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Recombination rate variation, hitchhiking, and central-peripheral structure shape deleterious load in black cottonwood Jason Holliday Department of Forest Resources and Environmental Conservation Virginia Tech Understanding the adaptive past to predict the adaptive future • The rate of adaptation to anthropogenic climate change depends on: – – – – Number of loci involved Distribution of effect sizes Distribution of adaptive alleles in the genome New mutation vs standing variation • Many non-adaptive processes also play a role: – Historical demography (e.g., bottlenecks) – Migration rate relative to selection – Deleterious alleles Populus trichocarpa as model to understand adaptive potential and constraint • Compact (~480mb), sequenced genome • Clonal propagation • Wide latitudinal and altitudinal range = strong differentiation for adaptive traits • High gene flow via wind polination = low background population structure • Postglacial history = possbile adaptive constraint Sampling and phenotyping • 449 samples spanning the latitudinal and altitudinal range of the species – Outgroups: P. tremula, P. tremuloides, P. deltoides • Re-sequence most of the ‘gene space’ – Sequence capture • Replicated gardens in Virginia and British Columbia – Phenotyped for growth, bud phenology, cold hardiness Genotyping by sequence capture Sequence capture recovers regions of interest in a mostly repeatable way Coverage is tightly linked to bait locations Genomic sampling • ~ 2 million single nucleotide polymorphisms passed quality filters Adaptation is not just about having the ‘right’ alleles; it’s also about not having the ‘wrong’ alleles • Many tree species suffer substantial inbreeding depression, while hybrid vigor is common • Likely due in part to accumulation of deleterious alleles Wang et al 2004 Deleterious alleles • Coding SNPs often simply categorized as synonymous (same amino acid) or non-synonymous (different amino acid) • But not all non-synonymous SNPs are equivalent ≠ Ala Gly Ala Cys Factors that may govern accumulation of deleterious allele • Genomic – Recombination – Hitchhiking – Direct positive selection – are some of these alleles conditionally advantageous? • Demographic – Population history (bottlenecks, etc) – Population size (efficiency of selection) Sorting Intolerant From Tolerant (SIFT) • Uses multiple alignments from related species to classify SNPs as tolerated or damaging • Examples: – If no amino acid substitution is found at that site, any nonsyn change is deleterious – If only hydrophobic residues found, changes to other amino acid classes deleterious • No information about protein structure, but performs similarly to algorithms that account for this – Advantage: can be used on just about any sequence, not just those with known structure information Deleterious SNPs segregate at lower frequency than tolerated SNPs Derived allele frequency Deleterious : tolerated ratio Percent Deleterious SNPs segregate at lower frequency than tolerated SNPs Derived allele frequency Determinants of deleterious frequency: recombination More generally – recombination rate variation correlated with deleterious ratio Determinants of deleterious frequency: hitchhiking • iHS = measure of incomplete hitchhiking events • iHS higher for windows enriched for deleterious SNPs Density • Deleterious ratio higher in top 1% of iHS windows 60 40 All Deleterious enriched 20 0 • Signal of direct or linked selection? 0.6 0.8 1.0 Normalized iHS 1.2 Any evidence for direct selection? • Suggests deleterious alleles mostly not direct targets of positive selection 0.15 0.00 • Deleterious alleles underrepresented among FST outliers 0.05 0.10 • FST outliers identified across three sampling transects (two altitudinal and one latitudinal) All SNPs Significant outliers Coquihalla Highway 99 Deleterious:Tolerated ratio Rangewide Determinants of deleterious frequency: historical demography • Like many northern species, poplar experienced bottlenecks associated with Pleistocene glaciation – Increased drift in leading edge populations • More generally, variation in Ne across the range may lead to differential efficiency of purifying selection Determinants of deleterious frequency: historical demography Why does this matter? Deleterious alleles affect fitness BC Garden VA Garden Can we detect the signature of deleterious alleles at individual SNP loci? • Sort of – deleterious alleles overrepresented among associated genes, but underrepresented among associated SNPs • Low frequency deleterious alleles generating ‘synthetic’ associations? Conclusions • Deleterious alleles impact performance, and may explain some phenotypic associations for tolerated SNPs • Accumulate as a result of recombination rate variation, hitchhiking, and demographic history • More common in peripheral populations – Response to selection may be weaker in these populations, which suggests less adaptive potential under climate change Acknowledgements • • • • Mandy Zhang, Lecong Zhou, Haktan Suren, Rajesh Bawa Kyle Peer, Clay Sawyers, Debbie Byrd (VA Garden) Mike Carlson (BC Forest Service) and Cees Van Oosten (BC Garden) Carl Douglas and BC Forest Service – access to some BC samples