Whole-genome sequencing analysis of suicide deaths integrating brain-regulatory eQTLs data to identify risk loci and genes.

Recent large-scale genome-wide association studies (GWAS) have started to identify potential genetic risk loci associated with risk of suicide; however, a large portion of suicide-associated genetic factors affecting gene expression remain elusive. Dysregulated gene expression, not assessed by GWAS, may play a significant role in increasing the risk of suicide death. We performed the first comprehensive genomic association analysis prioritizing brain expression quantitative trait loci (eQTLs) within regulatory regions in suicide deaths from the Utah Suicide Genetic Risk Study (USGRS). 440,324 brain-regulatory eQTLs were obtained by integrating brain eQTLs, histone modification ChIP-seq, ATAC-seq, DNase-seq, and Hi-C results from publicly available data. Subsequent genomic analyses were conducted in whole-genome sequencing (WGS) data from 986 suicide deaths of non-Finnish European (NFE) ancestry and 415 ancestrally matched controls. Additional independent USGRS suicide deaths with genotyping array data (n = 4657) and controls from the Genome Aggregation Database were explored for WGS result replication. One significant eQTL locus, rs926308 (p = 3.24e-06), was identified. The rs926308-T is associated with lower expression of RFPL3S, a gene important for neocortex development and implicated in arousal. Gene-based analyses performed using Sherlock Bayesian statistical integrative analysis also detected 20 genes with expression changes that may contribute to suicide risk. From analyzing publicly available transcriptomic data, ten of these genes have previous evidence of differential expression in suicide death or in psychiatric disorders that may be associated with suicide, including schizophrenia and autism (ZNF501, ZNF502, CNN3, IGF1R, KLHL36, NBL1, PDCD6IP, SNX19, BCAP29, and ARSA). Electronic health records (EHR) data was further merged to evaluate if there were clinically relevant subsets of suicide deaths associated with genetic variants. In summary, our study identified one risk locus and ten genes associated with suicide risk via gene expression, providing new insight into possible genetic and molecular mechanisms leading to suicide.

Epigenetic interplay between methylation and miRNA in bladder cancer: focus on isoform expression.

BACKGROUND: Various epigenetic factors are responsible for the non-genetic regulation on gene expression. The epigenetically dysregulated oncogenes or tumor suppressors by miRNA and/or DNA methylation are often observed in cancer cells. Each of these epigenetic regulators has been studied well in cancer progressions; however, their mutual regulatory relationship in cancer still remains unclear. In this study, we propose an integrative framework to systematically investigate epigenetic interactions between miRNA and methylation at the alternatively spliced mRNA level in bladder cancer. Each of these epigenetic regulators has been studied well in cancer progressions; however, their mutual regulatory relationship in cancer still remains unclear. RESULTS: The integrative analyses yielded 136 significant combinations (methylation, miRNA and isoform). Further, overall survival analysis on the 136 combinations based on methylation and miRNA, high and low expression groups resulted in 13 combinations associated with survival. Additionally, different interaction patterns were examined. CONCLUSIONS: Our study provides a higher resolution of molecular insight into the crosstalk between two epigenetic factors, DNA methylation and miRNA. Given the importance of epigenetic interactions and alternative splicing in cancer, it is timely to identify and understand the underlying mechanisms based on epigenetic markers and their interactions in cancer, leading to alternative splicing with primary functional impact.

Alternative Splicing Regulation of Low-Frequency Genetic Variants in Exon 2 of TREM2 in Alzheimer's Disease by Splicing-Based Aggregation.

