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Motivation: Allele-specific expression (ASE) analyses aim to detect imbalanced expression of maternal versus paternal copies of an autosomal gene. Such allelic imbalance can result from a variety of cis-acting causes, including disruptive mutations within one copy of a gene that impact the stability of transcripts, as well as regulatory variants outside the gene that impact transcription initiation. Current methods for ASE estimation suffer from a number of shortcomings, such as relying on only one variant within a gene, assuming perfect phasing information across multiple variants within a gene, or failing to account for alignment biases and possible genotyping errors. Results: We developed BEASTIE, a Bayesian hierarchical model designed for precise ASE quantification at the gene level, based on given genotypes and RNA-Seq data. BEASTIE addresses the complexities of allelic mapping bias, genotyping error, and phasing errors by incorporating empirical phasing error rates derived from Genome-in-a-Bottle individual NA12878. BEASTIE surpasses existing methods in accuracy, especially in scenarios with high phasing errors. This improvement is critical for identifying rare genetic variants often obscured by such errors. Through rigorous validation on simulated data and application to real data from the 1000 Genomes Project, we establish the robustness of BEASTIE. These findings underscore the value of BEASTIE in revealing patterns of ASE across gene sets and pathways. Availability and Implementation: The software is freely available from https://github.com/x811zou/BEASTIE . BEASTIE is available as Python source code and as a Docker image. Supplementary information: Additional information is available online.
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OBJECTIVE: Relapsing polychondritis (RP) is a systemic inflammatory disease of unknown aetiology. The objective of this study was to examine the contribution of rare genetic variations to RP. METHODS: We performed a case-control exome-wide rare variant association analysis that included 66 unrelated European American cases with RP and 2923 healthy controls (HC). Gene-level collapsing analysis was performed using Firth's logistics regression. Exploratory pathway analysis was performed using three different methods: Gene Set Enrichment Analysis, sequence kernel association test and higher criticism test. Plasma DCBLD2 levels were measured in patients with RP and HC using ELISA. RESULTS: In the collapsing analysis, RP was associated with a significantly higher burden of ultra-rare damaging variants in the DCBLD2 gene (7.6% vs 0.1%, unadjusted OR=79.8, p=2.93×10-7). Plasma DCBLD2 protein levels were significantly higher in RP than in HC (median 4.06 ng/µL vs 0.05 ng/µL, p<0.001). The pathway analysis revealed a statistically significant enrichment of genes in the tumour necrosis factor signalling pathway driven by rare damaging variants in RELB, RELA and REL using higher criticism test weighted by eigenvector centrality. CONCLUSIONS: This study identified specific rare variants in the DCBLD2 gene as a putative genetic risk factor for RP. These findings should be validated in additional patients with RP and supported by future functional experiments.
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Variación Genética , Policondritis Recurrente , Humanos , Predisposición Genética a la Enfermedad , Secuenciación del Exoma , Policondritis Recurrente/genética , Exoma/genéticaRESUMEN
Cerebral Cavernous Malformations (CCMs) are vascular malformations of the central nervous system which can lead to moderate to severe neurological phenotypes in patients. A majority of CCM lesions are driven by a cancer-like three-hit mutational mechanism, including a somatic, activating mutation in the oncogene PIK3CA, as well as biallelic loss-of-function mutations in a CCM gene. However, standard sequencing approaches often fail to yield a full complement of pathogenic mutations in many CCMs. We suggest this reality reflects the limited sensitivity to identify low-frequency variants and the presence of mutations undetectable with bulk short-read sequencing. Here we report a single-nucleus DNA-sequencing approach that leverages the underlying biology of CCMs to identify lesions with somatic loss-of-heterozygosity, a class of such hidden mutations. We identify an alternative genetic mechanism for CCM pathogenesis and establish a method that can be repurposed to investigate the genetic underpinning of other disorders with multiple somatic mutations.
