Rare Non-coding Variants Research Articles

Association of common and rare variants with Alzheimer's disease in more than 13,000 diverse individuals with whole-genome sequencing from the Alzheimer's Disease Sequencing Project.

Alzheimer's disease (AD) is a common disorder of the elderly that is both highly heritable and genetically heterogeneous. We investigated the association of AD with both common variants and aggregates of rare coding and non-coding variants in 13,371 individuals of diverse ancestry with whole genome sequencing (WGS) data. Pooled-population analyses of all individuals identified genetic variants at apolipoprotein E (APOE) and BIN1 associated with AD (p<5×10-8). Subgroup-specific analyses identified a haplotype on chromosome 14 including PSEN1 associated with AD in Hispanics, further supported by aggregate testing of rare coding and non-coding variants in the region. Common variants in LINC00320 were observed associated with AD in Black individuals (p=1.9×10-9). Finally, we observed rare non-coding variants in the promoter of TOMM40 distinct of APOE in pooled-population analyses (p=7.2×10-8). We observed that complementary pooled-population and subgroup-specific analyses offered unique insights into the genetic architecture of AD. We determine the association of genetic variants with Alzheimer's disease (AD) using 13,371 individuals of diverse ancestry with whole genome sequencing (WGS) data. We identified genetic variants at apolipoprotein E (APOE), BIN1, PSEN1, and LINC00320 associated with AD. We observed rare non-coding variants in the promoter of TOMM40 distinct of APOE.

A Rare Noncoding Enhancer Variant in SCN5A Contributes to the High Prevalence of Brugada Syndrome in Thailand.

Brugada syndrome (BrS) is a cardiac arrhythmia disorder that causes sudden death in young adults. Rare genetic variants in the SCN5A gene encoding the Nav1.5 sodium channel and common noncoding variants at this locus are robustly associated with the condition. BrS is particularly prevalent in Southeast Asia but the underlying ancestry-specific factors remain largely unknown. Genome sequencing of BrS probands and population-matched controls from Thailand was performed to identify rare noncoding variants at the SCN5A-SCN10A locus that were enriched in patients with BrS. A likely causal variant was prioritized by computational methods and introduced into human induced pluripotent stem cell (hiPSC) lines using CRISPR-Cas9. The effect of the variant on SCN5A expression and Nav1.5 sodium channel current was then assessed in hiPSC-derived cardiomyocytes (hiPSC-CMs). A rare noncoding variant in an SCN5A intronic enhancer region was highly enriched in patients with BrS (detected in 3.9% of cases with a case-control odds ratio of 45.2). The variant affects a nucleotide conserved across all mammalian species and predicted to disrupt a Mef2 transcription factor binding site. Heterozygous introduction of the enhancer variant in hiPSC-CMs caused significantly reduced SCN5A expression from the variant-containing allele and a 30% reduction in Nav1.5-mediated sodium current density compared with isogenic controls, confirming its pathogenicity. Patients with the variant had severe phenotypes, with 89% experiencing cardiac arrest. This is the first example of a functionally validated rare noncoding variant at the SCN5A locus and highlights how genome sequencing in understudied populations can identify novel disease mechanisms. The variant partly explains the increased prevalence of BrS in this region and enables the identification of at-risk variant carriers to reduce the burden of sudden cardiac death in Thailand.

Noncoding variants are a rare cause of recessive developmental disorders in trans with coding variants

PurposeIdentifying pathogenic noncoding variants is challenging. A single protein-altering variant is often identified in a recessive gene in individuals with developmental disorders (DD), but the prevalence of pathogenic noncoding “second hits” in trans with these is unknown. MethodsIn 4073 genetically undiagnosed rare-disease trio probands from the 100,000 Genomes project, we identified rare heterozygous protein-altering variants in recessive DD-associated genes. We identified rare noncoding variants on the other haplotype in introns, untranslated regions, promoters, and candidate enhancer regions. We clinically evaluated the top candidates for phenotypic fit and performed functional testing where possible. ResultsWe identified 3761 rare heterozygous loss-of-function or ClinVar pathogenic variants in recessive DD-associated genes in 2430 probands. For 1366 (36.3%) of these, we identified at least 1 rare noncoding variant in trans. Bioinformatic filtering and clinical review, revealed 7 to be a good clinical fit. After detailed characterization, we identified likely diagnoses for 3 probands (in GAA, NPHP3, and PKHD1) and candidate diagnoses in a further 3 (PAH, LAMA2, and IGHMBP2). ConclusionWe developed a systematic approach to uncover new diagnoses involving compound heterozygous coding/noncoding variants and conclude that this mechanism is likely to be a rare cause of DDs.

