Cryptosporidium causes diarrhea and high mortality in young children in Africa and southern Asia. Low oocyst counts in stool often limit whole-genome sequencing from clinical samples. Here, we enrich for Cryptosporidium genomic DNA directly from stool samples using 74,973 RNA baits (CryptoCap_75K; 8.2 Mb) derived from gene-rich areas (100% coding capacity) within the Cryptosporidium parvum genome. This method produces genome-wide sequence data with sufficient depth and breadth of coverage using as few as 25 oocysts, including divergent species such as Cryptosporidium ubiquitum . To minimize reference bias, we utilize a dual-mapping strategy that integrates reads aligned to both C. parvum and C. ubiquitum to capture lineage-specific variation. Phylogenetic networks, haplotypes, and admixture analyses identify three C. ubiquitum groups, A and B exclusive to humans, with B showing evidence of admixture, whereas C is zoonotic. Group-specific polymorphisms cluster within discrete genomic regions, suggesting conserved haploblocks associate with host adaptation. This capture-based genomics approach provides high-resolution insights into Cryptosporidium population genetics and lays the groundwork for studies of zoonotic transmission, anthroponosis, and GWAS directly from clinical material.
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