scholarly journals Deleterious variation mimics signatures of genomic incompatibility and adaptive introgression

2017 ◽  
Author(s):  
Bernard Y. Kim ◽  
Christian D. Huber ◽  
Kirk E. Lohmueller
Keyword(s):  
Population Genetic ◽  
Natural Populations ◽  
Genetic Load ◽  
Population Admixture ◽  
Population Differences ◽  
Deleterious Mutations ◽  
Recombination Rates ◽  
Adaptive Introgression ◽  
Fitness Effects ◽  
New Mutations

AbstractWhile it is appreciated that population size changes can impact patterns of deleterious variation in natural populations, less attention has been paid to how population admixture affects the dynamics of deleterious variation. Here we use population genetic simulations to examine how admixture impacts deleterious variation under a variety of demographic scenarios, dominance coefficients, and recombination rates. Our results show that gene flow between populations can temporarily reduce the genetic load of smaller populations, especially if deleterious mutations are recessive. Additionally, when fitness effects of new mutations are recessive, between-population differences in the sites at which deleterious variants exist creates heterosis in hybrid individuals. This can lead to an increase in introgressed ancestry, particularly when recombination rates are low. Under certain scenarios, introgressed ancestry can increase from an initial frequency of 5% to 30-75% and fix at many loci, even in the absence of beneficial mutations. Further, deleterious variation and admixture can generate correlations between the frequency of introgressed ancestry and recombination rate or exon density, even in the absence of other types of selection. The direction of these correlations is determined by the specific demography and whether mutations are additive or recessive. Therefore, it is essential that null models include both demography and deleterious variation before invoking reproductive incompatibilities or adaptive introgression to explain unusual patterns of genetic variation.

scholarly journals Gene expression drives the evolution of dominance

2017 ◽  
Author(s):  
Christian D. Huber ◽  
Arun Durvasula ◽  
Angela M. Hancock ◽  
Kirk E. Lohmueller
Keyword(s):  
Complex Traits ◽  
Mating Systems ◽  
Multiple Mating ◽  
Expression Patterns ◽  
Natural Populations ◽  
Deleterious Mutations ◽  
Fitness Effects ◽  
Population Genomic ◽  
Degree Of Dominance ◽  
New Mutations

AbstractDominance is a fundamental concept in molecular genetics and has implications for understanding patterns of genetic variation, evolution, and complex traits. However, despite its importance, the degree of dominance has yet to be quantified in natural populations. Here, we leverage multiple mating systems in natural populations of Arabidopsis to co-estimate the distribution of fitness effects and dominance coefficients of new amino acid changing mutations. We find that more deleterious mutations are more likely to be recessive than less deleterious mutations. Further, this pattern holds across gene categories, but varies with the connectivity and expression patterns of genes. Our work argues that dominance arose as the inevitable consequence of the functional importance of genes and their optimal expression levels.One sentence summaryWe use population genomic data to characterize the degree of dominance for new mutations and develop a new theory for its evolution.

scholarly journals Recessive deleterious variation has a limited impact on signals of adaptive introgression in human populations

2020 ◽  
Author(s):  
Xinjun Zhang ◽  
Bernard Kim ◽  
Kirk E. Lohmueller ◽  
Emilia Huerta-Sánchez
Keyword(s):  
False Positive ◽  
False Positive Rate ◽  
Genomic Variation ◽  
Human Populations ◽  
Deleterious Mutations ◽  
Modern Humans ◽  
Recombination Rates ◽  
Limited Impact ◽  
Adaptive Mutations ◽  
Adaptive Introgression