A Genomics England haplotype reference panel and imputation of UK Biobank

We built a reference panel with 342 million autosomal variants using 78,195 individuals from the Genomics England (GEL) dataset, achieving a phasing switch error rate of 0.18% for European samples and imputation quality of r2 = 0.75 for variants with minor allele frequencies as low as 2 × 10−4 in white British samples. The GEL-imputed UK Biobank genome-wide association analysis identified 70% of associations found by direct exome sequencing (P < 2.18 × 10−11), while extending testing of rare variants to the entire genome. Coding variants dominated the rare-variant genome-wide association results, implying less disruptive effects of rare non-coding variants.

Massively parallel screen uncovers many rare 3' UTR variants regulating mRNA abundance of cancer driver genes.

Understanding the function of rare non-coding variants represents a significant challenge. Using MapUTR, a screening method, we studied the function of rare 3' UTR variants affecting mRNA abundance post-transcriptionally. Among 17,301 rare gnomAD variants, an average of 24.5% were functional, with 70% in cancer-related genes, many in critical cancer pathways. This observation motivated an interrogation of 11,929 somatic mutations, uncovering 3928 (33%) functional mutations in 155 cancer driver genes. Functional MapUTR variants were enriched in microRNA- or protein-binding sites and may underlie outlier gene expression in tumors. Further, we introduce untranslated tumor mutational burden (uTMB), a metric reflecting the amount of somatic functional MapUTR variants of a tumor and show its potential in predicting patient survival. Through prime editing, we characterized three variants in cancer-relevant genes (MFN2, FOSL2, and IRAK1), demonstrating their cancer-driving potential. Our study elucidates the function of tens of thousands of non-coding variants, nominates non-coding cancer driver mutations, and demonstrates their potential contributions to cancer.

Abstract IA18: Genetic susceptibility to breast cancer: Recent advances and application to personalised prevention

Abstract The past two decades have seen dramatic progress in our understanding of the inherited basis of breast cancer, driven by large international collaborative epidemiological studies. Genetic factors identified include rare coding variants in susceptibility genes, and more than 200 common polymorphisms, identified through genome-wide association studies (GWAS) and largely in non-coding regions, that confer more moderate risks. The majority of the common variants are more strongly associated with ER-positive disease, but a subset is specifically associated with ER-negative disease. Variants are strongly enriched for regulatory regions and transcription factor binding sites, and the putative target genes are strongly enriched for known breast cancer drivers: however, the underlying target genes and mechanisms remain largely obscure. The associations for common variants appear to be largely independent of each other and can be summarised by a polygenic risk score (PRS) that is strongly predictive of risk. The most extensively validated PRS, comprising 313 SNPs, is associated with a relative risk of approximately 1.6 per standard deviation; women in the top 1% of the risk distribution have an approximately 4-fold risk of ER-positive disease and 3-fold risk of ER-negative disease. The PRS was developed in women of European ancestry but is also predictive of risk in Asian ancestry women, though less so in African ancestry women. In contrast, despite their widespread use, the evidence for association with cancer for coding variants in genes on genetic testing panels is often weak. Recent very large-scale targeted sequencing studies, however, have clarified the position, providing strong evidence for an association between protein truncating or missense variants and breast cancer risk for nine genes: BRCA1, BRCA2, ATM, CHEK2, PALB2, BARD1, RAD51C, RAD51D and TP53. Recent large-scale exome-wide sequencing analysis has shown that rare variants in several additional genes are also risk associated, with the majority being tumour suppressor genes: these include MAP3K1, ATRIP and SAMHD1. These analyses also demonstrate, however, that the contribution of coding variation, beyond the known genes, is likely to be small. The currently identified variants explain about half of the familial risk of breast cancer. Part of the “missing” heritability is due to weaker common variants, many of which should be identified in ongoing larger GWAS. The causes of the remainder are obscure and may include rare non-coding variants, repeat polymorphisms, and epistatic interactions. Risk discrimination is most powerful when all risk factors are considered. The BOADICEA model, implemented in the CanRisk tool, provides a well validated model that incorporates the effects of gene variants, polygenic risk scores, lifestyle factors and breast density to predict breast and ovarian cancer risk. Multiple translational studies are ongoing to evaluate the feasibility and utility of such personalised risk prediction for stratifying screening and prevention. Citation Format: Douglas F Easton. Genetic susceptibility to breast cancer: Recent advances and application to personalised prevention [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Breast Cancer Research; 2023 Oct 19-22; San Diego, California. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_1):Abstract nr IA18.

