Genomic structural variations lead to dysregulation of important coding and non-coding RNA species in dilated cardiomyopathy

Structural variation of the coding and non-coding human pharmacogenome

Genetic variants in drug targets and genes encoding factors involved in drug absorption, distribution, metabolism and excretion (ADME) can have pronounced impacts on drug pharmacokinetics, response, and toxicity. While the landscape of genetic variability at the level of single nucleotide variants (SNVs) has been extensively studied in these pharmacogenetic loci, their structural variation is only poorly understood. Thus, we systematically analyzed the genetic structural variability across 908 pharmacogenes (344 ADME genes and 564 drug targets) based on publicly available whole genome sequencing data from 10,847 unrelated individuals. Overall, we extracted 14,984 distinct structural variants (SVs) ranging in size from 50 bp to 106 Mb. Each individual harbored on average 10.3 and 1.5 SVs with putative functional effects that affected the coding regions of ADME genes and drug targets, respectively. In addition, by cross-referencing pharmacogenomic SVs with experimentally determined binding data of 224 transcription factors across 130 cell types, we identified 1276 non-coding SVs that overlapped with gene regulatory elements. Based on these data, we estimate that non-coding structural variants account for 22% of the genetically encoded pharmacogenomic variability. Combined, these analyses provide the first comprehensive map of structural variability across pharmacogenes, derive estimates for the functional impact of non-coding SVs and incentivize the incorporation of structural genomic data into personalized drug response predictions.

An atlas of expression quantitative trait loci of microRNA in longissimus muscle of eight-way crossbred pigs

MicroRNAs (miRNAs) are key regulators of myocyte development and traits, yet insight into the genetic basis of variation in miRNA expression is still limited. Here, we present a systematic analysis of expression quantitative trait loci (eQTL) for miRNA profiling in longissimus muscle of pigs from an eight-breed crossed heterogeneous population. By integrating whole-genome sequencing and miRNAomics data, we map 54 cis- and 292 trans-eQTLs at high resolution that are associated with the expression of 54 and 92 miRNAs, respectively. Twenty-three trans-acting loci are identified to affect the expression of nine myomiRs (known muscle-specific miRNAs). MiRNAs in mammalian conserved miRNA clusters are found to be subjected to regulation by shared cis-eQTLs, while the expression of mature miRNA-5p/-3p counterparts is more likely to be regulated by different cis-eQTLs. Fine mapping and bioinformatics analyses pinpoint the peak cis-eSNP of miR-4331-5p, rs344650810, which is located in its seed region, as a causal variant for the changes in expression and function of this miRNA. Additionally, rs344650810 is significantly (P < 0.01) correlated with the density and percentage of type I muscle fibers. Altogether, this study provides a comprehensive atlas of miRNA-eQTLs in porcine skeletal muscle and new insights into regulatory mechanisms of miRNA expression.

NIMA-related kinase 9 regulates the phosphorylation of the essential myosin light chain in the heart

To adapt to changing hemodynamic demands, regulatory mechanisms modulate actin-myosin-kinetics by calcium-dependent and -independent mechanisms. We investigate the posttranslational modification of human essential myosin light chain (ELC) and identify NIMA-related kinase 9 (NEK9) to interact with ELC. NEK9 is highly expressed in the heart and the interaction with ELC is calcium-dependent. Silencing of NEK9 results in blunting of calcium-dependent ELC-phosphorylation. CRISPR/Cas9-mediated disruption of NEK9 leads to cardiomyopathy in zebrafish. Binding to ELC is mediated via the protein kinase domain of NEK9. A causal relationship between NEK9 activity and ELC-phosphorylation is demonstrated by genetic sensitizing in-vivo. Finally, we observe significantly upregulated ELC-phosphorylation in dilated cardiomyopathy patients and provide a unique map of human ELC-phosphorylation-sites. In summary, NEK9-mediated ELC-phosphorylation is a calcium-dependent regulatory system mediating cardiac contraction and inotropy.

