Whole-Exome Sequencing Reveals Uncaptured Variation and Distinct Ancestry in the Southern African Population of Botswana.

TitleWhole-Exome Sequencing Reveals Uncaptured Variation and Distinct Ancestry in the Southern African Population of Botswana.
Publication TypeJournal Article
Year of Publication2018
AuthorsRetshabile, G, Mlotshwa, BC, Williams, L, Mwesigwa, S, Mboowa, G, Huang, Z, Rustagi, N, Swaminathan, S, Katagirya, E, Kyobe, S, Wayengera, M, Kisitu, GP, Kateete, DP, Wampande, EM, Maplanka, K, Kasvosve, I, Pettitt, ED, Matshaba, M, Nsangi, B, Marape, M, Tsimako-Johnstone, M, Brown, CW, Yu, F, Kekitiinwa, A, Joloba, M, Mpoloka, SW, Mardon, G, Anabwani, G, Hanchard, NA
Corporate AuthorsCollaborative African Genomics Network (CAfGEN) of the H3Africa Consortium
JournalAm J Hum Genet
Volume102
Issue5
Pagination731-743
Date Published2018 05 03
ISSN1537-6605
KeywordsAfrican Continental Ancestry Group, Botswana, Cohort Studies, Gene Pool, Genetic Variation, Genetics, Population, Genome, Human, Geography, Humans, Phylogeny, Principal Component Analysis, Whole Exome Sequencing
Abstract

Large-scale, population-based genomic studies have provided a context for modern medical genetics. Among such studies, however, African populations have remained relatively underrepresented. The breadth of genetic diversity across the African continent argues for an exploration of local genomic context to facilitate burgeoning disease mapping studies in Africa. We sought to characterize genetic variation and to assess population substructure within a cohort of HIV-positive children from Botswana-a Southern African country that is regionally underrepresented in genomic databases. Using whole-exome sequencing data from 164 Batswana and comparisons with 150 similarly sequenced HIV-positive Ugandan children, we found that 13%-25% of variation observed among Batswana was not captured by public databases. Uncaptured variants were significantly enriched (p = 2.2 × 10) for coding variants with minor allele frequencies between 1% and 5% and included predicted-damaging non-synonymous variants. Among variants found in public databases, corresponding allele frequencies varied widely, with Botswana having significantly higher allele frequencies among rare (

DOI10.1016/j.ajhg.2018.03.010
Alternate JournalAm J Hum Genet
PubMed ID29706352
PubMed Central IDPMC5986695
Grant List2013096 / DDCF / Doris Duke Charitable Foundation / United States
U54 AI110398 / AI / NIAID NIH HHS / United States

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