Association of Common and Rare Variants with Alzheimer’s Disease in 16,905 individuals with Whole‐Genome Sequence Data from the Alzheimer’s Disease Sequencing Project

AbstractBackgroundWhole genome sequencing (WGS) data enables assessment of common and rare variants for association with human diseases. Here we report our analysis using ADSP R3 WGS data to discover genetic variants associated with AD.MethodWe performed association testing of common variants (minor allele frequency [MAF] &gt; 0.5%) as well as aggregates of rare (MAF &lt; 1%) coding and non‐coding variants. Given that ADSP is composed of multiple ancestry groups, we performed association testing across all participants (pooled population [PP], Ncases = 6,519 and Ncontrol = 6,852) and within the following populations: African Americans (AA, Ncases = 1,137 and Ncontrol = 1,707), Hispanics (HIS, Ncases = 1,021 and Ncontrol = 1,988), and Non‐Hispanic White (NHW, Ncases = 4,230 and Ncontrol = 3,109) defined by self‐reported race and ethnicity (Table 1).ResultAs expected, our most significant associations are at the APOE locus (chr19:44,905,796‐44,909,393) (Figure 1). In the pooled‐population analysis, we observed known AD associations for BIN1 (p = 3.2×10−09) variants with AD status. In the NHW analysis, we observed AD associations for variants in CR1 (p = 7.97×10−08), BIN1 (p = 2.16×10−08), ARHGEF33 (p = 4.85×10−8), ANK3 (p = 1.43×10−12) and MYCBP2‐AS1 (p = 4.59×10−08), and in the AA analysis, we observed a significant variant near LINC00320 (p = 1.5×10−8). In the HIS subset, a region (chr14:72,698,038‐75,846,454) has 31 significant variants (p = 3.9×10−11) crossing multiple genes. This region covers PSEN1 G206A (rs63750082), a well‐known early‐onset AD mutation. Local‐ancestry analysis shows that the mutations, including G206A, are of African ancestry. Using kinship coefficients calculated within this dataset, it was determined that the signals are not driven by a familial linkage disequilibrium.We observed gene‐based aggregation of coding variants in PSEN1 in the pooled‐population and HIS analyses (p&lt;5×10−8) (Figure 2). In our gene‐centric noncoding aggregates analysis, we identified noncoding variants in the promotor of TOMM40 in the pooled‐population analysis (p = 7.2×10−08). After adjusting for APOE e4 (rs429358) and e2 (rs7412) alleles, there was an attenuation, but the association remained suggestive (p = 7.1×10−06).ConclusionWe performed common and rare association analysis of AD on ADSP WGS data. We observed associations with variants in known AD loci. We also observed population‐specific associations and an association of AD with rare noncoding variants in TOMM40, indicating WGS in diverse populations can lead to novel genetic associations with AD.

