A quantitative analysis of the FIV and HIV genome using bioinformatics software

Abstract

Among viruses, the human immunodeficiency virus (HIV) presented the greatest challenge to human kinds. the HIV and FIV gag genome was sequenced using the Illumina MiSeq Benchtop next-generation sequencer.The DNA sequences obtained were then run through the LALIGN bioinformatics software to compute the E value, bit score, waterman eggert score, percent identity,which are four important indicators of how similar the sequences are. The E value was 3.1 x 10 ^-9, the percent identity was 54.4 percent and the bit score was 51.9. It was also sensed that base 1600 to 1990 in HIV and base 800 to 910 in FIV have a higher than normal similarity. This reflects that while the DNA sequences of the gag region of both the HIV and FIV genome are rather similar and it is unlikely that this similarity is due to random chance, there are a noticeable amount of differences. A better understanding of the level of similarity and differences in the gag region of the genome sequence would facilitate our understanding of structural and cellular behavioral differences between FIV and HIV, and in the long term it prevides new explanations to differences observed in previous studies, or even facilitate the development of an effective HIV treatment.