This proposal addresses a critical issue in HIV-1 global surveillance and epidemiology study: how do we ensure the validity and reliability of virus genotyping information? Such information has frequently proven inconsistent, even erroneous, from public genome repositories (such as, GenBank). This situation will continue to deteriorate with the growing list of identified HIV sequences, as a result of increased sequencing and surveillance efforts, and in the face of lack of reliable genotyping reference sequences. Hence, developing strategies to ensure viral genotyping quality should be considered high priority in HIV research, particularly given the importance of genotyping information in regards to epidemiological surveillance, genomic research, and genomic health care. The overall goal of this project is to develop a platform for reliable HIV-1 genotyping, in particular for recombinant cases, which are more difficult than pure subtypes to be genotyped due to the complexity of recombination events. Additionally, we aim to develop a high-throughput and systematic platform that meets current research needs in the era of advanced genome sequencing. We plan to implement the following elements within such a platform: 1) an efficient computational pipeline for reliable HIV-1 genotyping; and 2) a reliable collection of HIV-1 recombinant sequences and a list of recombinants that can be used as valid and reliable genotyping references. Through this first of its kind, systematic investigation of genotyping quality of all published HIV sequences, our results will lay a robust foundation for HIV genomic research to help improve current knowledge of HIV evolutionary patterns under different epidemiological settings. More broadly, this proposed research strategy would also contribute to research in other organisms that similarly require reliable classifications for case definition and treatment options.
This proposal addresses a critical difficulty in conducting HIV genomic studies and epidemiological surveillance, in which the virus classification has long been plagued by inconsistent, even erroneous, genotyping procedures. Combining interdisciplinary skills in molecular epidemiology and computational biology, we propose to develop a streamlined platform to ensure HIV genotyping validity and reliability. The proposed study will provide a reliable genotyping basic procedure for HIV genomic research and genomic health care.
| 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 |
