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Recombination Form and Epidemiology of HIV-1 Unique Recombinant Strains Identified in Yunnan, China

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Title
Recombination Form and Epidemiology of HIV-1 Unique Recombinant Strains Identified in Yunnan, China
Published in
PLOS ONE, October 2012
DOI 10.1371/journal.pone.0046777
Pubmed ID
Authors

Lin Li, Lili Chen, Shaomin Yang, Tianyi Li, Jianjian Li, Yongjian Liu, Lei Jia, Bihui Yang, Zuoyi Bao, Hanping Li, Xiaolin Wang, Daomin Zhuang, Siyang Liu, Jingyun Li

Abstract

Several studies identified HIV-1 recombination in some distinct areas in Yunnan, China. However, no comprehensive studies had been fulfilled in the whole province up to now. To illustrate the epidemiology and recombination form of Unique Recombinant Forms (URFs) circulating in Yunnan, 788 HIV-1 positive individuals residing in 15 prefectures of Yunnan were randomly enrolled into the study. Full-length gag and pol genes were amplified and sequenced. Maximum likelihood tree was constructed for phylogenetic analysis. Recombinant breakpoints and genomic schematics were identified with online software jpHMM. 63 (10.2%) unique recombinant strains were identified from 617 strains with subtypes. The URFs distributed significantly differently among prefectures (Pearson chi-square test, P<0.05). IDUs contained more URFs than sexual transmitted population (Pearson chi-square test, P<0.05). Two main recombinant forms were identified by considering the presence of CRF01_AE segments in full length gag-pol genes, which were B'/C and B'/C/CRF01-AE recombinants. Three clusters were identified in the ML tree which contained more than three sequences and supported by high bootstrap values. One CRF was identified. Many of URFs contained identical breakpoints. The results will contribute to our understanding on HIV recombination and provide clues to the identification of potential CRFs in China.

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Geographical breakdown

Country Count As %
Brazil 1 4%
Unknown 22 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 35%
Researcher 3 13%
Student > Master 3 13%
Student > Bachelor 2 9%
Student > Postgraduate 2 9%
Other 3 13%
Unknown 2 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 5 22%
Medicine and Dentistry 4 17%
Nursing and Health Professions 3 13%
Biochemistry, Genetics and Molecular Biology 2 9%
Computer Science 2 9%
Other 5 22%
Unknown 2 9%