On the prospect of achieving accurate joint estimation of selection with population history

Johri, Parul; Eyre‐Walker, Adam; Gutenkunst, Ryan N.; Lohmueller, Kirk E.; Jensen, Jeffrey D.

doi:10.1093/gbe/evac088

Cited by 37 publications

(38 citation statements)

References 87 publications

(105 reference statements)

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“…These two-step procedures suffer from the difficulty of rejecting the null hypothesis of selective neutrality and the issue of underestimating the population size and selection coefficients ( Paris et al 2019 ), in particular with an increase in the proportion of selected loci across the genome. A method to address this issue can be to co-estimate the population size with purifying and background selection in the first step as a null model and then fix that model in the second step ( Johri et al 2020 , 2021 ; Johri, Aquadro, et al 2022 ; Johri, Eyre-Walker, et al 2022 ). Joint inference of demographic and selective parameters from ancient genomes, an important topic of future investigation, is anticipated to significantly improve the estimation of selection coefficients and even permit the inference of demographic changes.…”

Section: Discussionmentioning

confidence: 99%

Estimating Temporally Variable Selection Intensity from Ancient DNA Data

Dai

Lyu

et al. 2023

Molecular Biology and Evolution

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Novel technologies for recovering DNA information from archaeological and historical specimens have made available an ever-increasing amount of temporally spaced genetic samples from natural populations. These genetic time series permit the direct assessment of patterns of temporal changes in allele frequencies, and hold the promise of improving power for the inference of selection. Increased time resolution can further facilitate testing hypotheses regarding the drivers of past selection events such as the incidence of plant and animal domestication. However, studying past selection processes through ancient DNA (aDNA) still involves considerable obstacles such as postmortem damage, high fragmentation, low coverage and small samples. To circumvent these challenges, we introduce a novel Bayesian framework for the inference of temporally variable selection based on genotype likelihoods instead of allele frequencies, thereby enabling us to model sample uncertainties resulting from the damage and fragmentation of aDNA molecules. Also, our approach permits the reconstruction of the underlying allele frequency trajectories of the population through time, which allows for a better understanding of the drivers of selection. We evaluate its performance through extensive simulations and demonstrate its utility with an application to the ancient horse samples genotyped at the loci for coat colouration. Our results reveal that incorporating sample uncertainties can further improve the inference of selection.

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Section: Discussionmentioning

confidence: 99%

Estimating Temporally Variable Selection Intensity from Ancient DNA Data

Dai

Lyu

et al. 2023

Molecular Biology and Evolution

View full text Add to dashboard Cite

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“…These two-step procedures suffer from the difficulty of rejecting the null hypothesis of selective neutrality and the issue of underestimating the population size and selection coefficients (Paris et al, 2019), in particular with an increase in the proportion of selected loci across the genome. A method to address this issue can be to co-estimate the population size with purifying and background selection in the first step as a null model and then fix that model in the second step (Johri et al, 2020, 2021, 2022a,b). Joint inference of demographic and selective parameters from ancient genomes, an important topic of future investigation, is anticipated to significantly improve the estimation of selection coefficients and even permit the inference of demographic changes.…”

Section: Discussionmentioning

confidence: 99%

Estimating temporally variable selection intensity from ancient DNA data

Dai

Lyu

et al. 2022

Preprint

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Novel technologies for recovering DNA information from archaeological and historical specimens have made available an ever-increasing amount of temporally-spaced genetic samples from natural populations. These genetic time series permit the direct assessment of patterns of temporal changes in allele frequencies, and hold the promise of improving power for inference of selection. Increased time resolution can further facilitate testing hypotheses regarding the drivers of past selection events like plant and animal domestication. However, studying past selection processes through ancient DNA (aDNA) still involves considerable obstacles such as postmortem damage, high fragmentation, low coverage and small samples. To address these challenges, we introduce a novel Bayesian approach for the inference of temporally variable selection based on genotype likelihoods instead of allele frequencies, thereby enabling us to account for sample uncertainties resulting from the damage and fragmentation of aDNA molecules. Also, our method permits the reconstruction of the underlying mutant allele frequency trajectory of the population through time, which allows for a better understanding of the drivers of selection. We evaluate its performance through extensive simulations and illustrate its utility with an application to the ancient horse samples genotyped at the loci for coat colouration.

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“…This is hard to fit with estimates of the time of speciation between B. platyphylla and B. pendula which different studies place between 36,000 years (Tsuda et al, 2017) and 2.6 million years (Chen et al, 2021) ago. We note, however, that our demographic simulation results are provisional as it is hard to distinguish among the many factors that affect patterns genetic variation (Jorhi et al, 2022), and our assumptions about mutation rate and generation time may be incorrect. We cannot therefore exclude the possibility that our simulations are picking up signals of B. platyphylla population isolation due to separate refugia in recent glaciations.…”

Section: Pan Eurasian Population Genetic Structure Of White Birchmentioning

confidence: 97%

Genomic signals of local adaptation and hybridization in Asian white birch

et al. 2022

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Disentangling the numerous processes that affect patterns of genome‐wide diversity in widespread tree species has important implications for taxonomy, conservation, and forestry. Here, we investigate the population genomic structure of Asian white birch (Betula platyphylla) in China and seek to explain it in terms of hybridization, demography and adaptation. We generate whole genome sequence data from 83 individuals across the species range in China. Combining this with an existing data set for 79 European and Russian white birches, we show a clear distinction between B. pendula and B. platyphylla, which have sometimes been lumped taxonomically. Genomic diversity of B. platyphylla in north‐western China and Central Russia is affected greatly by hybridization with B. pendula. Excluding these hybridized populations, B. platyphylla in China has a linear distribution from north‐eastern to south‐western China, along the edge of the inland mountainous region. Within this distribution, three genetic clusters are found, which we model as long diverged with subsequent episodes of gene flow. Patterns of covariation between allele frequencies and environmental variables in B. platyphylla suggest the role of natural selection in the distribution of diversity at 7609 SNPs of which 3767 were significantly differentiated among the genetic clusters. The putative adaptive SNPs are distributed throughout the genome and span 1633 genic regions. Of these genic regions, 87 were previously identified as candidates for selective sweeps in Eurasian B. pendula. We use the 7609 environmentally associated SNPs to estimate the risk of nonadaptedness for each sequenced B. platyphylla individual under a scenario of future climate change, highlighting areas where populations may be under future threat from rising temperatures.

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On the prospect of achieving accurate joint estimation of selection with population history

Cited by 37 publications

References 87 publications

Estimating Temporally Variable Selection Intensity from Ancient DNA Data

Estimating Temporally Variable Selection Intensity from Ancient DNA Data

Estimating temporally variable selection intensity from ancient DNA data

Genomic signals of local adaptation and hybridization in Asian white birch

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