Analysis of interactions between the epigenome and structural mutability of the genome using Genboree Workbench tools

Environmental carcinogens disproportionally mutate genes implicated in neurodevelopmental disorders

Introduction

De novo mutations contribute to a large proportion of sporadic psychiatric and developmental disorders, yet the potential role of environmental carcinogens as drivers of causal de novo mutations in neurodevelopmental disorders is poorly studied.

Methods

To explore environmental mutation vulnerability of disease-associated gene sets, we analyzed publicly available whole genome sequencing datasets of mutations in human induced pluripotent stem cell clonal lines exposed to 12 classes of environmental carcinogens, and human lung cancers from individuals living in highly polluted regions. We compared observed rates of exposure-induced mutations in disease-related gene sets with the expected rates of mutations based on control genes randomly sampled from the genome using exact binomial tests. To explore the role of sequence characteristics in mutation vulnerability, we modeled the effects of sequence length, gene expression, and percent GC content on mutation rates of entire genes and gene coding sequences using multivariate Quasi-Poisson regressions.

Results

We demonstrate that several mutagens, including radiation and polycyclic aromatic hydrocarbons, disproportionately mutate genes related to neurodevelopmental disorders including autism spectrum disorders, schizophrenia, and attention deficit hyperactivity disorder. Other disease genes including amyotrophic lateral sclerosis, Alzheimer's disease, congenital heart disease, orofacial clefts, and coronary artery disease were generally not mutated more than expected. Longer sequence length was more strongly associated with elevated mutations in entire genes compared with mutations in coding sequences. Increased expression was associated with decreased coding sequence mutation rate, but not with the mutability of entire genes. Increased GC content was associated with increased coding sequence mutation rates but decreased mutation rates in entire genes.

Discussion

Our findings support the possibility that neurodevelopmental disorder genetic etiology is partially driven by a contribution of environment-induced germ line and somatic mutations.

Mutator-Derived lncRNA Landscape: A Novel Insight Into the Genomic Instability of Prostate Cancer

Background

Increasing evidence has emerged to reveal the correlation between genomic instability and long non-coding RNAs (lncRNAs). The genomic instability-derived lncRNA landscape of prostate cancer (PCa) and its critical clinical implications remain to be understood.

Methods

Patients diagnosed with PCa were recruited from The Cancer Genome Atlas (TCGA) program. Genomic instability-associated lncRNAs were identified by a mutator hypothesis-originated calculative approach. A signature (GILncSig) was derived from genomic instability-associated lncRNAs to classify PCa patients into high-risk and low-risk groups. The biochemical recurrence (BCR) model of a genomic instability-derived lncRNA signature (GILncSig) was established by Cox regression and stratified analysis in the train set. Then its prognostic value and association with clinical features were verified by Kaplan–Meier (K-M) analysis and receiver operating characteristic (ROC) curve in the test set and the total patient set. The regulatory network of transcription factors (TFs) and lncRNAs was established to evaluate TF–lncRNA interactions.

Results

A total of 95 genomic instability-associated lncRNAs of PCa were identified. We constructed the GILncSig based on 10 lncRNAs with independent prognostic value. GILncSig separated patients into the high-risk (n = 121) group and the low-risk (n = 121) group in the train set. Patients with high GILncSig score suffered from more frequent BCR than those with low GILncSig score. The results were further validated in the test set, the whole TCGA cohort, and different subgroups stratified by age and Gleason score (GS). A high GILncSig risk score was significantly associated with a high mutation burden and a low critical gene expression (PTEN and CDK12) in PCa. The predictive performance of our BCR model based on GILncSig outperformed other existing BCR models of PCa based on lncRNAs. The GILncSig also showed a remarkable ability to predict BCR in the subgroup of patients with TP53 mutation or wild type. Transcription factors, such as FOXA1, JUND, and SRF, were found to participate in the regulation of lncRNAs with prognostic value.

