Biology subjects

Moltke, I.

Publications and source records attributed to Moltke, I..

12 recordsLinked to original sources

bioRxiv2025

From deserts to forests: sequencing of the giant forest hog completes the genomic history of the African Suids

The giant forest hog (GFH, Hylochoerus meinertzhageni), the largest and most elusive wild pig, is found in a disjunct range across equatorial Africa, primarily inhabiting forests and woodlands. It is the only remaining African suid species without whole-genome data. The GFH is currently classified into three subspecies, differing in skull morphology and size. Here, we present the first whole-genome data of nine GFHs; one from Guinea and eight Uganda, representing the two geographically most distant subspecies. This genomic evidence allowed us to resolve the previously uncertain placement of the GFH among African suids as a sister group to the warthogs (Phacochoerus spp.). Also, we found a deep evolutionary split between the two GFH populations resulting in a level of genetic differentiation (FST > 0.75), which is similar to or higher than values observed among species of African wild pigs. The GFH likely diverged from warthogs around 4.6 Mya while the two study populations of GFH diverged at least 0.5 Mya and, subsequently, experienced very dissimilar demographic trajectories. The individual from Guinea had half of the heterozygosity level of the Uganda population, and lower value compared to all the African suids, probably as a result of the long term low Ne and isolation. Due to the close affinity of GFH with the African rainforest biotic zone, our findings have implications for understanding the history of habitat change in Africa. They also indicate a very deep and previously underappreciated evolutionary divergence within the GFH that may have implications for its conservation.

genomics↗

bioRxiv2024

Detecting epidemic-driven selection: a simulation-based tool to optimize sampling design and analysis strategies

Throughout history, populations from numerous species have been decimated by epidemic outbreaks, like the 19th-century rinderpest outbreak in Cape buffalo ({approx} 90% mortality) and Black Death in humans ({approx} 50% mortality). Recent studies have raised the enticing idea that such epidemic outbreaks have led to strong natural selection acting on disease-protective variants in the host populations. However, so far there are few, if any, clear examples of such selection having taken place. This could be because so far studies have not had sufficient power to detect the type of selection an epidemic outbreak must induce: strong but extremely short-term selection on standing variation. We present here a simulation-framework that allows users to explore under what circumstances it is possible to detect epidemic-driven selection using standard selection scan methods like FSTand iHS. Using two examples, we illustrate how the framework can be used. Furthermore, via these examples, we show that comparing survivors to the dead has the potential to render higher power than more commonly used sampling schemes. And importantly, we show that even for outbreaks with high mortality, like the Black Death, strong selection may have led to only modest shifts in allele frequency, suggesting large sample sizes are required to obtain appropriate power to detect the selection. We hope this framework can help in designing well-powered future studies and thus lead to a clarification of the role epidemic-driven selection has played in the evolution of different species. Significance StatementOur study introduces a simulation-based framework, SimOutbreakSelection (SOS), which enables researchers to design studies that have power to detect epidemic-driven selection while taking sampling time points and demographic history into account. We use rinderpest in African Buffalo and the Black Death in Medieval Sweden as examples to showcase the framework. Via these examples we also show that large sample sizes are needed even for severe epidemics like the Black Death and that the often used sampling strategy where samples from before the epidemic and samples from after are compared is not always optimal.

