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The spillovers of betacoronaviruses in humans and the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants highlight the need for broad coronavirus countermeasures. We describe five monoclonal antibodies (mAbs) cross-reacting with the stem helix of multiple betacoronavirus spike glycoproteins isolated from COVID-19 convalescent individuals. Using structural and functional studies, we show that the mAb with the greatest breadth (S2P6) neutralizes pseudotyped viruses from three different subgenera through the inhibition of membrane fusion, and we delineate the molecular basis for its cross-reactivity. S2P6 reduces viral burden in hamsters challenged with SARS-CoV-2 through viral neutralization and Fc-mediated effector functions. Stem helix antibodies are rare, oftentimes of narrow specificity, and can acquire neutralization breadth through somatic mutations. These data provide a framework for structure-guided design of pan-betacoronavirus vaccines eliciting broad protection. ispartof: SCIENCE vol:373 issue:6559 pages:1109-1115 ispartof: location:United States status: published

Understanding the significance of genetic variants in the noncoding genome is emerging as the next challenge in human genomics. We used the power of 11,257 whole-genome sequences and 16,384 heptamers (7-nt motifs) to build a map of sequence constraint for the human species. This build differed substantially from traditional maps of interspecies conservation and identified regulatory elements among the most constrained regions of the genome. Using new Hi-C experimental data, we describe a strong pattern of coordination over 2 Mb where the most constrained regulatory elements associate with the most essential genes. Constrained regions of the noncoding genome are up to 52-fold enriched for known pathogenic variants as compared to unconstrained regions (21-fold when compared to the genome average). This map of sequence constraint across thousands of individuals is an asset to help interpret noncoding elements in the human genome, prioritize variants and reconsider gene units at a larger scale.

Studies of host genetic determinants of pathogen sequence variation can identify sites of genomic conflicts, by highlighting variants that are implicated in immune response on the host side and adaptive escape on the pathogen side. However, systematic genetic differences in host and pathogen populations can lead to inflated type I (false positive) and type II (false negative) error rates in genome-wide association analyses. Here, we demonstrate through simulation that correcting for both host and pathogen stratification reduces spurious signals and increases power to detect real associations in a variety of tested scenarios. We confirm the validity of the simulations by showing comparable results in an analysis of paired human and HIV genomes.

Significance Advances in technology are enabling evaluation for prevention and early detection of age-related chronic diseases associated with premature mortality, such as cancer and cardiovascular diseases. These diseases kill about one-third of men and one-quarter of women between the ages of 50 and 74 years old in the United States. We used whole-genome sequencing, advanced imaging, and other clinical testing to screen 209 active, symptom-free adults. We identified a broad set of complementary age-related chronic disease risks associated with premature mortality., Reducing premature mortality associated with age-related chronic diseases, such as cancer and cardiovascular disease, is an urgent priority. We report early results using genomics in combination with advanced imaging and other clinical testing to proactively screen for age-related chronic disease risk among adults. We enrolled active, symptom-free adults in a study of screening for age-related chronic diseases associated with premature mortality. In addition to personal and family medical history and other clinical testing, we obtained whole-genome sequencing (WGS), noncontrast whole-body MRI, dual-energy X-ray absorptiometry (DXA), global metabolomics, a new blood test for prediabetes (Quantose IR), echocardiography (ECHO), ECG, and cardiac rhythm monitoring to identify age-related chronic disease risks. Precision medicine screening using WGS and advanced imaging along with other testing among active, symptom-free adults identified a broad set of complementary age-related chronic disease risks associated with premature mortality and strengthened WGS variant interpretation. This and other similarly designed screening approaches anchored by WGS and advanced imaging may have the potential to extend healthy life among active adults through improved prevention and early detection of age-related chronic diseases (and their risk factors) associated with premature mortality.

