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Lohmueller, K.

Publications and source records attributed to Lohmueller, K..

4 recordsLinked to original sources

Pervasive cryptic selection in the human noncoding genome

The prevailing dogma in evolutionary genetics holds that mutations within sequences that are conserved across a phylogeny are deleterious in those species, and mutations outside are neutrally evolving. Indeed, such comparative genomic approaches have estimated that mutations in approximately 5% of the human genome experience negative selection. However, sites that have biological function in certain lineages but not in others, i.e. functional turnover, may violate this assumption since these sites may be invisible to comparative genomic approaches. Thus, the extent of such cryptic, or hidden, negative selection remains elusive. Here, we developed a statistical test to detect cryptic selection in human polymorphism data. Applying our approach to simulated data shows that cryptic selection shapes the site frequency spectrum (SFS) and the statistical detection power depends on the proportion of mutations experiencing cryptic selection, the amount of sequence tested, and the sample size. We applied our method to polymorphism data from the 1000 Genomes Project, comparing variants in putatively functional noncoding regions to those in putatively neutral regions. We detected pervasive signals of cryptic selection in putatively functional regions, even after filtering out the top 70% of conserved sites. Using simulations with varying levels of cryptic selection, we estimated the extent of genome-wide constraint in the human genome. Our approximation suggests that mutations in at least 7% of the human genome are under negative selection, which is greater than the estimates from conservation-based methods, and that many of these mutations have escaped detection by comparative genomic methods. In sum, our results highlight the evolutionary dynamic nature of the noncoding genome and suggest the need to account for functional turnover when identifying putatively neutral variants for evolutionary analyses.

evolutionary biology↗

Inferring the mode and strength of ongoing selection

Genome sequence data is no longer scarce. The UK Biobank alone comprises 200,000 individual genomes, with more on the way, leading the field of human genetics towards sequencing entire populations. Within the next decades, other model organisms will follow suit, especially domesticated species such as crops and livestock. Having sequences from most individuals in a population will present new challenges for using these data to improve health and agriculture in the pursuit of a sustainable future. Existing population genetic methods are designed to model hundreds of randomly sampled sequences, but are not optimized for extracting the information contained in the larger and richer datasets that are beginning to emerge, with thousands of closely related individuals. Here we develop a new method called TIDES (Trio-based Inference of Dominance and Selection) that uses data from tens of thousands of family trios to make inferences about natural selection acting in a single generation. TIDES further improves on the state-of-the-art by making no assumptions regarding demography, linkage or dominance. We discuss how our method paves the way for studying natural selection from new angles.

evolutionary biology↗

Negative selection on complex traits limits genetic risk prediction accuracy between populations

Accurate genetic risk prediction is a key goal for medical genetics and great progress has been made toward identifying individuals with extreme risk across several traits and diseases (Collins and Varmus, 2015). However, many of these studies are done in predominantly European populations (Bustamante et al., 2011; Popejoy and Fullerton, 2016). Although GWAS effect sizes correlate across ancestries (Wojcik et al., 2019), risk scores show substantial reductions in accuracy when applied to non-European populations (Kim et al., 2018; Martin et al., 2019; Scutari et al., 2016). We use simulations to show that human demographic history and negative selection on complex traits result in population specific genetic architectures. For traits under moderate negative selection, ~50% of the heritability can be accounted for by variants in Europe that are absent from Africa. We show that this directly leads to poor performance in risk prediction when using variants discovered in Europe to predict risk in African populations, especially in the tails of the risk distribution. To evaluate the impact of this effect in genomic data, we built a Bayesian model to stratify heritability between European-specific and shared variants and applied it to 43 traits and diseases in the UK Biobank. Across these phenotypes, we find ~50% of the heritability comes from European-specific variants, setting an upper bound on the accuracy of genetic risk prediction in non-European populations using effect sizes discovered in European populations. We conclude that genetic association studies need to include more diverse populations to enable to utility of genetic risk prediction in all populations.

genetics↗

Deleterious variation mimics signatures of genomic incompatibility and adaptive introgression

While 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.

evolutionary biology↗