AbstractAdmixture with archaic hominins has altered the landscape of genomic variation in modern human populations. Several gene regions have been previously identified as candidates of adaptive introgression (AI) that facilitated human adaptation to specific environments. However, simulation-based studies have suggested that population genetics processes other than adaptive mutations, such as heterosis from recessive deleterious variants private to populations before admixture, can also lead to patterns in genomic data that resemble adaptive introgression. The extent to which the presence of deleterious variants affect the false-positive rate and the power of current methods to detect AI has not been fully assessed. Here, we used extensive simulations to show that recessive deleterious mutations can increase the false positive rates of tests for AI compared to models without deleterious variants. We further examined candidates of AI in modern humans identified from previous studies and show that, although deleterious variants may hinder the performance of AI detection in modern humans, most signals remained robust when deleterious variants are included in the null model. While deleterious variants may have a limited impact on detecting signals of adaptive introgression in humans, we found that at least two AI candidate genes, HYAL2 and HLA, are particularly susceptible to high false positive rates due to the recessive deleterious mutations. By quantifying parameters that affect heterosis, we show that the high false positives are largely attributed to the high exon densities together with low recombination rates in the genomic regions, which can further be exaggerated by the population growth in recent human evolution. Although the combination of such parameters is rare in the human genome, caution is still warranted in other species with different genomic composition and demographic histories.

scholarly journals Inbreeding depression and genetic load at partially linked loci in a metapopulation

2010 ◽  
Vol 92 (2) ◽  
pp. 127-140 ◽  
Author(s):  
SHU-RONG ZHOU ◽  
JOHN R. PANNELL
Keyword(s):  
Inbreeding Depression ◽  
Random Mating ◽  
Genetic Load ◽  
Minor Effect ◽  
Deleterious Mutations ◽  
Recombination Rates ◽  
Sexual Systems ◽  
Biological Phenomena ◽  
Population Turnover ◽  
Wide Range

SummaryInbreeding depression has important implications for a wide range of biological phenomena, such as inbreeding avoidance, the evolution and maintenance of sexual systems and extinction rates of small populations. Previous investigations have asked how inbreeding depression evolves in single and subdivided populations through the fixation of deleterious mutations as a result of drift, as well as through the expression of deleterious mutations segregating in a population. These studies have focused on the effects of mutation and selection at single loci, or at unlinked loci. Here, we used simulations to investigate the evolution of genetic load and inbreeding depression due to multiple partially linked loci in metapopulations. Our results indicate that the effect of linkage depends largely on the kinds of deleterious alleles involved. For weakly deleterious and partially recessive mutations, the speed of mutation accumulation at segregating loci in a random-mating subdivided population of a given structure tends to be retarded by increased recombination between adjacent loci – although the highest numbers of fixation of slightly recessive mutant alleles were for low but finite recombination rates. Although linkage had a relatively minor effect on the evolution of metapopulations unless very low values of recombination were assumed, close linkage between adjacent loci tended to enhance population structure and population turnover. Finally, within-deme inbreeding depression, between-deme inbreeding depression and heterosis generally increased with decreased recombination rates. Moreover, increased selfing reduced the effective amount of recombination, and hence the effects of tight linkage on metapopulation genetic structure were decreased with increasing selfing. In contrast, linkage had little effect on the fate of lethal and highly recessive alleles. We compare our simulation results with predictions made by models that ignore the complexities of recombination.

scholarly journals The genetic structure of natural populations of Drosophila melanogaster. XXIV. Effects of hybrid dysgenesis on the components of genetic variance of variability.

Genetics ◽  
1991 ◽  
Vol 127 (3) ◽  
pp. 545-552
Author(s):  
D S Suh ◽  
T Mukai
Keyword(s):  
Drosophila Melanogaster ◽  
Population Genetic ◽  
Genetic Parameters ◽  
Genetic Variance ◽  
Additive Genetic Variance ◽  
Natural Populations ◽  
Deleterious Mutations ◽  
Degree Of Dominance ◽  
Population Genetic Parameters ◽  
P Type

Abstract Eight hundred second chromosomes were extracted from the Ishigakijima population, one of the southernmost populations of Drosophila melanogaster in Japan. Half of them were extracted in Native cytoplasm (P-type), and half in Foreign cytoplasm (M-type). Various population-genetic parameters, including the frequency of lethal-carrying second chromosomes (Q = 0.235 for the Native; 0.218 for the Foreign), the allelism rate of lethal second chromosome (Ic = 0.0217 for the Native; 0.0134 for the Foreign), the homozygous detrimental and lethal loads (D = 0.179 for the Native; 0.270 for the Foreign; L = 0.262 for the Native; 0.240 for the Foreign), the average degree of dominance of mildly deleterious mutations (ĥE = 0.244 for the Native; 0.208 for the Foreign), and the components of genetic variance for viability [additive (sigma A2) and dominance (sigma D2)](ŝigma A2 = 0.0187 for the Native; 0.0172 for the Foreign; ŝigma D2 = 0.0005 for the Native; 0.0009 for the Foreign) were estimated. The data indicate that D was significantly larger and hE was significantly smaller in the Foreign cytoplasm. However, the estimates of additive and dominance variances were not significantly different between the two cytoplasms. The additive genetic variance for viability in the Ishigakijima population was greater than expected on the basis of mutation-selection balance confirming previous studies on papers of D. melanogaster in warm climates.

scholarly journals The Impact of Recessive Deleterious Variation on Signals of Adaptive Introgression in Human Populations

Genetics ◽  
2020 ◽  
Vol 215 (3) ◽  
pp. 799-812 ◽  
Author(s):  
Xinjun Zhang ◽  
Bernard Kim ◽  
Kirk E. Lohmueller ◽  
Emilia Huerta-Sánchez
Keyword(s):  
Human Genome ◽  
False Positive ◽  
False Positive Rate ◽  
Genomic Variation ◽  
Human Populations ◽  
Deleterious Mutations ◽  
Recombination Rates ◽  
Adaptive Mutations ◽  
Adaptive Introgression ◽  
The Impact

Admixture with archaic hominins has altered the landscape of genomic variation in modern human populations. Several gene regions have been identified previously as candidates of adaptive introgression (AI) that facilitated human adaptation to specific environments. However, simulation-based studies have suggested that population genetic processes other than adaptive mutations, such as heterosis from recessive deleterious variants private to populations before admixture, can also lead to patterns in genomic data that resemble AI. The extent to which the presence of deleterious variants affect the false-positive rate and the power of current methods to detect AI has not been fully assessed. Here, we used extensive simulations under parameters relevant for human evolution to show that recessive deleterious mutations can increase the false positive rates of tests for AI compared to models without deleterious variants, especially when the recombination rates are low. We next examined candidates of AI in modern humans identified from previous studies, and show that 24 out of 26 candidate regions remain significant, even when deleterious variants are included in the null model. However, two AI candidate genes, HYAL2 and HLA, are particularly susceptible to high false positive signals of AI due to recessive deleterious mutations. These genes are located in regions of the human genome with high exon density together with low recombination rate, factors that we show increase the rate of false-positives due to recessive deleterious mutations. Although the combination of such parameters is rare in the human genome, caution is warranted in such regions, as well as in other species with more compact genomes and/or lower recombination rates. In sum, our results suggest that recessive deleterious mutations cannot account for the signals of AI in most, but not all, of the top candidates for AI in humans, suggesting they may be genuine signals of adaptation.

scholarly journals Estimation of Deleterious-Mutation Parameters in Natural Populations

Genetics ◽  
1996 ◽  
Vol 144 (1) ◽  
pp. 349-360 ◽  
Author(s):  
Hong-Wen Deng ◽  
Michael Lynch
Keyword(s):  
Genetic Variance ◽  
Deleterious Mutation ◽  
Natural Populations ◽  
Breeding Systems ◽  
Deleterious Mutations ◽  
Empirical Estimates ◽  
Mean Fitness ◽  
The Mean ◽  
New Mutations

