Intra-subtype recombination is an efficient strategy applied by HIV-1 (human immunodeficiency virus type 1) to generate extraordinary virus diversity that contributes to intra-patient quasi-species and drug resistance. Here we propose a novel methodology to detect HIV-1 intra-subtype recombination to fill the gap between the necessity of tracking HIV genetic changes along disease progression and transmission and lack of intra-subtype analysis methodologies. Due to greater sequence similarity, intra-subtype recombination is harder to detect than inter-subtype recombination. Therefore the detection of intra- subtype recombination, not only in the HIV case but also in other organisms, should consider appropriate array of sequences that can reflect a full spectrum of diversity within a subtype. In this regard, we hypothesize that these sequences have existed more abundantly in sequenced fragments but are less present in sequenced complete genome sequences, while the latter are widely used in any kind of HIV recombination studies. Our rationale derives from our previous study, in which we successfully identified sub-subtypes within HIV-1 subtype J. Our findings were based on sequenced fragments rather than complete genome sequences. We believe that the repertoire of all published sequence fragments contains a great degree of sequence diversity that we have overlooked in many aspects of studies, including viral molecular evolution and molecular epidemiology studies. The objective of this project is to (1) identify sub-subtype representative sequences within each HIV-1 subtype;and (2) implement a high-throughput scheme for detection of viral intra-subtype recombination. Our proposed study will provide a basis for a rational and quantitative evaluation of the prevalence of HIV-1 intra-subtype recombinants, which is critical for tracking the dynamic and complex HIV epidemic and designing improved antiviral therapies and vaccines. Last but not the least, our proposed research strategy can also be applied to the recombination study in other viruses.
Our proposed study will provide a basis for rational and quantitative evaluation of the prevalence of HIV-1 intra-subtype recombinants, which is critical for tracking the dynamic and complex HIV epidemic, and designing improved antiviral therapies and vaccines.
| Jia, MingRui; Shaw, Timothy; Zhang, Xing et al. (2017) Decoding noises in HIV computational genotyping. Virology 511:249-255 |
| Griffin, Tess Z; Kang, Weiliang; Ma, Yongjie et al. (2015) The HAND Database: a gateway to understanding the role of HIV in HIV-associated neurocognitive disorders. BMC Med Genomics 8:70 |
| Shaw, Timothy I; Zhang, Ming (2013) HIV N-linked glycosylation site analyzer and its further usage in anchored alignment. Nucleic Acids Res 41:W454-8 |