PGG.SV: a whole-genome-sequencing-based structural variant resource and data analysis platform

Structural variations (SVs) play important roles in human evolution and diseases, but there is a lack of data resources concerning representative samples, especially for East Asians. Taking advantage of both next-generation sequencing and third-generation sequencing data at the whole-genome level, we developed the database PGG.SV to provide a practical platform for both regionally and globally representative structural variants. In its current version, PGG.SV archives 584 277 SVs obtained from whole-genome sequencing data of 6048 samples, including 1030 long-read sequencing genomes representing 177 global populations. PGG.SV provides (i) high-quality SVs with fine-scale and precise genomic locations in both GRCh37 and GRCh38, covering underrepresented SVs in existing sequencing and microarray data; (ii) hierarchical estimation of SV prevalence in geographical populations; (iii) informative annotations of SV-related genes, potential functions and clinical effects; (iv) an analysis platform to facilitate SV-based case-control association studies and (v) various visualization tools for understanding the SV structures in the human genome. Taken together, PGG.SV provides a user-friendly online interface, easy-to-use analysis tools and a detailed presentation of results. PGG.SV is freely accessible via https://www.biosino.org/pggsv.

Evidence-Based Assessment of Genes in Dilated Cardiomyopathy

BACKGROUND

Each of the cardiomyopathies, classically categorized as hypertrophic cardiomyopathy, dilated cardiomyopathy (DCM), and arrhythmogenic right ventricular cardiomyopathy, has a signature genetic theme. Hypertrophic cardiomyopathy and arrhythmogenic right ventricular cardiomyopathy are largely understood as genetic diseases of sarcomere or desmosome proteins, respectively. In contrast, >250 genes spanning >10 gene ontologies have been implicated in DCM, representing a complex and diverse genetic architecture. To clarify this, a systematic curation of evidence to establish the relationship of genes with DCM was conducted.

METHODS

An international panel with clinical and scientific expertise in DCM genetics evaluated evidence supporting monogenic relationships of genes with idiopathic DCM. The panel used the Clinical Genome Resource semiquantitative gene-disease clinical validity classification framework with modifications for DCM genetics to classify genes into categories on the basis of the strength of currently available evidence. Representation of DCM genes on clinically available genetic testing panels was evaluated.

RESULTS

Fifty-one genes with human genetic evidence were curated. Twelve genes (23%) from 8 gene ontologies were classified as having definitive (BAG3, DES, FLNC, LMNA, MYH7, PLN, RBM20, SCN5A, TNNC1, TNNT2, TTN) or strong (DSP) evidence. Seven genes (14%; ACTC1, ACTN2, JPH2, NEXN, TNNI3, TPM1, VCL) including 2 additional ontologies were classified as moderate evidence; these genes are likely to emerge as strong or definitive with additional evidence. Of these 19 genes, 6 were similarly classified for hypertrophic cardiomyopathy and 3 for arrhythmogenic right ventricular cardiomyopathy. Of the remaining 32 genes (63%), 25 (49%) had limited evidence, 4 (8%) were disputed, 2 (4%) had no disease relationship, and 1 (2%) was supported by animal model data only. Of the 16 evaluated clinical genetic testing panels, most definitive genes were included, but panels also included numerous genes with minimal human evidence.

CONCLUSIONS

In the curation of 51 genes, 19 had high evidence (12 definitive/strong, 7 moderate). It is notable that these 19 genes explain only a minority of cases, leaving the remainder of DCM genetic architecture incompletely addressed. Clinical genetic testing panels include most high-evidence genes; however, genes lacking robust evidence are also commonly included. We recommend that high-evidence DCM genes be used for clinical practice and that caution be exercised in the interpretation of variants in variable-evidence DCM genes.

Understanding the genetics of adult-onset dilated cardiomyopathy: what a clinician needs to know

There is increasing understanding of the genetic basis to dilated cardiomyopathy and in this review, we offer a practical primer for the practising clinician. We aim to help all clinicians involved in the care of patients with dilated cardiomyopathy to understand the clinical relevance of the genetic basis of dilated cardiomyopathy, introduce key genetic concepts, explain which patients and families may benefit from genetic testing, which genetic tests are commonly performed, how to interpret genetic results, and the clinical applications of results. We conclude by reviewing areas for future research in this dynamic field.

Mapping methylation quantitative trait loci in cardiac tissues nominates risk loci and biological pathways in congenital heart disease

Background

Most congenital heart defects (CHDs) result from complex interactions among genetic susceptibilities, epigenetic modifications, and maternal environmental exposures. Characterizing the complex relationship between genetic, epigenetic, and transcriptomic variation will enhance our understanding of pathogenesis in this important type of congenital disorder. We investigated cis-acting effects of genetic single nucleotide polymorphisms (SNPs) on local DNA methylation patterns within 83 cardiac tissue samples and prioritized their contributions to CHD risk by leveraging results of CHD genome-wide association studies (GWAS) and their effects on cardiac gene expression.