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Hemangioma Cavernoso del Sistema Nervioso Central , Humanos , Hemangioma Cavernoso del Sistema Nervioso Central/genética , Hemangioma Cavernoso del Sistema Nervioso Central/patología , Proteína KRIT1/genética , Proteínas Proto-Oncogénicas/genética , Proteínas Reguladoras de la Apoptosis/genética , Mutación , Análisis de Secuencia de ADNRESUMEN
Clinical response to adoptive T cell therapies is associated with the transcriptional and epigenetic state of the cell product. Thus, discovery of regulators of T cell gene networks and their corresponding phenotypes has potential to improve T cell therapies. Here we developed pooled, epigenetic CRISPR screening approaches to systematically profile the effects of activating or repressing 120 transcriptional and epigenetic regulators on human CD8+ T cell state. We found that BATF3 overexpression promoted specific features of memory T cells and attenuated gene programs associated with cytotoxicity, regulatory T cell function, and exhaustion. Upon chronic antigen stimulation, BATF3 overexpression countered phenotypic and epigenetic signatures of T cell exhaustion. Moreover, BATF3 enhanced the potency of CAR T cells in both in vitro and in vivo tumor models and programmed a transcriptional profile that correlates with positive clinical response to adoptive T cell therapy. Finally, we performed CRISPR knockout screens that defined cofactors and downstream mediators of the BATF3 gene network.
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Repeticiones Palindrómicas Cortas Agrupadas y Regularmente Espaciadas , Neoplasias , Humanos , Repeticiones Palindrómicas Cortas Agrupadas y Regularmente Espaciadas/genética , Linfocitos T CD8-positivos , Epigénesis GenéticaRESUMEN
Objective: Relapsing polychondritis (RP) is a systemic inflammatory disease of unknown etiology. The study objective was to examine the contribution of rare genetic variations in RP. Methods: We performed a case-control exome-wide rare variant association analysis including 66 unrelated European American RP cases and 2923 healthy controls. Gene-level collapsing analysis was performed using Firth's logistics regression. Pathway analysis was performed on an exploratory basis with three different methods: Gene Set Enrichment Analysis (GSEA), sequence kernel association test (SKAT) and higher criticism test. Plasma DCBLD2 levels were measured in patients with RP and healthy controls using enzyme-linked immunosorbent assay (ELISA). Results: In the collapsing analysis, RP was associated with higher burden of ultra-rare damaging variants in the DCBLD2 gene (7.6% vs 0.1%, unadjusted odds ratio = 79.8, p = 2.93 × 10-7). Patients with RP and ultra-rare damaging variants in DCBLD2 had a higher prevalence of cardiovascular manifestations. Plasma DCBLD2 protein levels were significantly higher in RP than healthy controls (5.9 vs 2.3, p < 0.001). Pathway analysis showed statistically significant enrichment of genes in the tumor necrosis factor (TNF) signaling pathway driven by rare damaging variants in RELB, RELA and REL using higher criticism test weighted by degree and eigenvector centrality. Conclusions: This study identified specific rare variants in DCBLD2 as putative genetic risk factors for RP. Genetic variation within the TNF pathway is also potentially associated with development of RP. These findings should be validated in additional patients with RP and supported by future functional experiments.
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Genomic regions subject to purifying selection are more likely to carry disease-causing mutations than regions not under selection. Cross species conservation is often used to identify such regions but with limited resolution to detect selection on short evolutionary timescales such as that occurring in only one species. In contrast, genetic intolerance looks for depletion of variation relative to expectation within a species, allowing species-specific features to be identified. When estimating the intolerance of noncoding sequence, methods strongly leverage variant frequency distributions. As the expected distributions depend on ancestry, if not properly controlled for, ancestral population source may obfuscate signals of selection. We demonstrate that properly incorporating ancestry in intolerance estimation greatly improved variant classification. We provide a genome-wide intolerance map that is conditional on ancestry and likely to be particularly valuable for variant prioritization.
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Genoma Humano , Genómica , Evolución Biológica , Genética de Población , Humanos , Selección GenéticaRESUMEN
Gene set-based signal detection analyses are used to detect an association between a trait and a set of genes by accumulating signals across the genes in the gene set. Since signal detection is concerned with identifying whether any of the genes in the gene set are non-null, a goodness-of-fit (GOF) test can be used to compare whether the observed distribution of gene-level tests within the gene set agrees with the theoretical null distribution. Here, we present a flexible gene set-based signal detection framework based on tail-focused GOF statistics. We show that the power of the various statistics in this framework depends critically on two parameters: the proportion of genes within the gene set that are non-null and the degree of separation between the null and alternative distributions of the gene-level tests. We give guidance on which statistic to choose for a given situation and implement the methods in a fast and user-friendly R package, wHC (https://github.com/mqzhanglab/wHC). Finally, we apply these methods to a whole exome sequencing study of amyotrophic lateral sclerosis.