Conclusion

In summary, we developed a prognostic signature of BCR based on genomic instability-associated lncRNAs for PCa, which may provide new insights into the epigenetic mechanism of BCR.

OUP accepted manuscript

Motivation

Genome annotations are a common way to represent genomic features such as genes, regulatory elements or epigenetic modifications. The amount of overlap between two annotations is often used to ascertain if there is an underlying biological connection between them. In order to distinguish between true biological association and overlap by pure chance, a robust measure of significance is required. One common way to do this is to determine if the number of intervals in the reference annotation that intersect the query annotation is statistically significant. However, currently employed statistical frameworks are often either inefficient or inaccurate when computing P-values on the scale of the whole human genome.

Results

We show that finding the P-values under the typically used ‘gold’ null hypothesis is NP-hard. This motivates us to reformulate the null hypothesis using Markov chains. To be able to measure the fidelity of our Markovian null hypothesis, we develop a fast direct sampling algorithm to estimate the P-value under the gold null hypothesis. We then present an open-source software tool MCDP that computes the P-values under the Markovian null hypothesis in O(m2+n) time and O(m) memory, where m and n are the numbers of intervals in the reference and query annotations, respectively. Notably, MCDP runtime and memory usage are independent from the genome length, allowing it to outperform previous approaches in runtime and memory usage by orders of magnitude on human genome annotations, while maintaining the same level of accuracy.

Availability and implementation

The software is available at https://github.com/fmfi-compbio/mc-overlaps. All data for reproducibility are available at https://github.com/fmfi-compbio/mc-overlaps-reproducibility.

Supplementary information

Supplementary data are available at Bioinformatics online.

Comprehensive analysis of epigenetic signatures of human transcription control

Advances in sequencing technologies have enabled exploration of epigenetic and transcriptional profiles at a genome-wide level. The epigenetic and transcriptional landscapes are now available in hundreds of mammalian cell and tissue contexts. Many studies have performed multi-omics analyses using these datasets to enhance our understanding of relationships between epigenetic modifications and transcription regulation. Nevertheless, most studies so far have focused on the promoters/enhancers and transcription start sites, and other features of transcription control including exons, introns and transcription termination remain underexplored. We investigated the interplay between epigenetic modifications and diverse transcription features using the data generated by the Roadmap Epigenomics project. A comprehensive analysis of histone modifications, DNA methylation, and RNA-seq data of thirty-three human cell lines and tissue types allowed us to confirm the generality of previously described relationships, as well as to generate new hypotheses about the interplay between epigenetic modifications and transcription features. Importantly, our analysis included previously under-explored features of transcription control, namely, transcription termination sites, exon-intron boundaries, and the exon inclusion ratio. We have made the analyses freely available to the scientific community at joshiapps.cbu.uib.no/perepigenomics_app/ for easy exploration, validation and hypothesis generation.

The Dynamic Platelet Transcriptome in Obesity and Weight Loss

OBJECTIVE

Adiposity is associated with oxidative stress, inflammation, and glucose intolerance. Previous data suggest that platelet gene expression is associated with key cardiometabolic phenotypes, including body mass index but stable in healthy individuals over time. However, modulation of gene expression in platelets in response to metabolic shifts (eg, weight reduction) is unknown and may be important to defining mechanism. Approach and Results: Platelet RNA sequencing and aggregation were performed from 21 individuals with massive weight loss (>45 kg) following bariatric surgery. Based on RNA sequencing data, we measured the expression of 67 genes from isolated platelet RNA using high-throughput quantitative reverse transcription quantitative PCR in 1864 FHS (Framingham Heart Study) participants. Many transcripts not previously studied in platelets were differentially expressed with bariatric surgical weight loss, appeared specific to platelets (eg, not differentially expressed in leukocytes), and were enriched for a nonalcoholic fatty liver disease pathway. Platelet aggregation studies did not detect alteration in platelet function after significant weight loss. Linear regression models demonstrated several platelet genes modestly associated with cross-sectional cardiometabolic phenotypes, including body mass index. There were no associations between studied transcripts and incident diabetes or cardiovascular end points.

