Background selection and biased gene conversion affect more than 95% of the human genome and bias demographic inferences

Pouyet, Fanny; Aeschbacher, Simon; Thiéry, Alexandre; Excoffier, Laurent

doi:10.7554/elife.36317

Cited by 142 publications

(180 citation statements)

References 77 publications

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“…A recent study estimated that more than 95% of the human genome is affected by background selection or biased gene conversion, and thus is evolving in a nonneutral manner (Pouyet et al. 2018). Furthermore, parallel adaptation for a derived haplotype at a specific locus in two populations can be misinterpreted as selection on the ancestral haplotype in a third population in three‐population comparisons, such as implemented in the population branch statistic (see Mathieson 2019; Fig.…”

Section: Detecting Positive Selection On a Monogenic Or Oligogenic Traitmentioning

confidence: 99%

Inference of natural selection from ancient DNA

Dehasque

Ávila‐Arcos²,

Díez-del-Molino

et al. 2020

Evolution Letters

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Evolutionary processes, including selection, can be indirectly inferred based on patterns of genomic variation among contemporary populations or species. However, this often requires unrealistic assumptions of ancestral demography and selective regimes.Sequencing ancient DNA from temporally spaced samples can inform about past selection processes, as time series data allow direct quantification of population parameters collected before, during, and after genetic changes driven by selection. In this 9 4Comment and Opinion, we advocate for the inclusion of temporal sampling and the generation of paleogenomic datasets in evolutionary biology, and highlight some of the recent advances that have yet to be broadly applied by evolutionary biologists.In doing so, we consider the expected signatures of balancing, purifying, and positive selection in time series data, and detail how this can advance our understanding of the chronology and tempo of genomic change driven by selection. However, we also recognize the limitations of such data, which can suffer from postmortem damage, fragmentation, low coverage, and typically low sample size. We therefore highlight the many assumptions and considerations associated with analyzing paleogenomic data and the assumptions associated with analytical methods. K E Y W O R D S : Adaptation, ancient DNA, natural selection, paleogenomics, time series. Impact SummaryThe search for signatures of natural selection on the genome is still most commonly based on screening modern genomes for regions of reduced diversity or increased differentiation between populations. This framework is essentially a snapshot in time of a process that may have played out over many millennia, during which changes in population size, ecology and gene flow between populations may have played a role in determining genetic variation. Here, we outline how utilising ancient DNA (aDNA) techniques to sequence time series of genomes spanning changes in natural selection can provide a more nuanced understanding of how natural selection has impacted genomic variation in present-day populations. In particular, we argue that the advent of paleo-population genomics, in which datasets of multiple individuals spanning millennia have been sequenced, offers unprecedented opportunity to estimate changes in allele frequencies through time. We outline considerations and the types of data that would be needed for the inference of positive selection on traits associated with single and many genes (polygenic), genome-wide negative (background) selection, and balancing selection. However, we recognise that there are currently few datasets existing that are suitable for these types of investigation. There is thus a bias towards study species that have undergone strong selection over relatively recent timescales that are within the scope of aDNA, such as has occurred in domesticated species. We also detail a number of caveats associated with working with aDNA data, which is by its nature comprised of short, degraded DNA fragments, typicall...

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Section: Detecting Positive Selection On a Monogenic Or Oligogenic Traitmentioning

confidence: 99%

Inference of natural selection from ancient DNA

Dehasque

Ávila‐Arcos²,

Díez-del-Molino

et al. 2020

Evolution Letters

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“…Nevertheless, understanding the impact of linked selection, especially in the form of background selection, is important for inference of adaptation, since genomic regions experiencing different magnitudes of background selection are expected to harbor different baseline levels of diversity (Burri et al, 2015;Comeron, 2014Comeron, , 2017Elyashiv et al, 2016;Huber, DeGiorgio, Hellmann, & Nielsen, 2016). As linked selection can affect a large proportion of the genome (Pouyet, Aeschbacher, Thiéry, & Excoffier, 2018;Woerner, Veeramah, Watkins, & Hammer, 2018), characterizing its effects is of great importance. If not properly accounted for, linked selection may thus give rise to a false signal of population size expansion in demographic inference (Ewing & Jensen, 2016) and result in incorrect model selection (Schrider, Shanku, & Kern, 2016).…”

Section: Introductionmentioning

confidence: 99%

“…If not properly accounted for, linked selection may thus give rise to a false signal of population size expansion in demographic inference (Ewing & Jensen, 2016) and result in incorrect model selection (Schrider, Shanku, & Kern, 2016). As linked selection can affect a large proportion of the genome (Pouyet, Aeschbacher, Thiéry, & Excoffier, 2018;Woerner, Veeramah, Watkins, & Hammer, 2018), characterizing its effects is of great importance.…”

