Optimization of whole-genome sequencing of Plasmodium falciparum from low-density dried blood spot samples

Whole-genome sequencing (WGS) is becoming increasingly useful to study the biology, epidemiology, and ecology of malaria parasites. Despite ease of sampling, DNA extracted from dried blood spots (DBS) has a high ratio of human DNA compared to parasite DNA, which poses a challenge for downstream genetic analyses. The effects of multiple

Overall, Tween-Chelex extracted samples that were treated with McrBC digestion and are amplified using 6A10AD sWGA conditions had minimal dropout rate, higher percentages of coverage at higher depth, and more accurate SNP concordance than QiaAMP extracted samples. These findings extend the results of previously reported methods, making whole genome sequencing accessible to a larger number of low density samples that are commonly encountered in cross-sectional surveys.

Low parasite density mock DBS samples were created, extracted either with Tween-Chelex or QIAamp, treated with or without McrBC, and amplified with one of three different amplification techniques (two sWGA primer sets and one rWGA). Extraction conditions were evaluated on performance of sequencing depth, percentiles of coverage, and expected SNP concordance.

At 100 parasites/μL, Chelex-Tween-McrBC samples had higher coverage (5 × depth = 93% genome) than QIAamp extracted samples (5 × depth = 76% genome). The two evaluated sWGA primer sets showed minor differences in overall genome coverage and SNP concordance, with a newly proposed combination of 20 primers showing a modest improvement in coverage over those previously published. Conclusions: Overall, Tween-Chelex extracted samples that were treated with McrBC digestion and are amplified using 6A10AD sWGA conditions had minimal dropout rate, higher percentages of coverage at higher depth, and more accurate SNP concordance than QiaAMP extracted samples. These findings extend the results of previously reported methods, making whole genome sequencing accessible to a larger number of low density samples that are commonly encountered in cross-sectional surveys.