CONCLUSIONS

In summary, while there is no change in platelet aggregation function after significant weight loss, the human platelet experiences a dramatic transcriptional shift that implicates pathways potentially relevant to improved cardiometabolic risk postweight loss (eg, nonalcoholic fatty liver disease). Further studies are needed to determine the mechanistic importance of these observations.

Longitudinal saliva omics responses to immune perturbation: a case study

Saliva omics has immense potential for non-invasive diagnostics, including monitoring very young or elderly populations, or individuals in remote locations. In this study, multiple saliva omics from an individual were monitored over three periods (100 timepoints) involving: (1) hourly sampling over 24 h without intervention, (2) hourly sampling over 24 h including immune system activation using the standard 23-valent pneumococcal polysaccharide vaccine, (3) daily sampling for 33 days profiling the post-vaccination response. At each timepoint total saliva transcriptome and proteome, and small RNA from salivary extracellular vesicles were profiled, including mRNA, miRNA, piRNA and bacterial RNA. The two 24-h periods were used in a paired analysis to remove daily variation and reveal vaccination responses. Over 18,000 omics longitudinal series had statistically significant temporal trends compared to a healthy baseline. Various immune response and regulation pathways were activated following vaccination, including interferon and cytokine signaling, and MHC antigen presentation. Immune response timeframes were concordant with innate and adaptive immunity development, and coincided with vaccination and reported fever. Overall, mRNA results appeared more specific and sensitive (timewise) to vaccination compared to other omics. The results suggest saliva omics can be consistently assessed for non-invasive personalized monitoring and immune response diagnostics.

Discovery and Verification of Extracellular miRNA Biomarkers for Non-invasive Prediction of Pre-eclampsia in Asymptomatic Women

Development of effective prevention and treatment strategies for pre-eclampsia is limited by the lack of accurate methods for identification of at-risk pregnancies. We performed small RNA sequencing (RNA-seq) of maternal serum extracellular RNAs (exRNAs) to discover and verify microRNAs (miRNAs) differentially expressed in patients who later developed pre-eclampsia. Sera collected from 73 pre-eclampsia cases and 139 controls between 17 and 28 weeks gestational age (GA), divided into separate discovery and verification cohorts, are analyzed by small RNA-seq. Discovery and verification of univariate and bivariate miRNA biomarkers reveal that bivariate biomarkers verify at a markedly higher rate than univariate biomarkers. The majority of verified biomarkers contain miR-155-5p, which has been reported to mediate the pre-eclampsia-associated repression of endothelial nitric oxide synthase (eNOS) by tumor necrosis factor alpha (TNF-α). Deconvolution analysis reveals that several verified miRNA biomarkers come from the placenta and are likely carried by placenta-specific extracellular vesicles.

Global impact of somatic structural variation on the DNA methylome of human cancers

Background

Genomic rearrangements exert a heavy influence on the molecular landscape of cancer. New analytical approaches integrating somatic structural variants (SSVs) with altered gene features represent a framework by which we can assign global significance to a core set of genes, analogous to established methods that identify genes non-randomly targeted by somatic mutation or copy number alteration. While recent studies have defined broad patterns of association involving gene transcription and nearby SSV breakpoints, global alterations in DNA methylation in the context of SSVs remain largely unexplored.

