
Genome-Wide Analyses of Individual Strongyloides stercoralis (Nematoda: Rhabditoidea) Provide Insights into Population Structure and Reproductive Life Cycles
Author(s) -
Taisei Kikuchi,
Akinori Hino,
Teruhisa Tanaka,
Myo Pa Pa Thet Hnin Htwe Aung,
Tanzila Afrin,
Eiji Nagayasu,
Ryusei Tanaka,
Miwa Higashiarakawa,
Kyu Kyu Win,
Tetsuya Hirata,
Wah Win Htike,
Jiro Fujita,
Haruhiko Maruyama
Publication year - 2016
Publication title -
plos neglected tropical diseases
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.99
H-Index - 135
eISSN - 1935-2735
pISSN - 1935-2727
DOI - 10.1371/journal.pntd.0005253
Subject(s) - biology , genome , strongyloides stercoralis , loss of heterozygosity , population , genetics , evolutionary biology , phylogenetic tree , haplotype , helminths , zoology , genotype , gene , allele , demography , sociology
The helminth Strongyloides stercoralis , which is transmitted through soil, infects 30–100 million people worldwide. S . stercoralis reproduces sexually outside the host as well as asexually within the host, which causes a life-long infection. To understand the population structure and transmission patterns of this parasite, we re-sequenced the genomes of 33 individual S . stercoralis nematodes collected in Myanmar (prevalent region) and Japan (non-prevalent region). We utilised a method combining whole genome amplification and next-generation sequencing techniques to detect 298,202 variant positions (0.6% of the genome) compared with the reference genome. Phylogenetic analyses of SNP data revealed an unambiguous geographical separation and sub-populations that correlated with the host geographical origin, particularly for the Myanmar samples. The relatively higher heterozygosity in the genomes of the Japanese samples can possibly be explained by the independent evolution of two haplotypes of diploid genomes through asexual reproduction during the auto-infection cycle, suggesting that analysing heterozygosity is useful and necessary to infer infection history and geographical prevalence.