TREM2 is among the most well-known Alzheimer's disease (AD) risk genes; however, the functional roles of its AD-associated variants remain to be elucidated, and most known risk alleles are low-frequency variants whose investigation is challenging. Here, we utilized a splicing-guided aggregation method in which multiple low-frequency TREM2 variants were bundled together to investigate the functional impact of those variants on alternative splicing in AD. We analyzed whole genome sequencing (WGS) and RNA-seq data generated from cognitively normal elderly controls (CN) and AD patients in two independent cohorts, representing three regions in the frontal lobe of the human brain: the dorsolateral prefrontal cortex (CN = 213 and AD = 376), frontal pole (CN = 72 and AD = 175), and inferior frontal (CN = 63 and AD = 157). We observed an exon skipping event in the second exon of TREM2, with that exon tending to be more frequently skipped (p = 0.0012) in individuals having at least one low-frequency variant that caused loss-of-function for a splicing regulatory element. In addition, genes differentially expressed between AD patients with high vs. low skipping of the second exon (i.e., loss of a TREM2 functional domain) were significantly enriched in immune-related pathways. Our splicing-guided aggregation method thus provides new insight into the regulation of alternative splicing of the second exon of TREM2 by low-frequency variants and could be a useful tool for further exploring the potential molecular mechanisms of multiple, disease-associated, low-frequency variants.

Alternative Splicing Regulation of an Alzheimer's Risk Variant in CLU.

Clusterin (CLU) is one of the risk genes most associated with late onset Alzheimer's disease (AD), and several genetic variants in CLU are associated with AD risk. However, the functional role of known AD risk genetic variants in CLU has been little explored. We investigated the effect of an AD risk variant (rs7982) in the 5th exon of CLU on alternative splicing by using an integrative approach of brain-tissue-based RNA-Seq and whole genome sequencing data from Accelerating Medicines Partnership-Alzheimer's Disease (AMP-AD). RNA-Seq data were generated from three regions in the temporal lobe of the brain-the temporal cortex, superior temporal gyrus, and parahippocampal gyrus. The rs7982 was significantly associated with intron retention (IR) of the 5th exon of CLU; as the number of alternative alleles (G) increased, the IR rates decreased more significantly in females than in males. Our results suggest a sex-dependent role of rs7982 in AD pathogenesis via splicing regulation.

A machine learning approach using conditional normalizing flow to address extreme class imbalance problems in personal health records.

BACKGROUND: Supervised machine learning models have been widely used to predict and get insight into diseases by classifying patients based on personal health records. However, a class imbalance is an obstacle that disrupts the training of the models. In this study, we aimed to address class imbalance with a conditional normalizing flow model, one of the deep-learning-based semi-supervised models for anomaly detection. It is the first introduction of the normalizing flow algorithm for tabular biomedical data. METHODS: We collected personal health records from South Korean citizens (n = 706), featuring genetic data obtained from direct-to-customer service (microarray chip), medical health check-ups, and lifestyle log data. Based on the health check-up data, six chronic diseases were labeled (obesity, diabetes, hypertriglyceridemia, dyslipidemia, liver dysfunction, and hypertension). After preprocessing, supervised classification models and semi-supervised anomaly detection models, including conditional normalizing flow, were evaluated for the classification of diabetes, which had extreme target imbalance (about 2%), based on AUROC and AUPRC. In addition, we evaluated their performance under the assumption of insufficient collection for patients with other chronic diseases by undersampling disease-affected samples. RESULTS: While LightGBM (the best-performing model among supervised classification models) showed AUPRC 0.16 and AUROC 0.82, conditional normalizing flow achieved AUPRC 0.34 and AUROC 0.83 during fifty evaluations of the classification of diabetes, whose base rate was very low, at 0.02. Moreover, conditional normalizing flow performed better than the supervised model under a few disease-affected data numbers for the other five chronic diseases - obesity, hypertriglyceridemia, dyslipidemia, liver dysfunction, and hypertension. For example, while LightGBM performed AUPRC 0.20 and AUROC 0.75, conditional normalizing flow showed AUPRC 0.30 and AUROC 0.74 when predicting obesity, while undersampling disease-affected samples (positive undersampling) lowered the base rate to 0.02. CONCLUSIONS: Our research suggests the utility of conditional normalizing flow, particularly when the available cases are limited, for predicting chronic diseases using personal health records. This approach offers an effective solution to deal with sparse data and extreme class imbalances commonly encountered in the biomedical context.

Absence of nonfatal suicidal behavior preceding suicide death reveals differences in clinical risks.