evolutionary biology↗

bioRxiv2024

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↗

bioRxiv2024

Sucrase isomaltase dysfunction influences dietary sucrose intake and preference

ObjectiveTo characterise the role of Sucrase-isomaltase (SI) in regulating dietary behaviours, such as sweet preference and food liking in Si knockout (Sis-KO) mice and in population-based cohorts from Greenland and the UK. DesignWe profiled the appetitive and post-ingestive response to dietary carbohydrates in SI knockout (Sis-KO) mice. Alongside this, we conducted detailed dietary analysis of 45 foods in two Greenlandic population-based cohorts (IHIT, n=2778 and 68 foods, and B2018, n=2203 and 45 foods) with the presence of a common (allele frequency = 14.3%) SI Loss of function (LoF) variant, c.273-274delAG. Finally, we explored the association between SI hypomorphic variants, liking of 140 foods, and sucrose content using data from 134,766 UKBB participants with exome sequencing and questionnaire data available. ResultsSucrose naive Sis-KO mice had a significantly reduced intake of dietary sucrose, and preference for 10% liquid sucrose, in two-bottle preference studies. Mechanistically, oral administration of the short-chain fatty acid acetate reduced sucrose-preference in wild-type mice. In Greenlandic LoF homozygous carriers we show that the previously reported reduction in sugar intake may primarily be explained by a lower intake of cake and pastries, and of candy and chocolate and that added sugar is the main factor explaining these associations. In the UKBB, a negative association with "cake icing", the food with the highest sucrose content per 100g, was detected in SI hypomorphic carriers, as well as in sensitivity analyses conducted only including carriers of known CSID LoF variants. Further, a negative linear relationship was also observed between the effect estimates of hypomorphic SI variants on food liking and the estimated sucrose content per 100g of 88 sucrose-containing foods, indicating that food dislike in SI carriers correlates with the amount of sucrose in food. ConclusionCollectively, we demonstrated that genetic variation in the SI gene is associated with significant changes in sucrose preference, characterised by a rapid avoidance of dietary sucrose in Sis-KO mice, as well as lower consumption and increased disliking of sucrose rich foods in Greenlanders and Europeans, respectively. This work demonstrates that genetic variation in the SI gene may impact physiology beyond the gastrointestinal tract and suggest the possibility to target SI to reduce the preference, and intake, of dietary sucrose with implications for digestive and metabolic health.

genetics↗

bioRxiv2023

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↗

bioRxiv2023

Insufficient evidence for natural selection associated with the Black Death

Klunk et al. analyzed ancient DNA data from individuals in London and Denmark before, during and after the Black Death [1], and argued that allele frequency changes at immune genes were too large to be produced by random genetic drift and thus must reflect natural selection. They also identified four specific variants that they claimed show evidence of selection including at ERAP2, for which they estimate a selection coefficient of 0.39-several times larger than any selection coefficient on a common human variant reported to date. Here we show that these claims are unsupported for four reasons. First, the signal of enrichment of large allele frequency changes in immune genes comparing people in London before and after the Black Death disappears after an appropriate randomization test is carried out: the P value increases by ten orders of magnitude and is no longer significant. Second, a technical error in the estimation of allele frequencies means that none of the four originally reported loci actually pass the filtering thresholds. Third, the filtering thresholds do not adequately correct for multiple testing. Finally, in the case of the ERAP2 variant rs2549794, which Klunk et al. show experimentally may be associated with a host interaction with Y. pestis, we find no evidence of significant frequency change either in the data that Klunk et al. report, or in published data spanning 2,000 years. While it remains plausible that immune genes were subject to natural selection during the Black Death, the magnitude of this selection and which specific genes may have been affected remains unknown.

genomics↗

bioRxiv2022

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↗

bioRxiv2022

Population Structure and Migration in the Eastern Highlands of Papua New Guinea; a Region Impacted by the kuru Epidemic

Populations of the Eastern Highlands of Papua New Guinea (EHPNG, area 11,157 km2) lived in relative isolation from the rest of the world until the mid-20th century, and the region contains a wealth of linguistic and cultural diversity. Notably, several populations of EHPNG were devastated by an epidemic prion disease, kuru, which at its peak in the mid-twentieth century led to some villages being almost depleted of adult women. Until now, population genetic analyses to learn about genetic diversity, migration, admixture and the impact of the kuru epidemic have been restricted to a small number of variants or samples. Here, we present a population genetic analysis of the region based on genome-wide genotype data of 943 individuals from 21 linguistic groups and 68 villages in EHPNG, including 34 villages in the South Fore linguistic group, which the group most affected by kuru. We find a striking degree of genetic population structure in the relatively small region (average FST between linguistic groups 0.024; area similar to Jamaica). The genetic population structure correlates well with linguistic grouping, with some noticeable exceptions. Also, we find evidence of a series of discrete admixture events that appear to coincide with previously expected introduction dates and movement of the sweet potato in the region. Finally, we find signatures of more recent migration within the EHPNG region and observe a substantial excess of female migration into the heavily kuru-affected South Fore linguistic group (p=0.0017, Chi Squared Test), likely reflecting the sex-bias in incidence of kuru. These data provide an in-depth look at the population genetics of a region devastated by a prion disease epidemic and which was until recently relatively isolated from the rest of the world.

genetics↗

bioRxiv2020

NGSremix: A software tool for estimating pairwise relatedness between admixed individuals from next-generation sequencing data