FRI455 Polycystic Ovary Syndrome-Associated DENND1A Non-Coding Risk Loci Alter Gene Expression

Abstract Disclosure: L. Sankaranarayanan: None. G. Johnson: None. A. Barrera: None. A.E. Dunaif: None. T. Reddy: None. Polycystic ovary syndrome (PCOS) is a leading cause of infertility and type 2 diabetes affecting 10-15% of menstruating people worldwide. PCOS is characterized by increased circulating testosterone levels, ovulatory dysfunction and insulin resistance. Genome wide association studies (GWAS) have identified ∼20 replicated common PCOS susceptibility loci in European and Han Chinese cohorts. The associated variants are predominantly non-coding and implicate neuroendocrine, reproductive, and metabolic causal pathways. Rare non-coding variants in DENND1A, a GWAS candidate gene that regulates androgen biosynthesis, were present in ∼50% of PCOS families by whole genome sequencing. These associations suggest non-coding genetic contributions to the development of PCOS. We tested the hypothesis that PCOS GWAS risk loci contribute to PCOS pathogenesis by altering gene regulation. We first identified ∼1500 functioning regulatory elements across the GWAS associated regions using a high throughput reporter assay, STARR-seq, in two different cell lines. We used H295R, an adrenal cell line model for testosterone production and COV434, an ovarian granulosa cell line. We identified cell-line specific and overlapping regulatory regions suggesting that there is context specific gene regulation. Sixty percent of the identified regions are in previously documented open chromatin regions from DNase-seq and ATAC-seq studies supporting our hypothesis that these regulatory regions are functional. We additionally experimentally tested the regulatory effect of five of the regulatory regions identified in the DENND1A locus in H295R cells using CRISPR-based epigenetic editing tools. This endogenous perturbation increases DENND1A gene levels (measured by qPCR) and also increased testosterone produced by the H295R cells (measured by ELISA), suggesting that these regions are biologically relevant to PCOS pathogenesis.We investigated allele-specific regulatory activity in a multi-ethnic pool of five genomes from healthy individuals. We identified 21 common genetic variants (minor allele frequency in the population &amp;gt;0.05) that alter regulatory activity in the DENND1A locus, including two that are ancestry-specific. Further, rs12237685 and rs28441318 are also eQTLS for DENND1A from the GTEX project and reside within open chromatin regions in ovarian cells. The functional consequences of non-coding genetic variants associated with complex traits has been exceptionally difficult to elucidate. Our findings suggest that both the common genetic variants and rare PCOS patient-associated DENND1A variants and altered gene expression. Further, some of those variants may contribute to allele-specific genetic risk for PCOS. Presentation Date: Friday, June 16, 2023

Unraveling the role of non-coding rare variants in epilepsy.

The discovery of new variants has leveled off in recent years in epilepsy studies, despite the use of very large cohorts. Consequently, most of the heritability is still unexplained. Rare non-coding variants have been largely ignored in studies on epilepsy, although non-coding single nucleotide variants can have a significant impact on gene expression. We had access to whole genome sequencing (WGS) from 247 epilepsy patients and 377 controls. To assess the functional impact of non-coding variants, ExPecto, a deep learning algorithm was used to predict expression change in brain tissues. We compared the burden of rare non-coding deleterious variants between cases and controls. Rare non-coding highly deleterious variants were significantly enriched in Genetic Generalized Epilepsy (GGE), but not in Non-Acquired Focal Epilepsy (NAFE) or all epilepsy cases when compared with controls. In this study we showed that rare non-coding deleterious variants are associated with epilepsy, specifically with GGE. Larger WGS epilepsy cohort will be needed to investigate those effects at a greater resolution. Nevertheless, we demonstrated the importance of studying non-coding regions in epilepsy, a disease where new discoveries are scarce.

Diagnostic genome sequencing improves diagnostic yield: a prospective single-centre study in 1000 patients with inherited eye diseases

PurposeGenome sequencing (GS) is expected to reduce the diagnostic gap in rare disease genetics. We aimed to evaluate a scalable framework for genome-based analyses ‘beyond the exome’ in regular care...

A whole-genome reference panel of 14,393 individuals for East Asian populations accelerates discovery of rare functional variants.