Polygenic approaches using genome-wide data have been hugely successful in confirming and quantifying the heritability of complex human traits. Here, we highlight their ability to identify potential novel risk variants by looking for variants with pleiotropic effect in genetically overlapping phenotypes.We used LD Score Regression in a sample of 6,315 HIV+ European individuals and 7,247 controls to test for phenotypes genetically overlapping with susceptibility to HIV-1 infection. Using LD Hub, a web tool that performs LD Score Regression, identified two phenotypes with significant genetic overlap: schizophrenia (rG =0.19, p=0.0007 and ulcerative colitis (rG=0.22, p= 0.0061). We further showed that the genetic overlap between HIV acquisition and schizophrenia is likely driven in part by their shared overlap with cannabis use and sexual behavior. BUMHBOX analyses suggested that these genetic overlaps were driven by genome-wide pleiotropy with HIV acquisition rather than heterogeneity within the HIV acquisition sample. The two diseases identified as genetically overlapping with HIV-1 acquisition have >100 associated variants, and we tested if any of them significantly associated with HIV acquisition. We observed three variants that exceeded our threshold for statistical significance. Two of these were eQTLs in whole blood for genes coding for proteins suspected to be involved in HIV biology: rs1819333 in CCR6 (p=0.0002) and rs4932178 in FURIN (p=0.00033). However, no signal was found for these variants in two smaller African samples totaling 1015 cases and 963 controls, though the mode of acquisition and genetic architecture of these populations differed.These results highlight the ability to use polygenic methods to gain new insights into complex diseases and identify potential associations with individual variants. Crucially, the leveraging of existing, publically available data makes these methods a cost-effective approach. In this case, our results add to the evidence for the role of risk taking behavior and inflammation of the bowel in HIV acquisition.Author SummaryThe biology of what puts certain individuals at greater risk of HIV acquisition is poorly understood. Using several novel polygenic methods, we identify supporting evidence for two important factors leading to acquisition. First, the role of an individual’s genetic predisposition to risk taking behaviours such as number of sexual partners, age at first sexual intercourse drug use, and mental health problems. Second, the role of gut inflammation, in particular a genetic overlap between HIV acquisition with inflammatory bowel disease and the potential role of CCR6 during infection.

Viral respiratory infections are usually mild and self-limiting; still they exceptionally result in life-threatening infections in previously healthy children. To investigate a potential genetic cause, we recruited 120 previously healthy children requiring support in intensive care because of a severe illness caused by a respiratory virus. Using exome and transcriptome sequencing, we identified and characterized three rare loss-of-function variants in IFIH1, which encodes an RIG-I-like receptor involved in the sensing of viral RNA. Functional testing of the variants IFIH1 alleles demonstrated that the resulting proteins are unable to induce IFN-β, are intrinsically less stable than wild-type IFIH1, and lack ATPase activity. In vitro assays showed that IFIH1 effectively restricts replication of human respiratory syncytial virus and rhinoviruses. We conclude that IFIH1 deficiency causes a primary immunodeficiency manifested in extreme susceptibility to common respiratory RNA viruses.

One out of three pediatric sepsis deaths in high income countries occur in previously healthy children. Primary immunodeficiencies have been postulated to underlie fulminant sepsis, but this concept remains to be confirmed in clinical practice. Pseudomonas aeruginosa (P. aeruginosa) is a common bacterium mostly associated with healthcare-related infections in immunocompromised individuals. However, in rare cases, it can cause sepsis in previously healthy children. We used exome sequencing and bioinformatic analysis to systematically search for genetic factors underpinning severe P. aeruginosa infection in the pediatric population. We collected blood samples from 11 previously healthy children, with no family history of immunodeficiency, who presented with severe sepsis due to community-acquired P. aeruginosa bacteremia. Genomic DNA was extracted from blood or tissue samples obtained intravitam or postmortem. We obtained high-coverage exome sequencing data and searched for rare loss-of-function variants. After rigorous filtrations, 12 potentially causal variants were identified. 2 out of 8 (25%) fatal cases were found to carry novel pathogenic variants in primary immunodeficiency genes, including BTK and DNMT3B. This study demonstrates that exome sequencing allows to identify rare, deleterious human genetic variants responsible for fulminant sepsis in apparently healthy children. Diagnosing primary immunodeficiencies in such patients is of high relevance to survivors and affected families. We propose that unusually severe and fatal sepsis cases in previously healthy children should be considered for exome/genome sequencing to search for underlying primary immunodeficiencies.

