Dataset Information

Analysis of sequence diversity and selection pressure in HIV-1 clade C gp41 from India.

ABSTRACT: Evaluation of viral diversity is critical for the rational design of treatment modalities against Human immunodeficiency virus (HIV). Predominated by HIV-1 clade C (HIV-1C), the epidemic in India represents the third largest population infected with HIV-1 globally. Glycoprotein 41 (gp41) is critical for viral replication and is a target for the design of therapeutic strategies. However, documentation of viral diversity of gp41 gene in infected individuals from India remains limited. Present study employed high throughput sequencing to examine variation in gp41 amplicons generated from blood derived viruses in 24 HIV-1C infected individuals from Mumbai, India. Sequence diversity profiles were documented in different functional domains of gp41. Furthermore, through a meta-analysis approach, all reported gp41 sequences from India (N = 70) were compared with those from South Africa (N = 126), country with the largest HIV epidemic globally, also predominated by HIV-1C. A total of 44 positions displayed statistically significant differential (p < 0.05) Shannon entropy in the two regions. This comparison also identified 11 codon sites undergoing distinct selection, 8 of which remained differentially selected in an extended comparison of data from Asia (N = 137) and Africa(N = 383). Assessment of correlated mutation networks associated with differentially selected residues revealed common as well as distinct interaction networks. Furthermore, codon usage analysis revealed 17 differentially selected codons (Mann-Whitney test, p < 0.001) in Asia and Africa. Dissimilar trends in GC content across codon positions were also observed. In depth understanding of these divergent evolutionary signatures through extended analysis with larger data-sets would assist development of effective interventions being considered for HIV-1C.

SUBMITTER: Sutar J

PROVIDER: S-EPMC7458999 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:The genome-wide scan for selection is an important method for identifying loci involved in adaptive evolution. However, theory that underlies standard scans for selection assumes a simple mutation model. In particular, recurrent mutation of the selective target is not considered. Although this assumption is reasonable for single-nucleotide variants (SNVs), a microsatellite targeted by selection will reliably violate this assumption due to high mutation rate. Moreover, the mutation rate of microsatellites is generally high enough to ensure that recurrent mutation is pervasive rather than occasional. It is therefore unclear if positive selection targeting microsatellites can be detected using standard scanning statistics. Examples of functional variation at microsatellites underscore the significance of understanding the genomic effects of microsatellite selection. Here, we investigate the joint effects of selection and complex mutation on linked sequence diversity, comparing simulations of microsatellite selection and SNV-based selective sweeps. We find that selection on microsatellites is generally difficult to detect using popular summaries of the site frequency spectrum, and, under certain conditions, using popular methods such as the integrated haplotype statistic and SweepFinder. However, comparisons of the number of haplotypes (K) and segregating sites (S) often provide considerable power to detect selection on microsatellites. We apply this knowledge to a scan of autosomes in the human CEU population (CEPH population sampled from Utah). In addition to the most commonly reported targets of selection in European populations, we identify numerous novel genomic regions that bear highly anomalous haplotype configurations. Using one of these regions-intron 1 of MAGI2-as an example, we show that the anomalous configuration is coincident with a perfect CA repeat of length 22. We conclude that standard genome-wide scans will commonly fail to detect mutationally complex targets of selection but that comparisons of K and S will, in many cases, facilitate their identification.

Dataset Information

Analysis of sequence diversity and selection pressure in HIV-1 clade C gp41 from India.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets