Human Immunodeficiency Virus (HIV) is a lentivirus that causes Acquired Immunodeficiency Syndrome (AIDS) resulting in the progressive failure of the immune system. Due to its rapid replication rate and high mutation frequency, the virus is able to evade the immune system and thwart an efficacious response. Current HIV infection prophylaxes and therapeutics are not optimal and there is an urgent need to develop an efficacious HIV vaccine. Recently, high-throughput sequencing of the Immunoglobulin (Ig) repertoire from HIV-infected humans and immunized Rhesus macaques has led to important insights into vaccines against HIV-1. Further elucidation of the antibody response in these crucial animal studies will require substantially greater power to analyze the Ig repertoires than is currently possible. Reliable information on macaque Ig genes is insufficient due to the incompleteness of the whole genome sequence (WGS) and the inherent difficulty of obtaining complete Ig sequences due to its complex and repetitive nature. To address this issue, we have generated a high quality, annotated WGS with precisely annotated Ig loci from ten macaques. We used low error, synthetic long reads generated by Illumina TruSeq technology, Illumina 150bp, paired-end reads (110X coverage) and Irys genome mapping technology to assemble the genome de novo. We employed a bait-and-sequence strategy using human Ig probes to capture macaque Ig genes for the accurate assembly and annotation of Ig genes and alleles. Together, these data will generate a complete Rhesus macaque genome with detailed information on allelic diversity at the Ig loci. This study is essential for making the macaque a viable model for adaptive immunity. In addition, it will provide information on the similarities and differences between macaque and human Ig genes that will aid in the design and interpretation of vaccine studies.
Identifer | oai:union.ndltd.org:bu.edu/oai:open.bu.edu:2144/20786 |
Date | 09 March 2017 |
Creators | Ramesh, Akshaya |
Source Sets | Boston University |
Language | en_US |
Detected Language | English |
Type | Thesis/Dissertation |
Page generated in 0.0016 seconds