Background. The impact of human genetic background on low-trauma fracture (LTF) risk has not been evaluated in the context of human immunodeficiency virus (HIV) and clinical LTF risk factors. Methods. In the general population, 6 common single-nucleotide polymorphisms (SNPs) associate with LTF through genome-wide association study. Using genome-wide SNP arrays and imputation, we genotyped these SNPs in HIV-positive, white Swiss HIV Cohort Study participants. We included 103 individuals with a first, physician-validated LTF and 206 controls matched on gender, whose duration of observation and whose antiretroviral therapy start dates were similar using incidence density sampling. Analyses of nongenetic LTF risk factors were based on 158 cases and 788 controls. Results. A genetic risk score built from the 6 LTF-associated SNPs did not associate with LTF risk, in both models including and not including parental hip fracture history. The contribution of clinical LTF risk factors was limited in our dataset. Conclusions. Genetic LTF markers with a modest effect size in the general population do not improve fracture prediction in persons with HIV, in whom clinical LTF risk factors are prevalent in both cases and controls.

Human APOBEC3 cytidine deaminases are intrinsic resistance factors to HIV-1. However, HIV-1 encodes a viral infectivity factor (Vif) that degrades APOBEC3 proteins. In vitro APOBEC3F (A3F) anti-HIV-1 activity is weaker than A3G but is partially resistant to Vif degradation unlike A3G. It is unknown whether A3F protein affects HIV-1 disease in vivo. To assess the effect of A3F gene on host susceptibility to HIV- acquisition and disease progression, we performed a genetic association study in six well-characterized HIV-1 natural cohorts. A common six-Single Nucleotide Polymorphism (SNP) haplotype of A3F tagged by a codon-changing variant (p. I231V, with allele (V) frequency of 48% in European Americans) was associated with significantly lower set-point viral load and slower rate of progression to AIDS (Relative Hazards (RH) = 0.71, 95% CI: 0.56, 0.91) and delayed development of pneumocystis pneumonia (PCP) (RH = 0.53, 95% CI: 0.37–0.76). A validation study in the International Collaboration for the Genomics of HIV (ICGH) showed a consistent association with lower set-point viral load. An in vitro assay revealed that the A3F I231V variant may influence Vif mediated A3F degradation. Our results provide genetic epidemiological evidence that A3F modulates HIV-1/AIDS disease progression., Author Summary Cytidine deaminases of the human APOBEC3 (A3) gene family serve as intrinsic resistance factors to HIV-1 and other retroviruses. HIV-1 encodes the viral infectivity factor (Vif) protein that degrades APOBEC3 proteins via the ubiquitination-proteosomal pathway. APOBEC3F (A3F), unlike APOBEC3G (A3G), is partially resistant to Vif-mediated degradation. The antiviral activity of the A3 family has largely been demonstrated in in vitro experiments, and there is mounting evidence that A3G genetic variants influence HIV disease progression. It is not resolved if A3F protein affects HIV disease in vivo. To assess the in vivo effect of A3F, we performed a genetic association study of genetic variants in A3F for their influence on HIV- acquisition and HIV disease progression. A common A3F haplotype was associated with a 30% reduced rate of AIDS disease progression, lower set-point viral load and delayed development of pneumocystis pneumonia (PCP) in European Americans. This study provides the first epidemiological evidence that A3F might modify HIV-1/AIDS pathogenesis.

We evaluated the fraction of variation in HIV-1 set point viral load attributable to viral or human genetic factors by using joint host/pathogen genetic data from 541 HIV infected individuals. We show that viral genetic diversity explains 29% of the variation in viral load while host factors explain 8.4%. Using a joint model including both host and viral effects, we estimate a total of 30% heritability, indicating that most of the host effects are reflected in viral sequence variation., Author Summary Viral loads of Human Immunodeficiency Virus infections are correlated between the donor and the recipient of the transmission pair. Similarly, human genetic factors may modulate viral load. In this study we estimate the extents to which viral load is heritable either via the viral genotype (from donor to recipient) or via the host’s Human Leukocyte Antigen (HLA) genotype. We find that a major fraction of inter individual variability is explained by the similarity of the viral genotypes, and that human genetic variation in the HLA region provide little additional explanatory power.