Underrepresentation of non-European (EUR) populations hinders growth of global precision medicine. Resources such as imputation reference panels that match the study population are necessary to find low-frequency variants with substantial effects. We created a reference panel consisting of 14,393 whole-genome sequences including more than 11,000 Asian individuals. Genome-wide association studies were conducted using the reference panel and a population-specific genotype array of 72,298 subjects for eight phenotypes. This panel yields improved imputation accuracy of rare and low-frequency variants within East Asian populations compared with the largest reference panel. Thirty-nine previously unidentified associations were found, and more than half of the variants were East Asian specific. We discovered genes with rare protein-altering variants, including LTBP1 for height and GPR75 for body mass index, as well as putative regulatory mechanisms for rare noncoding variants with cell type-specific effects. We suggest that this dataset will add to the potential value of Asian precision medicine.

The genomic landscape of familial glioma.

Glioma is a rare brain tumor with a poor prognosis. Familial glioma is a subset of glioma with a strong genetic predisposition that accounts for approximately 5% of glioma cases. We performed whole-genome sequencing on an exploratory cohort of 203 individuals from 189 families with a history of familial glioma and an additional validation cohort of 122 individuals from 115 families. We found significant enrichment of rare deleterious variants of seven genes in both cohorts, and the most significantly enriched gene was HERC2 (P=0.0006). Furthermore, we identified rare noncoding variants in both cohorts that were predicted to affect transcription factor binding sites or cause cryptic splicing. Last, we selected a subset of discovered genes for validation by CRISPR knockdown screening and found that DMBT1, HP1BP3, and ZCH7B3 have profound impacts on proliferation. This study performs comprehensive surveillance of the genomic landscape of familial glioma.

Whole Genome Joint Analysis for identification of rare non-coding causative variants - case report of a child with mitochondrial disease

Whole Genome Joint Analysis for identification of rare non-coding causative variants - case report of a child with mitochondrial disease

Oligogenic Architecture of Rare Noncoding Variants Distinguishes 4 Congenital Heart Disease Phenotypes.

Congenital heart disease (CHD) is highly heritable, but the power to identify inherited risk has been limited to analyses of common variants in small cohorts. We performed reimputation of 4 CHD cohorts (n=55 342) to the TOPMed reference panel (freeze 5), permitting meta-analysis of 14 784 017 variants including 6 035 962 rare variants of high imputation quality as validated by whole genome sequencing. Meta-analysis identified 16 novel loci, including 12 rare variants, which displayed moderate or large effect sizes (median odds ratio, 3.02) for 4 separate CHD categories. Analyses of chromatin structure link 13 of the genome-wide significant loci to key genes in cardiac development; rs373447426 (minor allele frequency, 0.003 [odds ratio, 3.37 for Conotruncal heart disease]; P=1.49×10-8) is predicted to disrupt chromatin structure for 2 nearby genes BDH1 and DLG1 involved in Conotruncal development. A lead variant rs189203952 (minor allele frequency, 0.01 [odds ratio, 2.4 for left ventricular outflow tract obstruction]; P=1.46×10-8) is predicted to disrupt the binding sites of 4 transcription factors known to participate in cardiac development in the promoter of SPAG9. A tissue-specific model of chromatin conformation suggests that common variant rs78256848 (minor allele frequency, 0.11 [odds ratio, 1.4 for Conotruncal heart disease]; P=2.6×10-8) physically interacts with NCAM1 (PFDR=1.86×10-27), a neural adhesion molecule acting in cardiac development. Importantly, while each individual malformation displayed substantial heritability (observed h2 ranging from 0.26 for complex malformations to 0.37 for left ventricular outflow tract obstructive disease) the risk for different CHD malformations appeared to be separate, without genetic correlation measured by linkage disequilibrium score regression or regional colocalization. We describe a set of rare noncoding variants conferring significant risk for individual heart malformations which are linked to genes governing cardiac development. These results illustrate that the oligogenic basis of CHD and significant heritability may be linked to rare variants outside protein-coding regions conferring substantial risk for individual categories of cardiac malformation.

