Variants In Non-coding Regions Research Articles

Identification of common predisposing loci to hematopoietic cancers in four dog breeds.

Histiocytic sarcoma (HS) is a rare but aggressive cancer in both humans and dogs. The spontaneous canine model, which has clinical, epidemiological, and histological similarities with human HS and specific breed predispositions, provides a unique opportunity to unravel the genetic basis of this cancer. In this study, we aimed to identify germline risk factors associated with the development of HS in canine-predisposed breeds. We used a methodology that combined several genome-wide association studies in a multi-breed and multi-cancer approach as well as targeted next-generation sequencing, and imputation We combined several dog breeds (Bernese mountain dogs, Rottweilers, flat-coated retrievers, and golden retrievers), and three hematopoietic cancers (HS, lymphoma, and mast cell tumor). Results showed that we not only refined the previously identified HS risk CDKN2A locus, but also identified new loci on canine chromosomes 2, 5, 14, and 20. Capture and targeted sequencing of specific loci suggested the existence of regulatory variants in non-coding regions and methylation mechanisms linked to risk haplotypes, which lead to strong cancer predisposition in specific dog breeds. We also showed that these canine cancer predisposing loci appeared to be due to the additive effect of several risk haplotypes involved in other hematopoietic cancers such as lymphoma or mast cell tumors as well. This illustrates the pleiotropic nature of these canine cancer loci as observed in human oncology, thereby reinforcing the interest of predisposed dog breeds to study cancer initiation and progression.

Functional Interrogation of Enhancer Connectome Prioritizes Candidate Target Genes at Ovarian Cancer Susceptibility Loci.

Identifying causal regulatory variants and their target genes from the majority of non-coding disease-associated genetic loci is the main challenge in post-Genome-Wide Association Studies (GWAS) functional studies. Although chromosome conformation capture (3C) and its derivative technologies have been successfully applied to nominate putative causal genes for non-coding variants, many GWAS target genes have not been identified yet. This study generated a high-resolution contact map from epithelial ovarian cancer (EOC) cells with two H3K27ac-HiChIP libraries and analyzed the underlying gene networks for 15 risk loci identified from the largest EOC GWAS. By combinatory analysis of 4,021 fine-mapped credible variants of EOC GWAS and high-resolution contact map, we obtained 162 target genes that mainly enriched in cancer related pathways. Compared with GTEx eQTL genes in ovarian tissue and annotated proximal genes, 132 HiChIP targets were first identified for EOC causal variants. More than half of the credible variants (CVs) involved interactions that were over 185 kb in distance, indicating that long-range transcriptional regulation is an important mechanism for the function of GWAS variants in EOC. We also found that many HiChIP gene targets showed significantly differential expressions between normal ovarian and EOC tumor samples. We validated one of these targets by manipulating the rs9303542 located region with CRISPR-Cas9 deletion and dCas9-VP64 activation experiments and found altered expression of HOXB7 and HOXB8 at 17q21.32. This study presents a systematic analysis to identify putative target genes for causal variants of EOC, providing an in-depth investigation of the mechanisms of non-coding regulatory variants in the etiology and pathogenesis of ovarian cancer.

Rare Recurrent Variants in Noncoding Regions Impact Attention-Deficit Hyperactivity Disorder (ADHD) Gene Networks in Children of both African American and European American Ancestry.

Attention-deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder with poorly understood molecular mechanisms that results in significant impairment in children. In this study, we sought to assess the role of rare recurrent variants in non-European populations and outside of coding regions. We generated whole genome sequence (WGS) data on 875 individuals, including 205 ADHD cases and 670 non-ADHD controls. The cases included 116 African Americans (AA) and 89 European Americans (EA), and the controls included 408 AA and 262 EA. Multiple novel rare recurrent variants were identified in exonic regions, functionally classified as stop-gains and frameshifts for known ADHD genes. Deletion in introns of the protocadherins families and the ncRNA HGB8P were identified in two independent EA ADHD patients. A meta-analysis of the two ethnicities for differential ADHD recurrent variants compared to controls shows a small number of overlaps. These results suggest that rare recurrent variants in noncoding regions may be involved in the pathogenesis of ADHD in children of both AA and EA ancestry; thus, WGS could be a powerful discovery tool for studying the molecular mechanisms of ADHD.