Results

We identified 13,901 potential methylation quantitative trait loci (mQTLs) with a false discovery threshold of 5%. Further co-localization analyses and Mendelian randomization indicated that genetic variants near the HLA-DRB6 gene on chromosome 6 may contribute to CHD risk by regulating the methylation status of nearby CpG sites. Additional SNPs in genomic regions on chromosome 10 (TNKS2-AS1 gene) and chromosome 14 (LINC01629 gene) may simultaneously influence epigenetic and transcriptomic variations within cardiac tissues.

Conclusions

Our results support the hypothesis that genetic variants may influence the risk of CHDs through regulating the changes of DNA methylation and gene expression. Our results can serve as an important source of information that can be integrated with other genetic studies of heart diseases, especially CHDs.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12863-021-00975-2.

The Evolving Story in the Genetic Analysis for Heart Failure

Genomic studies of cardiovascular diseases have achieved great success, not only in Mendelian genetic diseases such as hereditary arrhythmias and cardiomyopathies, but also in common diseases such as ischemic heart disease and atrial fibrillation. However, only limited success has been achieved in heart failure due to the complexity of its disease background. In this paper, we will review the genetic research for heart failure to date and discuss how we can discover new aspects of heart failure from the viewpoint of genomic perspective.

Differential Methylation in the GSTT1 Regulatory Region in Sudden Unexplained Death and Sudden Unexpected Death in Epilepsy

Sudden cardiac death (SCD) is a diagnostic challenge in forensic medicine. In a relatively large proportion of the SCDs, the deaths remain unexplained after autopsy. This challenge is likely caused by unknown disease mechanisms. Changes in DNA methylation have been associated with several heart diseases, but the role of DNA methylation in SCD is unknown. In this study, we investigated DNA methylation in two SCD subtypes, sudden unexplained death (SUD) and sudden unexpected death in epilepsy (SUDEP). We assessed DNA methylation of more than 850,000 positions in cardiac tissue from nine SUD and 14 SUDEP cases using the Illumina Infinium MethylationEPIC BeadChip. In total, six differently methylated regions (DMRs) between the SUD and SUDEP cases were identified. The DMRs were located in proximity to or overlapping genes encoding proteins that are a part of the glutathione S-transferase (GST) superfamily. Whole genome sequencing (WGS) showed that the DNA methylation alterations were not caused by genetic changes, while whole transcriptome sequencing (WTS) showed that DNA methylation was associated with expression levels of the GSTT1 gene. In conclusion, our results indicate that cardiac DNA methylation is similar in SUD and SUDEP, but with regional differential methylation in proximity to GST genes.

Genetic variations associated with long noncoding RNAs

Genetic variations, including single nucleotide polymorphisms (SNPs) and structural variations, are widely distributed in the genome, including the long noncoding RNA (lncRNA) regions. The changes at locus might produce numerous effects in a variety of aspects. Multiple bioinformatics resources and tools were also developed for systematically dealing with genetic variations associated with lncRNAs. Moreover, correlation of the genetic variations in lncRNAs with immune disease, cancers, and other disease as well as development process were all included for discussion. In this essay, we summarized how and in what aspects these changes would affect lncRNA functions.

Cardioinformatics: the nexus of bioinformatics and precision cardiology

Cardiovascular disease (CVD) is the leading cause of death worldwide, causing over 17 million deaths per year, which outpaces global cancer mortality rates. Despite these sobering statistics, most bioinformatics and computational biology research and funding to date has been concentrated predominantly on cancer research, with a relatively modest footprint in CVD. In this paper, we review the existing literary landscape and critically assess the unmet need to further develop an emerging field at the multidisciplinary interface of bioinformatics and precision cardiovascular medicine, which we refer to as 'cardioinformatics'.

