 QTL

mark1 mark2

Select recombinants by PCR >200 from >1250 plants

HighLow~2Mb ~8cM

>400 SFPsCol

Kas

Col Col

Col het

Col

~2

Kas

het Col

het het

het

~43

Kas

Kas Col

Kas het

Kas

~268

~43 ~539 ~43

~268 ~43 ~2

Kas

eXtreme Array Fine Mapping

Potential Deletions

>500 potential deletions45 confirmed by Ler sequence

23 (of 114) transposons

Disease Resistance(R) gene clusters

Single R gene deletions

Genes involved in Secondary metabolism

Unknown genes

Potential Deletions Suggest Candidate Genes

FLOWERING1 QTL

Chr1 (bp)

Flowering Time QTL caused by a natural deletion in FLM

MAF1

FLM natural deletion

(Werner et al PNAS 2005)

Fast Neutron deletions

FKF1 80kb deletion CHR1 cry2 10kb deletion CHR1

Het

Natural Copy Variation on Tiling Arrays

Segregating self seed from wild ME isolate (Early – Late)

Unite Genetic and Physical Map

• Shotgun genomic or 454 reads• ESTs/ cDNAs/ BAC ends• 1000s of contigs

• Genotype mapping population on arrays– Create very high density genetic map

• Known position of genes/contigs allow QTL candidatet gene identification– Control hybridization variation for gene expression

Aquilegia (Columbines)

Recent adaptive radiation, 350Mb genome

Genetics of Speciationalong a Hybrid Zone

Aquilegia (Columbine) NSF Genome Complexity

• Microarray floral development – QTL candidates

• Physical Map (BAC tiling path)– Physical assignment of ESTs

• QTL for pollinator preference – ~400 RILs, map abiotic stress

– QTL fine mapping/ LD mapping

• Develop transformation techniques– VIGS

• Whole Genome Sequencing (JGI 2007)

Scott Hodges (UCSB)

Elena Kramer (Harvard)

Magnus Nordborg (USC)

Justin Borevitz (U Chicago)

Jeff Tompkins (Clemson)

http://www.plosone.org/

NaturalVariation.orgNaturalVariation.orgUSC

Magnus NordborgPaul Marjoram

Max Planck

Detlef Weigel

Scripps

Sam Hazen

University of Michigan

Sebastian Zoellner

USC

Magnus NordborgPaul Marjoram

Max Planck

Detlef Weigel

Scripps

Sam Hazen

University of Michigan

Sebastian Zoellner

University of Chicago

Xu ZhangYan Li

Peter RoycewiczEvadne Smith

Megan DunningJoy Bergelson

Michigan State

Shinhan Shiu

PurdueIvan Baxter

University of Chicago

Xu ZhangYan Li

Peter RoycewiczEvadne Smith

Megan DunningJoy Bergelson

Michigan State

Shinhan Shiu

PurdueIvan Baxter

Talking points

• How to clone QTL?

• Why? - ,

• Is it worth it

• Macro evolution vs micro– Large steps vs gradual small steps