Biology subjects

Kubatko, L.

Publications and source records attributed to Kubatko, L..

2 recordsLinked to original sources

bioRxiv2018

Evolutionary insights into Bean common mosaic necrosis virus and Cowpea aphid borne mosaic virus using global isolates and thirteen new near complete genomes from Kenya

Plant viral diseases are one of the major limitations in legume production within sub Saharan Africa (SSA), as they account for up to 100 % in production losses within smallholder farms. In this study, field surveys were conducted in the western highlands of Kenya with viral symptomatic leaf samples collected. Subsequently, next-generation sequencing was carried out. The main aim was to gain insights into the selection pressure and evolutionary relationships of Bean common mosaic necrosis virus (BCMNV) and Cowpea aphid-borne mosaic virus (CABMV), within symptomatic common beans and cowpeas. Eleven near complete genomes of BCMNV and two for CABMV sequences were obtained from SSA. Bayesian phylogenomic analysis and tests for differential selection pressure within sites and across tree branches of the viral genomes was carried out. Three distinct well-supported clades were identified across the whole genome tree, and were in agreement with individual gene trees. Selection pressure analysis within sites and across phylogenetic branches suggested both viruses were evolving independently, but under strong purifying selection, with a slow evolutionary rate. These findings provide valuable insights on the evolution of BCMNV and CABMV genomes and their relationship to other viral genomes globally. These results will contribute greatly to the knowledge gap surrounding the phylogenomic relationship of these viruses, particularly for CABMV, for which there are few genome sequences available, and support the current breeding efforts towards resistance for BCMNV and CABMV.

evolutionary biology↗

bioRxiv2017

SNP genotyping and parameter estimation in polyploids using low-coverage sequencing data

MotivationGenotyping and parameter estimation using high throughput sequencing data are everyday tasks for population geneticists, but methods developed for diploids are typically not applicable to polyploid taxa. This is due to their duplicated chromosomes, as well as the complex patterns of allelic exchange that often accompany whole genome duplication (WGD) events. For WGDs within a single lineage (auto polyploids), inbreeding can result from mixed mating and/or double reduction. For WGDs that involve hybridization (allopolyploids), alleles are typically inherited through independently segregating subgenomes.\n\nResultsWe present two new models for estimating genotypes and population genetic parameters from genotype likelihoods for auto- and allopolyploids. We then use simulations to compare these models to existing approaches at varying depths of sequencing coverage and ploidy levels. These simulations show that our models typically have lower levels of estimation error for genotype and parameter estimates, especially when sequencing coverage is low. Finally, we also apply these models to two empirical data sets from the literature. Overall, we show that the use of genotype likelihoods to model non-standard inheritance patterns is a promising approach for conducting population genomic inferences in polyploids.\n\nAvailabilityA C++ program, EBG, is provided to perform inference using the models we describe. It is available under the GNU GPLv3 on GitHub:\n\nhttps://github.com/pblischak/polyploid-genotyping.\n\nContact: blischak.4@osu.edu.

bioinformatics↗