European American Stratification in Ovarian Cancer Case Control Data: The Utility of Genome-Wide Data for Inferring Ancestry

We investigated the ability of several principal components analysis (PCA)-based strategies to detect and control for population stratification using data from a multi-center study of epithelial ovarian cancer among women of European-American ethnicity. These include a correction based on an ancestry informative markers (AIMs) panel designed to capture European ancestral variation and corrections utilizing un-thinned genome-wide SNP data; case-control samples were drawn from four geographically distinct North-American sites. The AIMs-only and genome-wide first principal components (PC1) both corresponded to the previously described North or Northwest-Southeast axis of European variation. We found that the genome-wide PCA captured this primary dimension of variation more precisely and identified additional axes of genome-wide variation of relevance to epithelial ovarian cancer. Associations evident between the genome-wide PCs and study site corroborate North American immigration history and suggest that undiscovered dimensions of variation lie within Northern Europe. The structure captured by the genome-wide PCA was also found within control individuals and did not reflect the case-control variation present in the data. The genome-wide PCA highlighted three regions of local LD, corresponding to the lactase (LCT) gene on chromosome 2, the human leukocyte antigen system (HLA) on chromosome 6 and to a common inversion polymorphism on chromosome 8. These features did not compromise the efficacy of PCs from this analysis for ancestry control. This study concludes that although AIMs panels are a cost-effective way of capturing population structure, genome-wide data should preferably be used when available

Dual infection by cassava begomoviruses in two leguminous species (Fabaceae) in Yangambi, Northeastern Democratic Republic of Congo

A study on cassava mosaic begomoviruses was conducted around Yangambi (DR Congo) by sampling 10 different leguminous species with or without symptoms similar to cassava mosaic disease. DNA was isolated to amplify CMBs using primers targeting AC2 and AC4 genes for virus detection by PCR. The results showed a dual infection by ACMV and EACMV in two weed species, Centrosema pubescens and Pueraria javanica, associated with mosaic symptoms. The DNA-A genome component of ACMV and EACMV from the infested weeds was sequenced. Seven ACMV and four EACMV isolates are reported. The major ACMV strains were closely related to ACMV-NGogo, ACMV-IC and ACMV-UGMld, whereas all EACMV strains were closely related to a Uganda variant, the most prevalent virus. This study shows that whiteflies may transmit CMBs to non-cassava plants under high epidemic pressure