Mapping mutational effects along the evolutionary landscape of HIV envelope
- Fred Hutchinson Cancer Research Center, United States
Abstract
The immediate evolutionary space accessible to HIV is largely determined by how single amino-acid mutations affect fitness. These mutational effects can shift as the virus evolves. However, the prevalence of such shifts in mutational effects remains unclear. Here we quantify the effects on viral growth of all amino-acid mutations to two HIV envelope (Env) proteins that differ at >100 residues. Most mutations similarly affect both Envs, but the amino-acid preferences of a minority of sites have clearly shifted. These shifted sites usually prefer a specific amino acid in one Env, but tolerate many amino acids in the other. Surprisingly, shifts are only slightly enriched at sites that have substituted between the Envs-and many occur at residues that do not even contact substitutions. Therefore, long-range epistasis can unpredictably shift Env's mutational tolerance during HIV evolution, although the amino-acid preferences of most sites are conserved between moderately diverged viral strains.
Data availability
-
Deep mutational scanning of BF520Publicly available at the NCBI SAMN06313000.
-
Deep mutational scanning of BG505Publicly available at the NCBI SAMN07718028.
-
Computer codehttps://github.com/jbloomlab/EnvMutationalShiftsPaper.
Article and author information
Author details
Funding
National Institutes of Health (R01-AI127893)
- Jesse D Bloom
National Science Foundation (DGE-1256082)
- Adam S Dingens
Howard Hughes Medical Institute (Faculty Scholar Grant)
- Jesse D Bloom
Simons Foundation (Faculty Scholar Grant)
- Jesse D Bloom
Collaboration for AIDS Vaccine Discovery (OPP1111923)
- Jesse D Bloom
National Institutes of Health (DP1-DA039543)
- Julie Overbaugh
National Institutes of Health (T32GM007270)
- Hugh K Haddox
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2018, Haddox et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 5,575
- views
-
- 705
- downloads
-
- 107
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
Further reading
-
- Evolutionary Biology
- Genetics and Genomics
Cattle (Bos taurus) play an important role in the life of humans in the Iberian Peninsula not just as a food source but also in cultural events. When domestic cattle were first introduced to Iberia, wild aurochs (Bos primigenius) were still present, leaving ample opportunity for mating (whether intended by farmers or not). Using a temporal bioarchaeological dataset covering eight millennia, we trace gene flow between the two groups. Our results show frequent hybridisation during the Neolithic and Chalcolithic, likely reflecting a mix of hunting and herding or relatively unmanaged herds, with mostly male aurochs and female domestic cattle involved. This is supported by isotopic evidence consistent with ecological niche sharing, with only a few domestic cattle possibly being managed. The proportion of aurochs ancestry in domestic cattle remains relatively constant from about 4000 years ago, probably due to herd management and selection against first generation hybrids, coinciding with other cultural transitions. The constant level of wild ancestry (~20%) continues into modern Western European breeds including Iberian cattle selected for aggressiveness and fighting ability. This study illuminates the genomic impact of human actions and wild introgression in the establishment of cattle as one of the most important domestic species today.
-
- Evolutionary Biology
- Genetics and Genomics
Expression quantitative trait loci (eQTLs) provide a key bridge between noncoding DNA sequence variants and organismal traits. The effects of eQTLs can differ among tissues, cell types, and cellular states, but these differences are obscured by gene expression measurements in bulk populations. We developed a one-pot approach to map eQTLs in Saccharomyces cerevisiae by single-cell RNA sequencing (scRNA-seq) and applied it to over 100,000 single cells from three crosses. We used scRNA-seq data to genotype each cell, measure gene expression, and classify the cells by cell-cycle stage. We mapped thousands of local and distant eQTLs and identified interactions between eQTL effects and cell-cycle stages. We took advantage of single-cell expression information to identify hundreds of genes with allele-specific effects on expression noise. We used cell-cycle stage classification to map 20 loci that influence cell-cycle progression. One of these loci influenced the expression of genes involved in the mating response. We showed that the effects of this locus arise from a common variant (W82R) in the gene GPA1, which encodes a signaling protein that negatively regulates the mating pathway. The 82R allele increases mating efficiency at the cost of slower cell-cycle progression and is associated with a higher rate of outcrossing in nature. Our results provide a more granular picture of the effects of genetic variants on gene expression and downstream traits.
