Exon-level Analysis Research Articles

Landscape of pathogenic germline variants in patients with lung cancer.

388570 Background: Few studies have aimed to investigate the prevalence and spectrum of pathogenic germline variants (PGVs) in patients diagnosed with lung cancer. Given the growing opportunities for precision therapies based on PGVs in DNA damage-repair (DDR)/homologous recombination-repair (HRR) genes and the importance of identifying PGVs to inform future cancer screening and cascade testing, we investigated the prevalence and potential clinical implications of PGVs in individuals with lung cancer. Methods: Deidentified data were retrospectively reviewed for 7,788 individuals diagnosed with lung cancer for whom germline DNA sequencing and exon-level copy number analysis were performed between 2014-2022 at a commercial diagnostic laboratory. The diagnosis of lung cancer was based on ICD-10 codes or language on the test requisition suggesting a primary lung cancer diagnosis. Individuals with requisitions suggesting lung metastases, neuroendocrine tumors or sarcomas as the basis for testing were excluded. Number of genes tested varied per ordering clinician preference. Clinically actionable PGVs were defined as those associated with clinical management recommendations or trial eligibility per current, standard of care guidelines. Descriptive statistics were utilized. Results: The cohort was predominantly female (71.1%), White (64.5%), and most had a history of > 1 cancer (71.1%). A median of 79 genes (range 1-159) were tested. Testing identified 1,503 PGVs in 81 known cancer-risk genes in 1,161/7,788 (14.9%) patients; an additional 229 (2.9%) patients carried a single PGV in a gene associated with autosomal recessive inheritance. PGV rates stratified by self-reported ancestry: Black/African American, 11.8%; Asian or Pacific Islander, 11.8%; Hispanic, 14.5%; White, 15.4%. Among genes with >1,000 individuals tested, PGVs were most common in BRCA2 (2.8%), CHEK2 (2.1%), ATM (1.9%), TP53 (1.3%), BRCA1 (1.2%), and EGFR (1.0%). Of 1,161 individuals, 712 (61.3%) had a PGV in a DDR/HRR gene, making them potentially eligible for a clinical treatment trial, and 1,104/1,161 (95.1%) had a PGV that was potentially clinically actionable. Conclusions: From this large cohort of individuals with lung cancer, 14.9% had PGVs, nearly all of which were clinically actionable. Notably, HRR PGVs were common (64%). Currently, the U.S. Food and Drug Administration has approved and the National Comprehensive Cancer Network Guidelines endorse targeted therapies for patients with breast, pancreatic, prostate, and ovarian cancers who carry HRR PGVs. Recently, the NCCN Guidelines panel recommended germline testing be considered for all patients diagnosed with colorectal cancer. Given the profound implications for both patients and their families that result from identifying PGVs, our results suggest that all patients with lung cancer also be considered for germline genetic testing.

Zhx2 Is a Candidate Gene Underlying Oxymorphone Metabolite Brain Concentration Associated with State-Dependent Oxycodone Reward.

Understanding the pharmacogenomics of opioid metabolism and behavior is vital to therapeutic success, as mutations can dramatically alter therapeutic efficacy and addiction liability. We found robust, sex-dependent BALB/c substrain differences in oxycodone behaviors and whole brain concentration of oxycodone metabolites. BALB/cJ females showed robust state-dependent oxycodone reward learning as measured via conditioned place preference when compared with the closely related BALB/cByJ substrain. Accordingly, BALB/cJ females also showed a robust increase in brain concentration of the inactive metabolite noroxycodone and the active metabolite oxymorphone compared with BALB/cByJ mice. Oxymorphone is a highly potent, full agonist at the mu opioid receptor that could enhance drug-induced interoception and state-dependent oxycodone reward learning. Quantitative trait locus (QTL) mapping in a BALB/c F2 reduced complexity cross revealed one major QTL on chromosome 15 underlying brain oxymorphone concentration that explained 32% of the female variance. BALB/cJ and BALB/cByJ differ by fewer than 10,000 variants, which can greatly facilitate candidate gene/variant identification. Hippocampal and striatal cis-expression QTL (eQTL) and exon-level eQTL analysis identified Zhx2, a candidate gene coding for a transcriptional repressor with a private BALB/cJ retroviral insertion that reduces Zhx2 expression and sex-dependent dysregulation of cytochrome P450 enzymes. Whole brain proteomics corroborated the Zhx2 eQTL and identified upregulated CYP2D11 that could increase brain oxymorphone in BALB/cJ females. To summarize, Zhx2 is a highly promising candidate gene underlying brain oxycodone metabolite levels. Future studies will validate Zhx2 and its site of action using reciprocal gene editing and tissue-specific viral manipulations in BALB/c substrains. SIGNIFICANCE STATEMENT: Our findings show that genetic variation can result in sex-specific alterations in whole brain concentration of a bioactive opioid metabolite after oxycodone administration, reinforcing the need for sex as a biological factor in pharmacogenomic studies. The cooccurrence of female-specific increased oxymorphone and state-dependent reward learning suggests that this minor yet potent and efficacious metabolite of oxycodone could increase opioid interoception and drug-cue associative learning of opioid reward, which has implications for cue-induced relapse of drug-seeking behavior and for precision pharmacogenetics.