Investigation of Rare Non-Coding Variants in Familial Multiple Myeloma

Multiple myeloma (MM) is a plasma cell malignancy whereby a single clone of plasma cells over-propagates in the bone marrow, resulting in the increased production of monoclonal immunoglobulin. While the complex genetic architecture of MM is well characterized, much less is known about germline variants predisposing to MM. Genome-wide sequencing approaches in MM families have started to identify rare high-penetrance coding risk alleles. In addition, genome-wide association studies have discovered several common low-penetrance risk alleles, which are mainly located in the non-coding genome. Here, we further explored the genetic basis in familial MM within the non-coding genome in whole-genome sequencing data. We prioritized and characterized 150 upstream, 5' untranslated region (UTR) and 3' UTR variants from 14 MM families, including 20 top-scoring variants. These variants confirmed previously implicated biological pathways in MM development. Most importantly, protein network and pathway enrichment analyses also identified 10 genes involved in mitogen-activated protein kinase (MAPK) signaling pathways, which have previously been established as important MM pathways.

De novo and inherited variants in coding and regulatory regions in genetic cardiomyopathies

BackgroundCardiomyopathies are a leading cause of progressive heart failure and sudden cardiac death; however, their genetic aetiology remains poorly understood. We hypothesised that variants in noncoding regulatory regions and oligogenic inheritance mechanisms may help close the diagnostic gap.MethodsWe first analysed whole-genome sequencing data of 143 parent–offspring trios from Genomics England 100,000 Genomes Project. We used gene panel testing and a phenotype-based, variant prioritisation framework called Exomiser to identify candidate genes in trios. To assess the contribution of noncoding DNVs to cardiomyopathies, we intersected DNVs with open chromatin sequences from single-cell ATAC-seq data of cardiomyocytes. We also performed a case–control analysis in an exome-negative cohort, including 843 probands and 19,467 controls, to assess the association between noncoding variants in known cardiomyopathy genes and disease.ResultsIn the trio analysis, a definite or probable genetic diagnosis was identified in 21 probands according to the American College of Medical Genetics guidelines. We identified novel DNVs in diagnostic-grade genes (RYR2, TNNT2, PTPN11, MYH7, LZR1, NKX2-5), and five cases harbouring a combination of prioritised variants, suggesting that oligogenic inheritance and genetic modifiers contribute to cardiomyopathies. Phenotype-based ranking of candidate genes identified in noncoding DNV analysis revealed JPH2 as the top candidate. Moreover, a case–control analysis revealed an enrichment of rare noncoding variants in regulatory elements of cardiomyopathy genes (p = .035, OR = 1.43, 95% Cl = 1.095–1.767) versus controls. Of the 25 variants associated with disease (p< 0.5), 23 are novel and nine are predicted to disrupt transcription factor binding motifs.ConclusionOur results highlight complex genetic mechanisms in cardiomyopathies and reveal novel genes for future investigations.

Whole genome sequence analysis of blood lipid levels in >66,000 individuals

Blood lipids are heritable modifiable causal factors for coronary artery disease. Despite well-described monogenic and polygenic bases of dyslipidemia, limitations remain in discovery of lipid-associated alleles using whole genome sequencing (WGS), partly due to limited sample sizes, ancestral diversity, and interpretation of clinical significance. Among 66,329 ancestrally diverse (56% non-European) participants, we associate 428M variants from deep-coverage WGS with lipid levels; ~400M variants were not assessed in prior lipids genetic analyses. We find multiple lipid-related genes strongly associated with blood lipids through analysis of common and rare coding variants. We discover several associated rare non-coding variants, largely at Mendelian lipid genes. Notably, we observe rare LDLR intronic variants associated with markedly increased LDL-C, similar to rare LDLR exonic variants. In conclusion, we conducted a systematic whole genome scan for blood lipids expanding the alleles linked to lipids for multiple ancestries and characterize a clinically-relevant rare non-coding variant model for lipids.

Testing for association with rare variants in the coding and non-coding genome: RAVA-FIRST, a new approach based on CADD deleteriousness score.

