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.

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.

Epigenome-wide association studies without the need for cell-type composition.

In epigenome-wide association studies, cell-type composition often differs between cases and controls, yielding associations that simply tag cell type rather than reveal fundamental biology. Current solutions require actual or estimated cell-type composition--information not easily obtainable for many samples of interest. We propose a method, FaST-LMM-EWASher, that automatically corrects for cell-type composition without the need for explicit knowledge of it, and then validate our method by comparison with the state-of-the-art approach. Corresponding software is available from http://www.microsoft.com/science/.

HIV-1 adaptation to NK-cell-mediated immune pressure.

Natural killer (NK) cells have an important role in the control of viral infections, recognizing virally infected cells through a variety of activating and inhibitory receptors. Epidemiological and functional studies have recently suggested that NK cells can also contribute to the control of HIV-1 infection through recognition of virally infected cells by both activating and inhibitory killer immunoglobulin-like receptors (KIRs). However, it remains unknown whether NK cells can directly mediate antiviral immune pressure in vivo in humans. Here we describe KIR-associated amino-acid polymorphisms in the HIV-1 sequence of chronically infected individuals, on a population level. We show that these KIR-associated HIV-1 sequence polymorphisms can enhance the binding of inhibitory KIRs to HIV-1-infected CD4(+) T cells, and reduce the antiviral activity of KIR-positive NK cells. These data demonstrate that KIR-positive NK cells can place immunological pressure on HIV-1, and that the virus can evade such NK-cell-mediated immune pressure by selecting for sequence polymorphisms, as was previously described for virus-specific T cells and neutralizing antibodies. NK cells might therefore have a previously underappreciated role in contributing to viral evolution.

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.

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.

Increased sequence coverage through combined targeting of variant and conserved epitopes correlates with control of HIV replication.

A major challenge in the development of an HIV vaccine is that of contending with the extensive sequence variability found in circulating viruses. Induction of HIV-specific T-cell responses targeting conserved regions and induction of HIV-specific T-cell responses recognizing a high number of epitope variants have both been proposed as strategies to overcome this challenge. We addressed the ability of cytotoxic T lymphocytes from 30 untreated HIV-infected subjects with and without control of virus replication to recognize all clade B Gag sequence variants encoded by at least 5% of the sequences in the Los Alamos National Laboratory HIV database (1,300 peptides) using gamma interferon and interleukin-2 (IFN-γ/IL-2) FluoroSpot analysis. While targeting of conserved regions was similar in the two groups (P = 0.47), we found that subjects with control of virus replication demonstrated marginally lower recognition of Gag epitope variants than subjects with normal progression (P = 0.05). In viremic controllers and progressors, we found variant recognition to be associated with viral load (r = 0.62, P = 0.001). Interestingly, we show that increased overall sequence coverage, defined as the overall proportion of HIV database sequences targeted through the Gag-specific repertoire, is inversely associated with viral load (r = -0.38, P = 0.03). Furthermore, we found that sequence coverage, but not variant recognition, correlated with increased recognition of a panel of clade B HIV founder viruses (r = 0.50, P = 0.004). We propose sequence coverage by HIV Gag-specific immune responses as a possible correlate of protection that may contribute to control of virus replication. Additionally, sequence coverage serves as a valuable measure by which to evaluate the protective potential of future vaccination strategies.

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.

Literome: PubMed-scale genomic knowledge base in the cloud.

MOTIVATION: Advances in sequencing technology have led to an exponential growth of genomics data, yet it remains a formidable challenge to interpret such data for identifying disease genes and drug targets. There has been increasing interest in adopting a systems approach that incorporates prior knowledge such as gene networks and genotype-phenotype associations. The majority of such knowledge resides in text such as journal publications, which has been undergoing its own exponential growth. It has thus become a significant bottleneck to identify relevant knowledge for genomic interpretation as well as to keep up with new genomics findings. RESULTS: In the Literome project, we have developed an automatic curation system to extract genomic knowledge from PubMed articles and made this knowledge available in the cloud with a Web site to facilitate browsing, searching and reasoning. Currently, Literome focuses on two types of knowledge most pertinent to genomic medicine: directed genic interactions such as pathways and genotype-phenotype associations. Users can search for interacting genes and the nature of the interactions, as well as diseases and drugs associated with a single nucleotide polymorphism or gene. Users can also search for indirect connections between two entities, e.g. a gene and a disease might be linked because an interacting gene is associated with a related disease. AVAILABILITY AND IMPLEMENTATION: Literome is freely available at literome.azurewebsites.net. Download for non-commercial use is available via Web services.

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.

High-dimensional immunomonitoring models of HIV-1-specific CD8 T-cell responses accurately identify subjects achieving spontaneous viral control.

