Toward the genetic basis of adaptation: Arrays/Association Mapping
Justin BorevitzEcology & EvolutionUniversity of Chicagohttp://naturalvariation.org/
Widely Distributed
http://www.inra.fr/qtlat/NaturalVar/NewCollection.htm
Olivier Loudet
Aranzana, et al PLOS genetics (2005), Sung Kim, Keyan Zhao
17k SNPs 96 lines
Local Population Variation
Scott HodgesIvan Baxter
Seasonal Variation
Matt Horton
Megan Dunning
Light Affects the Entire Plant Life Cycle
de-etiolation
hypocotyl
}
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
Day Length
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Developmental Plasticity == BehaviorDevelopmental Plasticity == Behavior
Talk Outline• Arabidopsis Light Response
– PHYA, QTL mapping• Whole Genome Tiling Arrays
– Alternative splicing/Methylation – Single Feature Polymorphisms (SFPs)– Potential deletions/ Copy Number Variants– Genetic Mapping
• Resequencing/ Haplotypes– Variation Scanning
• Aquilegia for Genetics of Adaptive Radiations
• Arabidopsis Light Response– PHYA, QTL mapping
• Whole Genome Tiling Arrays– Alternative splicing/Methylation – Single Feature Polymorphisms (SFPs)– Potential deletions/ Copy Number Variants– Genetic Mapping
• Resequencing/ Haplotypes– Variation Scanning
• Aquilegia for Genetics of Adaptive Radiations
Quantitative Trait Loci
Tiling Arrays vs Resequencing Arrays
• AtTILE1, universal whole genome array
25mer every ~35bp, > 6.5 Million features
single array, many individuals.
• Re-sequencing array 120Mbp*8features
~1 Billion features, 8 wafers
20 Accessions available mid year
Perlegen, Max Planck (Weigel),
USC (Nordborg), Salk (Ecker)
GeneChip
Which arrays should be used?
cDNA array
Long oligo array
Which 25mer arrays should be used?
Gene array
Exon array
Tiling array
Which 25mer arrays should be used?
Tiling/SNP array
SNP array
Ressequencing array
RNA DNA
Universal Whole Genome Array
Transcriptome AtlasExpression levelsTissues specificity
Transcriptome AtlasExpression levelsTissues specificity
Gene DiscoveryGene model correctionNon-coding/ micro-RNAAntisense transcription
Gene DiscoveryGene model correctionNon-coding/ micro-RNAAntisense transcription
Alternative SplicingAlternative Splicing Comparative GenomeHybridization (CGH)
Insertion/Deletions
Comparative GenomeHybridization (CGH)
Insertion/Deletions
MethylationMethylation
ChromatinImmunoprecipitation
ChIP chip
ChromatinImmunoprecipitation
ChIP chip
Polymorphism SFPsDiscovery/Genotyping
Polymorphism SFPsDiscovery/Genotyping
Control for hybridization/genetic polymorphismsto understand true EXPRESSION polymorphismsTrue cis variation == Allele Specific Expression
Alternative Splicing
V V V C C C
VanCol
Xu Zhang
Potential Deletions
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
Intergenic Exon intron
SFPs 60770 23519 17216
total 685575 665524 301648
% 8.86% 3.53% 5.71%
SFPs/gene 0 >=1 >=2 >=3 >=4 >=5
genes 16322 9146 4304 2495 1687 1121
Methods for labeling
• Extract genomic 100ng DNA (single leaf)
• Digest with either msp1 or hpa2 CCGG
• Label with biotin random primers
• Hybridize to array
• Fit model
methylated features and mSFPs
>10,000 of 100,000 at 5% FDR
Enzyme effect, on CCGG features GxE
276 at 15% FDR
mQTL?
SFP Resequencing
• Advantages– Discovery and typing tool– Indels, rare variants, HMM tool– Quantitative score– Good for low polymorphism < 1%
• Caveats– No SNP knowledge, synonymous?– Bad for high polymorphism > 1%
• Rearrangements, Reference sequence
Chip genotyping of a Recombinant Inbred Line
29kb interval
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
FLM
FLM natural deletion
(Werner et al PNAS 2005)
Natural Variation on Tiling Arrays
Map bibb100 bibb mutant plants100 wt mutant plants
Array Mapping
Hazen et al Plant Physiology 2005
eXtreme Array Mapping
Histogram of Kas/Col RILs Red light
hypocotyl length (mm)
cou
nts
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46
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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
Drosophila, Chao-Qiang Lai -Tufts University
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
Array Haplotyping
• What about Diversity/selection across the genome?
• A genome wide estimate of population genetics parameters, θw, π, Tajima’D, ρ
• LD decay, Haplotype block size• Deep population structure?• Col, Lz, Bur, Ler, Bay, Shah, Cvi, Kas,
C24, Est, Kin, Mt, Nd, Sorbo, Van, Ws2Fl-1, Ita-0, Mr-0, St-0, Sah-0
Array Haplotyping
Inbred lines
Low effectiverecombinationdue to partialselfing
Extensive LDblocks
Col Ler Cvi Kas Bay Shah Lz Nd
Chr
omos
ome1
~50
0kb
SFPs for reverse genetics
http://naturalvariation.org/sfp
14 Accessions 30,950 SFPs`
Chromosome Wide Diversity
Diversity 50kb windows
Tajima’s D like 50kb windows
RPS4 unknown
R genes vs bHLH
(-1,-0.8] (-0.6,-0.4] (-0.2,0] (0.2,0.4] (0.6,0.8]
Selection
Tajima's D like statistic
freq
uen
cy
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RgenesbHLH
Experimental Design of Association Study
• Sample > 3000 wild strains, ~100 SNPs
• Select 500 less structured reference fine mapping set for SFP resequencing
• Scan Genome for variation/selection
• Measure phenotype in Seasonal Chambers
• Haplotype map/ LD recombination blocks
• Associate Quantitative phenotypes with HapMap
Aquilegia (Columbines)
Recent adaptive radiation, 350Mb genome
Species with> 20k ESTs 11/14/2003
Animal lineage: good coverage
Plant lineage: crop plant coverage
• 300 F3 RILs growing (Evadne Smith)• TIGR gene index 85,000 ESTs >16,00 SNPs• Complete BAC physical map Clemson• Nimblegen arrays
Aquilegia (Columbines)
Genetics of Speciationalong a Hybrid Zone
NSF Genome Complexity
• Microarray 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?)
Scott Hodges (UCSB)
Elena Kramer (Harvard)
Magnus Nordborg (USC)
Justin Borevitz (U Chicago)
Jeff Tompkins (Clemson)
NaturalVariation.orgNaturalVariation.orgUSC
Magnus NordborgPaul Marjoram
Max Planck
Detlef Weigel
Scripps
Sam Hazen
University of Michigan
Sebastian Zollner
University of Chicago
Xu ZhangEvadne SmithKen Okamoto
Michigan State
Shinhan Shui
PurdueIvan Baxter
University of Guelph, Canada
Dave Wolyn
Sainsbury Laboratory
Jonathan Jones
University of Chicago
Xu ZhangEvadne SmithKen Okamoto
Michigan State
Shinhan Shui
PurdueIvan Baxter
University of Guelph, Canada
Dave Wolyn
Sainsbury Laboratory
Jonathan Jones
USC
Magnus NordborgPaul Marjoram
Max Planck
Detlef Weigel
Scripps
Sam Hazen
University of Michigan
Sebastian Zollner