Results

By data integration of whole genome sequencing, RNA sequencing, and DNA methylation arrays from more than 1400 human cancers, we identify hundreds of genes and associated CpG islands (CGIs) for which the nearby presence of a somatic structural variant (SSV) breakpoint is recurrently associated with altered expression or DNA methylation, respectively, independently of copy number alterations. CGIs with SSV-associated increased methylation are predominantly promoter-associated, while CGIs with SSV-associated decreased methylation are enriched for gene body CGIs. Rearrangement of genomic regions normally having higher or lower methylation is often involved in SSV-associated CGI methylation alterations. Across cancers, the overall structural variation burden is associated with a global decrease in methylation, increased expression in methyltransferase genes and DNA damage response genes, and decreased immune cell infiltration.

Conclusion

Genomic rearrangement appears to have a major role in shaping the cancer DNA methylome, to be considered alongside commonly accepted mechanisms including histone modifications and disruption of DNA methyltransferases.

Bringing radiomics into a multi-omics framework for a comprehensive genotype-phenotype characterization of oncological diseases

Genomic and radiomic data integration, namely radiogenomics, can provide meaningful knowledge in cancer diagnosis, prognosis and treatment. Despite several data structures based on multi-layer architecture proposed to combine multi-omic biological information, none of these has been designed and assessed to include radiomic data as well. To meet this need, we propose to use the MultiAssayExperiment (MAE), an R package that provides data structures and methods for manipulating and integrating multi-assay experiments, as a suitable tool to manage radiogenomic experiment data. To this aim, we first examine the role of radiogenomics in cancer phenotype definition, then the current state of radiogenomics data integration in public repository and, finally, challenges and limitations of including radiomics in MAE, designing an extended framework and showing its application on a case study from the TCGA-TCIA archives. Radiomic and genomic data from 91 patients have been successfully integrated in a single MAE object, demonstrating the suitability of the MAE data structure as container of radiogenomic data.

Small RNA Sequencing of Sporadic Amyotrophic Lateral Sclerosis Cerebrospinal Fluid Reveals Differentially Expressed miRNAs Related to Neural and Glial Activity

Amyotrophic lateral sclerosis (ALS) is a clinical subtype of motor neurone disease (MND), a fatal neurodegenerative disease involving the loss of both the upper and lower motor neurones from the motor cortex, brainstem, and spinal cord. Identifying specific disease biomarkers would help to not only improve diagnostic delay but also to classify disease subtypes, monitor response to therapeutic drugs and track disease progression. miRNAs are small non-coding RNA responsible for regulating gene expression and ultimately protein expression and have been used as biomarkers for many cancers and neurodegenerative disorders. Investigating the detection of miRNAs in cerebrospinal fluid (CSF), the fluid that bathes the central nervous system (CNS) is a prime target for identifying potential biomarkers for ALS. This is the first study to investigate the expression of miRNAs in the CSF of ALS patients using small RNA sequencing. We detected 11 differentially expressed miRNAs in the CSF of sporadic ALS (sALS) patients related to neural and glial activity. Additionally, miRNAs involved in glucose metabolism and the regulation of oxidative stress were also identified. Detecting the presence of potential CSF derived miRNA biomarkers in sALS could open up a whole new area of knowledge to help gain a better understanding of disease pathophysiology. Additionally, with further investigation, the tracking of CSF miRNA over the disease course could be used to follow the disease progression and monitor the effect of novel therapeutics that could be personalized to an individual disease phenotype.

MicroRNA and mRNA Dysregulation in Astrocytes Infected with Zika Virus

The Zika virus (ZIKV) epidemic is an ongoing public health concern. ZIKV is a flavivirus reported to be associated with microcephaly, and recent work in animal models demonstrates the ability of the virus to cross the placenta and affect fetal brain development. Recent findings suggest that the virus preferentially infects neural stem cells and thereby deregulates gene expression, cell cycle progression, and increases cell death. However, neuronal stem cells are not the only brain cells that are susceptible to ZIKV and infection of other brain cells may contribute to disease progression. Herein, we characterized ZIKV replication in astrocytes, and profiled temporal changes in host microRNAs (miRNAs) and transcriptomes during infection. We observed the deregulation of numerous processes known to be involved in flavivirus infection, including genes involved in the unfolded protein response pathway. Moreover, a number of miRNAs were upregulated, including miR-30e-3p, miR-30e-5p, and, miR-17-5p, which have been associated with other flavivirus infections. This study highlights potential miRNAs that may be of importance in ZIKV pathogenesis.