Nonfatal suicidality is the most robust predictor of suicide death. However, only ~10% of those who survive an attempt go on to die by suicide. Moreover, ~50% of suicide deaths occur in the absence of prior known attempts, suggesting risks other than nonfatal suicide attempt need to be identified. We studied data from 4,000 population-ascertained suicide deaths and 26,191 population controls to improve understanding of risks leading to suicide death. This study included 2,253 suicide deaths and 3,375 controls with evidence of nonfatal suicidality (SUI_SI/SB and CTL_SI/SB) from diagnostic codes and natural language processing of electronic health records notes. Characteristics of these groups were compared to 1,669 suicides with no prior nonfatal SI/SB (SUI_None) and 22,816 controls with no lifetime suicidality (CTL_None). The SUI_None and CTL_None groups had fewer diagnoses and were older than SUI_SI/SB and CTL_SI/SB. Mental health diagnoses were far less common in both the SUI_None and CTL_None groups; mental health problems were less associated with suicide death than with presence of SI/SB. Physical health diagnoses were conversely more often associated with risk of suicide death than with presence of SI/SB. Pending replication, results indicate highly significant clinical differences among suicide deaths with versus without prior nonfatal SI/SB.

TREM2 splice isoforms generate soluble TREM2 species that disrupt long-term potentiation.

BACKGROUND: TREM2 is a transmembrane receptor expressed by myeloid cells and acts to regulate their immune response. TREM2 governs the response of microglia to amyloid and tau pathologies in the Alzheimer's disease (AD) brain. TREM2 is also present in a soluble form (sTREM2), and its CSF levels fluctuate as a function of AD progression. Analysis of stroke and AD mouse models revealed that sTREM2 proteins bind to neurons, which suggests sTREM2 may act in a non-cell autonomous manner to influence neuronal function. sTREM2 arises from the proteolytic cleavage of the membrane-associated receptor. However, alternatively spliced TREM2 species lacking a transmembrane domain have been postulated to contribute to the pool of sTREM2. Thus, both the source of sTREM2 species and its actions in the brain remain unclear. METHODS: The expression of TREM2 isoforms in the AD brain was assessed through the analysis of the Accelerating Medicines Partnership for Alzheimer's Disease Consortium transcriptomics data, as well as qPCR analysis using post-mortem samples of AD patients and of the AD mouse model 5xFAD. TREM2 cleavage and secretion were studied in vitro using HEK-293T and HMC3 cell lines. Synaptic plasticity, as evaluated by induction of LTP in hippocampal brain slices, was employed as a measure of sTREM2 actions. RESULTS: Three distinct TREM2 transcripts, namely ENST00000373113 (TREM2230), which encodes the full-length transmembrane receptor, and the alternatively spliced isoforms ENST00000373122 (TREM2222) and ENST00000338469 (TREM2219), are moderately increased in specific brain regions of patients with AD. We provide experimental evidence that TREM2 alternatively spliced isoforms are translated and secreted as sTREM2. Furthermore, our functional analysis reveals that all sTREM2 species inhibit LTP induction, and this effect is abolished by the GABAA receptor antagonist picrotoxin. CONCLUSIONS: TREM2 transcripts can give rise to a heterogeneous pool of sTREM2 which acts to inhibit LTP. These results provide novel insight into the generation, regulation, and function of sTREM2 which fits into the complex biology of TREM2 and its role in human health and disease. Given that sTREM2 levels are linked to AD pathogenesis and progression, our finding that sTREM2 species interfere with LTP furthers our understanding about the role of TREM2 in AD.

Brain Region-Dependent Alternative Splicing of Alzheimer Disease (AD)-Risk Genes Is Associated With Neuropathological Features in AD.

