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Photo credits: Brook Moyers, Hoekstra lab, Whitehead + Crawford 2006
Detecting adaptive differentiation in structured populations with - - PowerPoint PPT Presentation
Detecting adaptive differentiation in structured populations with - - PowerPoint PPT Presentation
Detecting adaptive differentiation in structured populations with genomic data and common gardens Emily Josephs @emjosephs Photo credits: Brook Moyers, Hoekstra lab, Whitehead + Crawford 2006 Detecting local adaptation requires knowing about
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Lowland maize Highland maize Rice varieties
Detecting local adaptation requires knowing about (1) genetic variation in traits
Photo credits: IRRI, Childs et al., Poland et al Northern leaf blight in maize
- Pop. A
- Pop. B
Common garden
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Lowland maize Highland maize Rice varieties
Detecting local adaptation requires knowing about (1) genetic variation in traits (VA)
Photo credits: IRRI, Childs et al., Poland et al Northern leaf blight in maize
- Pop. A
- Pop. B
Common garden Crosses to get
VA
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Lowland maize Highland maize Rice varieties
Detecting local adaptation requires knowing about (1) genetic variation and (2) relatedness
Photo credits: IRRI, Childs et al., Poland et al Northern leaf blight in maize
- Pop. A
- Pop. B
Divergence time
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Lowland maize Highland maize Rice varieties Photo credits: IRRI, Childs et al., Poland et al Northern leaf blight in maize
- Pop. A
- Pop. B
Detecting local adaptation requires knowing about (1) genetic variation and (2) relatedness
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Qst- Fst comparisons test for excess trait divergence
Prout and Barker 1993, Spitze 1993, Whitlock 1999
btw-pop genetic var. for trait total genetic var. for trait
Qst
btw-pop neutral genetic var. total neutral genetic var.
Fst
vs.
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Qst- Fst comparisons test for excess trait divergence
Prout and Barker 1993, Spitze 1993, Whitlock 1999
btw-pop genetic var. for trait total genetic var. for trait
Qst
btw-pop neutral genetic var. total neutral genetic var.
Fst =
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Qst- Fst comparisons test for excess trait divergence
Prout and Barker 1993, Spitze 1993, Whitlock 1999
btw-pop genetic var. for trait total genetic var. for trait
Qst
btw-pop neutral genetic var. total neutral genetic var.
Fst >
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Lots of datasets that have genomes + phenotypes from diversity panels
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How can we systematically detect local adaptation... In quantitative traits? In gene expression? For GxE?
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Relatedness between populations can be summarized with a kinship matrix.
A1 A2 B1 B2 A1 A2 B1 B2
Lighter colors = more related
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The eigenvectors of the kinship matrix (PCs) summarize relatedness
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Size
How do PCs relate to traits?
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Size
A correlation btw PC & trait can be consistent with drift
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Size
A correlation btw PC & trait can be consistent with drift
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Modelling the slope expected due to drift
Slope of trait against PC m
Size
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Modelling the slope expected due to drift
Slope of trait against PC m Mean slope
Size
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Amount of relatedness explained by PC m
Modelling the slope expected due to drift
Slope of trait against PC m Mean slope
Size
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Amount of relatedness explained by PC m
Modelling the slope expected due to drift
Can estimate VA from a subset of PCs
Slope of trait against PC m Mean slope
Size
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Selection can increase trait divergence
Size
Amount of relatedness explained by PC m
Can estimate VA from a subset of PCs
Slope of trait against PC m Mean slope
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Selection can increase trait divergence
Size
Amount of relatedness explained by PC m
Can estimate VA from a subset of PCs
Slope of trait against PC m Mean slope
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Size
Slope of trait against PC m Mean slope Amount of relatedness explained by PC m
Testing for diversifying selection
Can estimate VA from a subset of PCs
Number of PCs used to estimate VA
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How can we systematically detect local adaptation... In quantitative traits? In gene expression? For GxE?
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Detecting local adaptation in maize
Wikipedia
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Detecting local adaptation in maize
240 domesticated inbred maize lines (Flint-Garcia et al. 2005). Whole genome sequence data (Panzea). 22 traits measured in common garden.
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The kinship matrix of 240 maize lines
Lighter colors = more related Individuals Individuals
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The kinship matrix of 240 maize lines
Lighter colors = more related Individuals Individuals
PC 2 PC 1
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Neutral expectations of relationship between PC and trait
Kernel number
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Divergence along PC1 consistent with drift
Kernel number
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Flowering time
Neutral expectations of relationship between PC and trait
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Adaptive divergence in flowering time along PC 1
FDR < 0.05
Flowering time
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Signatures of adaptation across traits
Josephs et al. 2018 Genetics
p = White circles mean FDR < 0.05
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How can we systematically detect local adaptation... In quantitative traits? In gene expression? For GxE?
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Testing for selection on gene expression
Gene expression data (RNAseq) for 208 maize lines in 7 tissues
Kremling et al. 2018 Jennifer Blanc
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How many genes show evidence of selection on expression?
Kernel
Jennifer Blanc
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Which tissues show strongest evidence of adaptation?
Kernel Leaf (day) Leaf (night)
Jennifer Blanc
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Evidence of local adaptation for gene expression
Jennifer Blanc Blanc et al. in prep
Leaf night (day 8) Leaf night (day 26) Leaf day (day 8) Leaf day (day 26) 3rd leaf tip 3rd leaf base Kernel Seedling shoot Seedling root
Number of genes that show evidence of selection on expression
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How can we systematically detect local adaptation... In quantitative traits? In gene expression? For GxE?
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The environment shapes traits
Clausen, Keck, and Heisey
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Genetic variation for plasticity (‘GxE’)
Clausen, Keck, and Heisey
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- A. thaliana flowering time as a model for GxE
1001 Genomes Consortium, Kathleen Donohue
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Flowering time at 16oC is locally adapted
p = 0.0002 Bonferoni p = 0.0015
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Flowering time at 10oC is also locally adapted
p = 0.006 Bonferoni p = 0.03
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Using the reaction norm to measure plasticity
Temperature Days to flower
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Using the reaction norm to measure plasticity
Temperature Days to flower
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Variation in reaction norm consistent with drift
p = 0.03 Bonferoni p = 0.16 Later flowering at 16oC than 10oC Earlier flowering at 16oC than 10oC Reaction norm
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How to deal with trait correlations?
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How to deal with trait correlations?
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We can use PC + trait relationships to detect adaptation
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We can use PC + trait relationships to detect adaptation
Local adaptation shapes trait divergence
Flowering time
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We can use PC + trait relationships to detect adaptation
Local adaptation shapes trait divergence These methods can be used in additional systems!!!
https://github.com/emjosephs/quaint
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Thanks!
Jeremy Berg Jennifer Blanc Karl Kremling Ed Buckler Cinta Romay Kate Crosby Coop Lab Ross-Ibarra Lab Graham Coop Jeff Ross-Ibarra
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The Josephs lab at Contact me! Josep993@msu.edu, http://JosephsLab.github.io/
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We can use PC + trait relationships to detect adaptation
Local adaptation shapes trait divergence These methods can be used in additional systems!!!
https://github.com/emjosephs/quaint
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Adaptive divergence along additional PCs
FDR < 0.05
Flowering time
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What about detecting adaptation in genotypes that haven’t been phenotyped?
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Testing for adaptation with polygenic scores
Polygenic score
Allele frequency Effect size At all GWAS loci Berg and Coop 2014
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Evidence for polygenic adaptation in European maize
Josephs et al. 2018 Biorxiv