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Multilocus Sequence Subtyping and Genetic Structure of Cryptosporidium muris and Cryptosporidium andersoni

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Title
Multilocus Sequence Subtyping and Genetic Structure of Cryptosporidium muris and Cryptosporidium andersoni
Published in
PLOS ONE, August 2012
DOI 10.1371/journal.pone.0043782
Pubmed ID
Authors

Rongjun Wang, Fuchun Jian, Longxian Zhang, Changshen Ning, Aiqin Liu, Jinfeng Zhao, Yaoyu Feng, Meng Qi, Helei Wang, Chaochao Lv, Guanghui Zhao, Lihua Xiao

Abstract

In this study, nine C. muris and 43 C. andersoni isolates from various animals in China were subtyped by a multilocus sequence typing (MLST) tool. DNA sequence analyses showed the presence of 1-2 subtypes of C. muris and 2-6 subtypes of C. andersoni at each of the four loci (MS1, MS2, MS3, and MS16), nine of which represented new subtypes. Altogether, two C. muris and 10 C. andersoni MLST subtypes were detected. Linkage disequilibrium analysis indicated although the overall population structure of the two parasites was clonal, the Chinese C. andersoni in cattle has an epidemic structure. Three and two clusters were produced in the C. muris and C. andersoni populations by Structure 2.3.3 analysis, with Chinese C. muris and C. andersoni substructures differing from other countries. Thus, this study suggested the prevalence of C. andersoni in China is not attributed to the introduction of dairy cattle. More studies involving more genetic loci and systematic sampling are needed to better elucidate the population genetic structure of C. muris and C. andersoni in the world and the genetic basis for the difference in host specificity among the two most common gastric parasites.

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The data shown below were compiled from readership statistics for 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Mexico 1 3%
Unknown 31 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 12 38%
Student > Ph. D. Student 5 16%
Student > Master 4 13%
Professor > Associate Professor 3 9%
Professor 2 6%
Other 3 9%
Unknown 3 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 13 41%
Biochemistry, Genetics and Molecular Biology 4 13%
Immunology and Microbiology 3 9%
Medicine and Dentistry 2 6%
Veterinary Science and Veterinary Medicine 2 6%
Other 1 3%
Unknown 7 22%