32. Genetic testing for individuals with non-syndromic differences in sex development (DSD): collaborative approach yields results

Differences of Sex Development (DSD) are a group of conditions in which there is atypical anatomic, gonadal, or chromosomal sex. With input from multiple stakeholders, our laboratory recently validated a genetic testing panel for non-syndromic DSD, which utilizes targeted next generation sequencing and exon-level microarray analysis. Data from the first 37 consecutive tests is presented here. The majority of patients in this cohort were evaluated in our institution's DSD clinic, which includes providers specializing in pediatric and reproductive endocrinology, genetics, urology, gynecology and child and adolescent psychology. Almost all patients had prior karyotype, SRY FISH, and/or chromosomal microarray testing. Exclusion criteria for panel testing included the presence of syndromic features or suspected 21-hydryoxylase deficiency. Pathogenic or likely pathogenic variants in genes associated with dominant conditions were reported for 15 (40.5%) individuals. The pathogenic and likely pathogenic variants were identified in 10 different genes: AMH, AMHR2, ANOS1, AR (in 5 unrelated individuals), CYP17A1, MAMLD1 (in two unrelated individuals), MAP3K1, PROKR2, SRY, and STAR. For 3 other individuals (8%), a single pathogenic variant was reported in a gene associated with a recessive condition. Variants of uncertain clinical significance were reported for 5 individuals (13.5%), and no variants were reported for 14 individuals (38%). Close collaboration between the laboratory and the clinical team during the test validation process, as well as ongoing discussions surrounding test utilization, enabled development of a panel most appropriate for our patient population, with a high diagnostic rate. The targeted panel approach avoided issues related to incidental findings and contributed to the lower rate of reported variants of uncertain significance. Future goals for the DSD panel include streamlining the laboratory workflow and regular updates to panel content to include genes recently implicated in DSD-related conditions.

Phenotypic expansion and variable expressivity in individuals with JARID2-related intellectual disability: A case series.

Loss of function variants in JARID2 were recently reported in 16 patients with a neurodevelopmental disorder characterized by delays, intellectual and learning disability, autism, behavioral abnormalities, and dysmorphic features. Most cases were de novo, with only one variant inherited from an affected parent. Here, we present seven additional individuals from five families with pathogenic or likely pathogenic JARID2 variants, confirming this gene-disease association and highlighting palatal abnormalities and heart defects as part of the phenotype. In addition, we report inheritance of JARID2 variants from mildly affected parents, demonstrating the variable expressivity of the disease. We also note the high prevalence of intragenic JARID2 copy number variants, emphasizing the importance of exon-level analysis.

Prenatal hydrops fetalis associated with infantile free sialic acid storage disease due to a novel homozygous deletion in the SLC17A5 gene

Nonimmune hydrops fetalis, the excessive accumulation of serous fluid in the subcutaneous tissues and serous cavities of the fetus, has many possible etiologies, providing a diagnostic challenge for the physician. Lysosomal storage diseases have been reported in up to 5%–16% of nonimmune hydrops fetalis pregnancies. Infantile free sialic acid storage disease (ISSD) (OMIM #269920) is a severe form of autosomal recessive sialic acid storage disease. ISSD is caused by mutations in SLC17A5 (OMIM #604322), which encodes sialin, a lysosomal-membrane sialic acid transporter. We describe a case of fetal hydrops due to a novel homozygous deletion in the SLC17A5 gene. Prenatal single-nucleotide polymorphism (SNP) array analysis was performed on amniocytes after the discovery of fetal hydrops at 24 wk gestation revealing no copy-number variants. The SNP array, however, reported several regions of homozygosity (ROHs) including one on Chromosome 6 encompassing the SLC17A5 gene. High levels of urine sialic acid in the newborn were detected. SLC17A5 gene sequencing was initiated with no sequence variants identified; however, the assay failed to amplify exons 8 and 9, prompting an exon-level copy-number analysis that revealed a novel homozygous deletion of exons 8 and 9, inherited from heterozygous carrier parents. ISSD should be considered in the workup of patients with nonimmune hydrops fetalis, and analysis for SLC17A5 deletions should be carried out when variants are not detected by gene sequencing.

23. Incidental findings on XON array: Our experience over the last two years

Exon-level copy number variation (CNV) can be difficult to assess using whole-exome sequencing (WES) or whole-genome SNP microarray (CMA). The clinical implementation of the CytoScan XON array has allowed for the evaluation of exon-level CNVs that previously were either difficult to identify or missed entirely by preceding testing methods. Increasing the resolution of detection has not only aided in diagnosis of recessive disorders in which exome analysis identified a single variant within a candidate gene, but has also been useful in the diagnosis of dominant disorders in cases for which exome and/or CMA is negative. Furthermore, the increased resolution of detection in the assessment of exon-level CNVs has led to the discovery of significant incidental findings in a select few cases. In this report, we assess the prevalence and clinical significance of incidental findings detected by clinical XON array analysis over the last two years at the Greenwood Genetic Center. To illustrate our findings, four cases have been selected from approximately 300 to date with various clinical indications including: abnormal prenatal screening, hearing loss accompanied by developmental delay, and two cases with multiple congenital anomalies. For each case presented, previous testing was unremarkable and XON array analysis of phenotype-driven genes was negative. However, further analysis of the unmasked XON array data identified a potential causative aberration in each patient (e.g. exonic CNVs involving: CDH23, ARSA, PKD1 and ARID1A). This collection of cases not only demonstrates the utility and potential of the XON array in the context of complicated cases with unknown genetic etiology for which WES and CMA is negative, but provides further evidence for the importance of incidental findings in exon-level analysis.

Proteomic and Transcriptomic Analysis Identify Spliceosome as a Significant Component of the Molecular Machinery in the Pituitary Tumors Derived from POU1F1- and NR5A1-Cell Lineages.

Background: Pituitary adenomas (PA) are the second most common tumor in the central nervous system and have low counts of mutated genes. Splicing occurs in 95% of the coding RNA. There is scarce information about the spliceosome and mRNA-isoforms in PA, and therefore we carried out proteomic and transcriptomic analysis to identify spliceosome components and mRNA isoforms in PA. Methods: Proteomic profile analysis was carried out by nano-HPLC and mass spectrometry with a quadrupole time-of-flight mass spectrometer. The mRNA isoforms and transcriptomic profiles were carried out by microarray technology. With proteins and mRNA information we carried out Gene Ontology and exon level analysis to identify splicing-related events. Results: Approximately 2000 proteins were identified in pituitary tumors. Spliceosome proteins such as SRSF1, U2AF1 and RBM42 among others were found in PA. These results were validated at mRNA level, which showed up-regulation of spliceosome genes in PA. Spliceosome-related genes segregate and categorize PA tumor subtypes. The PA showed alterations in CDK18 and THY1 mRNA isoforms which could be tumor specific. Conclusions: Spliceosome components are significant constituents of the PA molecular machinery and could be used as molecular markers and therapeutic targets. Splicing-related genes and mRNA-isoforms profiles characterize tumor subtypes.

5' UTR variants in the quantitative trait gene Hnrnph1 support reduced 5' UTR usage and hnRNP H protein as a molecular mechanism underlying reduced methamphetamine sensitivity.

We previously identified a 210kb region on chromosome 11 (50.37-50.58Mb, mm10) containing two protein-coding genes (Hnrnph1, Rufy1) that was necessary for reduced methamphetamine-induced locomotor activity in C57BL/6J congenic mice harboring DBA/2J polymorphisms. Gene editing of a small deletion in the first coding exon supported Hnrnph1 as a quantitative trait gene. We have since shown that Hnrnph1 mutants also exhibit reduced methamphetamine-induced reward, reinforcement, and dopamine release. However, the quantitative trait variants (QTVs) that modulate Hnrnph1 function at the molecular level are not known. Nine single nucleotide polymorphisms and seven indels distinguish C57BL/6J from DBA/2J within Hnrnph1, including four variants within the 5' untranslated region (UTR). Here, we show that a 114kb introgressed region containing Hnrnph1 and Rufy1 was sufficient to cause a decrease in MA-induced locomotor activity. Gene-level transcriptome analysis of striatal tissue from 114kb congenics vs Hnrnph1 mutants identified a nearly perfect correlation of fold-change in expression for those differentially expressed genes that were common to both mouse lines, indicating functionally similar effects on the transcriptome and behavior. Exon-level analysis (including noncoding exons) revealed decreased 5' UTR usage of Hnrnph1 and immunoblot analysis identified a corresponding decrease in hnRNP H protein in 114kb congenic mice. Molecular cloning of the Hnrnph1 5' UTR containing all four variants (but none of them individually) upstream of a reporter induced a decrease in reporter signal in both HEK293 and N2a cells, thus, identifying a set of QTVs underlying molecular regulation of Hnrnph1.

Pathway-guided analysis identifies Myc-dependent alternative pre-mRNA splicing in aggressive prostate cancers

We sought to define the landscape of alternative pre-mRNA splicing in prostate cancers and the relationship of exon choice to known cancer driver alterations. To do so, we compiled a metadataset composed of 876 RNA-sequencing (RNA-Seq) samples from five publicly available sources representing a range of prostate phenotypes from normal tissue to drug-resistant metastases. We subjected these samples to exon-level analysis with rMATS-turbo, purpose-built software designed for large-scale analyses of splicing, and identified 13,149 high-confidence cassette exon events with variable incorporation across samples. We then developed a computational framework, pathway enrichment-guided activity study of alternative splicing (PEGASAS), to correlate transcriptional signatures of 50 different cancer driver pathways with these alternative splicing events. We discovered that Myc signaling was correlated with incorporation of a set of 1,039 cassette exons enriched in genes encoding RNA binding proteins. Using a human prostate epithelial transformation assay, we confirmed the Myc regulation of 147 of these exons, many of which introduced frameshifts or encoded premature stop codons. Our results connect changes in alternative pre-mRNA splicing to oncogenic alterations common in prostate and many other cancers. We also establish a role for Myc in regulating RNA splicing by controlling the incorporation of nonsense-mediated decay-determinant exons in genes encoding RNA binding proteins.

Germline multigene panel testing in colorectal cancer: Precision therapy and clinical management implications.

3582 Background: Recent studies suggest that the prevalence of abnormalities in homologous recombination deficiency (HRD) genes and other cancer genes not traditionally associated with colorectal cancer (CRC) may be more common in patients with CRC than previously appreciated. Herein, we investigate the efficacy of comprehensive multigene panels in patients with CRC to identify candidates for precision therapies. Methods: DNA sequencing and exon-level copy number analysis were performed in over 9000 patients (pts) referred because of personal history of colon cancer between 2013 and 2018 at a commercial diagnostic laboratory. The genes requisitioned varied but consistently included 14 genes on a hereditary CRC panel; the patient data were de-identified and further analyzed for all 83 genes on a large hereditary cancer syndrome panel under an IRB-approved protocol. Results: Pathogenic/likely pathogenic (P/LP) findings were identified in 2101 of 9669 pts (21%), 1838 (19%) pts when MUTYH heterozygotes are excluded. When restricted to five Lynch syndrome (LS) genes, only 9% of patients had a P/LP finding, which increased to 15% of patients when 19 guidelines-based CRC genes were assessed. 137 pts (1.4%) had two or more P/LP variants. P/LP variants were in MLH1, MSH2, MSH6, PMS2, CHEK2, APC, MUTYH, BRCA2, ATM, BRCA1, PALB2, RAD50, BRIP1, TP53, EPCAM, among others, of which 1.4% were BRCA1/2. When a comprehensive multigene panel was utilized P/LP variants in genes with known therapeutic implications, such as in HRD and mismatch repair deficiency (MMRD), were detected in 1408 (14%) of patients, and 1670 (17%) had P/LP variants in genes with established clinical management guidelines. Conclusions: This study suggests that 1 in 5 patients with CRC harbor actionable germline variants, up to one-half of which remain undetected when only LS genes are tested. Comprehensive panel testing identified candidates for precision treatment and established management recommendations, and have clinical implications for both pts and their at risk family members.

Using equivalence class counts for fast and accurate testing of differential transcript usage.

Background: RNA sequencing has enabled high-throughput and fine-grained quantitative analyses of the transcriptome. While differential gene expression is the most widely used application of this technology, RNA-seq data also has the resolution to infer differential transcript usage (DTU), which can elucidate the role of different transcript isoforms between experimental conditions, cell types or tissues. DTU has typically been inferred from exon-count data, which has issues with assigning reads unambiguously to counting bins, and requires alignment of reads to the genome. Recently, approaches have emerged that use transcript quantification estimates directly for DTU. Transcript counts can be inferred from 'pseudo' or lightweight aligners, which are significantly faster than traditional genome alignment. However, recent evaluations show lower sensitivity in DTU analysis compared to exon-level analysis. Transcript abundances are estimated from equivalence classes (ECs), which determine the transcripts that any given read is compatible with. Recent work has proposed performing a variety of RNA-seq analysis directly on equivalence class counts (ECCs). Methods: Here we demonstrate that ECCs can be used effectively with existing count-based methods for detecting DTU. We evaluate this approach on simulated human and drosophila data, as well as on a real dataset through subset testing. Results: We find that ECCs have similar sensitivity and false discovery rates as exon-level counts but can be generated in a fraction of the time through the use of pseudo-aligners. Conclusions: We posit that equivalence class read counts are a natural unit on which to perform differential transcript usage analysis.

Using equivalence class counts for fast and accurate testing of differential transcript usage

Background: RNA sequencing has enabled high-throughput and fine-grained quantitative analyses of the transcriptome. While differential gene expression is the most widely used application of this technology, RNA-seq data also has the resolution to infer differential transcript usage (DTU), which can elucidate the role of different transcript isoforms between experimental conditions, cell types or tissues. DTU has typically been inferred from exon-count data, which has issues with assigning reads unambiguously to counting bins, and requires alignment of reads to the genome. Recently, approaches have emerged that use transcript quantification estimates directly for DTU. Transcript counts can be inferred from 'pseudo' or lightweight aligners, which are significantly faster than traditional genome alignment. However, recent evaluations show lower sensitivity in DTU analysis compared to exon-level analysis. Transcript abundances are estimated from equivalence classes (ECs), which determine the transcripts that any given read is compatible with. Recent work has proposed performing a variety of RNA-seq analysis directly on equivalence class counts (ECCs). Methods: Here we demonstrate that ECCs can be used effectively with existing count-based methods for detecting DTU. We evaluate this approach on simulated human and drosophila data, as well as on a real dataset through subset testing. Results: We find that ECCs have similar sensitivity and false discovery rates as exon-level counts but can be generated in a fraction of the time through the use of pseudo-aligners. Conclusions: We posit that equivalence class read counts are a natural unit on which to perform differential transcript usage analysis.

Exon level machine learning analyses elucidate novel candidate miRNA targets in an avian model of fetal alcohol spectrum disorder.

Gestational alcohol exposure causes fetal alcohol spectrum disorder (FASD) and is a prominent cause of neurodevelopmental disability. Whole transcriptome sequencing (RNA-Seq) offer insights into mechanisms underlying FASD, but gene-level analysis provides limited information regarding complex transcriptional processes such as alternative splicing and non-coding RNAs. Moreover, traditional analytical approaches that use multiple hypothesis testing with a false discovery rate adjustment prioritize genes based on an adjusted p-value, which is not always biologically relevant. We address these limitations with a novel approach and implemented an unsupervised machine learning model, which we applied to an exon-level analysis to reduce data complexity to the most likely functionally relevant exons, without loss of novel information. This was performed on an RNA-Seq paired-end dataset derived from alcohol-exposed neural fold-stage chick crania, wherein alcohol causes facial deficits recapitulating those of FASD. A principal component analysis along with k-means clustering was utilized to extract exons that deviated from baseline expression. This identified 6857 differentially expressed exons representing 1251 geneIDs; 391 of these genes were identified in a prior gene-level analysis of this dataset. It also identified exons encoding 23 microRNAs (miRNAs) having significantly differential expression profiles in response to alcohol. We developed an RDAVID pipeline to identify KEGG pathways represented by these exons, and separately identified predicted KEGG pathways targeted by these miRNAs. Several of these (ribosome biogenesis, oxidative phosphorylation) were identified in our prior gene-level analysis. Other pathways are crucial to facial morphogenesis and represent both novel (focal adhesion, FoxO signaling, insulin signaling) and known (Wnt signaling) alcohol targets. Importantly, there was substantial overlap between the exomes themselves and the predicted miRNA targets, suggesting these miRNAs contribute to the gene-level expression changes. Our novel application of unsupervised machine learning in conjunction with statistical analyses facilitated the discovery of signaling pathways and miRNAs that inform mechanisms underlying FASD.

Transcriptome analysis reveals an altered expression profile of zinc transporters in colorectal cancer

Zinc is a transition metal and catalytic cofactor involved in many biological processes including proliferation, development, differentiation, and metabolism. Zinc transporters (ZnTs) play a fundamental role in cellular zinc homeostasis. ZnTsare responsible of zinc efflux and are encoded by 10 genes belonging to solute carrier family 30A (SLC30A1-10), while zinc-regulated transporter (ZRT)/iron-regulated transporter (IRT)-like protein (ZIP) transporters are responsible for the influx of zinc into the cytoplasm and are encoded by 14 genes belonging to solute carrier family 39A (SLC39A1-14). In this study, we analyzed, by transcriptome analysis, the microRNA levels of ZnT-encoding and ZIP-encoding genes in colorectal cancer (CRC) samples matched to normal colon tissues and in CRC cell lines. Results revealed an upregulation of specific ZnT and ZIP transcripts in CRC. Upregulation of SLC30A5, SLC30A6, SLC30A7 transcripts, encoding zinc efflux transporters ZnT5, ZnT6,ZnT7, localized on endoplasmic reticulummembranes, might be part of a coordinated transcriptional program associated to the increased activity of the early secretory pathway, while transcriptional upregulation of several specific ZIP transporters (SLC39A6, SLC39A7, SLC39A9, SLC39A10, and SLC39A11) could contribute in meeting the increased demand of zinc in cancer cells. Moreover, exon-level analysis of SLC30A9, a nuclear receptor coactivator involved in the transcriptional regulation of Wnt-responsive genes, revealed the differential expression of alternative transcripts in CRC and normal colonic mucosa.

Profiling RNA-Seq at multiple resolutions markedly increases the number of causal eQTLs in autoimmune disease.

Genome-wide association studies have identified hundreds of risk loci for autoimmune disease, yet only a minority (~25%) share genetic effects with changes to gene expression (eQTLs) in immune cells. RNA-Seq based quantification at whole-gene resolution, where abundance is estimated by culminating expression of all transcripts or exons of the same gene, is likely to account for this observed lack of colocalisation as subtle isoform switches and expression variation in independent exons can be concealed. We performed integrative cis-eQTL analysis using association statistics from twenty autoimmune diseases (560 independent loci) and RNA-Seq data from 373 individuals of the Geuvadis cohort profiled at gene-, isoform-, exon-, junction-, and intron-level resolution in lymphoblastoid cell lines. After stringently testing for a shared causal variant using both the Joint Likelihood Mapping and Regulatory Trait Concordance frameworks, we found that gene-level quantification significantly underestimated the number of causal cis-eQTLs. Only 5.0–5.3% of loci were found to share a causal cis-eQTL at gene-level compared to 12.9–18.4% at exon-level and 9.6–10.5% at junction-level. More than a fifth of autoimmune loci shared an underlying causal variant in a single cell type by combining all five quantification types; a marked increase over current estimates of steady-state causal cis-eQTLs. Causal cis-eQTLs detected at different quantification types localised to discrete epigenetic annotations. We applied a linear mixed-effects model to distinguish cis-eQTLs modulating all expression elements of a gene from those where the signal is only evident in a subset of elements. Exon-level analysis detected disease-associated cis-eQTLs that subtly altered transcription globally across the target gene. We dissected in detail the genetic associations of systemic lupus erythematosus and functionally annotated the candidate genes. Many of the known and novel genes were concealed at gene-level (e.g. IKZF2, TYK2, LYST). Our findings are provided as a web resource.

Involvement of DPP9 in gene fusions in serous ovarian carcinoma

BackgroundA fusion gene is a hybrid gene consisting of parts from two previously independent genes. Chromosomal rearrangements leading to gene breakage are frequent in high-grade serous ovarian carcinomas and have been reported as a common mechanism for inactivating tumor suppressor genes. However, no fusion genes have been repeatedly reported to be recurrent driver events in ovarian carcinogenesis. We combined genomic and transcriptomic information to identify novel fusion gene candidates and aberrantly expressed genes in ovarian carcinomas.MethodsExamined were 19 previously karyotyped ovarian carcinomas (18 of the serous histotype and one undifferentiated). First, karyotypic aberrations were compared to fusion gene candidates identified by RNA sequencing (RNA-seq). In addition, we used exon-level gene expression microarrays as a screening tool to identify aberrantly expressed genes possibly involved in gene fusion events, and compared the findings to the RNA-seq data.ResultsWe found a DPP9-PPP6R3 fusion transcript in one tumor showing a matching genomic 11;19-translocation. Another tumor had a rearrangement of DPP9 with PLIN3. Both rearrangements were associated with diminished expression of the 3′ end of DPP9 corresponding to the breakpoints identified by RNA-seq. For the exon-level expression analysis, candidate fusion partner genes were ranked according to deviating expression compared to the median of the sample set. The results were collated with data obtained from the RNA-seq analysis. Several fusion candidates were identified, among them TMEM123-MMP27, ZBTB46-WFDC13, and PLXNB1-PRKAR2A, all of which led to stronger expression of the 3′ genes. In view of our previous findings of nonrandom rearrangements of chromosome 19 in this cancer type, particular emphasis was given to changes of this chromosome and a DDA1-FAM129C fusion event was identified.ConclusionsWe have identified novel fusion gene candidates in high-grade serous ovarian carcinoma. DPP9 was involved in two different fusion transcripts that both resulted in deregulated expression of the 3′ end of the transcript and thus possible loss of the active domains in the DPP9 protein. The identified rearrangements might play a role in tumorigenesis or tumor progression.

Need for re-evaluation of current guidelines based on results from germline genetic testing in prostate cancer.

5009 Background: Inherited risk for prostate cancer (PCa) is potentially associated with more aggressive disease. Recent data indicate that DNA repair gene abnormalities may be much more common than previously appreciated, especially BRCA2, ATM, CHEK2, BRCA1, RAD51D, and PALB2. Herein, we investigate the efficacy of a targeted gene panel in men with PCa and evaluate clinical factors in relationship to current guidelines for genetic screening. Methods: DNA sequencing and exon-level copy number analysis were performed in 1158 PCa patients (pts) between 2013 and 2016 at a commercial diagnostic laboratory. The genes requisitioned varied but consistently included 14 genes on a hereditary PCa panel, most of which were DNA repair genes. Evaluation included Gleason scores and eligibility for genetic screening based on any NCCN testing criteria in pts with positive findings (pathogenic, likely pathogenic, and risk allele). Results: Pathogenic findings were identified in 199 of 1158 (17.2%) pts, 13 pts (1.0%) had two variants. Roughly 75% of detected variants were in genes on the hereditary PCa panel, of which 34.4% were BRCA1/2. Positive variants in HOXB13, a gene associated only with PCa risk, were identified in eight (3.8%) pts. DNA mismatch repair variants, alterations with substantial known therapeutic implications, were detected in 1.7% of samples. A total of 12.4% of pts with Gleason scores of ≤6, compared with 15.4% of those with scores of ≥7 had a pathogenic variant. Within this cohort, 126 (63%) patients with positive results were eligible for genetic testing based on currently available NCCN guidelines, whereas 73 (37%) would not have qualified. Conclusions: Current NCCN guidelines and Gleason scores cannot be used to reliably stratify PCa pts for the presence/absence of pathogenic germline variants. Most positive results identified in this study have important management implications for pts and their families. The percentage of pts with germline variants who did not meet current genetic screening criteria underscores the need for revisiting current guidelines which cannot, at this time, reliably be used to predict pathologic findings on genetic testing.

Multivariate eQTL mapping uncovers functional variation on the X-chromosome associated with complex disease traits.

Very few studies have investigated the associations between genetic polymorphisms and gene expression on the X-chromosome. This is a major bottleneck when conducting functional follow-up studies of trait-associated variants, as those identified in genome-wide association studies (GWAS). We used a multivariate approach to test the association between individual single nucleotide polymorphisms (SNPs) and exon expression levels measured in 356 Epstein-Barr virus-transformed lymphoblastoid cell lines (LCLs) from the Geuvadis RNA sequencing project to identify SNPs associated with variation in gene expression on the X-chromosome, which we refer to as eSNPs. At an FDR of 5%, we discovered 548 independent [linkage disequilibrium (LD) r (2)<0.1] eSNPs on the X-chromosome. Of these, 35 were in LD (r (2)>0.8) with previously published disease- or trait-associated variants identified through GWAS. One of the strongest eSNPs identified was rs35975601, which was associated with F8A1 expression (p value=3×10(-20)) and was in LD with a type 1 diabetes risk variant. Additionally, we identified a number of genes for which eSNPs were in LD with multiple diseases or traits, including DNASE1L1 which was mapped to bilirubin levels, type 1 diabetes and schizophrenia. Our results also indicate that multivariate exon-level analysis provides a more powerful approach than univariate gene-level analysis, particularly when SNPs influence the expression of different exons with different magnitude and/or direction of effect. The associations identified in our study may provide new insights into the molecular process by which gene expression may contribute to trait variation or disease risk in humans.

IGEMS: an integrated model for identification of alternative exon usage events.

DNA microarrays and RNAseq are complementary methods for studying RNA molecules. Current computational methods to determine alternative exon usage (AEU) using such data require impractical visual inspection and still yield high false-positive rates. Integrated Gene and Exon Model of Splicing (iGEMS) adapts a gene-level residuals model with a gene size adjusted false discovery rate and exon-level analysis to circumvent these limitations. iGEMS was applied to two new DNA microarray datasets, including the high coverage Human Transcriptome Arrays 2.0 and performance was validated using RT-qPCR. First, AEU was studied in adipocytes treated with (n = 9) or without (n = 8) the anti-diabetes drug, rosiglitazone. iGEMS identified 555 genes with AEU, and robust verification by RT-qPCR (∼90%). Second, in a three-way human tissue comparison (muscle, adipose and blood, n = 41) iGEMS identified 4421 genes with at least one AEU event, with excellent RT-qPCR verification (95%, n = 22). Importantly, iGEMS identified a variety of AEU events, including 3′UTR extension, as well as exon inclusion/exclusion impacting on protein kinase and extracellular matrix domains. In conclusion, iGEMS is a robust method for identification of AEU while the variety of exon usage between human tissues is 5–10 times more prevalent than reported by the Genotype-Tissue Expression consortium using RNA sequencing.

Triple-layer dissection of the lung adenocarcinoma transcriptome: regulation at the gene, transcript, and exon levels.

Lung adenocarcinoma is one of the most deadly human diseases. However, the molecular mechanisms underlying this disease, particularly RNA splicing, have remained underexplored. Here, we report a triple-level (gene-, transcript-, and exon-level) analysis of lung adenocarcinoma transcriptomes from 77 paired tumor and normal tissues, as well as an analysis pipeline to overcome genetic variability for accurate differentiation between tumor and normal tissues. We report three major results. First, more than 5,000 differentially expressed transcripts/exonic regions occur repeatedly in lung adenocarcinoma patients. These transcripts/exonic regions are enriched in nicotine metabolism and ribosomal functions in addition to the pathways enriched for differentially expressed genes (cell cycle, extracellular matrix receptor interaction, and axon guidance). Second, classification models based on rationally selected transcripts or exonic regions can reach accuracies of 0.93 to 1.00 in differentiating tumor from normal tissues. Of the 28 selected exonic regions, 26 regions correspond to alternative exons located in such regulators as tumor suppressor (GDF10), signal receptor (LYVE1), vascular-specific regulator (RASIP1), ubiquitination mediator (RNF5), and transcriptional repressor (TRIM27). Third, classification systems based on 13 to 14 differentially expressed genes yield accuracies near 100%. Genes selected by both detection methods include C16orf59, DAP3, ETV4, GABARAPL1, PPAR, RADIL, RSPO1, SERTM1, SRPK1, ST6GALNAC6, and TNXB. Our findings imply a multilayered lung adenocarcinoma regulome in which transcript-/exon-level regulation may be dissociated from gene-level regulation. Our described method may be used to identify potentially important genes/transcripts/exonic regions for the tumorigenesis of lung adenocarcinoma and to construct accurate tumor vs. normal classification systems for this disease.