Dataset Information

Estimating time of HIV-1 infection from next-generation sequence diversity.

ABSTRACT: Estimating the time since infection (TI) in newly diagnosed HIV-1 patients is challenging, but important to understand the epidemiology of the infection. Here we explore the utility of virus diversity estimated by next-generation sequencing (NGS) as novel biomarker by using a recent genome-wide longitudinal dataset obtained from 11 untreated HIV-1-infected patients with known dates of infection. The results were validated on a second dataset from 31 patients. Virus diversity increased linearly with time, particularly at 3rd codon positions, with little inter-patient variation. The precision of the TI estimate improved with increasing sequencing depth, showing that diversity in NGS data yields superior estimates to the number of ambiguous sites in Sanger sequences, which is one of the alternative biomarkers. The full advantage of deep NGS was utilized with continuous diversity measures such as average pairwise distance or site entropy, rather than the fraction of polymorphic sites. The precision depended on the genomic region and codon position and was highest when 3rd codon positions in the entire pol gene were used. For these data, TI estimates had a mean absolute error of around 1 year. The error increased only slightly from around 0.6 years at a TI of 6 months to around 1.1 years at 6 years. Our results show that virus diversity determined by NGS can be used to estimate time since HIV-1 infection many years after the infection, in contrast to most alternative biomarkers. We provide the regression coefficients as well as web tool for TI estimation.

SUBMITTER: Puller V

PROVIDER: S-EPMC5638550 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature

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Estimating time of HIV-1 infection from next-generation sequence diversity.

Puller Vadim V Neher Richard R Albert Jan J

PLoS computational biology 20171002 10

Estimating the time since infection (TI) in newly diagnosed HIV-1 patients is challenging, but important to understand the epidemiology of the infection. Here we explore the utility of virus diversity estimated by next-generation sequencing (NGS) as novel biomarker by using a recent genome-wide longitudinal dataset obtained from 11 untreated HIV-1-infected patients with known dates of infection. The results were validated on a second dataset from 31 patients. Virus diversity increased linearly w ...[more]

PMID: 28968389

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Project description:Approximately 36.7 million people were living with the human immunodeficiency virus (HIV) at the end of 2016 according to UNAIDS, representing a global prevalence rate of 0.8%. In Brazil, an HIV prevalence of 0.24% has been estimated, which represents approximately 830,000 individuals living with the virus. As a touristic and commercial hub in Latin America, Brazil harbors an elevated HIV genetic variability, further contributed by the selective pressure exerted by the host immune system and by antiretroviral treatment. Through the progress of the next-generation sequencing (NGS) techniques, it has been possible to expand the study of HIV genetic diversity, evolutionary, and epidemic processes, allowing the generation of HIV complete or near full-length genomes (NFLG) and improving the characterization of intra- and interhost diversity of viral populations. Greater sensitivity in the detection of viral recombinant forms represents one of the major improvements associated with this development. It is possible to identify unique or circulating recombinant forms using the near full-length viral genomes with increasing accuracy. It also permits the characterization of multiple viral infections within individual hosts. Previous Brazilian studies using NGS to analyze HIV diversity were able to identify several distinct unique and circulating recombinant forms and evidenced dual infections. These data unveiled unprecedented high rates of viral recombination and highlighted that novel recombinants are continually arising in the Brazilian epidemic. In the pooled analysis depicted in this report, HIV subtypes have been determined from HIV-positive patients in five states of Brazil with some of the highest HIV prevalence, three in the Southeast (Rio de Janeiro, São Paulo, and Minas Gerais), one in the Northeast (Pernambuco) and one in the South (Rio Grande do Sul). Combined data analysis showed a significant prevalence of recombinant forms (29%; 101/350), and a similar 26% when only NFLGs were considered. Moreover, the analysis was able to evidence the occurrence of multiple infections in some individuals. Our data highlight the great HIV genetic diversity found in Brazil and unveils a more accurate scenario of the HIV evolutionary dynamics in the region.

Project description:Admixture-the mixing of genomes from divergent populations-is increasingly appreciated as a central process in evolution. To characterize and quantify patterns of admixture across the genome, a number of methods have been developed for local ancestry inference. However, existing approaches have a number of shortcomings. First, all local ancestry inference methods require some prior assumption about the expected ancestry tract lengths. Second, existing methods generally require genotypes, which is not feasible to obtain for many next-generation sequencing projects. Third, many methods assume samples are diploid, however a wide variety of sequencing applications will fail to meet this assumption. To address these issues, we introduce a novel hidden Markov model for estimating local ancestry that models the read pileup data, rather than genotypes, is generalized to arbitrary ploidy, and can estimate the time since admixture during local ancestry inference. We demonstrate that our method can simultaneously estimate the time since admixture and local ancestry with good accuracy, and that it performs well on samples of high ploidy-i.e. 100 or more chromosomes. As this method is very general, we expect it will be useful for local ancestry inference in a wider variety of populations than what previously has been possible. We then applied our method to pooled sequencing data derived from populations of Drosophila melanogaster on an ancestry cline on the east coast of North America. We find that regions of local recombination rates are negatively correlated with the proportion of African ancestry, suggesting that selection against foreign ancestry is the least efficient in low recombination regions. Finally we show that clinal outlier loci are enriched for genes associated with gene regulatory functions, consistent with a role of regulatory evolution in ecological adaptation of admixed D. melanogaster populations. Our results illustrate the potential of local ancestry inference for elucidating fundamental evolutionary processes.

Dataset Information

Estimating time of HIV-1 infection from next-generation sequence diversity.

Publications

Estimating time of HIV-1 infection from next-generation sequence diversity.

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