Abstract The rate and average effects of spontaneous deleterious mutations are important determinants of the evolution of breeding systems and of the vulnerability of small populations to extinction. Nevertheless, few attempts have been made to estimate the properties of such mutations, and those studies that have been performed have been extremely labor intensive, relying on long-term, laboratory mutation-accumulation experiments. We present an alternative to the latter approach. For populations in which the genetic variance for fitness is a consequence of selection-mutation balance, the mean fitness and genetic variance of fitness in outbred and inbred generations can be expressed as simple functions of the genomic mutation rate, average homozygous effect and average dominance coefficient of new mutations. Using empirical estimates for the mean and genetic variance of fitness, these expressions can then be solved to obtain joint estimates of the deleterious-mutation parameters. We employ computer simulations to evaluate the degree of bias of the estimators and present some general recommendations on the application of the technique. Our procedures provide some hope for obtaining estimates of the properties of deleterious mutations from a wide phylogenetic range of species as well as a mechanism for testing the validity of alternative models for the maintenance of genetic variance for fitness.

scholarly journals Gene flow biases population genetic inference of recombination rate

2021 ◽  
Author(s):  
Kieran Samuk ◽  
Mohamed A.F. Noor
Keyword(s):  
Gene Flow ◽  
Recombination Rate ◽  
Population Genetic ◽  
Natural Populations ◽  
Recombination Rates ◽  
False Negatives ◽  
Isolation With Migration ◽  
Simplifying Assumptions ◽  
Population Genetic Inference ◽  
Genetic Inference

Accurate estimates of the rate of recombination are key to understanding a host of evolutionary processes as well as the evolution of recombination rate itself. Model-based population genetic methods that infer recombination rates from patterns of linkage disequilibrium (LD) in the genome have become a popular method to estimate rates of recombination. However, these LD-based methods make a variety of simplifying assumptions about the populations of interest that are often not met in natural populations. One such assumption is the absence of gene flow from other populations. Here, we use forward-time population genetic simulations of isolation-with-migration scenarios to explore how gene flow affects the accuracy of LD-based estimators of recombination rate. We find that moderate levels of gene flow can result in either the overestimation or underestimation of recombination rates by up to 20-50% depending on the timing of divergence. We also find that these biases can affect the detection of interpopulation differences in recombination rate, causing both false positive and false negatives depending on the scenario. We discuss future possibilities for mitigating these biases and recommend that investigators exercise caution and confirm that their study populations meet assumptions before deploying these methods.

scholarly journals Inference of the distribution of selection coefficients for new nonsynonymous mutations using large samples

2016 ◽  
Author(s):  
Bernard Y. Kim ◽  
Christian D. Huber ◽  
Kirk E. Lohmueller
Keyword(s):  
Frequency Spectrum ◽  
Mixture Distribution ◽  
Deleterious Mutations ◽  
Selection Coefficient ◽  
Sequencing Project ◽  
Fitness Effects ◽  
Large Samples ◽  
Exome Sequencing Project ◽  
Number Of Individuals ◽  
New Mutations

ABSTRACTThe distribution of fitness effects (DFE) has considerable importance in population genetics. To date, estimates of the DFE come from studies using a small number of individuals. Thus, estimates of the proportion of moderately to strongly deleterious new mutations may be unreliable because such variants are unlikely to be segregating in the data. Additionally, the true functional form of the DFE is unknown, and estimates of the DFE differ significantly between studies. Here we present a flexible and computationally tractable method, called Fit∂a∂i, to estimate the DFE using the site frequency spectrum from a large number of individuals. We apply our approach to the frequency spectrum of 1300 Europeans from the Exome Sequencing Project ESP6400 dataset, 1298 Danes from the LuCamp dataset, and 432 Europeans from the 1000 Genomes Project to estimate the DFE of deleterious nonsynonymous mutations. We infer significantly fewer (0.38-0.84x) strongly deleterious mutations with selection coefficient |s| > 0.01 and more (1.24-1.43x) weakly deleterious mutations with selection coefficient |s| < 0.001 compared to previous estimates. Furthermore, a DFE that is a mixture distribution of a point mass at neutrality plus a gamma distribution fits best to two of the three datasets. Our results suggest that nearly neutral forces play a larger role in human evolution than previously thought.

