Using population-specific add-on polymorphisms to improve genotype imputation in underrepresented populations

Xu, Z. M.; Rüeger, S.; Zwyer, M.; Brites, D.; Hiza, H.; Reinhard, M.; Borrell, S.; Isihaka, F.; Temba, H.; Maroa, T.; Naftari, R.; Hella, J.; Sasamalo, M.; Reither, K.; Portevin, D.; Gagneux, S.; Fellay, J.

doi:10.1101/2021.02.03.429542

bioRxiv · 10.1101/2021.02.03.429542

Using population-specific add-on polymorphisms to improve genotype imputation in underrepresented populations

Xu, Z. M.·Rüeger, S.·Zwyer, M.·Brites, D.·Hiza, H.·Reinhard, M.·Borrell, S.·Isihaka, F.·Temba, H.·Maroa, T.·Naftari, R.·Hella, J.·Sasamalo, M.·Reither, K.·Portevin, D.·Gagneux, S.·Fellay, J.

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Abstract

Genome-wide association studies rely on the statistical inference of untyped variants, called imputation, to increase the coverage of genotyping arrays. However, the results are often suboptimal in populations underrepresented in existing reference panels and array designs, since the selected single nucleotide polymorphisms (SNPs) may fail to capture population-specific haplotype structures, hence the full extent of common genetic variation. Here, we propose to sequence the full genome of a small subset of an underrepresented study cohort to inform the selection of population-specific add-on SNPs, such that the remaining array-genotyped cohort could be more accurately imputed. Using a Tanzania-based cohort as a proof-of-concept, we demonstrate the validity of our approach by showing improvements in imputation accuracy after the addition of our designed addon SNPs to the base H3Africa array.

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Xu, Z. M., Rüeger, S., Zwyer, M., Brites, D., Hiza, H., Reinhard, M., Borrell, S., Isihaka, F., Temba, H., Maroa, T., Naftari, R., Hella, J., Sasamalo, M., Reither, K., Portevin, D., Gagneux, S., Fellay, J.. 2021-02-03. Using population-specific add-on polymorphisms to improve genotype imputation in underrepresented populations. https://doi.org/10.1101/2021.02.03.429542

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