Estimation of relatedness between pairs of individuals is important in many genetic research areas. When estimating relatedness, it is important to account for admixture if this is present. However, the methods that can account for admixture are all based on genotype data as input, which is a problem for low depth next-generation sequencing (NGS) data from which genotypes are called with high uncertainty. Here we present a software tool, NGSremix, for maximum likelihood estimation of relatedness between pairs of admixed individuals from low depth NGS data, which takes the uncertainty of the genotypes into account via geno-type likelihoods. Using both simulated and real NGS data for admixed individuals with an average depth of 4x or below we show that our method works well and clearly outperforms all the commonly used state-of-the-art relatedness estimation methods PLINK, KING, relateAdmix, and ngsRelate that all perform quite poorly. Hence, NGSremix is a useful new tool for estimating relatedness in admixed populations from low-depth NGS data. NGSremix is implemented in C/C++ in a multi-threaded software and is freely available on Github https://github.com/KHanghoj/NGSremix.

bioinformatics↗

bioRxiv2019

Population genomics of the Viking world

The Viking maritime expansion from Scandinavia (Denmark, Norway, and Sweden) marks one of the swiftest and most far-flung cultural transformations in global history. During this time (c. 750 to 1050 CE), the Vikings reached most of western Eurasia, Greenland, and North America, and left a cultural legacy that persists till today. To understand the genetic structure and influence of the Viking expansion, we sequenced the genomes of 442 ancient humans from across Europe and Greenland ranging from the Bronze Age (c. 2400 BC) to the early Modern period (c. 1600 CE), with particular emphasis on the Viking Age. We find that the period preceding the Viking Age was accompanied by foreign gene flow into Scandinavia from the south and east: spreading from Denmark and eastern Sweden to the rest of Scandinavia. Despite the close linguistic similarities of modern Scandinavian languages, we observe genetic structure within Scandinavia, suggesting that regional population differences were already present 1,000 years ago. We find evidence for a majority of Danish Viking presence in England, Swedish Viking presence in the Baltic, and Norwegian Viking presence in Ireland, Iceland, and Greenland. Additionally, we see substantial foreign European ancestry entering Scandinavia during the Viking Age. We also find that several of the members of the only archaeologically well-attested Viking expedition were close family members. By comparing Viking Scandinavian genomes with present-day Scandinavian genomes, we find that pigmentation-associated loci have undergone strong population differentiation during the last millennia. Finally, we are able to trace the allele frequency dynamics of positively selected loci with unprecedented detail, including the lactase persistence allele and various alleles associated with the immune response. We conclude that the Viking diaspora was characterized by substantial foreign engagement: distinct Viking populations influenced the genomic makeup of different regions of Europe, while Scandinavia also experienced increased contact with the rest of the continent.

genetics↗

bioRxiv2018

Cohort-wide deep whole genome sequencing and the allelic architecture of complex traits

The role of rare variants in complex traits remains uncharted. Here, we conduct deep whole genome sequencing of 1,457 individuals from an isolated population, and test for rare variant burdens across six cardiometabolic traits. We identify a role for rare regulatory variation, which has hitherto been missed. We find evidence of rare variant burdens overlapping with, and mostly independent of established common variant signals (ADIPOQ and adiponectin, P=4.2x10-8; APOC3 and triglyceride levels, P=1.58x10-26; GGT1 and gamma-glutamyltransferase, P=2.3x10-6; UGT1A9 and bilirubin, P=1.9x10-8), and identify replicating evidence for a burden associated with triglyceride levels in FAM189A (P=2.26x10-8), indicating a role for this gene in lipid metabolism.

genetics↗

bioRxiv2018

Allele frequency-free inference of close familial relationships from genotypes or low depth sequencing data

Knowledge of how individuals are related is important in many areas of research and numerous methods for inferring pairwise relatedness from genetic data have been developed. However, the majority of these methods were not developed for situations where data is limited. Specifically, most methods rely on the availability of population allele frequencies, the relative genomic position of variants, and accurate genotype data. But in studies of non-model organisms or ancient human samples, such data is not always available. Motivated by this, we present a new method for pairwise relatedness inference, which requires neither allele frequency information nor information on genomic position. Furthermore, it can be applied to both genotype data and to low-depth sequencing data where genotypes cannot be accurately called. We evaluate it using data from SNP arrays and low-depth sequencing from a range of human populations and show that it can be used to infer close familial relationships with a similar accuracy as a widely used method that relies on population allele frequencies. Additionally, we show that our method is robust to SNP ascertainment, which is important for application to a diverse range of populations and species.

genetics↗