PURPOSE: Alzheimer disease (AD) is one of the most complex diseases and is characterized by AD-related neuropathological features, including accumulation of amyloid-ß plaques and tau neurofibrillary tangles. Dysregulation of alternative splicing (AS) contributes to these features, and there is heterogeneity in features across brain regions between AD patients, leading to different severity and progression rates; however, brain region-specific AS mechanisms still remain unclear. Therefore, we aimed to systemically investigate AS in multiple brain regions of AD patients and how they affect clinical features. METHODS: We analyzed RNA sequencing (RNA-Seq) data obtained from brain regions (frontal and temporal) of AD patients. Reads were mapped to the hg19 reference genome using the STAR aligner, and exon skipping (ES) rates were estimated as percent spliced in (PSI) by rMATs. We focused on AD-risk genes discovered by genome-wide association studies, and accordingly evaluated associations between PSI of skipped exons in AD-risk genes and Braak stage and plaque density mean (PM) for each brain region. We also integrated whole-genome sequencing data of the ascertained samples with RNA-Seq data to identify genetic regulators of feature-associated ES. RESULTS: We identified 26 and 41 ES associated with Braak stage in frontal and temporal regions, respectively, and 10 and 50 ES associated with PM. Among those, 10 were frontal-specific (CLU and NTRK2), 65 temporal-specific (HIF1A and TRPC4AP), and 26 shared ES (APP) that accompanied functional Gene Ontology terms, including axonogenesis in shared-ES genes. We further identified genetic regulators that account for 44 ES (44% of the total). Finally, we present as a case study the systematic regulation of an ES in APP, which is important in AD pathogenesis. CONCLUSION: This study provides new insights into brain region-dependent AS regulation of the architecture of AD-risk genes that contributes to AD pathologies, ultimately allowing identification of a treatment target and region-specific biomarkers for AD.

ADAS-viewer: web-based application for integrative analysis of multi-omics data in Alzheimer's disease.

Alzheimer's disease (AD) is a neurodegenerative disorder and is represented by complicated biological mechanisms and complexity of brain tissue. Our understanding of the complicated molecular architecture that contributes to AD progression benefits from performing comprehensive and systemic investigations with multi-layered molecular and biological data from different brain regions. Since recently different independent studies generated various omics data in different brain regions of AD patients, multi-omics data integration can be a useful resource for better comprehensive understanding of AD. Here we present a web platform, ADAS-viewer, that provides researchers with the ability to comprehensively investigate and visualize multi-omics data from multiple brain regions of AD patients. ADAS-viewer offers means to identify functional changes in transcript and exon expression (i.e., alternative splicing) along with associated genetic or epigenetic regulatory effects. Specifically, it integrates genomic, transcriptomic, methylation, and miRNA data collected from seven different brain regions (cerebellum, temporal cortex, dorsolateral prefrontal cortex, frontal pole, inferior frontal gyrus, parahippocampal gyrus, and superior temporal gyrus) across three independent cohort datasets. ADAS-viewer is particularly useful as a web-based application for analyzing and visualizing multi-omics data across multiple brain regions at both transcript and exon level, allowing the identification of candidate biomarkers of Alzheimer's disease.

Transcriptome analysis of alternative splicing in the pathogen life cycle in human foreskin fibroblasts infected with Trypanosoma cruzi.

Trypanosoma cruzi is an intracellular protozoan parasite that causes Chagas disease as a zoonotic pathogen. The parasite has been shown to remodel expression in the host transcriptome under different conditions. Although alternative splicing (AS) is involved in virtually every biological function in eukaryotes, including cellular differentiation and responses to immune reactions, host AS events that occur as a result of T. cruzi infection have yet to be explored. In this study, we bioinformatically investigated the transcriptome AS dynamics of T. cruzi (Y strain) infected human foreskin fibroblasts using RNA-Seq data captured over four timepoints (4, 24, 48, and 72 h post infection (hpi)). We identified 1768, 399, 250, and 299 differentially expressed exons (AS exons) at 4, 24, 48, and 72 hpi, respectively, showing that host AS mechanism may have a significant role in the intracellular life cycle of the parasite. We present an exon skipping event in HDAC7, which is a candidate gene that is important in the parasite's cell cycle. To sum up, this bioinformatics analysis of transcriptome may provide new potential insight into AS regulation in human foreskin fibroblast (HFF) cells infected by T. cruzi and into its implication to the parasite life cycle. Moreover, identified AS genes may provide new potential molecular candidates for improving treatment.

