July 7, 2019  |  

Conservation genetics of an endangered grassland butterfly (Oarisma poweshiek) reveals historically high gene flow despite recent and rapid range loss

1. In poorly dispersing species gene flow can be facilitated when suitable habitat is widespread, allowing for increased dispersal between neighbouring locations. The Poweshiek skipperling [Oarisma poweshiek (Parker)], a federally endangered butterfly, has undergone a rapid, recent demographic decline following the loss of tallgrass prairie and fen habitats range wide. The loss of habitat, now restricted geographic range, and poor dispersal ability have left O. poweshiek at increased risk of extinction. 2. We studied the population genetics of six remaining populations of O. poweshiek in order to test the hypothesis that gene flow was historically high despite limited long-distance dispersal capability. Utilising nine microsatellite loci developed by PacBio sequencing, we tested for patterns of isolation by distance, low population genetic structure and alternative gene flow models. 3. Populations from southern Manitoba, Canada to the Lower Peninsula of Michigan, USA are only weakly genetically differentiated despite having low diversity. We found no support for isolation by distance, and Bayesian estimates of historical gene flow support our hypothesis that high levels of gene flow previously connected populations from Michigan to Wisconsin. 4. Prairie grasslands have been reduced tremendously over the past century, but the low mobility of O. poweshiek suggests that rapid loss of populations over the past decade cannot be simply explained by fragmentation of habitat. 5. As a species at high risk of extinction, understanding historical processes of gene flow will allow for informed management decisions with respect to head-starting individuals for population reintroductions and for conserving networks of habitat that will allow for high levels of gene flow.


July 7, 2019  |  

IWTomics: testing high-resolution sequence-based ‘Omics’ data at multiple locations and scales.

With increased generation of high-resolution sequence-based ‘Omics’ data, detecting statistically significant effects at different genomic locations and scales has become key to addressing several scientific questions. IWTomics is an R/Bioconductor package (integrated in Galaxy) that, exploiting sophisticated Functional Data Analysis techniques (i.e. statistical techniques that deal with the analysis of curves), allows users to pre-process, visualize and test these data at multiple locations and scales. The package provides a friendly, flexible and complete workflow that can be employed in many genomic and epigenomic applications.IWTomics is freely available at the Bioconductor website (http://bioconductor.org/packages/IWTomics) and on the main Galaxy instance (https://usegalaxy.org/).Supplementary data are available at Bioinformatics online.


July 7, 2019  |  

Satellite DNA evolution: old ideas, new approaches.

A substantial portion of the genomes of most multicellular eukaryotes consists of large arrays of tandemly repeated sequence, collectively called satellite DNA. The processes generating and maintaining different satellite DNA abundances across lineages are important to understand as satellites have been linked to chromosome mis-segregation, disease phenotypes, and reproductive isolation between species. While much theory has been developed to describe satellite evolution, empirical tests of these models have fallen short because of the challenges in assessing satellite repeat regions of the genome. Advances in computational tools and sequencing technologies now enable identification and quantification of satellite sequences genome-wide. Here, we describe some of these tools and how their applications are furthering our knowledge of satellite evolution and function. Copyright © 2018 Elsevier Ltd. All rights reserved.


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