Acute and Postacute COVID-19 Outcomes Among Immunologically Naive Adults During Delta vs Omicron Waves.

Importance: The US arrival of the Omicron variant led to a rapid increase in SARS-CoV-2 infections. While numerous studies report characteristics of Omicron infections among vaccinated individuals or persons with previous infection, comprehensive data describing infections among adults who are immunologically naive are lacking. Objectives: To examine COVID-19 acute and postacute clinical outcomes among a well-characterized cohort of unvaccinated and previously uninfected adults who contracted SARS-CoV-2 during the Omicron (BA.1/BA.2) surge, and to compare outcomes with infections that occurred during the Delta wave. Design, Setting, and Participants: This prospective multisite cohort study included community-dwelling adults undergoing high-resolution symptom and virologic monitoring in 8 US states between June 2021 and September 2022. Unvaccinated adults aged 30 to less than 65 years without an immunological history of SARS-CoV-2 who were at high risk of infection were recruited. Participants were followed for up to 48 weeks, submitting regular COVID-19 symptom surveys and nasal swabs for SARS-CoV-2 polymerase chain reaction (PCR) testing. Data were analyzed from May to October 2022. Exposures: Omicron (BA.1/BA.2 lineages) vs Delta SARS-CoV-2 infection, defined as a positive PCR test result that occurred during a period when the variant represented at least 50% of circulating SARS-CoV-2 variants in the participant's geographic region. Main Outcomes and Measure(s): The main outcomes examined were the prevalence and severity of acute (≤28 days after onset) and postacute (≥5 weeks after onset) symptoms. Results: Among 274 participants who were immunologically naive (mean [SD] age, 49 [9.7] years; 186 [68%] female; 19 [7%] Hispanic participants; 242 [88%] White participants), 166 (61%) contracted SARS-CoV-2. Of these, 137 infections (83%) occurred during the Omicron-predominant period and 29 infections (17%) occurred during the Delta-predominant period. Asymptomatic infections occurred among 7% (95% CI, 3%-12%) of Omicron-wave infections and 0% (95% CI, 0%-12%) of Delta-wave infections. Health care use among individuals with Omicron-wave infections was 79% (95% CI, 43%-92%) lower relative to individuals with Delta-wave infections (P = .001). Compared with individuals infected during the Delta wave, individuals infected during the Omicron wave also experienced a 56% (95% CI, 26%-74%, P = .004) relative reduction in the risk of postacute symptoms and a 79% (95% CI, 54%-91%, P < .001) relative reduction in the rate of postacute symptoms. Conclusions and Relevance: These findings suggest that among adults who were previously immunologically naive, few Omicron-wave (BA.1/BA.2) and Delta-wave infections were asymptomatic. Compared with individuals with Delta-wave infections, individuals with Omicron-wave infections were less likely to seek health care and experience postacute symptoms.

Acute and Post-Acute COVID-19 Outcomes Among Immunologically Naïve Adults During Delta Versus Omicron Waves.

Importance: The U.S. arrival of the Omicron variant led to a rapid increase in SARS-CoV-2 infections. While numerous studies report characteristics of Omicron infections among vaccinated individuals and/or persons with a prior history of infection, comprehensive data describing infections among immunologically naïve adults is lacking. Objective: To examine COVID-19 acute and post-acute clinical outcomes among a well-characterized cohort of unvaccinated and previously uninfected adults who contracted SARS-CoV-2 during the Omicron (BA.1/BA.2) surge, and to compare outcomes with infections that occurred during the Delta wave. Design: A prospective cohort undergoing high-resolution symptom and virologic monitoring between June 2021 and September 2022. Setting: Multisite recruitment of community-dwelling adults in 8 U.S. states. Participants: Healthy, unvaccinated adults between 30 to 64 years of age without an immunological history of SARS-CoV-2 who were at high-risk of infection were recruited. Participants were followed for up to 48 weeks, submitting regular COVID-19 symptom surveys and nasal swabs for SARS-CoV-2 PCR testing. Exposures: Omicron (BA.1/BA.2 lineages) versus Delta SARS-CoV-2 infection, defined as a positive PCR that occurred during a period when the variant represented ≥50% of circulating SARS-CoV-2 variants in the participant's geographic region. Main Outcomes and Measures: The main outcomes examined were the prevalence and severity of acute (≤28 days post-onset) and post-acute (≥5 weeks post-onset) symptoms. Results: Among 274 immunologically naïve participants, 166 (61%) contracted SARS-CoV-2. Of these, 137 (83%) and 29 (17%) infections occurred during the Omicron- and Delta-predominant periods, respectively. Asymptomatic infections occurred among 6.7% (95% CI: 3.1%, 12.3%) of Omicron cases and 0.0% (95% CI: 0.0%, 11.9%) of Delta cases. Healthcare utilization among Omicron cases was 79% (95% CI: 43%, 92%, P =0.001) lower relative to Delta cases. Relative to Delta, Omicron infections also experienced a 56% (95% CI: 26%, 74%, P =0.004) and 79% (95% CI: 54%, 91%, P <0.001) reduction in the risk and rate of post-acute symptoms, respectively. Conclusions and Relevance: These findings suggest that among previously immunologically naïve adults, few Omicron (BA.1/BA.2) and Delta infections are asymptomatic, and relative to Delta, Omicron infections were less likely to seek healthcare and experience post-acute symptoms.

Ranking of non-coding pathogenic variants and putative essential regions of the human genome.

A gene is considered essential if loss of function results in loss of viability, fitness or in disease. This concept is well established for coding genes; however, non-coding regions are thought less likely to be determinants of critical functions. Here we train a machine learning model using functional, mutational and structural features, including new genome essentiality metrics, 3D genome organization and enhancer reporter data to identify deleterious variants in non-coding regions. We assess the model for functional correlates by using data from tiling-deletion-based and CRISPR interference screens of activity of cis-regulatory elements in over 3 Mb of genome sequence. Finally, we explore two user cases that involve indels and the disruption of enhancers associated with a developmental disease. We rank variants in the non-coding genome according to their predicted deleteriousness. The model prioritizes non-coding regions associated with regulation of important genes and with cell viability, an in vitro surrogate of essentiality.

Assembly of the 373k gene space of the polyploid sugarcane genome reveals reservoirs of functional diversity in the world's leading biomass crop.

BACKGROUND: Sugarcane cultivars are polyploid interspecific hybrids of giant genomes, typically with 10-13 sets of chromosomes from 2 Saccharum species. The ploidy, hybridity, and size of the genome, estimated to have >10 Gb, pose a challenge for sequencing. RESULTS: Here we present a gene space assembly of SP80-3280, including 373,869 putative genes and their potential regulatory regions. The alignment of single-copy genes in diploid grasses to the putative genes indicates that we could resolve 2-6 (up to 15) putative homo(eo)logs that are 99.1% identical within their coding sequences. Dissimilarities increase in their regulatory regions, and gene promoter analysis shows differences in regulatory elements within gene families that are expressed in a species-specific manner. We exemplify these differences for sucrose synthase (SuSy) and phenylalanine ammonia-lyase (PAL), 2 gene families central to carbon partitioning. SP80-3280 has particular regulatory elements involved in sucrose synthesis not found in the ancestor Saccharum spontaneum. PAL regulatory elements are found in co-expressed genes related to fiber synthesis within gene networks defined during plant growth and maturation. Comparison with sorghum reveals predominantly bi-allelic variations in sugarcane, consistent with the formation of 2 "subgenomes" after their divergence ∼3.8-4.6 million years ago and reveals single-nucleotide variants that may underlie their differences. CONCLUSIONS: This assembly represents a large step towards a whole-genome assembly of a commercial sugarcane cultivar. It includes a rich diversity of genes and homo(eo)logous resolution for a representative fraction of the gene space, relevant to improve biomass and food production.

Assembly of the 373k gene space of the polyploid sugarcane genome reveals reservoirs of functional diversity in the world's leading biomass crop

Background: Sugarcane cultivars are polyploid interspecific hybrids of giant genomes, typically with 10–13 sets of chromosomes from 2 Saccharum species. The ploidy, hybridity, and size of the genome, estimated to have >10 Gb, pose a challenge for sequencing. Results: Here we present a gene space assembly of SP80-3280, including 373,869 putative genes and their potential regulatory regions. The alignment of single-copy genes in diploid grasses to the putative genes indicates that we could resolve 2–6 (up to 15) putative homo(eo)logs that are 99.1% identical within their coding sequences. Dissimilarities increase in their regulatory regions, and gene promoter analysis shows differences in regulatory elements within gene families that are expressed in a species-specific manner. We exemplify these differences for sucrose synthase (SuSy) and phenylalanine ammonia-lyase (PAL), 2 gene families central to carbon partitioning. SP80-3280 has particular regulatory elements involved in sucrose synthesis not found in the ancestor Saccharum spontaneum. PAL regulatory elements are found in co-expressed genes related to fiber synthesis within gene networks defined during plant growth and maturation. Comparison with sorghum reveals predominantly bi-allelic variations in sugarcane, consistent with the formation of 2 "subgenomes" after their divergence ~3.8–4.6 million years ago and reveals single-nucleotide variants that may underlie their differences. Conclusions: This assembly represents a large step towards a whole-genome assembly of a commercial sugarcane cultivar. It includes a rich diversity of genes and homo(eo)logous resolution for a representative fraction of the gene space, relevant to improve biomass and food production.

Assembly of the 373k gene space of the polyploid sugarcane genome reveals reservoirs of functional diversity in the world's leading biomass crop

Background: Sugarcane cultivars are polyploid interspecific hybrids of giant genomes, typically with 10–13 sets of chromosomes from 2 Saccharum species. The ploidy, hybridity, and size of the genome, estimated to have >10 Gb, pose a challenge for sequencing. Results: Here we present a gene space assembly of SP80-3280, including 373,869 putative genes and their potential regulatory regions. The alignment of single-copy genes in diploid grasses to the putative genes indicates that we could resolve 2–6 (up to 15) putative homo(eo)logs that are 99.1% identical within their coding sequences. Dissimilarities increase in their regulatory regions, and gene promoter analysis shows differences in regulatory elements within gene families that are expressed in a species-specific manner. We exemplify these differences for sucrose synthase (SuSy) and phenylalanine ammonia-lyase (PAL), 2 gene families central to carbon partitioning. SP80-3280 has particular regulatory elements involved in sucrose synthesis not found in the ancestor Saccharum spontaneum. PAL regulatory elements are found in co-expressed genes related to fiber synthesis within gene networks defined during plant growth and maturation. Comparison with sorghum reveals predominantly bi-allelic variations in sugarcane, consistent with the formation of 2 "subgenomes" after their divergence ~3.8–4.6 million years ago and reveals single-nucleotide variants that may underlie their differences. Conclusions: This assembly represents a large step towards a whole-genome assembly of a commercial sugarcane cultivar. It includes a rich diversity of genes and homo(eo)logous resolution for a representative fraction of the gene space, relevant to improve biomass and food production.

Ensembles of Lasso Screening Rules.

In order to solve large-scale lasso problems, screening algorithms have been developed that discard features with zero coefficients based on a computationally efficient screening rule. Most existing screening rules were developed from a spherical constraint and half-space constraints on a dual optimal solution. However, existing rules admit at most two half-space constraints due to the computational cost incurred by the half-spaces, even though additional constraints may be useful to discard more features. In this paper, we present AdaScreen, an adaptive lasso screening rule ensemble, which allows to combine any one sphere with multiple half-space constraints on a dual optimal solution. Thanks to geometrical considerations that lead to a simple closed form solution for AdaScreen, we can incorporate multiple half-space constraints at small computational cost. In our experiments, we show that AdaScreen with multiple half-space constraints simultaneously improves screening performance and speeds up lasso solvers.

Genetic variants associated with physical performance and anthropometry in old age: a genome-wide association study in the ilSIRENTE cohort.

Unraveling the complexity of aging is crucial for understanding its mechanisms and its role as a risk factor for most chronic conditions. Advancements marked by genome-wide association studies (GWASs) have sparked interest in gene cataloguing in the context of aging and age-related conditions. Here, we used GWAS to explore whether single nucleotide polymorphisms (SNPs) were associated with functional and anthropometric parameters in a cohort of old community-dwellers enrolled in the ilSIRENTE study. Analyses were carried out in men and women aged 80+ years enrolled in the ilSIRENTE study (n = 286) and replicated in the inCHIANTI study (n = 1055). Genotyping was accomplished on Infinium Human610-QUAD version 1. In the ilSIRENTE population, genetic variants in ZNF295 and C2CD2 (rs928874 and rs1788355) on chromosome 21q22.3, were significantly associated with the 4-meter gait speed (rs928874, p = 5.61 × 10-8; rs1788355, p = 5.73 × 10-8). This association was not replicated in the inCHIANTI population. Our findings suggest that specific SNPs may be associated with a key measure of physical performance in older adults. GWASs using larger samples are needed to confirm these preliminary results to enhance our comprehension of complex age-associated phenomena.

Profiling of Short-Tandem-Repeat Disease Alleles in 12,632 Human Whole Genomes.

Short tandem repeats (STRs) are hyper-mutable sequences in the human genome. They are often used in forensics and population genetics and are also the underlying cause of many genetic diseases. There are challenges associated with accurately determining the length polymorphism of STR loci in the genome by next-generation sequencing (NGS). In particular, accurate detection of pathological STR expansion is limited by the sequence read length during whole-genome analysis. We developed TREDPARSE, a software package that incorporates various cues from read alignment and paired-end distance distribution, as well as a sequence stutter model, in a probabilistic framework to infer repeat sizes for genetic loci, and we used this software to infer repeat sizes for 30 known disease loci. Using simulated data, we show that TREDPARSE outperforms other available software. We sampled the full genome sequences of 12,632 individuals to an average read depth of approximately 30× to 40× with Illumina HiSeq X. We identified 138 individuals with risk alleles at 15 STR disease loci. We validated a representative subset of the samples (n = 19) by Sanger and by Oxford Nanopore sequencing. Additionally, we validated the STR calls against known allele sizes in a set of GeT-RM reference cell-line materials (n = 6). Several STR loci that are entirely guanine or cytosines (G or C) have insufficient read evidence for inference and therefore could not be assayed precisely by TREDPARSE. TREDPARSE extends the limit of STR size detection beyond the physical sequence read length. This extension is critical because many of the disease risk cutoffs are close to or beyond the short sequence read length of 100 to 150 bases.

Linear mixed model for heritability estimation that explicitly addresses environmental variation.

The linear mixed model (LMM) is now routinely used to estimate heritability. Unfortunately, as we demonstrate, LMM estimates of heritability can be inflated when using a standard model. To help reduce this inflation, we used a more general LMM with two random effects-one based on genomic variants and one based on easily measured spatial location as a proxy for environmental effects. We investigated this approach with simulated data and with data from a Uganda cohort of 4,778 individuals for 34 phenotypes including anthropometric indices, blood factors, glycemic control, blood pressure, lipid tests, and liver function tests. For the genomic random effect, we used identity-by-descent estimates from accurately phased genome-wide data. For the environmental random effect, we constructed a covariance matrix based on a Gaussian radial basis function. Across the simulated and Ugandan data, narrow-sense heritability estimates were lower using the more general model. Thus, our approach addresses, in part, the issue of "missing heritability" in the sense that much of the heritability previously thought to be missing was fictional. Software is available at https://github.com/MicrosoftGenomics/FaST-LMM.

Impact of pre-adapted HIV transmission.

Human leukocyte antigen class I (HLA)-restricted CD8(+) T lymphocyte (CTL) responses are crucial to HIV-1 control. Although HIV can evade these responses, the longer-term impact of viral escape mutants remains unclear, as these variants can also reduce intrinsic viral fitness. To address this, we here developed a metric to determine the degree of HIV adaptation to an HLA profile. We demonstrate that transmission of viruses that are pre-adapted to the HLA molecules expressed in the recipient is associated with impaired immunogenicity, elevated viral load and accelerated CD4(+) T cell decline. Furthermore, the extent of pre-adaptation among circulating viruses explains much of the variation in outcomes attributed to the expression of certain HLA alleles. Thus, viral pre-adaptation exploits 'holes' in the immune response. Accounting for these holes may be key for vaccine strategies seeking to elicit functional responses from viral variants, and to HIV cure strategies that require broad CTL responses to achieve successful eradication of HIV reservoirs.

Anti-hepatitis C virus T-cell immunity in the context of multiple exposures to the virus.

Characterisation of Hepatitis C virus (HCV)-specific CD8+ T-cell responses in the context of multiple HCV exposures is critical to identify broadly protective immune responses necessary for an effective HCV vaccine against the different HCV genotypes. However, host and viral genetic diversity complicates vaccine development. To compensate for the observed variation in circulating autologous viruses and host molecules that restrict antigen presentation (human leucocyte antigens; HLA), this study used a reverse genomics approach that identified sites of viral adaptation to HLA-restricted T-cell immune pressure to predict genotype-specific HCV CD8+ T-cell targets. Peptides representing these putative HCV CD8+ T-cell targets, and their adapted form, were used in individualised IFN-γ ELISpot assays to screen for HCV-specific T-cell responses in 133 HCV-seropositive subjects with high-risk of multiple HCV exposures. The data obtained from this study i) confirmed that genetic studies of viral evolution is an effective approach to detect novel in vivo HCV T-cell targets, ii) showed that HCV-specific T-cell epitopes can be recognised in their adapted form and would not have been detected using wild-type peptides and iii) showed that HCV-specific T-cell (but not antibody) responses against alternate genotypes in chronic HCV-infected subjects are readily found, implying clearance of previous alternate genotype infection. In summary, HCV adaptation to HLA Class I-restricted T-cell responses plays a central role in anti-HCV immunity and multiple HCV genotype exposure is highly prevalent in at-risk exposure populations, which are important considerations for future vaccine design.

ConPADE: genome assembly ploidy estimation from next-generation sequencing data.

As a result of improvements in genome assembly algorithms and the ever decreasing costs of high-throughput sequencing technologies, new high quality draft genome sequences are published at a striking pace. With well-established methodologies, larger and more complex genomes are being tackled, including polyploid plant genomes. Given the similarity between multiple copies of a basic genome in polyploid individuals, assembly of such data usually results in collapsed contigs that represent a variable number of homoeologous genomic regions. Unfortunately, such collapse is often not ideal, as keeping contigs separate can lead both to improved assembly and also insights about how haplotypes influence phenotype. Here, we describe a first step in avoiding inappropriate collapse during assembly. In particular, we describe ConPADE (Contig Ploidy and Allele Dosage Estimation), a probabilistic method that estimates the ploidy of any given contig/scaffold based on its allele proportions. In the process, we report findings regarding errors in sequencing. The method can be used for whole genome shotgun (WGS) sequencing data. We also show applicability of the method for variant calling and allele dosage estimation. Results for simulated and real datasets are discussed and provide evidence that ConPADE performs well as long as enough sequencing coverage is available, or the true contig ploidy is low. We show that ConPADE may also be used for related applications, such as the identification of duplicated genes in fragmented assemblies, although refinements are needed.

Accurate liability estimation improves power in ascertained case-control studies.

Linear mixed models (LMMs) have emerged as the method of choice for confounded genome-wide association studies. However, the performance of LMMs in nonrandomly ascertained case-control studies deteriorates with increasing sample size. We propose a framework called LEAP (liability estimator as a phenotype; https://github.com/omerwe/LEAP) that tests for association with estimated latent values corresponding to severity of phenotype, and we demonstrate that this can lead to a substantial power increase.