Rare variant association tests (RVAT) have been developed to study the contribution of rare variants widely accessible through high-throughput sequencing technologies. RVAT require to aggregate rare variants in testing units and to filter variants to retain only the most likely causal ones. In the exome, genes are natural testing units and variants are usually filtered based on their functional consequences. However, when dealing with whole-genome sequence (WGS) data, both steps are challenging. No natural biological unit is available for aggregating rare variants. Sliding windows procedures have been proposed to circumvent this difficulty, however they are blind to biological information and result in a large number of tests. We propose a new strategy to perform RVAT on WGS data: "RAVA-FIRST" (RAre Variant Association using Functionally-InfoRmed STeps) comprising three steps. (1) New testing units are defined genome-wide based on functionally-adjusted Combined Annotation Dependent Depletion (CADD) scores of variants observed in the gnomAD populations, which are referred to as "CADD regions". (2) A region-dependent filtering of rare variants is applied in each CADD region. (3) A functionally-informed burden test is performed with sub-scores computed for each genomic category within each CADD region. Both on simulations and real data, RAVA-FIRST was found to outperform other WGS-based RVAT. Applied to a WGS dataset of venous thromboembolism patients, we identified an intergenic region on chromosome 18 enriched for rare variants in early-onset patients. This region that was missed by standard sliding windows procedures is included in a TAD region that contains a strong candidate gene. RAVA-FIRST enables new investigations of rare non-coding variants in complex diseases, facilitated by its implementation in the R package Ravages.

TVAR: assessing tissue-specific functional effects of non-coding variants with deep learning.

Analysis of whole-genome sequencing (WGS) for genetics is still a challenge due to the lack of accurate functional annotation of non-coding variants, especially the rare ones. As eQTLs have been extensively implicated in the genetics of human diseases, we hypothesize that rare non-coding variants discovered in WGS play a regulatory role in predisposing disease risk. With thousands of tissue- and cell-type-specific epigenomic features, we propose TVAR. This multi-label learning-based deep neural network predicts the functionality of non-coding variants in the genome based on eQTLs across 49 human tissues in the GTEx project. TVAR learns the relationships between high-dimensional epigenomics and eQTLs across tissues, taking the correlation among tissues into account to understand shared and tissue-specific eQTL effects. As a result, TVAR outputs tissue-specific annotations, with an average AUROC of 0.77 across these tissues. We evaluate TVAR's performance on four complex diseases (coronary artery disease, breast cancer, Type 2 diabetes and Schizophrenia), using TVAR's tissue-specific annotations, and observe its superior performance in predicting functional variants for both common and rare variants, compared with five existing state-of-the-art tools. We further evaluate TVAR's G-score, a scoring scheme across all tissues, on ClinVar, fine-mapped GWAS loci, Massive Parallel Reporter Assay (MPRA) validated variants and observe the consistently better performance of TVAR compared with other competing tools. The TVAR source code and its scores on the ClinVar catalog, fine mapped GWAS Loci, high confidence eQTLs from GTEx dataset, and MPRA validated functional variants are available at https://github.com/haiyang1986/TVAR. Supplementary data are available at Bioinformatics online.

Massively parallel identification of functionally consequential noncoding genetic variants in undiagnosed rare disease patients

Clinical whole genome sequencing has enabled the discovery of potentially pathogenic noncoding variants in the genomes of rare disease patients with a prior history of negative genetic testing. However, interpreting the functional consequences of noncoding variants and distinguishing those that contribute to disease etiology remains a challenge. Here we address this challenge by experimentally profiling the functional consequences of rare noncoding variants detected in a cohort of undiagnosed rare disease patients at scale using a massively parallel reporter assay. We demonstrate that this approach successfully identifies rare noncoding variants that alter the regulatory capacity of genomic sequences. In addition, we describe an integrative analysis that utilizes genomic features alongside patient clinical data to further prioritize candidate variants with an increased likelihood of pathogenicity. This work represents an important step towards establishing a framework for the functional interpretation of clinically detected noncoding variants.