Disease-associated genetic variants in the regulatory regions of human genes: mechanisms of action on transcription and genomic resources for dissecting these mechanisms.

Whole genome and whole exome sequencing technologies play a very important role in the studies of the genetic aspects of the pathogenesis of various diseases. The ample use of genome-wide and exome-wide association study methodology (GWAS and EWAS) made it possible to identify a large number of genetic variants associated with diseases. This information is accumulated in the databases like GWAS central, GWAS catalog, OMIM, ClinVar, etc. Most of the variants identified by the GWAS technique are located in the noncoding regions of the human genome. According to the ENCODE project, the fraction of regions in the human genome potentially involved in transcriptional control is many times greater than the fraction of coding regions. Thus, genetic variation in noncoding regions of the genome can increase the susceptibility to diseases by disrupting various regulatory elements (promoters, enhancers, silencers, insulator regions, etc.). However, identification of the mechanisms of influence of pathogenic genetic variants on the diseases risk is difficult due to a wide variety of regulatory elements. The present review focuses on the molecular genetic mechanisms by which pathogenic genetic variants affect gene expression. At the same time, attention is concentrated on the transcriptional level of regulation as an initial step in the expression of any gene. A triggering event mediating the effect of a pathogenic genetic variant on the level of gene expression can be, for example, a change in the functional activity of transcription factor binding sites (TFBSs) or DNA methylation change, which, in turn, affects the functional activity of promoters or enhancers. Dissecting the regulatory roles of polymorphic loci have been impossible without close integration of modern experimental approaches with computer analysis of a growing wealth of genetic and biological data obtained using omics technologies. The review provides a brief description of a number of the most well-known public genomic information resources containing data obtained using omics technologies, including (1) resources that accumulate data on the chromatin states and the regions of transcription factor binding derived from ChIP-seq experiments; (2) resources containing data on genomic loci, for which allele-specific transcription factor binding was revealed based on ChIP-seq technology; (3) resources containing in silico predicted data on the potential impact of genetic variants on the transcription factor binding sites

A deep intronic variant is a common cause of OTC deficiency in individuals with previously negative genetic testing

Pathogenic variants in non-coding regions of genes encoding enzymes or transporters of the urea cycle can lead to urea cycle disorders (UCDs). However, not all commercially available testing platforms interrogate these regions. Here, we used a gene panel based on massively parallel sequencing (MPS) in 10 individuals with clinical or pedigree-based evidence of a proximal UCD but without a molecular confirmation of the diagnosis. We identified causal variant(s) in 5 of 10 individuals, including in 3 of 7 individuals in whom prior molecular testing was unrevealing. We show that a deep-intronic pathogenic variant in OTC, c.540+265G>A, is an important cause of ornithine transcarbamylase (OTC) deficiency.

Translating genetic risk variants in disease‐associated enhancers into novel mouse models of Alzheimer’s disease

AbstractBackgroundThe enrichment of late‐onset Alzheimer’s disease (LOAD) GWAS variants in noncoding regions of the genome reveals new potential for modeling disease risk. Yet, identifying noncoding causal variants and the cell types in which they are functional remains challenging. Translating noncoding variants into novel mouse models can elucidate phenotypic effects of those variants through specific perturbations of gene enhancers associated with LOAD risk.MethodWe developed a multi‐tier approach to translate noncoding GWAS risk variants into novel mouse models of LOAD. First, we used publicly available GWAS summary statistics and eQTL data from the AMP‐AD consortium (ROS/MAP, Mayo Clinic) across two brain regions (DLPFC, TCX) to prioritize LOAD risk variants. Then, a deep learning approach (DeepSEA) was implemented to identify regulatory variants in conserved enhancers that are likely to disrupt expression of nearby candidate genes in both human and mouse. Further, ATAC‐seq data from human and mouse was integrated to predict cell‐type specific effects of the prioritized regulatory elements. Finally, the top‐predicted disease‐associated variants were used to develop novel mouse models as part of the MODEL‐AD initiative.ResultOur integrative approach for prioritizing disease‐associated variants revealed a set of conserved risk variants that mediate the expression of nearby LOAD candidate genes in a cell type‐specific manner. These included several well‐known LOAD risk loci (BIN1, PT2KB, SCIMP, CD2AP). In addition, we identified a genome‐wide significant risk variant (rs4575098, p = 2.05 × 10(‐11), Jansen et al. 2019), which decreased expression of the novel candidate FCER1G in the brain of LOAD patients (ROS/MAP eQTL p = 1.81 × 10(‐05), beta = ‐0.27). This highly conserved variant resides in a microglia specific enhancer and overlaps with a binding site of the transcriptional regulator PU.1 (SPI1). We created a 2kb enhancer deletion mouse model for the FCER1G associated variant and knock‐in models for variants linked to increased expression in three well‐known GWAS loci (BIN1, SCIMP, PT2KB). We provide initial functional characterization for our novel models based on RNA‐seq data.ConclusionOur findings expand the list of LOAD candidate genes likely to be impacted by noncoding variants and provide a novel set of mouse models to study their effects in vivo.