The landscape of alternative splicing in HIV-1 infected CD4 T-cells.

BACKGROUND: Elucidating molecular mechanisms that are altered during HIV-1 infection may provide a better understanding of the HIV-1 life cycle and how it interacts with infected T-cells. One such mechanism is alternative splicing (AS), which has been studied for HIV-1 itself, but no systematic analysis has yet been performed on infected T-cells. We hypothesized that AS patterns in infected T-cells may illuminate the molecular mechanisms underlying HIV-1 infection and identify candidate molecular markers for specifically targeting infected T-cells. METHODS: We downloaded previously published raw RNA-seq data obtained from HIV-1 infected and non-infected T-cells. We estimated percent spliced in (PSI) levels for each AS exon, then identified differential AS events in the infected cells (FDR < 0.05, PSI difference > 0.1). We performed functional gene set enrichment analysis on the genes with differentially expressed AS exons to identify their functional roles. In addition, we used RT-PCR to validate differential alternative splicing events in cyclin T1 (CCNT1) as a case study. RESULTS: We identified 427 candidate genes with differentially expressed AS exons in infected T-cells, including 20 genes related to cell surface, 35 to kinases, and 121 to immune-related genes. In addition, protein-protein interaction analysis identified six essential subnetworks related to the viral life cycle, including Transcriptional regulation by TP53, Class I MHC mediated antigen, G2/M transition, and late phase of HIV life cycle. CCNT1 exon 7 was more frequently skipped in infected T-cells, leading to loss of the key Cyclin_N motif and affecting HIV-1 transcriptional elongation. CONCLUSIONS: Our findings may provide new insight into systemic host AS regulation under HIV-1 infection and may provide useful initial candidates for the discovery of new markers for specifically targeting infected T-cells.

Differential alternative splicing between hepatocellular carcinoma with normal and elevated serum alpha-fetoprotein.

BACKGROUND: Serum alpha-fetoprotein (AFP) is the approved serum marker for hepatocellular carcinoma (HCC) screening. However, not all HCC patients show high (≥ 20 ng/mL) serum AFP, and the molecular mechanisms of HCCs with normal (< 20 ng/mL) serum AFP remain to be elucidated. Therefore, we aimed to identify biological features of HCCs with normal serum AFP by investigating differential alternative splicing (AS) between HCCs with normal and high serum AFP. METHODS: We performed a genome-wide survey of AS events in 249 HCCs with normal (n = 131) and high (n = 118) serum AFP levels using RNA-sequencing data obtained from The Cancer Genome Atlas. RESULTS: In group comparisons of RNA-seq profiles from HCCs with normal and high serum AFP levels, 161 differential AS events (125 genes; ΔPSI > 0.05, FDR < 0.05) were identified to be alternatively spliced between the two groups. Those genes were enriched in cell migration or proliferation terms such as "the cell migration and growth-cone collapse" and "regulation of insulin-like growth factor (IGF) transport and uptake by IGF binding proteins". Most of all, two AS genes (FN1 and FAM20A) directly interact with AFP; these relate to the regulation of IGF transport and post-translational protein phosphorylation. Interestingly, 42 genes and 27 genes were associated with gender and vascular invasion (VI), respectively, but only eighteen genes were significant in survival analysis. We especially highlight that FN1 exhibited increased differential expression of AS events (ΔPSI > 0.05), in which exons 25 and 33 were more frequently skipped in HCCs with normal (low) serum AFP compared to those with high serum AFP. Moreover, these events were gender and VI dependent. CONCLUSION: We found that AS may influence the regulation of transcriptional differences inherent in the occurrence of HCC maintaining normal rather than elevated serum AFP levels.

Differential alternative splicing regulation among hepatocellular carcinoma with different risk factors.

BACKGROUND: Hepatitis B virus (HBV), hepatitis C virus (HCV), and alcohol consumption are predominant causes of hepatocellular carcinoma (HCC). However, the molecular mechanisms underlying how differently these causes are implicated in HCC development are not fully understood. Therefore, we investigated differential alternative splicing (AS) regulation among HCC patients with these risk factors. METHODS: We conducted a genome-wide survey of AS events associated with HCCs among HBV (n = 95), HCV (n = 47), or alcohol (n = 76) using RNA-sequencing data obtained from The Cancer Genome Atlas. RESULTS: In three group comparisons of HBV vs. HCV, HBV vs. alcohol, and HCV vs. alcohol for RNA seq (ΔPSI> 0.05, FDR < 0.05), 133, 93, and 29 differential AS events (143 genes) were identified, respectively. Of 143 AS genes, eight and one gene were alternatively spliced specific to HBV and HCV, respectively. Through functional analysis over the canonical pathways and gene ontologies, we identified significantly enriched pathways in 143 AS genes including immune system, mRNA splicing-major pathway, and nonsense-mediated decay, which may be important to carcinogenesis in HCC risk factors. Among eight genes with HBV-specific splicing events, HLA-A, HLA-C, and IP6K2 exhibited more differential expression of AS events (ΔPSI> 0.1). Intron retention of HLA-A was observed more frequently in HBV-associated HCC than HCV- or alcohol-associated HCC, and intron retention of HLA-C showed vice versa. Exon 3 (based on ENST00000432678) of IP6K2 was less skipped in HBV-associated in HCC compared to HCV- or alcohol-associated HCC. CONCLUSION: AS may play an important role in regulating transcription differences implicated in HBV-, HCV-, and alcohol-related HCC development.

Identification of exon skipping events associated with Alzheimer's disease in the human hippocampus.

BACKGROUND: At least 90% of human genes are alternatively spliced. Alternative splicing has an important function regulating gene expression and miss-splicing can contribute to risk for human diseases, including Alzheimer's disease (AD). METHODS: We developed a splicing decision model as a molecular mechanism to identify functional exon skipping events and genetic variation affecting alternative splicing on a genome-wide scale by integrating genomics, transcriptomics, and neuroimaging data in a systems biology approach. In this study, we analyzed RNA-Seq data of hippocampus brain tissue from Alzheimer's disease (AD; n = 24) and cognitively normal elderly controls (CN; n = 50) and identified three exon skipping events in two genes (RELN and NOS1) as significantly associated with AD (corrected p-value < 0.05 and fold change > 1.5). Next, we identified single-nucleotide polymorphisms (SNPs) affecting exon skipping events using the splicing decision model and then performed an association analysis of SNPs potentially affecting three exon skipping events with a global cortical measure of amyloid-ß deposition measured by [18F] Florbetapir position emission tomography (PET) scan as an AD-related quantitative phenotype. A whole-brain voxel-based analysis was also performed. RESULTS: Two exons in RELN and one exon in NOS1 showed significantly lower expression levels in the AD participants compared to CN participants, suggesting that the exons tend to be skipped more in AD. We also showed the loss of the core protein structure due to the skipped exons using the protein 3D structure analysis. The targeted SNP-based association analysis identified one intronic SNP (rs362771) adjacent to the skipped exon 24 in RELN as significantly associated with cortical amyloid-ß levels (corrected p-value < 0.05). This SNP is within the splicing regulatory element, i.e., intronic splicing enhancer. The minor allele of rs362771 conferred decreases in cortical amyloid-ß levels in the right temporal and bilateral parietal lobes. CONCLUSIONS: Our results suggest that exon skipping events and splicing-affecting SNPs in the human hippocampus may contribute to AD pathogenesis. Integration of multiple omics and neuroimaging data provides insights into possible mechanisms underlying AD pathophysiology through exon skipping and may help identify novel therapeutic targets.

Genetic variation affecting exon skipping contributes to brain structural atrophy in Alzheimer's disease.

Genetic variation in cis-regulatory elements related to splicing machinery and splicing regulatory elements (SREs) results in exon skipping and undesired protein products. We developed a splicing decision model to identify actionable loci among common SNPs for gene regulation. The splicing decision model identified SNPs affecting exon skipping by analyzing sequence-driven alternative splicing (AS) models and by scanning the genome for the regions with putative SRE motifs. We used non-Hispanic Caucasians with neuroimaging, and fluid biomarkers for Alzheimer's disease (AD) and identified 17,088 common exonic SNPs affecting exon skipping. GWAS identified one SNP (rs1140317) in HLA-DQB1 as significantly associated with entorhinal cortical thickness, AD neuroimaging biomarker, after controlling for multiple testing. Further analysis revealed that rs1140317 was significantly associated with brain amyloid-f deposition (PET and CSF). HLA-DQB1 is an essential immune gene and may regulate AS, thereby contributing to AD pathology. SRE may hold potential as novel therapeutic targets for AD.

CAS-viewer: web-based tool for splicing-guided integrative analysis of multi-omics cancer data.

BACKGROUND: The Cancer Genome Atlas (TCGA) project is a public resource that provides transcriptomic, DNA sequence, methylation, and clinical data for 33 cancer types. Transforming the large size and high complexity of TCGA cancer genome data into integrated knowledge can be useful to promote cancer research. Alternative splicing (AS) is a key regulatory mechanism of genes in human cancer development and in the interaction with epigenetic factors. Therefore, AS-guided integration of existing TCGA data sets will make it easier to gain insight into the genetic architecture of cancer risk and related outcomes. There are already existing tools analyzing and visualizing alternative mRNA splicing patterns for large-scale RNA-seq experiments. However, these existing web-based tools are limited to the analysis of individual TCGA data sets at a time, such as only transcriptomic information. RESULTS: We implemented CAS-viewer (integrative analysis of Cancer genome data based on Alternative Splicing), a web-based tool leveraging multi-cancer omics data from TCGA. It illustrates alternative mRNA splicing patterns along with methylation, miRNAs, and SNPs, and then provides an analysis tool to link differential transcript expression ratio to methylation, miRNA, and splicing regulatory elements for 33 cancer types. Moreover, one can analyze AS patterns with clinical data to identify potential transcripts associated with different survival outcome for each cancer. CONCLUSIONS: CAS-viewer is a web-based application for transcript isoform-driven integration of multi-omics data in multiple cancer types and will aid in the visualization and possible discovery of biomarkers for cancer by integrating multi-omics data from TCGA.

Rare variants in the splicing regulatory elements of EXOC3L4 are associated with brain glucose metabolism in Alzheimer's disease.

BACKGROUND: Alzheimer's disease (AD) is one of the most common neurodegenerative diseases that causes problems related to brain function. To some extent it is understood on a molecular level how AD arises, however there are a lack of biomarkers that can be used for early diagnosis. Two popular methods to identify AD-related biomarkers use genetics and neuroimaging. Genes and neuroimaging phenotypes have provided some insights as to the potential for AD biomarkers. While the field of imaging-genomics has identified genetic features associated with structural and functional neuroimaging phenotypes, it remains unclear how variants that affect splicing could be important for understanding the genetic etiology of AD. METHODS: In this study, rare variants (minor allele frequency < 0.01) in splicing regulatory element (SRE) loci from whole genome sequencing (WGS) in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort, were used to identify genes that are associated with global brain cortical glucose metabolism in AD measured by FDG PET-scans. Gene-based associated analyses of rare variants were performed using the program BioBin and the optimal Sequence Kernel Association Test (SKAT-O). RESULTS: The gene, EXOC3L4, was identified as significantly associated with global cortical glucose metabolism (FDR (false discovery rate) corrected p < 0.05) using SRE coding variants only. Three loci that may affect splicing within EXOC3L4 contribute to the association. CONCLUSION: Based on sequence homology, EXOC3L4 is likely a part of the exocyst complex. Our results suggest the possibility that variants which affect proper splicing of EXOC3L4 via SREs may impact vesicle transport, giving rise to AD related phenotypes. Overall, by utilizing WGS and functional neuroimaging we have identified a gene significantly associated with an AD related endophenotype, potentially through a mechanism that involves splicing.

Population-dependent Intron Retention and DNA Methylation in Breast Cancer.

Regulation of gene expression by DNA methylation in gene promoter regions is well studied; however, the effects of methylation in the gene body (exons and introns) on gene expression are comparatively understudied. Recently, hypermethylation has been implicated in the inclusion of alternatively spliced exons; moreover, exon recognition can be enhanced by recruiting the methyl-CpG-binding protein (MeCP2) to hypermethylated sites. This study examines whether the methylation status of an intron is correlated with how frequently the intron is retained during splicing using DNA methylation and RNA sequencing data from breast cancer tissue specimens in The Cancer Genome Atlas. Interestingly, hypomethylation of introns is correlated with higher levels of intron expression in mRNA and the methylation level of an intron is inversely correlated with its retention in mRNA from the gene in which it is located. Furthermore, significant population differences were observed in the methylation level of retained introns. In African-American donors, retained introns were not only less methylated compared to European-American donors, but also were more highly expressed. This underscores the need for understanding epigenetic differences in populations and their correlation with breast cancer is an important step toward achieving personalized cancer care.Implications: This research contributes to the understanding of how epigenetic markers in the gene body communicate with the transcriptional machinery to control transcript diversity and differential biological response to changes in methylation status could underlie some of the known, yet unexplained, disparities in certain breast cancer patient populations. Mol Cancer Res; 16(3); 461-9. ©2018 AACR.

The effects of alternative splicing on miRNA binding sites in bladder cancer.

Eukaryotic organisms have developed a variety of mechanisms to regulate translation post-transcriptionally, including but not limited to the use of miRNA silencing in many species. One method of post-transcriptional regulation is through miRNAs that bind to the 3' UTRs to regulate mRNA abundance and influence protein expression. Therefore, the diversity of mRNA 3' UTRs mediating miRNA binding sites influence miRNA-mediated regulation. Alternative polyadenylation, by shortening mRNA isoforms, increases the diversity of 3' UTRs; moreover, short mRNA isoforms elude miRNA-medicated repression. Because no current prediction methods for putative miRNA target sites consider whether or not 1) splicing-informed miRNA binding sites and/or 2) the use of 3' UTRs provide higher resolution or functionality, we sought to identify not only the genome-wide impact of using exons in mRNA 3' UTRs but also their functional connection to miRNA regulation and clinical outcomes in cancer. With a genome-wide expression of mRNA and miRNA quantified by 395 bladder cancer cases from The Cancer Genome Atlas (TCGA), we 1) demonstrate the diversity of 3' UTRs affecting miRNA efficiency and 2) identify a set of genes clinically associated with mRNA expression in bladder cancer. Knowledge of 3' UTR diversity will not only be a useful addition to current miRNA target prediction algorithms but also enhance the clinical utility of mRNA isoforms in the expression of mRNA in cancer. Thus, variability among cancer patient's variability in molecular signatures based on these exon usage events in 3' UTR along with miRNAs in bladder cancer may lead to better prognostic/treatment strategies for improved precision medicine.

Investigation of Splicing Quantitative Trait Loci in Arabidopsis thaliana.

The alteration of alternative splicing patterns has an effect on the quantification of functional proteins, leading to phenotype variation. The splicing quantitative trait locus (sQTL) is one of the main genetic elements affecting splicing patterns. Here, we report the results of genome-wide sQTLs across 141 strains of Arabidopsis thaliana with publicly available next generation sequencing datasets. As a result, we found 1,694 candidate sQTLs in Arabidopsis thaliana at a false discovery rate of 0.01. Furthermore, among the candidate sQTLs, we found 25 sQTLs that overlapped with the list of previously examined trait-associated single nucleotide polymorphisms (SNPs). In summary, this sQTL analysis provides new insight into genetic elements affecting alternative splicing patterns in Arabidopsis thaliana and the mechanism of previously reported trait-associated SNPs.