LncRNA AC061961.2 overexpression inhibited endoplasmic reticulum stress induced apoptosis in dilated cardiomyopathy rats and cardiomyocytes via activating wnt/β-catenin pathway

Down-regulated lncRNA AC061961.2 in dilated cardiomyopathy (DCM) patients was previous reported. Whether AC061961.2 has regulatory effect on DCM still need exploration. Here, we tried to investigate the effect of AC061961.2 on DCM. After DCM model rat was established through injecting Adriamycin, left ventricular end-diastolic diameter (LVEDD), left ventricular end-systolic diameter (LVESD), left ventricular ejection fraction (LVEF), and left ventricular fractional shortening (LVFS) were measured by echocardiography. Histopathological changes and apoptosis were detected by hematoxylin-eosin, Masson staining, and TUNEL. After cardiomyocytes were isolated and identified by immunofluorescence, DCM cell model was established by injecting adriamycin. After transfected with overexpressed-AC061961.2 plasmids, cell apoptosis was detected by flow cytometry. The expressions of AC061961.2, β-catenin, Axin2, c-Myc, CRP78, CHOP, Caspase-3, Bcl-2, and Bax in cardiomyocytes and heart tissues were detected by RT-qPCR or western blot. LVEDD and LVESD were increased while LVEF and LVFS were decreased in DCM rats. The histopathological of heart tissues showed a typical sign of DCM. Apoptosis were increased in heart tissues of DCM rats. In DCM rats, the expressions of AC061961.2, β-catenin, Axin2, c-Myc, and Bcl-2 were decreased, the expressions of CRP78, CHOP, Caspase-3, and Bax were increased. After the overexpression of AC061961.2, levels of β-catenin, Axin2, c-Myc, and Bcl-2 were increased, while levels of CRP78, CHOP, Caspase-3, and Bax were decreased, compared with that in DCM cardiomyocytes. LncRNA AC061961.2 overexpression inhibited endoplasmic reticulum stress induced apoptosis in DCM rats and cardiomyocytes via activating Wnt/β-catenin pathway.

Recent advances on the roles of LncRNAs in cardiovascular disease

Cardiovascular diseases are a main cause of mortality whose prevalence continues to increase worldwide. Long non-coding RNAs (lncRNAs) regulate a variety of biological processes by modifying and regulating transcription of coding genes, directly binding to proteins and even coding proteins themselves. LncRNAs play key roles in the occurrence and development of myocardial infarction, heart failure, myocardial hypertrophy, arrhythmias and other pathological processes that significantly affect the prognosis and survival of patients with cardiovascular diseases. We here review the latest research on lncRNAs in cardiovascular diseases as a basis to formulate future research on prevention and treatment of cardiovascular diseases.

The contribution of non-coding regulatory elements to cardiovascular disease

Cardiovascular disease collectively accounts for a quarter of deaths worldwide. Genome-wide association studies across a range of cardiovascular traits and pathologies have highlighted the prevalence of common non-coding genetic variants within candidate loci. Here, we review genetic, epigenomic and molecular approaches to investigate the contribution of non-coding regulatory elements in cardiovascular biology. We then discuss recent insights on the emerging role of non-coding variation in predisposition to cardiovascular disease, with a focus on novel mechanistic examples from functional genomics studies. Lastly, we consider the clinical significance of these findings at present, and some of the current challenges facing the field.

Epigenetic Regulation of Alternative mRNA Splicing in Dilated Cardiomyopathy

In recent years, the genetic architecture of dilated cardiomyopathy (DCM) has been more thoroughly elucidated. However, there is still insufficient knowledge on the modifiers and regulatory principles that lead to the failure of myocardial function. The current study investigates the association of epigenome-wide DNA methylation and alternative splicing, both of which are important regulatory principles in DCM. We analyzed screening and replication cohorts of cases and controls and identified distinct transcriptomic patterns in the myocardium that differ significantly, and we identified a strong association of intronic DNA methylation and flanking exons usage (p < 2 × 10^-16). By combining differential exon usage (DEU) and differential methylation regions (DMR), we found a significant change of regulation in important sarcomeric and other DCM-associated pathways. Interestingly, inverse regulation of Titin antisense non-coding RNA transcript splicing and DNA methylation of a locus reciprocal to TTN substantiate these findings and indicate an additional role for non-protein-coding transcripts. In summary, this study highlights for the first time the close interrelationship between genetic imprinting by DNA methylation and the transport of this epigenetic information towards the dynamic mRNA splicing landscape. This expands our knowledge of the genome-environment interaction in DCM besides simple gene expression regulation.