GNA11 Variants Identified in Patients with Hypercalcemia or Hypocalcemia.

Familial hypocalciuric hypercalcemia type 2 (FHH2) and autosomal dominant hypocalcemia type 2 (ADH2) are due to loss- and gain-of-function mutations, respectively, of the GNA11 gene that encodes the G protein subunit Gα11, a signaling partner of the calcium-sensing receptor (CaSR). To date, four probands with FHH2-associated Gα11 mutations and eight probands with ADH2-associated Gα11 mutations have been reported. In a 10-year period, we identified 37 different germline GNA11 variants in >1200 probands referred for investigation of genetic causes for hypercalcemia or hypocalcemia, comprising 14 synonymous, 12 noncoding, and 11 nonsynonymous variants. The synonymous and noncoding variants were predicted to be benign or likely benign by in silico analysis, with 5 and 3, respectively, occurring in both hypercalcemic and hypocalcemic individuals. Nine of the nonsynonymous variants (Thr54Met, Arg60His, Arg60Leu, Gly66Ser, Arg149His, Arg181Gln, Phe220Ser, Val340Met, Phe341Leu) identified in 13 probands have been reported to be FHH2- or ADH2-causing. Of the remaining nonsynonymous variants, Ala65Thr was predicted to be benign, and Met87Val, identified in a hypercalcemic individual, was predicted to be of uncertain significance. Three-dimensional homology modeling of the Val87 variant suggested it was likely benign, and expression of Val87 variant and wild-type Met87 Gα11 in CaSR-expressing HEK293 cells revealed no differences in intracellular calcium responses to alterations in extracellular calcium concentrations, consistent with Val87 being a benign polymorphism. Two noncoding region variants, a 40bp-5'UTR deletion and a 15bp-intronic deletion, identified only in hypercalcemic individuals, were associated with decreased luciferase expression in vitro but no alterations in GNA11 mRNA or Gα11 protein levels in cells from the patient and no abnormality in splicing of the GNA11 mRNA, respectively, confirming them to be benign polymorphisms. Thus, this study identified likely disease-causing GNA11 variants in <1% of probands with hypercalcemia or hypocalcemia and highlights the occurrence of GNA11 rare variants that are benign polymorphisms. © 2023 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).

Population-scale study of eRNA transcription reveals bipartite functional enhancer architecture

Enhancer RNAs (eRNA) are unstable non-coding RNAs, transcribed bidirectionally from active regulatory sequences, whose expression levels correlate with enhancer activity. We use capped-nascent-RNA sequencing to efficiently capture bidirectional transcription initiation across several human lymphoblastoid cell lines (Yoruba population) and detect ~75,000 eRNA transcription sites with high sensitivity and specificity. The use of nascent-RNA sequencing sidesteps the confounding effect of eRNA instability. We identify quantitative trait loci (QTLs) associated with the level and directionality of eRNA expression. High-resolution analyses of these two types of QTLs reveal distinct positions of enrichment at the central transcription factor (TF) binding regions and at the flanking eRNA initiation regions, both of which are associated with mRNA expression QTLs. These two regions—the central TF-binding footprint and the eRNA initiation cores—define a bipartite architecture of enhancers, inform enhancer function, and can be used as an indicator of the significance of non-coding regulatory variants.

