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Masafuera Rayadito (Aphrastura masafuerae; Furnariidae) is a Critically Endangered species endemic to Alejandro Selkirk Island (Juan Fernandez Archipelago, Chile). Categorized as probably extinct in 1980, later estimates, ranging from 140 (in 2002) to 500 individuals (in 2006-2007), showed a fluctuating population size of the species. The grazing of goats and cattle has increased habitat loss for the species. Other threats are lack of nesting sites, introduced species such as feral cats and rats (Rattus rattus and R. norvegicus), and increased populations of natural predators like the Masafuera Hawk. In order to increase the availability of nesting sites, 81 nest boxes were installed in different habitats in 2006, with evidence of use during subsequent breeding seasons. Despite conservation concerns, however, no genetic studies are yet available for this furnariid. This study reports for the first time the levels of genetic divergence of the species, based on nucleotide sequences of the mitochondrial DNA (cytochrome oxidase subunit 1 gene; COI). Aphrastura masafuerae is closely related to a widespread species of furnariid distributed mainly in Chile on the mainland, the Thorn-tailed Rayadito (A. spinicauda). The Masafuera Rayadito diverged from its mainland sister species probably during the Pleistocene 0.57 +/- 0.19 Myr ago. Consistent with mitochondrial and nuclear molecular clocks, the estimated time of the split between A. masafuerae and A. spinicauda is in perfect agreement with the geological origin of the Juan Fernandez Archipelago, which is of volcanic origin. In order to assess genetic variability within the population of this fragile bird, further studies using a multi-locus genetic approach at the population level are necessary.
The prevalence of contaminant microbial DNA in ancient bone samples represents the principal limiting factor for palaeogenomic studies, as it may comprise more than 99% of DNA molecules obtained. Efforts to exclude or reduce this contaminant fraction have been numerous but also variable in their success. Here, we present a simple but highly effective method to increase the relative proportion of endogenous molecules obtained from ancient bones. Using computed tomography (CT) scanning, we identify the densest region of a bone as optimal for sampling. This approach accurately identifies the densest internal regions of petrous bones, which are known to be a source of high-purity ancient DNA. For ancient long bones, CT scans reveal a high-density outermost layer, which has been routinely removed and discarded prior to DNA extraction. For almost all long bones investigated, we find that targeted sampling of this outermost layer provides an increase in endogenous DNA content over that obtained from softer, trabecular bone. This targeted sampling can produce as much as 50-fold increase in the proportion of endogenous DNA, providing a directly proportional reduction in sequencing costs for shotgun sequencing experiments. The observed increases in endogenous DNA proportion are not associated with any reduction in absolute endogenous molecule recovery. Although sampling the outermost layer can result in higher levels of human contamination, some bones were found to have more contamination associated with the internal bone structures. Our method is highly consistent, reproducible and applicable across a wide range of bone types, ages and species. We predict that this discovery will greatly extend the potential to study ancient populations and species in the genomics era.
Present-day domestic horses are immensely diverse in their maternally inherited mitochondrial DNA, yet they show very little variation on their paternally inherited Y chromosome. Although it has recently been shown that Y chromosomal diversity in domestic horses was higher at least until the Iron Age, when and why this diversity disappeared remain controversial questions. We genotyped 16 recently discovered Y chromosomal single-nucleotide polymorphisms in 96 ancient Eurasian stallions spanning the early domestication stages (Copper and Bronze Age) to the Middle Ages. Using this Y chromosomal time series, which covers nearly the entire history of horse domestication, we reveal how Y chromosomal diversity changed over time. Our results also show that the lack of multiple stallion lineages in the extant domestic population is caused by neither a founder effect nor random demographic effects but instead is the result of artificial selection-initially during the Iron Age by nomadic people from the Eurasian steppes and later during the Roman period. Moreover, the modern domestic haplotype probably derived from another, already advantageous, haplotype, most likely after the beginning of the domestication. In line with recent findings indicating that the Przewalski and domestic horse lineages remained connected by gene flow after they diverged about 45,000 years ago, we present evidence for Y chromosomal introgression of Przewalski horses into the gene pool of European domestic horses at least until medieval times.
Consensify
(2020)
A standard practise in palaeogenome analysis is the conversion of mapped short read data into pseudohaploid sequences, frequently by selecting a single high-quality nucleotide at random from the stack of mapped reads. This controls for biases due to differential sequencing coverage, but it does not control for differential rates and types of sequencing error, which are frequently large and variable in datasets obtained from ancient samples. These errors have the potential to distort phylogenetic and population clustering analyses, and to mislead tests of admixture using D statistics. We introduce Consensify, a method for generating pseudohaploid sequences, which controls for biases resulting from differential sequencing coverage while greatly reducing error rates. The error correction is derived directly from the data itself, without the requirement for additional genomic resources or simplifying assumptions such as contemporaneous sampling. For phylogenetic and population clustering analysis, we find that Consensify is less affected by artefacts than methods based on single read sampling. For D statistics, Consensify is more resistant to false positives and appears to be less affected by biases resulting from different laboratory protocols than other frequently used methods. Although Consensify is developed with palaeogenomic data in mind, it is applicable for any low to medium coverage short read datasets. We predict that Consensify will be a useful tool for future studies of palaeogenomes.