Immune screening identifies novel T cell targets encoded by antisense reading frames of HIV-1.

Cytotoxic-T lymphocyte (CTL) responses to epitopes in alternative HIV reading frames have been reported. However, the extent of CTL responses to putative proteins encoded in antisense reading frames is unknown. Using sequence alignments and computational approaches, we here predict five potential antisense HIV proteins and characterize common CTL responses against them. Results suggest that antisense-derived sequences are commonly transcribed and translated and could encode functional proteins that contain important targets of anti-HIV cellular immunity.

Further improvements to linear mixed models for genome-wide association studies.

We examine improvements to the linear mixed model (LMM) that better correct for population structure and family relatedness in genome-wide association studies (GWAS). LMMs rely on the estimation of a genetic similarity matrix (GSM), which encodes the pairwise similarity between every two individuals in a cohort. These similarities are estimated from single nucleotide polymorphisms (SNPs) or other genetic variants. Traditionally, all available SNPs are used to estimate the GSM. In empirical studies across a wide range of synthetic and real data, we find that modifications to this approach improve GWAS performance as measured by type I error control and power. Specifically, when only population structure is present, a GSM constructed from SNPs that well predict the phenotype in combination with principal components as covariates controls type I error and yields more power than the traditional LMM. In any setting, with or without population structure or family relatedness, a GSM consisting of a mixture of two component GSMs, one constructed from all SNPs and another constructed from SNPs that well predict the phenotype again controls type I error and yields more power than the traditional LMM. Software implementing these improvements and the experimental comparisons are available at http://microsoft.com/science.

Emergence of individual HIV-specific CD8 T cell responses during primary HIV-1 infection can determine long-term disease outcome.

UNLABELLED: Events during primary HIV-1 infection have been shown to be critical for the subsequent rate of disease progression. Early control of viral replication, resolution of clinical symptoms and development of a viral set point have been associated with the emergence of HIV-specific CD8 T cell responses. Here we assessed which particular HIV-specific CD8 T cell responses contribute to long-term control of HIV-1. A total of 620 individuals with primary HIV-1 infection were screened by gamma interferon (IFN-γ) enzyme-linked immunospot (ELISPOT) assay for HLA class I-restricted, epitope-specific CD8 T cell responses using optimally defined epitopes approximately 2 months after initial presentation. The cohort was predominantly male (97%) and Caucasian (83%) (Fiebig stages II/III [n = 157], IV [n = 64], V [n = 286], and VI [n = 88] and Fiebig stage not determined [n = 25]). Longitudinal viral loads, CD4 count, and time to ART were collected for all patients. We observed strong associations between viral load at baseline (initial viremia) and the established early viral set points (P < 0.0001). Both were significantly associated with HLA class I genotypes (P = 0.0009). While neither the breadth nor the magnitude of HIV-specific CD8 T cell responses showed an influence on the early viral set point, a broader HIV-specific CD8 T cell response targeting epitopes within HIV-1 Gag during primary HIV-1 infection was associated with slower disease progression. Moreover, the induction of certain HIV-specific CD8 T cell responses--but not others--significantly influenced the time to ART initiation. Individual epitope-specific CD8 T cell responses contribute significantly to HIV-1 disease control, demonstrating that the specificity of the initial HIV-specific CD8 T cell response rather than the restricting HLA class I molecule alone is a critical determinant of antiviral function. IMPORTANCE: Understanding which factors are involved in the control of HIV-1 infection is critical for the design of therapeutic strategies for patients living with HIV/AIDS. Here, using a cohort of over 600 individuals with acute and early HIV-1 infection, we assessed in unprecedented detail the individual contribution of epitope-specific CD8 T cell responses directed against HIV-1 to control of viremia and their impact on the overall course of disease progression.

HIV control is mediated in part by CD8+ T-cell targeting of specific epitopes.