Sequencing projects have identified large numbers of rare stop-gain and frameshift variants in the human genome. As most of these are observed in the heterozygous state, they test a gene?s tolerance to haploinsufficiency and dominant loss of function. We analyzed the distribution of truncating variants across 16,260 protein coding autosomal genes in 11,546 individuals. We observed 39,893 truncating variants affecting 12,062 genes, which significantly differed from an expectation of 12,916 genes under a model of neutral de novo mutation (p

Loss-of-function variants in innate immunity genes are associated with Mendelian disorders in the form of primary immunodeficiencies. Recent resequencing projects report that stop-gains and frameshifts are collectively prevalent in humans and could be responsible for some of the inter-individual variability in innate immune response. Current computational approaches evaluating loss-of-function in genes carrying these variants rely on gene-level characteristics such as evolutionary conservation and functional redundancy across the genome. However, innate immunity genes represent a particular case because they are more likely to be under positive selection and duplicated. To create a ranking of severity that would be applicable to innate immunity genes we evaluated 17,764 stop-gain and 13,915 frameshift variants from the NHLBI Exome Sequencing Project and 1,000 Genomes Project. Sequence-based features such as loss of functional domains, isoform-specific truncation and nonsense-mediated decay were found to correlate with variant allele frequency and validated with gene expression data. We integrated these features in a Bayesian classification scheme and benchmarked its use in predicting pathogenic variants against Online Mendelian Inheritance in Man (OMIM) disease stop-gains and frameshifts. The classification scheme was applied in the assessment of 335 stop-gains and 236 frameshifts affecting 227 interferon-stimulated genes. The sequence-based score ranks variants in innate immunity genes according to their potential to cause disease, and complements existing gene-based pathogenicity scores. Specifically, the sequence-based score improves measurement of functional gene impairment, discriminates across different variants in a given gene and appears particularly useful for analysis of less conserved genes., Author Summary There are well-characterized severe immunodeficiencies associated with loss-of-function variants in innate immunity genes. Genome sequencing projects identify rare stop-gain and frameshift variants in innate immunity genes whose phenotype is uncharacterized. Current methods to estimate the severity of rare stop-gains and frameshifts are based on evolutionary conservation of the gene, the likelihood for redundancy in its function or mutational burden. These parameters are not always applicable to innate immunity genes. We evaluated sequence-level characteristics of more than 30'000 stop-gains and frameshifts and prioritized variants according to their predicted functional consequences. Our scoring approach complements existing tools in the prediction of innate immunity OMIM disease variants and associates with functional readouts such as gene expression. In this framework, we show that many individuals do carry highly pathogenic variants in genes participating in antiviral defense. The clinical assessment of these variants is of significant interest.

Background: There is an ever-increasing volume of data on host genes that are modulated during HIV infection, influence disease susceptibility or carry genetic variants that impact HIV infection. We created GuavaH (Genomic Utility for Association and Viral Analyses in HIV, http://www.GuavaH.org), a public resource that supports multipurpose analysis of genome-wide genetic variation and gene expression profile across multiple phenotypes relevant to HIV biology. Findings: We included original data from 8 genome and transcriptome studies addressing viral and host responses in and ex vivo. These studies cover phenotypes such as HIV acquisition, plasma viral load, disease progression, viral replication cycle, latency and viral-host genome interaction. This represents genome-wide association data from more than 4,000 individuals, exome sequencing data from 392 individuals, in vivo transcriptome microarray data from 127 patients/conditions, and 60 sets of RNA-seq data. Additionally, GuavaH allows visualization of protein variation in similar to 8,000 individuals from the general population. The publicly available GuavaH framework supports queries on (i) unique single nucleotide polymorphism across different HIV related phenotypes, (ii) gene structure and variation, (iii) in vivo gene expression in the setting of human infection (CD4+ T cells), and (iv) in vitro gene expression data in models of permissive infection, latency and reactivation. Conclusions: The complexity of the analysis of host genetic influences on HIV biology and pathogenesis calls for comprehensive motors of research on curated data. The tool developed here allows queries and supports validation of the rapidly growing body of host genomic information pertinent to HIV research.

