Population-specific reference panels are crucial for genetic analyses: an example of the CREBRF locus in Native Hawaiians. (3rd June 2020) - Lin, Meng; Caberto, Christian; Wan, Peggy; Li, Yuqing; Lum-Jones, Annette; Tiirikainen, Maarit; Pooler, Loreall; Nakamura, Brooke; Sheng, Xin; Porcel, Jacqueline; Lim, Unhee; Setiawan, Veronica Wendy; et al.
Abstract: Statistical imputation applied to genome-wide array data is the most cost-effective approach to complete the catalog of genetic variation in a study population. However, imputed genotypes in underrepresented populations incur greater inaccuracies due to ascertainment bias and a lack of representation among reference individuals, further contributing to the obstacles to study these populations. Here we examined the consequences due to the lack of representation by genotyping in a large number of self-reported Native Hawaiians ( N  = 3693) a functionally important, Polynesian-specific variant in the CREBRF gene, rs373863828. We found the derived allele was significantly associated with several adiposity traits with large effects (e.g. ~ 1.28 kg/m 2 per allele in body mass index as the most significant; P  = 7.5 × 10 −5 ), consistent with the original findings in Samoans. Due to the current absence of Polynesian representation in publicly accessible reference sequences, rs373863828 or its proxies could not be tested through imputation using these existing resources. Moreover, the association signals at the entire CREBRF locus could not be captured by alternative approaches, such as admixture mapping. In contrast, highly accurate imputation can be achieved even if a small number (<200) of internally constructed Polynesian reference individuals were available; this would increase sample size and improve the statistical evidence of associations. Taken together, our results suggest the alarming possibility that lack of representation in reference panels could inhibit discovery of functionally important loci such as CREBRF . Yet, they could be easily detected and prioritized with improved representation of diverse populations in sequencing studies.