High-resolution population-specific recombination rates and their effect on phasing and genotype imputation

Previous research has shown that using population-specific reference panels has a significant effect on downstream population genomic analyses like haplotype phasing, genotype imputation, and association, especially in the context of population isolates. Here, we developed a high-resolution recombination rate mapping at 10 and 50 kb scale using high-coverage (20-30x) whole-genome sequenced data of 55 family trios from Finland and compared it to recombination rates of non-Finnish Europeans (NFE). We tested the downstream effects of the population-specific recombination rates in statistical phasing and genotype imputation in Finns as compared to the same analyses performed by using the NFE-based recombination rates. We found that Finnish recombination rates have a moderately high correlation (Spearman's rho = 0.67-0.79) with NFE, although on average (across all autosomal chromosomes), Finnish rates (2.268 +/- 0.4209 cM/Mb) are 12-14% lower than NFE (2.641 +/- 0.5032 cM/Mb). Finnish recombination map was found to have no significant effect in haplotype phasing accuracy (switch error rates similar to 2%) and average imputation concordance rates (97-98% for common, 92-96% for low frequency and 78-90% for rare variants). Our results suggest that haplotype phasing and genotype imputation mostly depend on population-specific contexts like appropriate reference panels and their sample size, but not on population-specific recombination maps. Even though recombination rate estimates had some differences between the Finnish and NFE populations, haplotyping and imputation had not been noticeably affected by the recombination map used. Therefore, the currently available HapMap recombination maps seem robust for population-specific phasing and imputation pipelines, even in the context of relatively isolated populations like Finland.

Automated summary

Population-specific recombination rates have a significant impact on downstream population genomic analyses like haplotype phasing and genotype imputation, but have a limited effect on the accuracy of these analyses in Finnish populations. The key factors influencing haplotyping and imputation are appropriate reference panels and sample size, rather than population-specific recombination maps.