Familial Recurrent Myocarditis Triggered by Exercise in Patients With a Truncating Variant of the Desmoplakin Gene

Background

Variants of the desmosomal protein desmoplakin are associated with arrhythmogenic cardiomyopathy, an important cause of ventricular arrhythmias in children and young adults. Disease penetrance of desmoplakin variants is incomplete and variant carriers may display noncardiac, dermatologic phenotypes. We describe a novel cardiac phenotype associated with a truncating desmoplakin variant, likely causing mechanical instability of myocardial desmosomes.

Methods and Results

In 2 young brothers with recurrent myocarditis triggered by physical exercise, screening of 218 cardiomyopathy‐related genes identified the heterozygous truncating variant p.Arg1458Ter in desmoplakin. Screening for infections yielded no evidence of viral or nonviral infections. Myosin and troponin I autoantibodies were detected at high titers. Immunohistology failed to detect any residual DSP protein in endomyocardial biopsies, and none of the histologic criteria of arrhythmogenic cardiomyopathy were fulfilled. Cardiac magnetic resonance imaging revealed no features associated with right ventricular arrhythmogenic cardiomyopathy, but multifocal subepicardial late gadolinium enhancement was present in the left ventricles of both brothers. Screening of adult cardiomyopathy cohorts for truncating variants identified the rare genetic variants p.Gln307Ter, p.Tyr1391Ter, and p.Tyr1512Ter, suggesting that over subsequent decades critical genetic/exogenous modifiers drive pathogenesis from desmoplakin truncations toward different end points.

Conclusions

The described novel phenotype of familial recurrent myocarditis associated with a desmoplakin truncation in adolescents likely represents a serendipitously revealed subtype of arrhythmogenic cardiomyopathy. It may be caused by a distinctive adverse effect of the variant desmoplakin upon the mechanical stability of myocardial desmosomes. Variant screening is advisable to allow early detection of patients with similar phenotypes.

Epigenetics in dilated cardiomyopathy

PURPOSE OF REVIEW

Characterized by enlarged ventricle and loss of systolic function, dilated cardiomyopathy (DCM) has the highest morbidity among all the cardiomyopathies. Although it is well established that DCM is typically caused by mutations in a large number of genes, there is an emerging appreciation for the contribution of epigenetic alteration in the development of DCM.

RECENT FINDINGS

We present some of the recent progress in the field of epigenetics in DCM by focusing on the four major epigenetic modifications, that is, DNA methylation, histone modification, chromatin remodeling as well as the noncoding RNAs. The major players involved in these DCM-related epigenetic reprogramming will be highlighted. Finally, the diagnostic and the therapeutic implications for DCM based on new knowledge of epigenetic regulation will also be discussed.

SUMMARY

As a rapidly expanding field, epigenetic studies in DCM have the promise to yield both novel mechanistic insights as well as potential new avenues for more effective treatment of the disease.

Comparison of multiple algorithms to reliably detect structural variants in pears

Background

Structural variations (SVs) have been reported to play an important role in genetic diversity and trait regulation. Many computer algorithms detecting SVs have recently been developed, but the use of multiple algorithms to detect high-confidence SVs has not been studied. The most suitable sequencing depth for detecting SVs in pear is also not known.

Results

In this study, a pipeline to detect SVs using next-generation and long-read sequencing data was constructed. The performances of seven types of SV detection software using next-generation sequencing (NGS) data and two types of software using long-read sequencing data (SVIM and Sniffles), which are based on different algorithms, were compared. Of the nine software packages evaluated, SVIM identified the most SVs, and Sniffles detected SVs with the highest accuracy (> 90%). When the results from multiple SV detection tools were combined, the SVs identified by both MetaSV and IMR/DENOM, which use NGS data, were more accurate than those identified by both SVIM and Sniffles, with mean accuracies of 98.7 and 96.5%, respectively. The software packages using long-read sequencing data required fewer CPU cores and less memory and ran faster than those using NGS data. In addition, according to the performances of assembly-based algorithms using NGS data, we found that a sequencing depth of 50× is appropriate for detecting SVs in the pear genome.

Conclusion

This study provides strong evidence that more than one SV detection software package, each based on a different algorithm, should be used to detect SVs with higher confidence, and that long-read sequencing data are better than NGS data for SV detection. The SV detection pipeline that we have established will facilitate the study of diversity in other crops.

