Population-specific genome graphs improve high-throughput sequencing data analysis: A case study on the Pan-African genome

Abstract

Graph-based genome reference representations have seen significant development, motivated by the inadequacy of the current human genome reference for capturing the diverse genetic information from different human populations and its inability to maintain the same level of accuracy for non-European ancestries. While there have been many efforts to develop computationally efficient graph-based bioinformatics toolkits, how to curate genomic variants and subsequently construct genome graphs remains an understudied problem that inevitably determines the effectiveness of the end-to-end bioinformatics pipeline. In this study, we discuss major obstacles encountered during graph construction and propose methods for sample selection based on population diversity, graph augmentation with structural variants and resolution of graph reference ambiguity caused by information overload. Moreover, we present the case for iteratively augmenting tailored genome graphs for targeted populations and test the proposed approach on the whole-genome samples of African ancestry. Our results show that, as more representative alternatives to linear or generic graph references, population-specific graphs can achieve significantly lower read mapping errors, increased variant calling sensitivity and provide the improvements of joint variant calling without the need of computationally intensive post-processing steps.

Exome variant discrepancies due to reference-genome differences

“…A recent report suggests that using a pan-genome reference assembled from 910 subjects of African descent 55 and a graph-based genome alignment strategy can improve variant calling from the African population. 56 In summary, our data show that the intrinsic differences between the GRCh37 and GRCh38 references significantly impact variant calling for certain genomic regions including 206 genes (57 paralogous genes, 28 pseudogenes, 8 genes implicated in Mendelian diseases on OMIM, no ACMG genes). Only 3 known P/LP variants and 15 rare, putatively deleterious variants were discordantly called due to reference differences.…”