Biology subjects

Kirk E Lohmueller

Publications and source records attributed to Kirk E Lohmueller.

5 recordsLinked to original sources

bioRxiv2016

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

The 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{partial}a{partial}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.

Evolutionary Biology↗

bioRxiv2016

Determining the factors driving selective effects of new nonsynonymous mutations

The distribution of fitness effects (DFE) of new mutations is a fundamental parameter in evolutionary genetics1-3. While theoretical models have emphasized the importance of distinct biological factors, such as protein folding4, back mutations5, species complexity6,7, and mutational robustness8 at determining the DFE, it remains unclear which of these models can describe the DFE in natural populations. Here, we show that the theoretical models make distinct predictions about how the DFE will differ between species. We further show that humans have a higher proportion of strongly deleterious mutations than Drosophila melanogaster. Comparing four categories of theoretical models, only Fishers Geometrical Model (FGM) is consistent with our data. FGM assumes that multiple phenotypes are under stabilizing selection, with the number of phenotypes defining a complexity of the organism. It suggests that long-term population size and cost of complexity drive the evolution of the DFE, with many implications for evolutionary and medical genomics.

Evolutionary Biology↗

bioRxiv2016

Extreme distribution of deleterious variation in a historically small and isolated population-insights from the Greenlandic Inuit

The genetic consequences of a severe bottleneck on genetic load in humans are widely disputed. Based on exome sequencing of 18 Greenlandic Inuit we show that the Inuit have undergone a severe ~20,000 yearlong bottleneck. This has led to a markedly more extreme distribution of deleterious alleles than seen for any other human population. Compared to populations with much larger population sizes, we see an overall reduction in the number of variable sites, increased numbers of fixed sites, a lower heterozygosity, and increased mean allele frequency as well as more homozygous deleterious genotypes. This means, that the Inuit population is the perfect population to examine the effect of a bottleneck on genetic load. Compared to the European, Asian and African populations, we do not observe a difference in the overall number of derived alleles. In contrast, using proxies for genetic load we find that selection has acted less efficiently in the Inuit, under a recessive model. This fits with our simulations that predict a similar number of derived alleles but a true higher genetic load for the Inuit regardless of the genetic model. Finally, we find that the Inuit population has a great potential for mapping of disease-causing variants that are rare in large populations. In fact, we show that these alleles are more likely to be common, and thus easy to map, in the Inuit than in the Finnish and Latino populations; populations considered highly valuable for mapping studies due to recent bottleneck events.

Genetics↗

bioRxiv2014

Leveraging ancestry to improve causal variant identification in exome sequencing for monogenic disorders

Recent breakthroughs in exome sequencing technology have made possible the identification of many causal variants of monogenic disorders. Although extremely powerful when closely related individuals (e.g. child and parents) are simultaneously sequenced, exome sequencing of individual only cases is often unsuccessful due to the large number of variants that need to be followed-up for functional validation. Many approaches remove from consideration common variants above a given frequency threshold (e.g. 1%), and then prioritize the remaining variants according to their allele frequency, functional, structural and conservation properties. In this work, we present methods that leverage the genetic structure of different populations while accounting for the finite sample size of the reference panels to improve the variant filtering step. Using simulations and real exome data from individuals with monogenic disorders, we show that our methods significantly reduce the number of variants to be followed-up (e.g. a 36% reduction from an average 418 variants per exome when ancestry is ignored to 267 when ancestry is taken into account for case-only sequenced individuals). Most importantly our proposed approaches are well calibrated with respect to the probability of filtering out a true causal variant (i.e. false negative rate, FNR), whereas existing approaches are susceptible to high FNR when reference panel sizes are limited.

Genetics↗

bioRxiv2014

The distribution of deleterious genetic variation in human populations

Population genetic studies suggest that most amino-acid changing mutations are deleterious. Such mutations are of tremendous interest in human population genetics as they are important for the evolutionary process and may contribute risk to common disease. Genomic studies over the past 5 years have documented differences across populations in the number of heterozygous deleterious genotypes, numbers of homozygous derived deleterious genotypes, number of deleterious segregating sites and proportion of sites that are potentially deleterious. These differences have been attributed to population history affecting the ability of natural selection to remove deleterious variants from the population. However, recent studies have suggested that the genetic load may not differ across populations, and that the efficacy of natural selection has not differed across human populations. Here I show that these observations are not incompatible with each other and that the apparent differences are due to examining different features of the genetic data and differing definitions of terms.

Evolutionary Biology↗