Leveraging genomic insights from the neglected malaria parasites P. malariae and P. ovale using selective whole genome amplification (SWGA) approach

Abstract

Background: Systematic genomics-guided population-based studies on the neglected malaria parasites, P. malariae, P. ovale curtisi, and P. ovale wallikeri species remain challenging due to their low parasitemia, underestimation, and lack of comprehensive genetic analysis. Techniques that cost-effectively allow the enriching of the genome of interest from complex genome backgrounds for sequencing studies help immensely to perform genomic analyses. One such technique is selective whole-genome amplification (SWGA).

Results: We applied SWGA using specifically designed primer sets targeting the pathogen genome to enrich parasite DNA from clinical samples. This enabled cost-effective and high-quality WGS for these neglected malaria species. WGS on SWGA-treated samples demonstrated improved genome coverage. Our method outperformed the published protocol for P.malariae with higher enrichment of the targeted genome. On average, P. malariae had 93% of the genome covered by ≥ 10 reads; parallel improvements in genome coverage were achieved for both P. ovale spp. with 81% on average of the genome covered by ≥ 10 reads. Consequently, the detection of thousands of additional SNPs not detectable in pre-SWGA samples was facilitated after SWGA, allowing more substantial downstream population genomics analysis, particularly for the polymorphic and antimalarial genes of great interest for all the species. Furthermore, leveraging the long DNA fragments generated by SWGA, we achieved high-quality genome assemblies for P. malariae and P. ovale using PacBio long reads sequencing technology.

Conclusions: SWGA approach implemented here provides a powerful tool for enhancing genomic analysis of these neglected parasites, revealing population diversity, drug resistance markers, and hypervariable regions. This methodology constitutes a transformative tool to surmount the challenges of genomic analysis for neglected malaria parasites and can improve malaria research and control.

Keywords: P. malariae; P. ovale curtisi; P. ovale wallikeri.; SNP; SWGA; WGS.

Fig. 1

Enrichment of P. malariae (a), P. ovale curtisi (b), and P. ovale wallikeri (c) genome sequences post SWGA. Fold enrichment for each sample was calculated by dividing the percentage of reads mapped to the corresponding genome before SWGA to post SWGA. Abbreviation: PM, P. malariae; POC, P. ovale curtisi; POW, P. ovale wallikeri

Fig. 2

SWGA performance of P. malariae and P. ovale curtisi (a) Line plot shows the percentage of genome covered with x-depth coverage for all P. malariae samples before and after SWGA. (b) Read depth coverage of pre-SWGA and post-SWGA for chromosome 2 and chromosome 12 (chosen as representative) to represent sample PM3. The number on the right shows the data range as read coverage. (c) Line plot shows the percentage of genome covered with x-depth coverage for all P. ovale curtisi samples before and after SWGA. (d) Read depth coverage of pre-SWGA and post-SWGA for chromosome 2 and chromosome 12 as representatives shown for sample POC6. The number on the right shows the data range as read coverage

Fig. 3

Maximum likelihood phylogenetic tree of P. malariae Maximum likelihood phylogeny unrooted tree was generated using the web iqtree from a total of 77, 247 core genome SNPs from 27 samples were used. Bootstrap support values from 1000 replicates are shown. The parameters used for tree construction using IQTREE are ModelFinder + tree reconstruction + ultrafast bootstrap (1000 replicates): “-m MFP -mtree -b 1000. The ModelFinder identified TVM + F + R2 as the best-fitting model. The tree was visualized using iTOL

Fig. 4

SNPs and the resulting amino acid changes identified in P. malariae merozoite surface protein 1 (msp1) gene locus before (a) and after SWGA (b) The Y-axis shows how many samples Sanger sequencing validated that mutation. The number inside the circle represents how many samples post-SWGA detected the same SNP

Fig. 5

Circos plot displaying the sequencing depth and coverage of PM7 SWGA from a PacBio Sequel II long-read sequencing data. The outer circle is the P. malariae UG01 genome. The inner circles are genome GC content, SWGA data coverage, and sequencing depth

Fig. 6

Collinear blocks assembled contigs between the P. malariae (PmalariaeUG01) and the PM7 derived from SWGA- DNA material sequenced on a PacBio Sequel II. Each color represents the best match between the two genomes. PmUG1–14 represents chromosomes 1–14 of P. malariae (PmalariaeUG01), and PmSWGA1-14 represents chromosomes 1–14 of the SWGA assembly