Biology subjects
Publications and source records attributed to Wanjiku, M..
Withdrawal StatementThe authors have withdrawn this manuscript because of several factual errors in it. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author.
Identifying population structure from multilocus genotype data is key to down-stream genetic analyses, including analysis of genome-wide association (GWAS), genetic genealogy and phylogenetics, in the fields of conservation, forensics, evolution and more. While inference of population structure has been dominated by Bayesian methods, maximum likelihood methods have some benefits in terms of reliability, consistency and efficiency. Here we extend the methods of Tang et al. [53] and Alexander et al. [2] to handle multi-allelic (e.g., SNP, STR, allozyme) and polyploid loci with missing data to infer genetic admixture proportions and subpopulation allele frequencies. Comparative analyses of our method, MULTICLUST, and STRUCTURE [42] on both simulated and empirical data indicate comparable, fast, reproducible, and accurate estimates of population admixture proportions and allele frequencies using MULTICLUST.MULTICLUST is implemented in the C programming language and is publicly accessible via www.github.com/arunsethuraman/multiclust.
Rice blast caused by Magnaporthe oryzae is one of the most economically damaging diseases of rice worldwide. The disease originated in Asia but was detected for the first time in Sub-Saharan Africa (SSA) around 100 years ago. Despite its importance, the evolutionary processes involved in shaping the population structure of M. oryzae in SSA remain unclear. In this study, we investigate the population history of M. oryzae using a combined dataset of 180 genomes. Our results show that SSA populations are more diverse than earlier perceived, and harbor all genetic groups previously reported in Asia. While M. oryzae populations in SSA and Asia draw from the same genetic pools, both are experiencing different evolutionary trajectories resulting from unknown selection pressures or demographic processes. The distribution of rare alleles, measured as Tajimas D values, show significant differences at the substructure level. Genome-wide analysis indicates potential events of population contraction strongly affecting M. oryzae in SSA. In addition, the distribution and haplotype diversity of effectors might suggest a process of local adaptation to SSA conditions. These findings provide additional clues about the evolutionary history of M. oryzae outside the center of origin and help to build customized disease management strategies.