UNLABELLED: The development of immunomonitoring models to determine HIV-1 vaccine efficacy is a major challenge. Studies suggest that HIV-1­specific CD8 T cells play a critical role in subjects achieving spontaneous viral control (HIV-1 controllers) and that they will be important in immune interventions. However, no single CD8 T-cell function is uniquely associated with controller status and the heterogeneity of responses targeting different epitopes further complicates the discovery of determinants of protective immunity. In the present study, we describe immunomonitoring models integrating multiple functions of epitope-specific CD8 T cells that distinguish controllers from subjects with treated or untreated progressive infection. Models integrating higher numbers of variables and trained with the least absolute shrinkage and selection operator (LASSO) variant of logistic regression and 10-fold cross-validation produce "diagnostic tests" that display an excellent capacity to delineate subject categories. The test accuracy reaches 75% area under the receiving operating characteristic curve in cohorts matched for prevalence of protective alleles. Linear mixed-effects model analyses show that the proliferative capacity, cytokine production, and kinetics of cytokine secretion are associated with HIV-1 control. Although proliferative capacity is the strongest single discriminant, integrated modeling of different dimensions of data leverages individual associations. This strategy may have important applications in predictive model development and immune monitoring of HIV-1 vaccine trials. KEY POINTS: Immune monitoring models integrating multiple functions of HIV-1-specific CD8 T cells distinguish controllers from subjects with progressive HIV-1 infection. This strategy may have important applications in predictive model development and immune monitoring of HIV-1 vaccine trials.

Adaptation of HIV-1 to human leukocyte antigen class I.

The rapid and extensive spread of the human immunodeficiency virus (HIV) epidemic provides a rare opportunity to witness host-pathogen co-evolution involving humans. A focal point is the interaction between genes encoding human leukocyte antigen (HLA) and those encoding HIV proteins. HLA molecules present fragments (epitopes) of HIV proteins on the surface of infected cells to enable immune recognition and killing by CD8(+) T cells; particular HLA molecules, such as HLA-B*57, HLA-B*27 and HLA-B*51, are more likely to mediate successful control of HIV infection. Mutation within these epitopes can allow viral escape from CD8(+) T-cell recognition. Here we analysed viral sequences and HLA alleles from >2,800 subjects, drawn from 9 distinct study cohorts spanning 5 continents. Initial analysis of the HLA-B*51-restricted epitope, TAFTIPSI (reverse transcriptase residues 128-135), showed a strong correlation between the frequency of the escape mutation I135X and HLA-B*51 prevalence in the 9 study cohorts (P = 0.0001). Extending these analyses to incorporate other well-defined CD8(+) T-cell epitopes, including those restricted by HLA-B*57 and HLA-B*27, showed that the frequency of these epitope variants (n = 14) was consistently correlated with the prevalence of the restricting HLA allele in the different cohorts (together, P < 0.0001), demonstrating strong evidence of HIV adaptation to HLA at a population level. This process of viral adaptation may dismantle the well-established HLA associations with control of HIV infection that are linked to the availability of key epitopes, and highlights the challenge for a vaccine to keep pace with the changing immunological landscape presented by HIV.

Patterns of methylation heritability in a genome-wide analysis of four brain regions.

DNA methylation has been implicated in a number of diseases and other phenotypes. It is, therefore, of interest to identify and understand the genetic determinants of methylation and epigenomic variation. We investigated the extent to which genetic variation in cis-DNA sequence explains variation in CpG dinucleotide methylation in publicly available data for four brain regions from unrelated individuals, finding that 3-4% of CpG loci assayed were heritable, with a mean estimated narrow-sense heritability of 30% over the heritable loci. Over all loci, the mean estimated heritability was 3%, as compared with a recent twin-based study reporting 18%. Heritable loci were enriched for open chromatin regions and binding sites of CTCF, an influential regulator of transcription and chromatin architecture. Additionally, heritable loci were proximal to genes enriched in several known pathways, suggesting a possible functional role for these loci. Our estimates of heritability are conservative, and we suspect that the number of identified heritable loci will increase as the methylome is assayed across a broader range of cell types and the density of the tested loci is increased. Finally, we show that the number of heritable loci depends on the window size parameter commonly used to identify candidate cis-acting single-nucleotide polymorphism variants.

Fine-mapping classical HLA variation associated with durable host control of HIV-1 infection in African Americans.

A small proportion of human immunodeficiency virus-1 (HIV-1) infected individuals, termed HIV-1 controllers, suppress viral replication to very low levels in the absence of therapy. Genetic investigations of this phenotype have strongly implicated variation in the class I major histocompatibility complex (MHC) region as key to HIV-1 control. We collected sequence-based classical class I HLA genotypes at 4-digit resolution in HIV-1-infected African American controllers and progressors (n = 1107), and tested them for association with host control using genome-wide single nucleotide polymorphism data to account for population structure. Several classical alleles at HLA-B were associated with host control, including B*57:03 [odds ratio (OR) = 5.1; P= 3.4 × 10(-18)] and B*81:01 (OR = 4.8; P= 1.3 × 10(-9)). Analysis of variable amino acid positions demonstrates that HLA-B position 97 is the most significant association with host control in African Americans (omnibus P = 1.2 × 10(-21)) and explains the signal of several HLA-B alleles, including B*57:03. Within HLA-B, we also identified independent effects at position 116 (omnibus P= 2.8 × 10(-15)) in the canonical F pocket, position 63 in the B pocket (P= 1.5 × 10(-3)) and the non-pocket position 245 (P= 8.8 × 10(-10)), which is thought to influence CD8-binding kinetics. Adjusting for these HLA-B effects, there is evidence for residual association in the MHC region. These results underscore the key role of HLA-B in affecting HIV-1 replication, likely through the molecular interaction between HLA-B and viral peptides presented by infected cells, and suggest that sites outside the peptide-binding pocket also influence HIV-1 control.