Section: Introductionmentioning

confidence: 99%

Impact of demography on linked selection in two outcrossing Brassicaceae species

Mattila

Laenen

Horváth

et al. 2019

Ecology and Evolution

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Genetic diversity is shaped by mutation, genetic drift, gene flow, recombination, and selection. The dynamics and interactions of these forces shape genetic diversity across different parts of the genome, between populations and species. Here, we have studied the effects of linked selection on nucleotide diversity in outcrossing populations of two Brassicaceae species, Arabidopsis lyrata and Capsella grandiflora, with contrasting demographic history. In agreement with previous estimates, we found evidence for a modest population size expansion thousands of generations ago, as well as efficient purifying selection in C. grandiflora. In contrast, the A. lyrata population exhibited evidence for very recent strong population size decline and weaker efficacy of purifying selection. Using multiple regression analyses with recombination rate and other genomic covariates as explanatory variables, we can explain 47% of the variance in neutral diversity in the C. grandiflora population, while in the A. lyrata population, only 11% of the variance was explained by the model. Recombination rate had a significant positive effect on neutral diversity in both species, suggesting that selection at linked sites has an effect on patterns of neutral variation. In line with this finding, we also found reduced neutral diversity in the vicinity of genes in the C. grandiflora population. However, in A. lyrata no such reduction in diversity was evident, a finding that is consistent with expectations of the impact of a recent bottleneck on patterns of neutral diversity near genes. This study thus empirically demonstrates how differences in demographic history modulate the impact of selection at linked sites in natural populations.

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“…For technical and computational reasons most popular models that estimate substitution rates assume that base composition is at equilibrium (Jukes and Cantor, 1969; Kimura, 1980; Felsenstein, 1981; Kimura, 1980, 1981). However, as there is a substantial base composition heterogeneity within and across genomes (Bernardi, 2000; Dreszer et al, 2007; Romiguier et al, 2010; Lartillot, 2013; Pouyet et al, 2017, 2018) this assumption is likely to be violated, and in fact base composition might change over time (Duret and Arndt, 2008).…”

Section: Introductionmentioning

confidence: 99%

Evidence for strong fixation bias at 4-fold degenerate sites across genes in the great tit genome

Gossmann

Bockwoldt

Diringer

et al. 2018

Preprint

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3It is well established that GC content varies across the genome in many species and that 4 GC biased gene conversion, one form of meiotic recombination, is likely to contribute to this 5 heterogeneity. Bird genomes provide an extraordinary system to study the impact of GC biased 6 gene conversion owed to their specific genomic features. They are characterised by a high 7 karyotype conservation with substantial heterogeneity in chromosome sizes, with up to a dozen 8 large macrochromosomes and many smaller microchromosomes common across all bird species. 9 This heterogeneity in chromosome morphology is also reflected by other genomic features, such 10 as smaller chromosomes being gene denser, more compact and more GC rich relative to their 11 macrochromosomal counterparts -illustrating that the intensity of GC biased gene conversion 12 varies across the genome. Here we study whether it is possible to infer heterogeneity in GC biased 13 gene conversion rates across the genome using a recently published method that accounts for 14 GC biased gene conversion when estimating branch lengths in a phylogenetic context. To infer the 15 strength of GC biased gene conversion we contrast branch length estimates across the genome 16 both taking and not taking non-stationary GC composition into account. Using simulations we 17 show that this approach works well when GC fixation bias is strong and note that the number of 18 substitutions along a branch is consistently overestimated when GC biased gene conversion is 19 1 Gossmann et al. GC fixation bias in bird genomesnot accounted for. We use this predictable feature to infer the strength of GC dynamics across the 20 great tit genome by applying our new test statistic to data at 4-fold degenerate sites from three 21 bird species -great tit, zebra finch and chicken -three species that are among the best annotated 22 bird genomes to date. We show that using a simple one-dimensional binning we fail to capture a 23 signal of fixation bias as observed in our simulations. However, using a multidimensional binning 24 strategy, we find evidence for heterogeneity in the strength of fixation bias, including AT fixation 25 bias. This highlights the difficulties when combining sequence data across different regions in the 26 genome. 27

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Background selection and biased gene conversion affect more than 95% of the human genome and bias demographic inferences

Cited by 142 publications

References 77 publications

Inference of natural selection from ancient DNA

Inference of natural selection from ancient DNA

Impact of demography on linked selection in two outcrossing Brassicaceae species

Evidence for strong fixation bias at 4-fold degenerate sites across genes in the great tit genome

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