scholarly journals On the Rate and Linearity of Viability Declines in Drosophila Mutation-Accumulation Experiments: Genomic Mutation Rates and Synergistic Epistasis Revisited

Genetics ◽  
2004 ◽  
Vol 166 (2) ◽  
pp. 797-806 ◽  
Author(s):  
James D Fry
Keyword(s):  
Mutation Rate ◽  
Average Rate ◽  
Natural Populations ◽  
Mutation Accumulation ◽  
High Rate ◽  
Deleterious Mutations ◽  
Order Of Magnitude ◽  
Contamination Event ◽  
Genomic Mutation ◽  
The 1960S

Abstract High rates of deleterious mutations could severely reduce the fitness of populations, even endangering their persistence; these effects would be mitigated if mutations synergize each others’ effects. An experiment by Mukai in the 1960s gave evidence that in Drosophila melanogaster, viability-depressing mutations occur at the surprisingly high rate of around one per zygote and that the mutations interact synergistically. A later experiment by Ohnishi seemed to support the high mutation rate, but gave no evidence for synergistic epistasis. Both of these studies, however, were flawed by the lack of suitable controls for assessing viability declines of the mutation-accumulation (MA) lines. By comparing homozygous viability of the MA lines to simultaneously estimated heterozygous viability and using estimates of the dominance of mutations in the experiments, I estimate the viability declines relative to an appropriate control. This approach yields two unexpected conclusions. First, in Ohnishi’s experiment as well as in Mukai’s, MA lines showed faster-than-linear declines in viability, indicative of synergistic epistasis. Second, while Mukai’s estimate of the genomic mutation rate is supported, that from Ohnishi’s experiment is an order of magnitude lower. The different results of the experiments most likely resulted from differences in the starting genotypes; even within Mukai’s experiment, a subset of MA lines, which I argue probably resulted from a contamination event, showed much slower viability declines than did the majority of lines. Because different genotypes may show very different mutational behavior, only studies using many founding genotypes can determine the average rate and distribution of effects of mutations relevant to natural populations.

scholarly journals Estimation of Parameters of Deleterious Mutations in Partial Selfing or Partial Outcrossing Populations and in Nonequilibrium Populations

Genetics ◽  
2000 ◽  
Vol 154 (4) ◽  
pp. 1893-1906 ◽  
Author(s):  
Jian Li ◽  
Hong-Wen Deng
Keyword(s):  
Computer Simulations ◽  
Natural Populations ◽  
Deleterious Mutations ◽  
Selfing Rate ◽  
Estimation Of Parameters ◽  
Animal Populations ◽  
Rapid Pace ◽  
Dynamics Of Populations ◽  
Mutation And Selection

Abstract The Deng-Lynch method was developed to estimate the rate and effects of deleterious genomic mutations (DGM) in natural populations under the assumption that populations are either completely outcrossing or completely selfing and that populations are at mutation-selection (M-S) balance. However, in many plant and animal populations, selfing or outcrossing is often incomplete in that a proportion of populations undergo inbreeding while the rest are outcrossing. In addition, the degrees of deviation of populations from M-S balance are often not known. Through computer simulations, we investigated the robustness and the applicability of the Deng-Lynch method under different degrees of partial selfing or partial outcrossing and for nonequilibrium populations approaching M-S balance at different stages. The investigation was implemented under constant, variable, and epistatic mutation effects. We found that, generally, the estimation by the Deng-Lynch method is fairly robust if the selfing rate (S) is &lt;0.10 in outcrossing populations and if S &gt; 0.8 in selfing populations. The estimation may be unbiased under partial selfing with variable and epistatic mutation effects in predominantly outcrossing populations. The estimation is fairly robust in nonequilibrium populations at different stages approaching M-S balance. The dynamics of populations approaching M-S balance under various parameters are also studied. Under mutation and selection, populations approach balance at a rapid pace. Generally, it takes 400–2000 generations to reach M-S balance even when starting from homogeneous individuals free of DGM. Our investigation here provides a basis for characterizing DGM in partial selfing or outcrossing populations and for nonequilibrium populations.

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