Integrative Multi-omic Analysis of Human Platelet eQTLs Reveals Alternative Start Site in Mitofusin 2

Platelets play a central role in ischemic cardiovascular events. Cardiovascular disease (CVD) is a major cause of death worldwide. Numerous genome-wide association studies (GWASs) have identified loci associated with CVD risk. However, our understanding of how these variants contribute to disease is limited. Using data from the platelet RNA and expression 1 (PRAX1) study, we analyzed cis expression quantitative trait loci (eQTLs) in platelets from 154 normal human subjects. We confirmed these results in silico by performing allele-specific expression (ASE) analysis, which demonstrated that the allelic directionality of eQTLs and ASE patterns correlate significantly. Comparison of platelet eQTLs with data from the Genotype-Tissue Expression (GTEx) project revealed that a number of platelet eQTLs are platelet specific and that platelet eQTL peaks localize to the gene body at a higher rate than eQTLs from other tissues. Upon integration with data from previously published GWASs, we found that the trait-associated variant rs1474868 coincides with the eQTL peak for mitofusin 2 (MFN2). Additional experimental and computational analyses revealed that this eQTL is linked to an unannotated alternate MFN2 start site preferentially expressed in platelets. Integration of phenotype data from the PRAX1 study showed that MFN2 expression levels were significantly associated with platelet count. This study links the variant rs1474868 to a platelet-specific regulatory role for MFN2 and demonstrates the utility of integrating multi-omic data with eQTL analysis in disease-relevant tissues for interpreting GWAS results.

Pulmonary Metastases Exhibit Epigenetic Clonality: Implications for Precision Cancer Therapy

BACKGROUND

Development of effective cancer therapies may be limited by intratumoral heterogeneity, which facilitates outgrowth and organ-specific dissemination of treatment resistant clones. At present, limited information is available regarding epigenetic landscapes of pulmonary metastases. This study was undertaken to characterize epigenetic signatures of pulmonary metastases and to identify potential therapeutic targets.

METHODS

RNA and DNA were extracted from 65 pulmonary metastases resected from 12 patients (5 with sarcoma, 7 with adrenocortical carcinoma). Quantitative reverse transcription polymerase chain reaction techniques were used to evaluate expression levels of cancer-testis (CT) genes (NY-ESO-1, MAGE-A3, MAGE-A9, MAGE-A12, GAGE1, CT-45, SSX-1, and SSX-2), tumor suppressor (TS) genes (p16 and RASSF1A), and genes encoding epigenetic modifiers (DNMT1, DNMT3A, DNMT3B, EZH2, EED, and SUZ12), aberrantly expressed in human malignant diseases. Pyrosequencing techniques were used to quantitate DNA methylation levels in LINE1, NBL2, and D4Z4 repetitive sequences and promoter methylation status of differentially regulated genes. Results of these analyses were compared with a standardized panel of normal lung tissues.

RESULTS

Pulmonary metastases exhibited histologically related and patient-specific global DNA demethylation. Significant interpatient heterogeneity of gene expression was observed even among patients with similar tumor histologic features. Epigenetic signatures appeared consistent among metastases from the same patient, irrespective of the time of resection (synchronous/metachronous) or the anatomic location. EZH2, EED, and SUZ12 (core components of Polycomb repressive complex-2 [PRC-2]) were upregulated in the majority of metastases.

CONCLUSIONS

Pulmonary metastases exhibit patient-specific epigenetic clonality, which may be exploited for precision therapies targeting aberrant CT or TS gene expression. PRC-2 may be a shared target for epigenetic therapy of pulmonary metastases.