Diversity, Differentiation, and Linkage Disequilibrium: Prospects for Association Mapping in the Malaria Vector Anopheles arabiensis. Issue 1 (1st January 2014) - Marsden, Clare Diana; Lee, Yoosook; Kreppel, Katharina; Weakley, Allison; Cornel, Anthony; Ferguson, Heather M; Eskin, Eleazar; Lanzaro, Gregory C
Abstract: Association mapping is a widely applied method for elucidating the genetic basis of phenotypic traits. However, factors such as linkage disequilibrium and levels of genetic diversity influence the power and resolution of this approach. Moreover, the presence of population subdivision among samples can result in spurious associations if not accounted for. As such, it is useful to have a detailed understanding of these factors before conducting association mapping experiments. Here we conducted whole-genome sequencing on 24 specimens of the malaria mosquito vector, Anopheles arabiensis, to further understanding of patterns of genetic diversity, population subdivision and linkage disequilibrium in this species. We found high levels of genetic diversity within the An. arabiensis genome, with ~800, 000 high-confidence, single- nucleotide polymorphisms detected. However, levels of nucleotide diversity varied significantly both within and between chromosomes. We observed lower diversity on the X chromosome, within some inversions, and near centromeres. Population structure was absent at the local scale (Kilombero Valley, Tanzania) but detected between distant populations (Cameroon vs. Tanzania) where differentiation was largely restricted to certain autosomal chromosomal inversions such as 2Rb . Overall, linkage disequilibrium within An. arabiensis decayed very rapidly (within 200 bp) across all chromosomes. However, elevated linkage disequilibrium was observed within some inversions, suggesting that recombination is reduced in those regions. The overall low levels of linkage disequilibrium suggests that association studies in this taxon will be very challenging for all but variants of large effect, and will require large sample sizes.