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, eLife digest Developing treatments or vaccines for HIV is challenging because the genetic makeup of the virus is constantly changing in an effort to outwit the human immune system. Moreover, the immune system is highly variable as a result of the long-standing co-evolution of humans and microbes. Each individual will try to oppose the invading virus in a unique way, forcing the virus to acquire specific mutations that can be interpreted as the genetic signature of this one-against-one battle. To explore the influence of co-evolution on HIV, Bartha et al. took samples of both human and viral genomes from 1071 individuals infected with HIV, the AIDS virus, and used genotyping and sequencing technology to obtain a comprehensive description of the genetic variation in both. Computational techniques were then used to search for links between variants in the human DNA sequences and variants in the viral sequences. The most common type of genetic variation found in the human genome is a single nucleotide polymorphism, or SNP for short: a SNP is produced when a single nucleotide – an A, C, G or T – is replaced by a different nucleotide. Bartha et al. found that SNPs within the human DNA sequences in their study were linked to variations in 48 amino acids in HIV. Moreover, all these SNPs were found within a group of genes known as the HLA (human leukocyte antigen) system, which encodes for proteins that play a vital role in the immune response. This work identified the areas of the human genome that put pressure on the AIDS virus, and the regions of the virus that serve to escape human control. The approach developed by Bartha et al. allows the interactions between a microbe and a human host to be studied by looking at the genome of the microbe and the genome of the infected person. It also differentiates host-induced mutations that limit the capacity of the virus to do harm from those that are tolerated by the pathogen. A similar strategy could be used to study other infectious diseases. DOI: http://dx.doi.org/10.7554/eLife.01123.002

HIV-1 infects CD4+ T cells and completes its replication cycle in approximately 24 hours. We employed repeated measurements in a standardized cell system and rigorous mathematical modeling to characterize the emergence of the viral replication intermediates and their impact on the cellular transcriptional response with high temporal resolution. We observed 7,991 (73%) of the 10,958 expressed genes to be modulated in concordance with key steps of viral replication. Fifty-two percent of the overall variability in the host transcriptome was explained by linear regression on the viral life cycle. This profound perturbation of cellular physiology was investigated in the light of several regulatory mechanisms, including transcription factors, miRNAs, host-pathogen interaction, and proviral integration. Key features were validated in primary CD4+ T cells, and with viral constructs using alternative entry strategies. We propose a model of early massive cellular shutdown and progressive upregulation of the cellular machinery to complete the viral life cycle., Author Summary Viral pathogens, such as HIV-1, are fully dependent of the cellular machinery to complete the replication cycle. The cell offers a permissive environment, and deploys a number of antiviral defense strategies. The present work follows the process of infection of the cell with simultaneous measurements of viral replication intermediates together with the concurrent assessment of the host transcriptional changes. The main observation is that the cell undergoes a profound modification of its physiology, with a marked early decrease in expression of several thousands of genes, followed by a more discrete increase in the expression of sets of genes that may contribute to the success of the viral replication program. The cell system used in this study has limited response of paradigmatic cellular defense genes. Key features of the experimental model were validated in primary cells and with different viral vectors. The data and model generated here constitute a resource that can be used for the assessment of single gene responses to HIV-1 infection, and as comparative reference for the understanding of other viral and cellular programs, such as those implicated in successful defense against viral infection or in latency.

Sequencing projects have identified large numbers of rare stop-gain and frameshift variants in the human genome. As most of these are observed in the heterozygous state, they test a gene’s tolerance to haploinsufficiency and dominant loss of function. We analyzed the distribution of truncating variants across 16,260 autosomal protein coding genes in 11,546 individuals. We observed 39,893 truncating variants affecting 12,062 genes, which significantly differed from an expectation of 12,916 genes under a model of neutral de novo mutation (p, PLoS Computational Biology, 11 (12), ISSN:1553-734X, ISSN:1553-7358

The article is missing grant details in the Funding section. Please see the correct Funding Statement here: This work was funded by the Swiss National Science Foundation (grant 310030–130699) to AT, AC and NB, by a Grand Challenges Exploration award from the Bill and Melinda Gates Foundation, and by the European Union's Seventh Framework Programme FP7/2007–2013/ under grant agreement n°305762. HFG is supported by SNF grant 127317. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