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Esclerosis Amiotrófica Lateral , Esclerosis Amiotrófica Lateral/genética , Pruebas Genéticas , Humanos , Fenotipo , Secuenciación del ExomaRESUMEN
MOTIVATION: Conservation is broadly used to identify biologically important (epi)genomic regions. In the case of tumor growth, preferential conservation of DNA methylation can be used to identify areas of particular functional importance to the tumor. However, reliable assessment of methylation conservation based on multiple tissue samples per patient requires the decomposition of methylation variation at multiple levels. RESULTS: We developed a Bayesian hierarchical model that allows for variance decomposition of methylation on three levels: between-patient normal tissue variation, between-patient tumor-effect variation and within-patient tumor variation. We then defined a model-based conservation score to identify loci of reduced within-tumor methylation variation relative to between-patient variation. We fit the model to multi-sample methylation array data from 21 colorectal cancer (CRC) patients using a Monte Carlo Markov Chain algorithm (Stan). Sets of genes implicated in CRC tumorigenesis exhibited preferential conservation, demonstrating the model's ability to identify functionally relevant genes based on methylation conservation. A pathway analysis of preferentially conserved genes implicated several CRC relevant pathways and pathways related to neoantigen presentation and immune evasion. Our findings suggest that preferential methylation conservation may be used to identify novel gene targets that are not consistently mutated in CRC. The flexible structure makes the model amenable to the analysis of more complex multi-sample data structures. AVAILABILITY AND IMPLEMENTATION: The data underlying this article are available in the NCBI GEO Database, under accession code GSE166212. The R analysis code is available at https://github.com/kevin-murgas/DNAmethylation-hierarchicalmodel. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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Neoplasias Colorrectales , Metilación de ADN , Humanos , Teorema de Bayes , Neoplasias Colorrectales/genética , Neoplasias Colorrectales/patología , Genoma , Genómica , Regulación Neoplásica de la Expresión GénicaRESUMEN
Despite widespread clinical genetic testing, many individuals with suspected genetic conditions lack a precise diagnosis, limiting their opportunity to take advantage of state-of-the-art treatments. In some cases, testing reveals difficult-to-evaluate structural differences, candidate variants that do not fully explain the phenotype, single pathogenic variants in recessive disorders, or no variants in genes of interest. Thus, there is a need for better tools to identify a precise genetic diagnosis in individuals when conventional testing approaches have been exhausted. We performed targeted long-read sequencing (T-LRS) using adaptive sampling on the Oxford Nanopore platform on 40 individuals, 10 of whom lacked a complete molecular diagnosis. We computationally targeted up to 151 Mbp of sequence per individual and searched for pathogenic substitutions, structural variants, and methylation differences using a single data source. We detected all genomic aberrations-including single-nucleotide variants, copy number changes, repeat expansions, and methylation differences-identified by prior clinical testing. In 8/8 individuals with complex structural rearrangements, T-LRS enabled more precise resolution of the mutation, leading to changes in clinical management in one case. In ten individuals with suspected Mendelian conditions lacking a precise genetic diagnosis, T-LRS identified pathogenic or likely pathogenic variants in six and variants of uncertain significance in two others. T-LRS accurately identifies pathogenic structural variants, resolves complex rearrangements, and identifies Mendelian variants not detected by other technologies. T-LRS represents an efficient and cost-effective strategy to evaluate high-priority genes and regions or complex clinical testing results.
