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When assuming a single dominance coefficient for all nonsynonymous mutations, we find that numerous h values can fit the data, so long as h is greater than ~0.15. Moreover, we also observe that theoretically-predicted models with a negative relationship between h and s can also fit the data well, including models with h = 0.05 for strongly deleterious mutations. Finally, we use our estimated dominance and selection parameters to inform simulations revisiting the question of whether the out-of-Africa bottleneck has led to differences in genetic load between African and non-African human populations. These simulations suggest that the relative burden of genetic load in non-African populations depends on the dominance model assumed, with slight increases for more weakly recessive models and slight decreases shown for more strongly recessive models. Moreover, these results also demonstrate that models of partially recessive nonsynonymous mutations can explain the observed severity of inbreeding depression in humans, bridging the gap between molecular population genetics and direct measures of fitness in humans. Our work represents a comprehensive assessment of dominance and deleterious variation in humans, with implications for parameterizing models of deleterious variation in humans and other mammalian species.</p>","PeriodicalId":49007,"journal":{"name":"PLoS Genetics","volume":"20 9","pages":"e1011198"},"PeriodicalIF":4.0000,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11446423/pdf/","citationCount":"0","resultStr":"{\"title\":\"Constraining models of dominance for nonsynonymous mutations in the human genome.\",\"authors\":\"Christopher C Kyriazis, Kirk E Lohmueller\",\"doi\":\"10.1371/journal.pgen.1011198\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Dominance is a fundamental parameter in genetics, determining the dynamics of natural selection on deleterious and beneficial mutations, the patterns of genetic variation in natural populations, and the severity of inbreeding depression in a population. Despite this importance, dominance parameters remain poorly known, particularly in humans or other non-model organisms. A key reason for this lack of information about dominance is that it is extremely challenging to disentangle the selection coefficient (s) of a mutation from its dominance coefficient (h). Here, we explore dominance and selection parameters in humans by fitting models to the site frequency spectrum (SFS) for nonsynonymous mutations. When assuming a single dominance coefficient for all nonsynonymous mutations, we find that numerous h values can fit the data, so long as h is greater than ~0.15. Moreover, we also observe that theoretically-predicted models with a negative relationship between h and s can also fit the data well, including models with h = 0.05 for strongly deleterious mutations. Finally, we use our estimated dominance and selection parameters to inform simulations revisiting the question of whether the out-of-Africa bottleneck has led to differences in genetic load between African and non-African human populations. These simulations suggest that the relative burden of genetic load in non-African populations depends on the dominance model assumed, with slight increases for more weakly recessive models and slight decreases shown for more strongly recessive models. Moreover, these results also demonstrate that models of partially recessive nonsynonymous mutations can explain the observed severity of inbreeding depression in humans, bridging the gap between molecular population genetics and direct measures of fitness in humans. 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引用次数: 0
摘要
优势度是遗传学中的一个基本参数,它决定了有害突变和有益突变的自然选择动态、自然种群的遗传变异模式以及种群近交抑郁的严重程度。尽管如此重要,优势参数仍然鲜为人知,尤其是在人类或其他非模式生物中。缺乏优势信息的一个重要原因是,将突变的选择系数(s)与其优势系数(h)区分开来极具挑战性。在这里,我们通过对非同义突变的位点频谱(SFS)拟合模型来探索人类的优势和选择参数。当假定所有非同义突变都有一个单一的优势系数时,我们发现只要 h 大于 ~0.15,众多 h 值都能拟合数据。此外,我们还观察到,理论上预测的 h 与 s 负相关的模型也能很好地拟合数据,包括 h = 0.05 的强致死突变模型。最后,我们利用估计的优势和选择参数进行模拟,重新探讨非洲以外的瓶颈是否导致非洲和非非洲人种群之间遗传负荷的差异。这些模拟结果表明,非洲以外人群遗传负荷的相对负担取决于所假设的显性模型,隐性较弱的模型略有增加,隐性较强的模型略有减少。此外,这些结果还证明,部分隐性非同义突变模型可以解释观察到的人类近亲繁殖抑制的严重程度,从而弥补了分子群体遗传学与人类健康状况直接测量之间的差距。我们的研究是对人类显性和有害变异的全面评估,对人类和其他哺乳动物有害变异模型的参数化具有重要意义。
Constraining models of dominance for nonsynonymous mutations in the human genome.
Dominance is a fundamental parameter in genetics, determining the dynamics of natural selection on deleterious and beneficial mutations, the patterns of genetic variation in natural populations, and the severity of inbreeding depression in a population. Despite this importance, dominance parameters remain poorly known, particularly in humans or other non-model organisms. A key reason for this lack of information about dominance is that it is extremely challenging to disentangle the selection coefficient (s) of a mutation from its dominance coefficient (h). Here, we explore dominance and selection parameters in humans by fitting models to the site frequency spectrum (SFS) for nonsynonymous mutations. When assuming a single dominance coefficient for all nonsynonymous mutations, we find that numerous h values can fit the data, so long as h is greater than ~0.15. Moreover, we also observe that theoretically-predicted models with a negative relationship between h and s can also fit the data well, including models with h = 0.05 for strongly deleterious mutations. Finally, we use our estimated dominance and selection parameters to inform simulations revisiting the question of whether the out-of-Africa bottleneck has led to differences in genetic load between African and non-African human populations. These simulations suggest that the relative burden of genetic load in non-African populations depends on the dominance model assumed, with slight increases for more weakly recessive models and slight decreases shown for more strongly recessive models. Moreover, these results also demonstrate that models of partially recessive nonsynonymous mutations can explain the observed severity of inbreeding depression in humans, bridging the gap between molecular population genetics and direct measures of fitness in humans. Our work represents a comprehensive assessment of dominance and deleterious variation in humans, with implications for parameterizing models of deleterious variation in humans and other mammalian species.
期刊介绍:
PLOS Genetics is run by an international Editorial Board, headed by the Editors-in-Chief, Greg Barsh (HudsonAlpha Institute of Biotechnology, and Stanford University School of Medicine) and Greg Copenhaver (The University of North Carolina at Chapel Hill).
Articles published in PLOS Genetics are archived in PubMed Central and cited in PubMed.