Challenges in identifying large germline structural variants for clinical use by long read sequencing

Genomic structural variations, previously considered rare events, are widely recognized as a major source of inter-individual variability and hence, a major hurdle in optimum patient stratification and disease management. Herein, we focus on large complex germline structural variations and present challenges towards target treatment via the synergy of state-of-the-art approaches and information technology tools. A complex structural variation detection remains challenging, as there is no gold standard for identifying such genomic variations with long reads, especially when the chromosomal rearrangement in question is a few Mb in length. A clinical case with a large complex chromosomal rearrangement serves as a paradigm. We feel that functional validation and data interpretation are of outmost importance for information growth to be translated into knowledge growth and hence, new working practices are highlighted.

Reconstruction and Analysis of the lncRNA-miRNA-mRNA Network Based on Competitive Endogenous RNA Reveal Functional lncRNAs in Dilated Cardiomyopathy

Dilated cardiomyopathy (DCM) is an important cause of sudden death and heart failure with an unknown etiology. Recent studies have suggested that long non-coding RNA (lncRNA) can interact with microRNA (miRNA) and indirectly interact with mRNA through competitive endogenous RNA (ceRNA) activities. However, the mechanism of ceRNA in DCM remains unclear. In this study, a miRNA array was first performed using heart samples from DCM patients and healthy controls. For further validation, we conducted real-time quantitative reverse transcription (RT)-PCR using samples from DCM patients and a doxorubicin-induced rodent model of cardiomyopathy, revealing that miR-144-3p and miR-451a were down-regulated, and miR-21-5p was up-regulated. Based on the ceRNA theory, we constructed a global triple network using data from the National Center for Biotechnology Information Gene Expression Omnibus (NCBI-GEO) and our miRNA array. The lncRNA-miRNA-mRNA network comprised 22 lncRNA nodes, 32 mRNA nodes, and 11 miRNA nodes. Hub nodes and the number of relationship pairs were then analyzed, and the results showed that two lncRNAs (NONHSAT001691 and NONHSAT006358) targeting miR-144/451 were highly related to DCM. Then, cluster module and random walk with restart for the ceRNA network were analyzed and identified four lncRNAs (NONHSAT026953/NONHSAT006250/NONHSAT133928/NONHSAT041662) targeting miR-21 that were significantly related to DCM. This study provides a new strategy for research on DCM or other diseases. Furthermore, lncRNA-miRNA pairs may be regarded as candidate diagnostic biomarkers or potential therapeutic targets of DCM.

Hypoxia-induced H19/YB-1 cascade modulates cardiac remodeling after infarction

Rationale: Long non-coding RNA (lncRNAs) has been identified as a pivotal novel regulators in cardiac development as well as cardiac pathogenesis. lncRNA H19 is known as a fetal gene but it is exclusively abundant in the heart and skeletal muscles in adulthood, and is evolutionarily conserved in humans and mice. It has been reported to possess a significant correlation with the risk of coronary artery diseases. However, the function of H19 is not well characterized in heart.

Methods: Loss-of-function and gain-of-function mouse models with left anterior descending coronary artery-ligation surgery were utilized to evaluate the functionality of H19 in vivo. For mechanistic studies, hypoxia condition were exerted in in vitro models to mimic cardiac ischemic injury. Chromatin isolation by RNA immunoprecipitation (ChIRP) was performed to reveal the interacting protein of lncRNA H19.

Results: lncRNA H19 was significantly upregulated in the infarct area post-surgery day 4 in mouse model. Ectopic expression of H19 in the mouse heart resulted in severe cardiac dilation and fibrosis. Several extracellular matrix (ECM) genes were significantly upregulated. While genetic ablation of H19 by CRISPR-Cas9 ameliorated post-MI cardiac remodeling with reduced expression in ECM genes. Through chromatin isolation by RNA purification (ChIRP), we identified Y-box-binding protein (YB)-1, a suppressor of Collagen 1A1, as an interacting protein of H19. Furthermore, H19 acted to antagonize YB-1 through direct interaction under hypoxia, which resulted in de-repression of Collagen 1A1 expression and cardiac fibrosis.

Conclusions: Together these results demonstrate that lncRNA H19 and its interacting protein YB-1 are crucial for ECM regulation during cardiac remodeling.