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Aberraciones Cromosómicas , Análisis Citogenético/métodos , Enfermedades Genéticas Congénitas/diagnóstico , Enfermedades Genéticas Congénitas/genética , Predisposición Genética a la Enfermedad , Genoma Humano , Mutación , Variaciones en el Número de Copia de ADN , Femenino , Pruebas Genéticas , Secuenciación de Nucleótidos de Alto Rendimiento , Humanos , Cariotipificación , Masculino , Análisis de Secuencia de ADNRESUMEN
BACKGROUND: Previous research in autism and other neurodevelopmental disorders (NDDs) has indicated an important contribution of protein-coding (coding) de novo variants (DNVs) within specific genes. The role of de novo noncoding variation has been observable as a general increase in genetic burden but has yet to be resolved to individual functional elements. In this study, we assessed whole-genome sequencing data in 2671 families with autism (discovery cohort of 516 families, replication cohort of 2155 families). We focused on DNVs in enhancers with characterized in vivo activity in the brain and identified an excess of DNVs in an enhancer named hs737. RESULTS: We adapted the fitDNM statistical model to work in noncoding regions and tested enhancers for excess of DNVs in families with autism. We found only one enhancer (hs737) with nominal significance in the discovery (p = 0.0172), replication (p = 2.5 × 10-3), and combined dataset (p = 1.1 × 10-4). Each individual with a DNV in hs737 had shared phenotypes including being male, intact cognitive function, and hypotonia or motor delay. Our in vitro assessment of the DNVs showed they all reduce enhancer activity in a neuronal cell line. By epigenomic analyses, we found that hs737 is brain-specific and targets the transcription factor gene EBF3 in human fetal brain. EBF3 is genome-wide significant for coding DNVs in NDDs (missense p = 8.12 × 10-35, loss-of-function p = 2.26 × 10-13) and is widely expressed in the body. Through characterization of promoters bound by EBF3 in neuronal cells, we saw enrichment for binding to NDD genes (p = 7.43 × 10-6, OR = 1.87) involved in gene regulation. Individuals with coding DNVs have greater phenotypic severity (hypotonia, ataxia, and delayed development syndrome [HADDS]) in comparison to individuals with noncoding DNVs that have autism and hypotonia. CONCLUSIONS: In this study, we identify DNVs in the hs737 enhancer in individuals with autism. Through multiple approaches, we find hs737 targets the gene EBF3 that is genome-wide significant in NDDs. By assessment of noncoding variation and the genes they affect, we are beginning to understand their impact on gene regulatory networks in NDDs.
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Trastorno Autístico/genética , Predisposición Genética a la Enfermedad , Hipotonía Muscular/genética , Trastornos del Neurodesarrollo/genética , Factores de Transcripción/genética , Trastorno Autístico/epidemiología , Trastorno Autístico/patología , Elementos de Facilitación Genéticos/genética , Exoma/genética , Femenino , Redes Reguladoras de Genes/genética , Humanos , Masculino , Hipotonía Muscular/epidemiología , Hipotonía Muscular/patología , Mutación/genética , Trastornos del Neurodesarrollo/epidemiología , Trastornos del Neurodesarrollo/patología , Neuronas/metabolismo , Neuronas/patologíaRESUMEN
High-throughput reporter assays such as self-transcribing active regulatory region sequencing (STARR-seq) have made it possible to measure regulatory element activity across the entire human genome at once. The resulting data, however, present substantial analytical challenges. Here, we identify technical biases that explain most of the variance in STARR-seq data. We then develop a statistical model to correct those biases and to improve detection of regulatory elements. This approach substantially improves precision and recall over current methods, improves detection of both activating and repressive regulatory elements, and controls for false discoveries despite strong local correlations in signal.
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Elementos de Facilitación Genéticos , Genoma Humano , Sesgo , Secuenciación de Nucleótidos de Alto Rendimiento/métodos , HumanosRESUMEN
BACKGROUND: In the majority of cases, the cause of stillbirth remains unknown despite detailed clinical and laboratory evaluation. Approximately 10 to 20% of stillbirths are attributed to chromosomal abnormalities. However, the causal nature of single-nucleotide variants and small insertions and deletions in exomes has been understudied. METHODS: We generated exome sequencing data for 246 stillborn cases and followed established guidelines to identify causal variants in disease-associated genes. These genes included those that have been associated with stillbirth and strong candidate genes. We also evaluated the contribution of 18,653 genes in case-control analyses stratified according to the degree of depletion of functional variation (described here as "intolerance" to variation). RESULTS: We identified molecular diagnoses in 15 of 246 cases of stillbirth (6.1%) involving seven genes that have been implicated in stillbirth and six disease genes that are good candidates for phenotypic expansion. Among the cases we evaluated, we also found an enrichment of loss-of-function variants in genes that are intolerant to such variation in the human population (odds ratio, 2.15; 95% confidence interval [CI], 1.46 to 3.06). Loss-of-function variants in intolerant genes were concentrated in genes that have not been associated with human disease (odds ratio, 2.22; 95% CI, 1.41 to 3.34), findings that differ from those in two postnatal clinical populations that were also evaluated in this study. CONCLUSIONS: Our findings establish the diagnostic utility of clinical exome sequencing to evaluate the role of small genomic changes in stillbirth. The strength of the novel risk signal (as generated through the stratified analysis) was similar to that in known disease genes, which indicates that the genetic cause of stillbirth remains largely unknown. (Funded by the Institute for Genomic Medicine.).