The magnitude of the human antibody response to viral antigens is highly variable. To explore the human genetic contribution to this variability, we performed genome-wide association studies of the immunoglobulin G response to 14 pathogenic viruses in 2,363 immunocompetent adults. Significant associations were observed in the major histocompatibility complex region on chromosome 6 for influenza A virus, Epstein-Barr virus, JC polyomavirus, and Merkel cell polyomavirus. Using local imputation and fine mapping, we identified specific amino acid residues in human leucocyte antigen (HLA) class II proteins as the most probable causal variants underlying these association signals. Common HLA-DRβ1 haplotypes showed virus-specific patterns of humoral-response regulation. We observed an overlap between variants affecting the humoral response to influenza A and EBV and variants previously associated with autoimmune diseases related to these viruses. The results of this study emphasize the central and pathogen-specific role of HLA class II variation in the modulation of humoral immune response to viral antigens in humans. unReviewed

Background Superinfection with drug resistant HIV strains could potentially contribute to compromised therapy in patients initially infected with drug-sensitive virus and receiving antiretroviral therapy. To investigate the importance of this potential route to drug resistance, we developed a bioinformatics pipeline to detect superinfection from routinely collected genotyping data, and assessed whether superinfection contributed to increased drug resistance in a large European cohort of viremic, drug treated patients. Methods We used sequence data from routine genotypic tests spanning the protease and partial reverse transcriptase regions in the Virolab and EuResist databases that collated data from five European countries. Superinfection was indicated when sequences of a patient failed to cluster together in phylogenetic trees constructed with selected sets of control sequences. A subset of the indicated cases was validated by re-sequencing pol and env regions from the original samples. Results 4425 patients had at least two sequences in the database, with a total of 13816 distinct sequence entries (of which 86% belonged to subtype B). We identified 107 patients with phylogenetic evidence for superinfection. In 14 of these cases, we analyzed newly amplified sequences from the original samples for validation purposes: only 2 cases were verified as superinfections in the repeated analyses, the other 12 cases turned out to involve sample or sequence misidentification. Resistance to drugs used at the time of strain replacement did not change in these two patients. A third case could not be validated by re-sequencing, but was supported as superinfection by an intermediate sequence with high degenerate base pair count within the time frame of strain switching. Drug resistance increased in this single patient. Conclusions Routine genotyping data are informative for the detection of HIV superinfection; however, most cases of non-monophyletic clustering in patient phylogenies arise from sample or sequence mix-up rather than from superinfection, which emphasizes the importance of validation. Non-transient superinfection was rare in our mainly treatment experienced cohort, and we found a single case of possible transmitted drug resistance by this route. We therefore conclude that in our large cohort, superinfection with drug resistant HIV did not compromise the efficiency of antiretroviral treatment.

Background The HIV-1 genome is subject to pressures that target the virus resulting in escape and adaptation. On the other hand, there is a requirement for sequence conservation because of functional and structural constraints. Mapping the sites of selective pressure and conservation on the viral genome generates a reference for understanding the limits to viral escape, and can serve as a template for the discovery of sites of genetic conflict with known or unknown host proteins. Results To build a thorough evolutionary, functional and structural map of the HIV-1 genome, complete subtype B sequences were obtained from the Los Alamos database. We mapped sites under positive selective pressure, amino acid conservation, protein and RNA structure, overlapping coding frames, CD8 T cell, CD4 T cell and antibody epitopes, and sites enriched in AG and AA dinucleotide motives. Globally, 33% of amino acid positions were found to be variable and 12% of the genome was under positive selection. Because interrelated constraining and diversifying forces shape the viral genome, we included the variables from both classes of pressure in a multivariate model to predict conservation or positive selection: structured RNA and α-helix domains independently predicted conservation while CD4 T cell and antibody epitopes were associated with positive selection. Conclusions The global map of the viral genome contains positive selected sites that are not in canonical CD8 T cell, CD4 T cell or antibody epitopes; thus, it identifies a class of residues that may be targeted by other host selective pressures. Overall, RNA structure represents the strongest determinant of HIV-1 conservation. These data can inform the combined analysis of host and viral genetic information.