FaST linear mixed models for genome-wide association studies.

We describe factored spectrally transformed linear mixed models (FaST-LMM), an algorithm for genome-wide association studies (GWAS) that scales linearly with cohort size in both run time and memory use. On Wellcome Trust data for 15,000 individuals, FaST-LMM ran an order of magnitude faster than current efficient algorithms. Our algorithm can analyze data for 120,000 individuals in just a few hours, whereas current algorithms fail on data for even 20,000 individuals (http://mscompbio.codeplex.com/).

Frequent and variable cytotoxic-T-lymphocyte escape-associated fitness costs in the human immunodeficiency virus type 1 subtype B Gag proteins.

Cytotoxic-T-lymphocyte (CTL) escape mutations undermine the durability of effective human immunodeficiency virus type 1 (HIV-1)-specific CD8(+) T cell responses. The rate of CTL escape from a given response is largely governed by the net of all escape-associated viral fitness costs and benefits. The observation that CTL escape mutations can carry an associated fitness cost in terms of reduced virus replication capacity (RC) suggests a fitness cost-benefit trade-off that could delay CTL escape and thereby prolong CD8 response effectiveness. However, our understanding of this potential fitness trade-off is limited by the small number of CTL escape mutations for which a fitness cost has been quantified. Here, we quantified the fitness cost of the 29 most common HIV-1B Gag CTL escape mutations using an in vitro RC assay. The majority (20/29) of mutations reduced RC by more than the benchmark M184V antiretroviral drug resistance mutation, with impacts ranging from 8% to 69%. Notably, the reduction in RC was significantly greater for CTL escape mutations associated with protective HLA class I alleles than for those associated with nonprotective alleles. To speed the future evaluation of CTL escape costs, we also developed an in silico approach for inferring the relative impact of a mutation on RC based on its computed impact on protein thermodynamic stability. These data illustrate that the magnitude of CTL escape-associated fitness costs, and thus the barrier to CTL escape, varies widely even in the conserved Gag proteins and suggest that differential escape costs may contribute to the relative efficacy of CD8 responses.

Significant reductions in Gag-protease-mediated HIV-1 replication capacity during the course of the epidemic in Japan.

Human immunodeficiency virus type 1 (HIV-1) evolves rapidly in response to host immune selection pressures. As a result, the functional properties of HIV-1 isolates from earlier in the epidemic may differ from those of isolates from later stages. However, few studies have investigated alterations in viral replication capacity (RC) over the epidemic. In the present study, we compare Gag-Protease-associated RC between early and late isolates in Japan (1994 to 2009). HIV-1 subtype B sequences from 156 antiretroviral-naïve Japanese with chronic asymptomatic infection were used to construct a chimeric NL4-3 strain encoding plasma-derived gag-protease. Viral replication capacity was examined by infecting a long terminal repeat-driven green fluorescent protein-reporter T cell line. We observed a reduction in the RC of chimeric NL4-3 over the epidemic, which remained significant after adjusting for the CD4(+) T cell count and plasma virus load. The same outcome was seen when limiting the analysis to a single large cluster of related sequences, indicating that our results are not due to shifts in the molecular epidemiology of the epidemic in Japan. Moreover, the change in RC was independent of genetic distance between patient-derived sequences and wild-type NL4-3, thus ruling out potential temporal bias due to genetic similarity between patient and historic viral backbone sequences. Collectively, these data indicate that Gag-Protease-associated HIV-1 replication capacity has decreased over the epidemic in Japan. Larger studies from multiple geographical regions will be required to confirm this phenomenon.

A powerful and efficient set test for genetic markers that handles confounders.

MOTIVATION: Approaches for testing sets of variants, such as a set of rare or common variants within a gene or pathway, for association with complex traits are important. In particular, set tests allow for aggregation of weak signal within a set, can capture interplay among variants and reduce the burden of multiple hypothesis testing. Until now, these approaches did not address confounding by family relatedness and population structure, a problem that is becoming more important as larger datasets are used to increase power. RESULTS: We introduce a new approach for set tests that handles confounders. Our model is based on the linear mixed model and uses two random effects-one to capture the set association signal and one to capture confounders. We also introduce a computational speedup for two random-effects models that makes this approach feasible even for extremely large cohorts. Using this model with both the likelihood ratio test and score test, we find that the former yields more power while controlling type I error. Application of our approach to richly structured Genetic Analysis Workshop 14 data demonstrates that our method successfully corrects for population structure and family relatedness, whereas application of our method to a 15 000 individual Crohn's disease case-control cohort demonstrates that it additionally recovers genes not recoverable by univariate analysis. AVAILABILITY: A Python-based library implementing our approach is available at http://mscompbio.codeplex.com.