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Variación Genética , Mutación , Mortinato/genética , Femenino , Mutación del Sistema de Lectura , Humanos , Mutación con Pérdida de Función , Mutación Missense , Embarazo , Secuenciación del ExomaRESUMEN
Case-control sampling is frequently used in genetic association studies to examine the relationship between disease and genetic exposures. Such designs usually collect extensive information on phenotypes beyond the primary disease, whose associations with the genetic exposures are also of great interest. Because the cases are over-sampled, appropriate analysis of secondary phenotypes should take into account this biased sampling design. We previously introduced a weighting-based estimator for appropriate secondary analysis, but have not thoroughly explored its statistical properties. In this article, we revisit our previous estimator to offer new insights and methodological extensions. Specifically, we extend our previous estimator and construct its more general form based on generalized least squares (GLS). Such an extension allows us to connect the GLS estimator with the generalized method of moments and motivates a new specification test designed to assess the adequacy of the disease model or the weights. The specification test statistic measures the weighted discrepancy between the case and control subsample estimators, and asymptotically follows a central Chi-squared distribution under correct disease model specification. We illustrate the GLS estimator and specification test using a case-control sample of peripheral arterial disease, and use simulations to further shed light on the operating characteristics of the specification test.
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Proyectos de Investigación , Estudios de Casos y Controles , Estudios de Asociación Genética , Análisis de los Mínimos Cuadrados , FenotipoRESUMEN
Gene-set analyses are used to assess whether there is any evidence of association with disease among a set of biologically related genes. Such an analysis typically treats all genes within the sets similarly, even though there is substantial, external, information concerning the likely importance of each gene within each set. For example, for traits that are under purifying selection, we would expect genes showing extensive genic constraint to be more likely to be trait associated than unconstrained genes. Here we improve gene-set analyses by incorporating such external information into a higher-criticism-based signal detection analysis. We show that when this external information is predictive of whether a gene is associated with disease, our approach can lead to a significant increase in power. Further, our approach is particularly powerful when the signal is sparse, that is when only a small number of genes within the set are associated with the trait. We illustrate our approach with a gene-set analysis of amyotrophic lateral sclerosis (ALS) and implicate a number of gene-sets containing SOD1 and NEK1 as well as showing enrichment of small p values for gene-sets containing known ALS genes. We implement our approach in the R package wHC.
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Esclerosis Amiotrófica Lateral/genética , Esclerosis Amiotrófica Lateral/patología , Exoma/genética , Predisposición Genética a la Enfermedad , Variación Genética , Humanos , Quinasa 1 Relacionada con NIMA/genética , Superóxido Dismutasa-1/genética , Interfaz Usuario-ComputadorRESUMEN
MOTIVATION: High-throughput reporter assays dramatically improve our ability to assign function to noncoding genetic variants, by measuring allelic effects on gene expression in the controlled setting of a reporter gene. Unlike genetic association tests, such assays are not confounded by linkage disequilibrium when loci are independently assayed. These methods can thus improve the identification of causal disease mutations. While work continues on improving experimental aspects of these assays, less effort has gone into developing methods for assessing the statistical significance of assay results, particularly in the case of rare variants captured from patient DNA. RESULTS: We describe a Bayesian hierarchical model, called Bayesian Inference of Regulatory Differences, which integrates prior information and explicitly accounts for variability between experimental replicates. The model produces substantially more accurate predictions than existing methods when allele frequencies are low, which is of clear advantage in the search for disease-causing variants in DNA captured from patient cohorts. Using the model, we demonstrate a clear tradeoff between variant sequencing coverage and numbers of biological replicates, and we show that the use of additional biological replicates decreases variance in estimates of effect size, due to the properties of the Poisson-binomial distribution. We also provide a power and sample size calculator, which facilitates decision making in experimental design parameters. AVAILABILITY AND IMPLEMENTATION: The software is freely available from www.geneprediction.org/bird. The experimental design web tool can be accessed at http://67.159.92.22:8080. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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Programas Informáticos , Alelos , Teorema de Bayes , Frecuencia de los Genes , Humanos , Desequilibrio de LigamientoRESUMEN
ARFGEF1 encodes a guanine exchange factor involved in intracellular vesicle trafficking, and is a candidate gene for childhood genetic epilepsies. To model ARFGEF1 haploinsufficiency observed in a recent Lennox Gastaut Syndrome patient, we studied a frameshift mutation (Arfgef1fs) in mice. Arfgef1fs/+ pups exhibit signs of developmental delay, and Arfgef1fs/+ adults have a significantly decreased threshold to induced seizures but do not experience spontaneous seizures. Histologically, the Arfgef1fs/+ brain exhibits a disruption in the apical lining of the dentate gyrus and altered spine morphology of deep layer neurons. In primary hippocampal neuron culture, dendritic surface and synaptic but not total GABAA receptors (GABAAR) are reduced in Arfgef1fs/+ neurons with an accompanying decrease in the number of GABAAR-containing recycling endosomes in cell body. Arfgef1fs/+ neurons also display differences in the relative ratio of Arf6+:Rab11+:TrfR+ recycling endosomes. Although the GABAAR-containing early endosomes in Arfgef1fs/+ neurons are comparable to wildtype, Arfgef1fs/+ neurons show an increase in the number of GABAAR-containing lysosomes in dendrite and cell body. Together, the altered endosome composition and decreased neuronal surface GABAAR results suggests a mechanism whereby impaired neuronal inhibition leads to seizure susceptibility.
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Endosomas/metabolismo , Factores de Intercambio de Guanina Nucleótido/metabolismo , Neuronas/metabolismo , Receptores de GABA-A/metabolismo , Convulsiones/metabolismo , Animales , Encéfalo/metabolismo , Preescolar , Factores de Intercambio de Guanina Nucleótido/genética , Haploinsuficiencia , Humanos , Lactante , Síndrome de Lennox-Gastaut/genética , Masculino , Proteínas de la Membrana , Ratones , Ratones NoqueadosRESUMEN
Changes in transcriptional regulation are thought to be a major contributor to the evolution of phenotypic traits, but the contribution of changes in chromatin accessibility to the evolution of gene expression remains almost entirely unknown. To address this important gap in knowledge, we developed a new method to identify DNase I Hypersensitive (DHS) sites with differential chromatin accessibility between species using a joint modeling approach. Our method overcomes several limitations inherent to conventional threshold-based pairwise comparisons that become increasingly apparent as the number of species analyzed rises. Our approach employs a single quantitative test which is more sensitive than existing pairwise methods. To illustrate, we applied our joint approach to DHS sites in fibroblast cells from five primates (human, chimpanzee, gorilla, orangutan, and rhesus macaque). We identified 89,744 DHS sites, of which 41% are identified as differential between species using the joint model compared with 33% using the conventional pairwise approach. The joint model provides a principled approach to distinguishing single from multiple chromatin accessibility changes among species. We found that nondifferential DHS sites are enriched for nucleotide conservation. Differential DHS sites with decreased chromatin accessibility relative to rhesus macaque occur more commonly near transcription start sites (TSS), while those with increased chromatin accessibility occur more commonly distal to TSS. Further, differential DHS sites near TSS are less cell type-specific than more distal regulatory elements. Taken together, these results point to distinct classes of DHS sites, each with distinct characteristics of selection, genomic location, and cell type specificity.