We evaluated the impact of coding variation on HIV control by exome sequencing with emphasis on known HIV host dependency factors. Outside of the MHC region, exonic variants with large effect sizes are not a major contributor to HIV control., Background Previous genetic association studies of human immunodeficiency virus-1 (HIV-1) progression have focused on common human genetic variation ascertained through genome-wide genotyping. Methods We sought to systematically assess the full spectrum of functional variation in protein coding gene regions on HIV-1 progression through exome sequencing of 1327 individuals. Genetic variants were tested individually and in aggregate across genes and gene sets for an influence on HIV-1 viral load. Results Multiple single variants within the major histocompatibility complex (MHC) region were observed to be strongly associated with HIV-1 outcome, consistent with the known impact of classical HLA alleles. However, no single variant or gene located outside of the MHC region was significantly associated with HIV progression. Set-based association testing focusing on genes identified as being essential for HIV replication in genome-wide small interfering RNA (siRNA) and clustered regularly interspaced short palindromic repeats (CRISPR) studies did not reveal any novel associations. Conclusions These results suggest that exonic variants with large effect sizes are unlikely to have a major contribution to host control of HIV infection.

Significance Increasing numbers of human genome population sequences provide new detail on the genetic variability of the human proteome. It is possible to identify proteins that are depleted in genetic variation, and this approach can now be extended to the identification of 3D features and structures that are uniquely intolerant to variation. We speculated that 3D features that are intolerant to variation correspond to privileged functional domains of the protein. We approached this question with sequence data nearly 140,000 individuals with modeling of >8,500 protein structures. In keeping with the hypothesis, structural predictions correlated with experimental functional readouts. We believe that information derived from human variation complements other metrics at the structural level and can serve to inform drug development., Sequence variation data of the human proteome can be used to analyze 3D protein structures to derive functional insights. We used genetic variant data from nearly 140,000 individuals to analyze 3D positional conservation in 4,715 proteins and 3,951 homology models using 860,292 missense and 465,886 synonymous variants. Sixty percent of protein structures harbor at least one intolerant 3D site as defined by significant depletion of observed over expected missense variation. Structural intolerance data correlated with deep mutational scanning functional readouts for PPARG, MAPK1/ERK2, UBE2I, SUMO1, PTEN, CALM1, CALM2, and TPK1 and with shallow mutagenesis data for 1,026 proteins. The 3D structural intolerance analysis revealed different features for ligand binding pockets and orthosteric and allosteric sites. Large-scale data on human genetic variation support a definition of functional 3D sites proteome-wide.

HIV latency is a major obstacle to curing infection. Current strategies to eradicate HIV aim at increasing transcription of the latent provirus. In the present study we observed that latently infected CD4+ T cells from HIV-infected individuals failed to produce viral particles upon ex vivo exposure to SAHA (vorinostat), despite effective inhibition of histone deacetylases. To identify steps that were not susceptible to the action of SAHA or other latency reverting agents, we used a primary CD4+ T cell model, joint host and viral RNA sequencing, and a viral-encoded reporter. This model served to investigate the characteristics of latently infected cells, the dynamics of HIV latency, and the process of reactivation induced by various stimuli. During latency, we observed persistence of viral transcripts but only limited viral translation. Similarly, the reactivating agents SAHA and disulfiram successfully increased viral transcription, but failed to effectively enhance viral translation, mirroring the ex vivo data. This study highlights the importance of post-transcriptional blocks as one mechanism leading to HIV latency that needs to be relieved in order to purge the viral reservoir., Author Summary HIV-infected individuals must receive lifelong antiviral therapy because treatment discontinuation generally results in rapid viral rebound. The field has identified a state of latency at the level of transcription of the integrated provirus as the major mechanism of persistence. A number of drugs are now tested that aim at inducing viral transcription as a step to purge the reservoir. The assessment of viral production in cells from HIV-infected individuals with optimal viral suppression revealed the failure of SAHA/vorinostat to efficiently generate viral particle production. To further investigate and characterize the process of latency at the transcriptome level, and the response to SAHA as well as various reactivating agents, we use a model of primary CD4+ lymphocytes. The main observation from this study is that viral transcripts persist during latency, and that the accumulation of viral transcripts does not result in efficient viral protein expression upon reactivation with agents such as SAHA. Our data suggest that post-transcriptional blocks also contribute to latency, and that additional strategies need to be explored to efficiently purge the viral reservoir.