Genetic loci associated with prevalent and incident myocardial infarction and coronary heart disease in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium

BackgroundGenome-wide association studies have identified multiple genomic loci associated with coronary artery disease, but most are common variants in non-coding regions that provide limited information on causal genes and etiology of the disease. To overcome the limited scope that common variants provide, we focused our investigation on low-frequency and rare sequence variations primarily residing in coding regions of the genome.Methods and resultsUsing samples of individuals of European ancestry from ten cohorts within the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, both cross-sectional and prospective analyses were conducted to examine associations between genetic variants and myocardial infarction (MI), coronary heart disease (CHD), and all-cause mortality following these events. For prevalent events, a total of 27,349 participants of European ancestry, including 1831 prevalent MI cases and 2518 prevalent CHD cases were used. For incident cases, a total of 55,736 participants of European ancestry were included (3,031 incident MI cases and 5,425 incident CHD cases). There were 1,860 all-cause deaths among the 3,751 MI and CHD cases from six cohorts that contributed to the analysis of all-cause mortality. Single variant and gene-based analyses were performed separately in each cohort and then meta-analyzed for each outcome. A low-frequency intronic variant (rs988583) in PLCL1 was significantly associated with prevalent MI (OR = 1.80, 95% confidence interval: 1.43, 2.27; P = 7.12 × 10−7). We conducted gene-based burden tests for genes with a cumulative minor allele count (cMAC) ≥ 5 and variants with minor allele frequency (MAF) < 5%. TMPRSS5 and LDLRAD1 were significantly associated with prevalent MI and CHD, respectively, and RC3H2 and ANGPTL4 were significantly associated with incident MI and CHD, respectively. No loci were significantly associated with all-cause mortality following a MI or CHD event.ConclusionThis study identified one known locus (ANGPTL4) and four new loci (PLCL1, RC3H2, TMPRSS5, and LDLRAD1) associated with cardiovascular disease risk that warrant further investigation.

Various haploinsufficiency mechanisms in Pitt-Hopkins syndrome

Pitt-Hopkins syndrome is a rare neurodevelopment disorder caused by haploinsufficiency of the transcription factor 4 (TCF4). The main clinical symptoms of Pitt-Hopkins syndrome are severe development delay, intellectual disability, characteristic facial phenotype, and breathing abnormalities, including episodic hyperventilation. Different pathogenic variants can lead to Pitt-Hopkins syndrome. The most common are large deletions at 18q21 encompassing the TCF4 gene and frameshifting/nonsense single nucleotide variants. However, variants in noncoding regions can also lead to Pitt-Hopkins syndrome by disrupting the normal pre-mRNA splicing machinery. Here we describe three patients with Pitt-Hopkins syndrome caused by a large deletion in chromosome 18, a nonsense variant, and a novel variant located in intron 11 of TCF4 c.922+5G > A. Using RT-PCR analysis and minigene splicing assay we showed that this intronic variant leads to exon 11 skipping resulting in a formation of a premature stop codon. To our knowledge, this is the first functional annotation of a splicing variant in Pitt-Hopkins syndrome.

Functional fine-mapping of noncoding risk variants in amyotrophic lateral sclerosis utilizing convolutional neural network

Recent large-scale genome-wide association studies have identified common genetic variations that may contribute to the risk of amyotrophic lateral sclerosis (ALS). However, pinpointing the risk variants in noncoding regions and underlying biological mechanisms remains a major challenge. Here, we constructed a convolutional neural network model with a large-scale GWAS meta-analysis dataset to unravel functional noncoding variants associated with ALS based on their epigenetic features. After filtering and prioritizing of candidates, we fine-mapped two new risk variants, rs2370964 and rs3093720, on chromosome 3 and 17, respectively. Further analysis revealed that these polymorphisms are associated with the expression level of CX3CR1 and TNFAIP1, and affect the transcription factor binding sites for CTCF, NFATc1 and NR3C1. Our results may provide new insights for ALS pathogenesis, and the proposed research methodology can be applied for other complex diseases as well.

