Powell, D. L. | bioRxiv Science

bioRxiv2019

Natural hybridization reveals incompatible alleles that cause melanoma in swordtail fish

The establishment of reproductive barriers between populations is the key process that fuels the evolution of new species. A genetic framework for this process was proposed over 80 years ago, which posits "incompatible" interactions between genes that result in reduced survival or reproduction in hybrids. Despite this foundational work, progress has been slow in identifying individual genes that underlie hybrid incompatibilities, with only a handful known to date. Here, we use a combination of approaches to precisely map the genes that drive the development of a melanoma incompatibility in swordtail fish hybrids. We find that one of the genes involved in this incompatibility also causes melanoma in hybrids between distantly related species. Moreover, we show that this melanoma reduces survival in the wild, likely due to progressive degradation of the fin. Together, this work represents only the second case where the genes underlying a vertebrate hybrid incompatibility have been identified and provides the first glimpse into the action of these genes in natural hybrid populations. One sentence summaryUsing a combination of mapping approaches, we identify interacting genes that lead to melanoma in hybrids and characterize their effects in natural hybrid populations.

evolutionary biology↗

bioRxiv2019

Versatile simulations of admixture and accurate local ancestry inference with mixnmatch and ancestryinfer

It is now clear that hybridization between species is much more common than previously recognized. As a result, we now know that the genomes of many modern species, including our own, are a patchwork of regions derived from past hybridization events. Increasingly researchers are interested in disentangling which regions of the genome originated from each parental species using local ancestry inference methods. Due to the diverse effects of admixture, this interest is shared across disparate fields, from human genetics to research in ecology and evolutionary biology. However, local ancestry inference methods are sensitive to a range of biological and technical parameters which can impact accuracy. Here we present paired simulation and ancestry inference pipelines, mixnmatch and ancestryinfer, to help researchers plan and execute local ancestry inference studies. mixnmatch can simulate arbitrarily complex demographic histories in the parental and hybrid populations, selection on hybrids, and technical variables such as coverage and contamination. ancestryinfer takes as input sequencing reads from simulated or real individuals, and implements an efficient local ancestry inference pipeline. We perform a series of simulations with mixnmatch to pinpoint factors that influence accuracy in local ancestry inference and highlight useful features of the two pipelines. Together, mixnmatch and ancestryinfer are powerful tools for predicting the performance of local ancestry inference methods on real data.

genomics↗