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Jorsboe, E.

Publications and source records attributed to Jorsboe, E..

4 recordsLinked to original sources

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↗

A Genotype Likelihood Framework for GWAS with Low Depth Sequencing Data from Admixed Individuals

1IntroductionAssociation studies using genetic data from SNP-chip based imputation or low depth sequencing data provide a cost efficient design for large scale studies. However, these approaches provide genetic data with uncertainty of the observed genotypes. Here we explore association methods that can be applied to data where the genotype is not directly observed. We investigate how using different priors when estimating genotype probabilities affects the association results in different scenarios such as studies with population structure and varying depth sequencing data. We also suggest a method (ANGSD-asso) that is computational feasible for analysing large scale low depth sequencing data sets, such as can be generated by the non-invasive prenatal testing (NIPT) with low-pass sequencing. MethodsANGSD-assos EM model works by modelling the unobserved genotype as a latent variable in a generalised linear model framework. The software is implemented in C/C++ and can be run multi-threaded enabling the analysis of big data sets. ANGSD-asso is based on genotype probabilities, they can be estimated in various ways, such as using the sample allele frequency as a prior, using the individual allele frequencies as a prior or using haplotype frequencies from haplotype imputation. Using simulations of sequencing data we explore how genotype probability based method compares to using genetic dosages in large association studies with genotype uncertainty. Results & DiscussionOur simulations show that in a structured population using the individual allele frequency prior has better power than the sample allele frequency. If there is a correlation between genotype uncertainty and phenotype, then the individual allele frequency prior also helps control the false positive rate. In the absence of population structure the sample allele frequency prior and the individual allele frequency prior perform similarly. In scenarios with sequencing depth and phenotype correlation ANGSD-assos EM model has better statistical power and less bias compared to using dosages. Lastly when adding additional covariates to the linear model ANGSD-assos EM model has more statistical power and provides less biased effect sizes than other methods that accommodate genotype uncertainly, while also being much faster. This makes it possible to properly account for genotype uncertainty in large scale association studies.

bioinformatics↗

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↗

Consequences of breed formation on patterns of genomic diversity and differentiation: the case of highly diverse peripheral Iberian cattle

BackgroundIberian primitive breeds exhibit a remarkable phenotypic diversity over a very limited geographical space. While genomic data are accumulating for most commercial cattle, it is still lacking for these primitive breeds. Whole genome data is key to understand the consequences of historic breed formation and the putative role of earlier admixture events in the observed diversity patterns.\n\nResultsWe sequenced 48 genomes belonging to eight Iberian native breeds and found that the individual breeds are genetically very distinct with FST values ranging from 4 to 16% and have levels of nucleotide diversity similar or larger than those of their European counterparts, namely Jersey and Holstein. All eight breeds display significant gene flow or admixture from African taurine cattle and include mtDNA and Y-chromosome haplotypes from multiple origins. Furthermore, we detected a very low differentiation of chromosome X relative to autosomes within all analyzed taurine breeds, potentially reflecting male-biased gene flow.\n\nConclusionsOur results show that an overall complex history of admixture resulted in unexpectedly high levels of genomic diversity for breeds with seemingly limited geographic ranges that are distantly located from the main domestication center for taurine cattle in the Near East. This is likely to result from a combination of trading traditions and breeding practices in Mediterranean countries. We also found that the levels of differentiation of autosomes vs sex chromosomes across all studied taurine and indicine breeds are likely to have been affected by widespread breeding practices associated with male-biased gene flow.

evolutionary biology↗