Effects of allele-specific open chromatin

Neurogenomics Genetic variants in noncoding regions of the genome may underlie the development of disease. However, we are just beginning to tease apart the function of such variants associated with neuropsychiatric disease. Using five types of neural progenitor cells derived from 20 human induced pluripotent stem cell lines, Zhang et al. looked at allele-specific open chromatin (ASoC) variants. Many ASoC variants overlapped with genomic elements, such as transcription factor binding sites, and loci identified in genome-wide association studies for neurological traits. From the experimental and computational analyses, they identified single-nucleotide polymorphisms and illuminate how one schizophrenia-associated variant affects neurodevelopment. Science , this issue p. [561][1] [1]: /lookup/doi/10.1126/science.aay3983

Predicting target genes of non-coding regulatory variants with IRT.

Interpreting genetic variants of unknown significance (VUS) is essential in clinical applications of genome sequencing for diagnosis and personalized care. Non-coding variants remain particularly difficult to interpret, despite making up a large majority of trait associations identified in genome-wide association studies (GWAS) analyses. Predicting the regulatory effects of non-coding variants on candidate genes is a key step in evaluating their clinical significance. Here, we develop a machine-learning algorithm, Inference of Connected expression quantitative trait loci (eQTLs) (IRT), to predict the regulatory targets of non-coding variants identified in studies of eQTLs. We assemble datasets using eQTL results from the Genotype-Tissue Expression (GTEx) project and learn to separate positive and negative pairs based on annotations characterizing the variant, gene and the intermediate sequence. IRT achieves an area under the receiver operating characteristic curve (ROC-AUC) of 0.799 using random cross-validation, and 0.700 for a more stringent position-based cross-validation. Further evaluation on rare variants and experimentally validated regulatory variants shows a significant enrichment in IRT identifying the true target genes versus negative controls. In gene-ranking experiments, IRT achieves a top-1 accuracy of 50% and top-3 accuracy of 90%. Salient features, including GC-content, histone modifications and Hi-C interactions are further analyzed and visualized to illustrate their influences on predictions. IRT can be applied to any VUS of interest and each candidate nearby gene to output a score reflecting the likelihood of regulatory effect on the expression level. These scores can be used to prioritize variants and genes to assist in patient diagnosis and GWAS follow-up studies. Codes and data used in this work are available at https://github.com/miaecle/eQTL_Trees. Supplementary data are available at Bioinformatics online.

Noncoding Variants Connect Enhancer Dysregulation with Nuclear Receptor Signaling in Hematopoietic Malignancies.

Mutations in protein-coding genes are well established as the basis for human cancer, yet how alterations within noncoding genome, a substantial fraction of which contain cis-regulatory elements (CRE), contribute to cancer pathophysiology remains elusive. Here, we developed an integrative approach to systematically identify and characterize noncoding regulatory variants with functional consequences in human hematopoietic malignancies. Combining targeted resequencing of hematopoietic lineage-associated CREs and mutation discovery, we uncovered 1,836 recurrently mutated CREs containing leukemia-associated noncoding variants. By enhanced CRISPR/dCas9-based CRE perturbation screening and functional analyses, we identified 218 variant-associated oncogenic or tumor-suppressive CREs in human leukemia. Noncoding variants at KRAS and PER2 enhancers reside in proximity to nuclear receptor (NR) binding regions and modulate transcriptional activities in response to NR signaling in leukemia cells. NR binding sites frequently colocalize with noncoding variants across cancer types. Hence, recurrent noncoding variants connect enhancer dysregulation with nuclear receptor signaling in hematopoietic malignancies. SIGNIFICANCE: We describe an integrative approach to identify noncoding variants in human leukemia, and reveal cohorts of variant-associated oncogenic and tumor-suppressive cis-regulatory elements including KRAS and PER2 enhancers. Our findings support a model in which noncoding regulatory variants connect enhancer dysregulation with nuclear receptor signaling to modulate gene programs in hematopoietic malignancies.See related commentary by van Galen, p. 646.This article is highlighted in the In This Issue feature, p. 627.

