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Biology subjects

Rasmussen, M. S.

Publications and source records attributed to Rasmussen, M. S..

6 recordsLinked to original sources

Measuring linkage disequilibrium and improvement of pruning and clumping in structured populations

Standard measures of linkage disequilibrium (LD) are affected by admixture and population structure, such that loci that are not in LD within each ancestral population appear linked when considered jointly. The influence of population structure on LD can cause problems for downstream analysis methods, in particular those that rely on LD pruning or clumping. To address this issue, we propose a measure of LD that accommodates population structure using the top inferred principal components. We estimate LD from the correlation of geno-type residuals and prove that this LD measure remains unaffected by population structure when analyzing multiple populations jointly, even with admixed individuals. Based on this adjusted measure of LD, we can perform LD pruning to remove the correlation between markers for downstream analysis. Traditional LD pruning is more likely to remove markers with high differences in allele frequencies between populations, which biases measures for genetic differentiation and removes markers that are not in LD in the ancestral populations. Using data from moderately differentiated human populations and highly differentiated giraffe populations we show that traditional LD pruning biases FST and PCA but that this can be alleviated with the adjusted LD measure. In addition, we show the adjusted LD leads to better PCA when pruning and that LD clumping retains more sites and the retained sites have stronger associations.

genetics↗

Extensive population structure highlights an apparent paradox of stasis in the impala (Aepyceros melampus)

Impalas are unusual among bovids because they have remained morphologically similar over millions of years - a phenomenon referred to as evolutionary stasis. Here, we sequenced 119 whole genomes from the two extant subspecies of impala, the common (Aepyceros melampus melampus) and black-faced (A. m. petersi) impala. We investigated the evolutionary forces working within the species to explore how they might be associated with its evolutionary stasis as a taxon. Despite being one of the most abundant bovid species, we found low genetic diversity overall, and a phylogeographic signal of spatial expansion from southern to eastern Africa. Contrary to expectations under a scenario of evolutionary stasis, we found pronounced genetic structure between and within the two subspecies with indications of ancient, but not recent, gene flow. Black-faced impala and eastern African common impala populations had more runs of homozygosity than common impala in southern Africa, and, using a proxy for genetic load, we found that natural selection is working less efficiently in these populations compared to the southern African populations. Together with the fossil record, our results are consistent with a fixed-optimum model of evolutionary stasis, in which impalas in the southern African core of the range are able to stay near their evolutionary fitness optimum as a generalist ecotone species, whereas eastern African impalas may struggle to do so due to the effects of genetic drift and reduced adaptation to the local habitat, leading to recurrent local extinction in eastern Africa and re-colonization from the South.

evolutionary biology↗

Inferring drift, genetic differentiation, and admixture graphs from low-depth sequencing data

A number of popular methods for inferring the evolutionary relationship between populations require essentially two components: First, they require estimates of f2-statistics, or some quantity that is a linear combination of these. Second, they require estimates of the variability of the statistic in question. Examples of methods in this class include qpGraph and TreeMix. It is known, however, that these statistics are biased when based on genotype calls at low depth. Moreover, as we show, this leads to downstream inference of significantly distorted trees. To solve this problem, we demonstrate how to accurately and efficiently compute a broad class of statistics from low-depth whole-genome sequencing data, including estimates of their standard errors, by using the site frequency spectrum. In particular, we focus on f2 and the sample covariance of allele frequencies to show how this method leads to accurate estimate of drift when fitting trees using qpGraph and TreeMix with low-depth data. However, the same considerations lead to uncertainty estimates for a variety of other statistics, including heterozygosity, kinship estimates (e.g. King), and quantities relating to genetic differentiation such as Fst and Dxy.

bioinformatics↗

African bush pigs exhibit porous species boundaries and appeared in Madagascar concurrently with human arrival

Several African mammals exhibit a phylogeographic pattern where closely related taxa are split between West/Central and East/Southern Africa, but their evolutionary relationships and histories remain controversial. Bushpigs (Potamochoerus larvatus) and red river hogs (P. porcus) are recognised as separate species due to morphological distinctions, a perceived lack of interbreeding at contact, and putatively old divergence times, but historically, they were considered conspecific. Moreover, the presence of Malagasy bushpigs as the sole large terrestrial mammal shared with the African mainland raises intriguing questions about its origin and arrival in Madagascar. Analyses of 67 whole genomes revealed a genetic continuum between the two species, with putative signatures of historical gene flow, variable FST values, and a recent divergence time (<500,000 years). Thus, our study challenges key arguments for splitting Potamochoerus into two species and suggests their speciation might be incomplete. Our findings also indicate that Malagasy bushpigs diverged from southern African populations and underwent a limited bottleneck 1,000-5,000 years ago, concurrent with human arrival in Madagascar. These results shed new light on the evolutionary history of an iconic and widespread African genus and provide insight into the longstanding biogeographic puzzle surrounding the bushpigs presence in Madagascar.

evolutionary biology↗

Persistent gene flow suggests an absence of reproductive isolation in an African antelope speciation model

African antelope diversity is a globally unique vestige of a much richer world-wide Pleistocene megafauna. Despite this, the evolutionary processes leading to the prolific radiation of African antelopes are not well understood. Here, we sequenced 145 whole genomes from both subspecies of the waterbuck, an African antelope believed to be in the process of speciation. We investigated genetic structure and population divergence and found evidence of a mid-Pleistocene separation on either side of the eastern Great Rift Valley, consistent with vicariance caused by a rain shadow along the so-called Kingdons Line. However, we also found pervasive evidence of not only isolated and recent, but also widespread historical gene flow across the Rift Valley barrier. By inferring the genome-wide landscape of variation among subspecies, we found 14 genomic regions of elevated differentiation, including a locus that may be related to each subspecies distinctive coat pigmentation pattern. We investigated these regions as candidate speciation islands. However, we observed no significant reduction in gene flow in these regions, nor any indications of selection against hybrids. Altogether, these results suggest a pattern whereby climatically driven vicariance is the most important process driving the African antelope radiation, and suggest that reproductive isolation may not set in until very late in the divergence process.

evolutionary biology↗

Estimation of site frequency spectra from low-coverage sequencing data using stochastic EM reduces overfitting, runtime, and memory usage

The site frequency spectrum (SFS) is an important summary statistic in population genetics used for inference on demographic history and selection. However, estimation of the SFS from called genotypes introduce bias when working with low-coverage sequencing data. Methods exist for addressing this issue, but sometimes suffer from two problems. First, they can have very high computational demands, to the point that it may not be possible to run estimation for genome-scale data. Second, existing methods are prone to overfitting, especially for multi-dimensional SFS estimation. In this article, we present a stochastic expectation-maximisation algorithm for inferring the SFS from NGS data that addresses these challenges. We show that this algorithm greatly reduces runtime and enables estimation with constant, trivial RAM usage. Further, the algorithm reduces overfitting and thereby improves downstream inference. An implementation is available at github.com/malthesr/winsfs.

bioinformatics↗