Author response: A genome-to-genome analysis of associations between human genetic variation, HIV-1 sequence diversity, and viral control

HIV-1 sequence diversity is affected by selection pressures arising from host genomic factors. Using paired human and viral data from 1071 individuals, we ran >3000 genome-wide scans, testing for associations between host DNA polymorphisms, HIV-1 sequence variation and plasma viral load (VL), while considering human and viral population structure. We observed significant human SNP associations to a total of 48 HIV-1 amino acid variants (p<2.4 × 10−12). All associated SNPs mapped to the HLA class I region. Clinical relevance of host and pathogen variation was assessed using VL results. We identified two critical advantages to the use of viral variation for identifying host factors: (1) association signals are much stronger for HIV-1 sequence variants than VL, reflecting the ‘intermediate phenotype’ nature of viral variation; (2) association testing can be run without any clinical data. The proposed genome-to-genome approach highlights sites of genomic conflict and is a strategy generally applicable to studies of host–pathogen interaction.

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Host genomics of the HIV-1 reservoir size and its decay rate during suppressive antiretroviral treatment

10.1101/19013763 ◽

2019 ◽

Author(s):

Christian W. Thorball ◽

Alessandro Borghesi ◽

Nadine Bachmann ◽

Chantal von Siebenthal ◽

Valentina Vongrad ◽

...

Keyword(s):

Genetic Variation ◽

Decay Rate ◽

Antiretroviral Treatment ◽

Rare Variants ◽

European Ancestry ◽

Viral Reservoir ◽

Human Genetic Variation ◽

Sequencing Data ◽

Common Genetic Variants ◽

Hiv 1

ABSTRACTIntroductionA major hurdle to HIV-1 eradication is the establishment of a latent viral reservoir early after primary infection. Several factors are known to influence the HIV-1 reservoir size and decay rate on suppressive antiretroviral treatment (ART), but little is known about the role of human genetic variation.MethodsWe measured the reservoir size at three time points over a median of 5.4 years, and searched for associations between human genetic variation and two phenotypic readouts: the reservoir size at the first time point and its decay rate over the study period. We assessed the contribution of common genetic variants using genome-wide genotyping data from 797 patients with European ancestry enrolled in the Swiss HIV Cohort Study and searched for a potential impact of rare variants and exonic copy number variants using exome sequencing data generated in a subset of 194 study participants.ResultsGenome- and exome-wide analyses did not reveal any significant association with the size of the HIV-1 reservoir or its decay rate on suppressive ART.ConclusionsOur results point to a limited influence of human genetics on the size of the HIV-1 reservoir and its long-term dynamics in successfully treated individuals.

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Author response: Gene-centric functional dissection of human genetic variation uncovers regulators of hematopoiesis

10.7554/elife.44080.041 ◽

2019 ◽

Author(s):

Satish K Nandakumar ◽

Sean K McFarland ◽

Laura M Mateyka ◽

Caleb A Lareau ◽

Jacob C Ulirsch ◽

...

Keyword(s):

Genetic Variation ◽

Author Response ◽

Human Genetic Variation ◽

Response Gene

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A Flow Procedure for the Linearization of Genome Sequence Graphs

10.1101/101501 ◽

2017 ◽

Cited By ~ 2

Author(s):

David Haussler ◽

Maciej Smuga-Otto ◽

Benedict Paten ◽

Adam M Novak ◽

Sergei Nikitin ◽

...

Keyword(s):

Genetic Variation ◽

Genome Sequence ◽

Graph Representation ◽

Graph Visualization ◽

Human Genetic Variation ◽

A Genome ◽

Sequence Graph ◽

Reference Genomes ◽

Single Graph ◽

Reference Human Genome

1AbstractEfforts to incorporate human genetic variation into the reference human genome have converged on the idea of a graph representation of genetic variation within a species, a genome sequence graph. A sequence graph represents a set of individual haploid reference genomes as paths in a single graph. When that set of reference genomes is sufficiently diverse, the sequence graph implicitly contains all frequent human genetic variations, including translocations, inversions, deletions, and insertions.In representing a set of genomes as a sequence graph one encounters certain challenges. One of the most important is the problem of graph linearization, essential both for efficiency of storage and access, as well as for natural graph visualization and compatibility with other tools. The goal of graph linearization is to order nodes of the graph in such a way that operations such as access, traversal and visualization are as efficient and effective as possible.A new algorithm for the linearization of sequence graphs, called the flow procedure, is proposed in this paper. Comparative experimental evaluation of the flow procedure against other algorithms shows that it outperforms its rivals in the metrics most relevant to sequence graphs.

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