Evidence for craniofacial enhancer variation underlying nonsyndromic cleft lip and palate

Nonsyndromic cleft lip with or without cleft palate (NSCLP) is a common birth defect for which only ~ 20% of the underlying genetic variation has been identified. Variants in noncoding regions have been increasingly suggested to contribute to the missing heritability. In this study, we investigated whether variation in craniofacial enhancers contributes to NSCLP. Candidate enhancers were identified using VISTA Enhancer Browser and previous publications. Prioritization was based on patterning defects in knockout mice, deletion/duplication of craniofacial genes in animal models and results of whole exome/whole genome sequencing studies. This resulted in 20 craniofacial enhancers to be investigated. Custom amplicon-based sequencing probes were designed and used for sequencing 380 NSCLP probands (from multiplex and simplex families of non-Hispanic white (NHW) and Hispanic ethnicities) using Illumina MiSeq. The frequencies of identified variants were compared to ethnically matched European (CEU) and Los Angeles Mexican (MXL) control genomes and used for association analyses. Variants in mm427/MSX1 and hs1582/SPRY1 showed genome-wide significant association with NSCLP (p ≤ 6.4 × 10-11). In silico analysis showed that these enhancer variants may disrupt important transcription factor binding sites. Haplotypes involving these enhancers and also mm435/ABCA4 were significantly associated with NSCLP, especially in NHW (p ≤ 6.3 × 10-7). Importantly, groupwise burden analysis showed several enhancer combinations significantly over-represented in NSCLP individuals, revealing novel NSCLP pathways and supporting a polygenic inheritance model. Our findings support the role of craniofacial enhancer sequence variation in the etiology of NSCLP.

Structural variations in a non-coding region at 1q32.1 are responsible for the NYS7 locus in two large families

Congenital motor nystagmus (CMN) is characterized by early-onset bilateral ocular oscillations without other ocular deficits. To date, mutations in only one gene have been identified to be responsible for CMN, i.e., FRMD7 for X-linked CMN. Four loci for autosomal dominant CMN, including NYS7 (OMIM 614826), have been mapped but the causative genes have yet to be identified. NYS7 was mapped to 1q32.1 based on independent genome-wide linkage scan on two large families with CMN. In this study, mutations in all known protein-coding genes, both intronic sequence with predicted effect and coding sequence, in the linkage interval were excluded by whole-genome sequencing. Then, long-read genome sequencing based on the Nanopore platform was performed with a sample from each of the two families. Two deletions with an overlapping region of 775,699 bp, located in a region without any known protein-coding genes, were identified in the two families in the linkage region. The two deletions as well as their breakpoints were confirmed by Sanger sequencing and co-segregated with CMN in the two families. The 775,699 bp deleted region contains uncharacterized non-protein-coding expressed sequences and pseudogenes but no protein-coding genes. However, Hi-C data predicted that the deletions span two topologically associated domains and probably lead to a change in the 3D genomic architecture. These results provide novel evidence of a strong association between structural variations in non-coding genomic regions and human hereditary diseases like CMN with a potential mechanism involving changes in 3D genome architecture, which provides clues regarding the molecular pathogenicity of CMN.

A de novo 2.2\u2009Mb recurrent 17q23.1q23.2 deletion unmasks novel putative regulatory non-coding SNVs associated with lethal lung hypoplasia and pulmonary hypertension: a case report

BackgroundApplication of whole genome sequencing (WGS) enables identification of non-coding variants that play a phenotype-modifying role and are undetectable by exome sequencing. Recently, non-coding regulatory single nucleotide variants (SNVs) have been reported in patients with lethal lung developmental disorders (LLDDs) or congenital scoliosis with recurrent copy-number variant (CNV) deletions at 17q23.1q23.2 or 16p11.2, respectively.Case presentationHere, we report a deceased newborn with pulmonary hypertension and pulmonary interstitial emphysema with features suggestive of pulmonary hypoplasia, resulting in respiratory failure and neonatal death soon after birth. Using the array comparative genomic hybridization and WGS, two heterozygous recurrent CNV deletions: ~ 2.2 Mb on 17q23.1q23.2, involving TBX4, and ~ 600 kb on 16p11.2, involving TBX6, that both arose de novo on maternal chromosomes were identified. In the predicted lung-specific enhancer upstream to TBX4, we have detected seven novel putative regulatory non-coding SNVs that were absent in 13 control individuals with the overlapping deletions but without any structural lung anomalies.ConclusionsOur findings further support a recently reported model of complex compound inheritance of LLDD in which both non-coding and coding heterozygous TBX4 variants contribute to the lung phenotype. In addition, this is the first report of a patient with combined de novo heterozygous recurrent 17q23.1q23.2 and 16p11.2 CNV deletions.