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Cromatina/química , Evolución Molecular , Animales , Línea Celular , Desoxirribonucleasa I , Genómica , Gorilla gorilla/genética , Humanos , Macaca mulatta/genética , Modelos Genéticos , Pan troglodytes/genética , Pongo/genética , Sitio de Iniciación de la TranscripciónRESUMEN
The first phase of genome-wide association studies (GWAS) assessed the role of common variation in human disease. Advances optimizing and economizing high-throughput sequencing have enabled a second phase of association studies that assess the contribution of rare variation to complex disease in all protein-coding genes. Unlike the early microarray-based studies, sequencing-based studies catalogue the full range of genetic variation, including the evolutionarily youngest forms. Although the experience with common variants helped establish relevant standards for genome-wide studies, the analysis of rare variation introduces several challenges that require novel analysis approaches.
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Variación Genética , Estudio de Asociación del Genoma Completo , Secuenciación de Nucleótidos de Alto Rendimiento , Herencia Multifactorial , Análisis de Secuencia por Matrices de Oligonucleótidos , Animales , HumanosRESUMEN
BACKGROUND: Studies have identified many common genetic associations that influence renal function and all-cause CKD, but these explain only a small fraction of variance in these traits. The contribution of rare variants has not been systematically examined. METHODS: We performed exome sequencing of 3150 individuals, who collectively encompassed diverse CKD subtypes, and 9563 controls. To detect causal genes and evaluate the contribution of rare variants we used collapsing analysis, in which we compared the proportion of cases and controls carrying rare variants per gene. RESULTS: The analyses captured five established monogenic causes of CKD: variants in PKD1, PKD2, and COL4A5 achieved study-wide significance, and we observed suggestive case enrichment for COL4A4 and COL4A3. Beyond known disease-associated genes, collapsing analyses incorporating regional variant intolerance identified suggestive dominant signals in CPT2 and several other candidate genes. Biallelic mutations in CPT2 cause carnitine palmitoyltransferase II deficiency, sometimes associated with rhabdomyolysis and acute renal injury. Genetic modifier analysis among cases with APOL1 risk genotypes identified a suggestive signal in AHDC1, implicated in Xia-Gibbs syndrome, which involves intellectual disability and other features. On the basis of the observed distribution of rare variants, we estimate that a two- to three-fold larger cohort would provide 80% power to implicate new genes for all-cause CKD. CONCLUSIONS: This study demonstrates that rare-variant collapsing analyses can validate known genes and identify candidate genes and modifiers for kidney disease. In so doing, these findings provide a motivation for larger-scale investigation of rare-variant risk contributions across major clinical CKD categories.
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Colágeno Tipo IV/genética , Secuenciación del Exoma , Variación Genética/genética , Proteínas Quinasas/genética , Insuficiencia Renal Crónica/genética , Canales Catiónicos TRPP/genética , Estudios de Casos y Controles , Femenino , Humanos , Masculino , Pronóstico , Proteína Quinasa D2 , Valores de Referencia , Insuficiencia Renal Crónica/diagnósticoRESUMEN
Different parts of a gene can be of differential importance to development and health. This regional heterogeneity is also apparent in the distribution of disease-associated mutations, which often cluster in particular regions of disease-associated genes. The ability to precisely estimate functionally important sub-regions of genes will be key in correctly deciphering relationships between genetic variation and disease. Previous methods have had some success using standing human variation to characterize this variability in importance by measuring sub-regional intolerance, i.e., the depletion in functional variation from expectation within a given region of a gene. However, the ability to precisely estimate local intolerance was restricted by the fact that only information within a given sub-region is used, leading to instability in local estimates, especially for small regions. We show that borrowing information across regions using a Bayesian hierarchical model stabilizes estimates, leading to lower variability and improved predictive utility. Specifically, our approach more effectively identifies regions enriched for ClinVar pathogenic variants. We also identify significant correlations between sub-region intolerance and the distribution of pathogenic variation in disease-associated genes, with AUCs for classifying de novo missense variants in Online Mendelian Inheritance in Man (OMIM) genes of up to 0.86 using exonic sub-regions and 0.91 using sub-regions defined by protein domains. This result immediately suggests that considering the intolerance of regions in which variants are found may improve diagnostic interpretation. We also illustrate the utility of integrating regional intolerance into gene-level disease association tests with a study of known disease-associated genes for epileptic encephalopathy.