UNLABELLED: We investigated the hypothesis that the correlation between the class I HLA types of an individual and whether that individual spontaneously controls HIV-1 is mediated by the targeting of specific epitopes by CD8(+) T cells. By measuring gamma interferon enzyme-linked immunosorbent spot (ELISPOT) assay responses to a panel of 257 optimally defined epitopes in 341 untreated HIV-infected persons, including persons who spontaneously control viremia, we found that the correlation between HLA types and control is mediated by the targeting of specific epitopes. Moreover, we performed a graphical model-based analysis that suggested that the targeting of specific epitopes is a cause of such control--that is, some epitopes are protective rather than merely associated with control--and identified eight epitopes that are significantly protective. In addition, we use an in silico analysis to identify protein regions where mutations are likely to affect the stability of a protein, and we found that the protective epitopes identified by the ELISPOT analysis correspond almost perfectly to such regions. This in silico analysis thus suggests a possible mechanism for control and could be used to identify protective epitopes that are not often targeted in natural infection but that may be potentially useful in a vaccine. Our analyses thus argue for the inclusion (and exclusion) of specific epitopes in an HIV vaccine. IMPORTANCE: Some individuals naturally control HIV replication in the absence of antiretroviral therapy, and this ability to control is strongly correlated with the HLA class I alleles that they express. Here, in a large-scale experimental study, we provide evidence that this correlation is mediated largely by the targeting of specific CD8(+) T-cell epitopes, and we identify eight epitopes that are likely to cause control. In addition, we provide an in silico analysis indicating that control occurs because mutations within these epitopes change the stability of the protein structures. This in silico analysis also identified additional epitopes that are not typically targeted in natural infection but may lead to control when included in a vaccine, provided that other epitopes that would otherwise distract the immune system from targeting them are excluded from the vaccine.

HIV transmission. Selection bias at the heterosexual HIV-1 transmission bottleneck.

Heterosexual transmission of HIV-1 typically results in one genetic variant establishing systemic infection. We compared, for 137 linked transmission pairs, the amino acid sequences encoded by non-envelope genes of viruses in both partners and demonstrate a selection bias for transmission of residues that are predicted to confer increased in vivo fitness on viruses in the newly infected, immunologically naïve recipient. Although tempered by transmission risk factors, such as donor viral load, genital inflammation, and recipient gender, this selection bias provides an overall transmission advantage for viral quasispecies that are dominated by viruses with high in vivo fitness. Thus, preventative or therapeutic approaches that even marginally reduce viral fitness may lower the overall transmission rates and offer long-term benefits even upon successful transmission.

Greater power and computational efficiency for kernel-based association testing of sets of genetic variants.

MOTIVATION: Set-based variance component tests have been identified as a way to increase power in association studies by aggregating weak individual effects. However, the choice of test statistic has been largely ignored even though it may play an important role in obtaining optimal power. We compared a standard statistical test-a score test-with a recently developed likelihood ratio (LR) test. Further, when correction for hidden structure is needed, or gene-gene interactions are sought, state-of-the art algorithms for both the score and LR tests can be computationally impractical. Thus we develop new computationally efficient methods. RESULTS: After reviewing theoretical differences in performance between the score and LR tests, we find empirically on real data that the LR test generally has more power. In particular, on 15 of 17 real datasets, the LR test yielded at least as many associations as the score test-up to 23 more associations-whereas the score test yielded at most one more association than the LR test in the two remaining datasets. On synthetic data, we find that the LR test yielded up to 12% more associations, consistent with our results on real data, but also observe a regime of extremely small signal where the score test yielded up to 25% more associations than the LR test, consistent with theory. Finally, our computational speedups now enable (i) efficient LR testing when the background kernel is full rank, and (ii) efficient score testing when the background kernel changes with each test, as for gene-gene interaction tests. The latter yielded a factor of 2000 speedup on a cohort of size 13 500. AVAILABILITY: Software available at http://research.microsoft.com/en-us/um/redmond/projects/MSCompBio/Fastlmm/. CONTACT: heckerma@microsoft.com SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.