Analyses of non-coding somatic drivers in 2,658 cancer whole genomes

The discovery of drivers of cancer has traditionally focused on protein-coding genes1–4. Here we present analyses of driver point mutations and structural variants in non-coding regions across 2,658 genomes from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium5 of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). For point mutations, we developed a statistically rigorous strategy for combining significance levels from multiple methods of driver discovery that overcomes the limitations of individual methods. For structural variants, we present two methods of driver discovery, and identify regions that are significantly affected by recurrent breakpoints and recurrent somatic juxtapositions. Our analyses confirm previously reported drivers6,7, raise doubts about others and identify novel candidates, including point mutations in the 5′ region of TP53, in the 3′ untranslated regions of NFKBIZ and TOB1, focal deletions in BRD4 and rearrangements in the loci of AKR1C genes. We show that although point mutations and structural variants that drive cancer are less frequent in non-coding genes and regulatory sequences than in protein-coding genes, additional examples of these drivers will be found as more cancer genomes become available.

Differential Allele-Specific Expression Uncovers Breast Cancer Genes Dysregulated by Cis Noncoding Mutations.

Identifying cancer-relevant mutations in noncoding regions is challenging due to the large numbers of such mutations, their low levels of recurrence, and difficulties in interpreting their functional impact. To uncover genes that are dysregulated due to somatic mutations in cis, we build upon the concept of differential allele-specific expression (ASE) and introduce methods to identify genes within an individual's cancer whose ASE differs from what is found in matched normal tissue. When applied to breast cancer tumor samples, our methods detect the known allele-specific effects of copy number variation and nonsense-mediated decay. Further, genes that are found to recurrently exhibit differential ASE across samples are cancer relevant. Genes with cis mutations are enriched for differential ASE, and we find 147 potentially functional noncoding mutations cis to genes that exhibit significant differential ASE. We conclude that differential ASE is a promising means for discovering gene dysregulation due to cis noncoding mutations.

Gene Expression in Patient-Derived Neural Progenitors Implicates WNT5A Signaling in the Etiology of Schizophrenia

BackgroundGenome-wide association studies of schizophrenia have demonstrated that variations in noncoding regions are responsible for most of the common variation heritability of the disease. It is hypothesized that these risk variants alter gene expression. Therefore, studying alterations in gene expression in schizophrenia may provide a direct approach to understanding the etiology of the disease. In this study we use cultured neural progenitor cells derived from olfactory neuroepithelium (CNON cells) as a genetically unaltered cellular model to elucidate the neurodevelopmental aspects of schizophrenia. MethodsWe performed a gene expression study using RNA sequencing of CNON cells from 111 control subjects and 144 individuals with schizophrenia. Differentially expressed genes were identified with DESeq2 software, using covariates to correct for sex, age, library batches, and 1 surrogate variable component. ResultsA total of 80 genes were differentially expressed (false discovery rate < 10%), showing enrichment in cell migration, cell adhesion, developmental process, synapse assembly, cell proliferation, and related Gene Ontology categories. Cadherin and Wnt signaling pathways were positive in overrepresentation test, and, in addition, many genes were specifically involved in WNT5A signaling. The differentially expressed genes were modestly, but significantly, enriched in the genes overlapping single nucleotide polymorphisms with genome-wide significant association from the Psychiatric Genomics Consortium genome-wide association study of schizophrenia. We also found substantial overlap with genes associated with other psychiatric disorders or brain development, enrichment in the same Gene Ontology categories as genes with mutations de novo in schizophrenia, and studies of induced pluripotent stem cell–derived neural progenitor cells. ConclusionsCNON cells are a good model of the neurodevelopmental aspects of schizophrenia and can be used to elucidate the etiology of the disorder.