Pathologic gene network rewiring implicates PPP1R3A as a central regulator in pressure overload heart failure

Heart failure is a leading cause of mortality, yet our understanding of the genetic interactions underlying this disease remains incomplete. Here, we harvest 1352 healthy and failing human hearts directly from transplant center operating rooms, and obtain genome-wide genotyping and gene expression measurements for a subset of 313. We build failing and non-failing cardiac regulatory gene networks, revealing important regulators and cardiac expression quantitative trait loci (eQTLs). PPP1R3A emerges as a regulator whose network connectivity changes significantly between health and disease. RNA sequencing after PPP1R3A knockdown validates network-based predictions, and highlights metabolic pathway regulation associated with increased cardiomyocyte size and perturbed respiratory metabolism. Mice lacking PPP1R3A are protected against pressure-overload heart failure. We present a global gene interaction map of the human heart failure transition, identify previously unreported cardiac eQTLs, and demonstrate the discovery potential of disease-specific networks through the description of PPP1R3A as a central regulator in heart failure.

The genetic and pathogenetic basis of heart failure is incompletely understood. Here, the authors present a high-fidelity tissue collection from rapidly preserved failing and non-failing control hearts which are used for eQTL mapping and network analysis, resulting in the prioritization of PPP1R3A as a heart failure gene.

Clinical and genetic insights into non-compaction: a meta-analysis and systematic review on 7598 individuals

BACKGROUND

Left ventricular non-compaction has been increasingly diagnosed in recent years. However, it is still debated whether non-compaction is a pathological condition or a physiological trait. In this meta-analysis and systematic review, we compare studies, which investigated these two different perspectives. Furthermore, we provide a comprehensive overview on the clinical outcome as well as genetic background of left ventricular non-compaction cardiomyopathy in adult patients.

METHODS AND RESULTS

We retrieved PubMed/Medline literatures in English language from 2000 to 19/09/2018 on clinical outcome and genotype of patients with non-compaction. We summarized and extensively reviewed all studies that passed selection criteria and performed a meta-analysis on key phenotypic parameters. Altogether, 35 studies with 2271 non-compaction patients were included in our meta-analysis. The mean age at diagnosis was the mid of their fifth decade. Two-thirds of patients were male. Congenital heart diseases including atrial or ventricular septum defect or Ebstein anomaly were reported in 7% of patients. Twenty-four percent presented with family history of cardiomyopathy. The mean frequency of neuromuscular diseases was 5%. Heart rhythm abnormalities were reported frequently: conduction disease in 26%, supraventricular tachycardia in 17%, and sustained or non-sustained ventricular tachycardia in 18% of patients. Three important outcome measures were reported including systemic thromboembolic events with a mean frequency of 9%, heart transplantation with 4%, and adequate ICD therapy with 15%. Nine studies investigated the genetics of non-compaction cardiomyopathy. The most frequently mutated gene was TTN with a pooled frequency of 11%. The average frequency of MYH7 mutations was 9%, for MYBPC3 mutations 5%, and for CASQ2 and LDB3 3% each. TPM1, MIB1, ACTC1, and LMNA mutations had an average frequency of 2% each. Mutations in PLN, HCN4, TAZ, DTNA, TNNT2, and RBM20 were reported with a frequency of 1% each. We also summarized the results of eight studies investigating the non-compaction in altogether 5327 athletes, pregnant women, patients with sickle cell disease, as well as individuals from population-based cohorts, in which the presence of left ventricular hypertrabeculation ranged from 1.3 to 37%.

CONCLUSION

The summarized data indicate that non-compaction may lead to unfavorable outcome in different cardiomyopathy entities. The presence of key features in a multimodal diagnostic approach could distinguish between benign morphological trait and manifest cardiomyopathy.

Genomic structural variations lead to dysregulation of important coding and non-coding RNA species in dilated cardiomyopathy

The transcriptome needs to be tightly regulated by mechanisms that include transcription factors, enhancers, and repressors as well as non‐coding RNAs. Besides this dynamic regulation, a large part of phenotypic variability of eukaryotes is expressed through changes in gene transcription caused by genetic variation. In this study, we evaluate genome‐wide structural genomic variants (SVs) and their association with gene expression in the human heart. We detected 3,898 individual SVs affecting all classes of gene transcripts (e.g., mRNA, miRNA, lncRNA) and regulatory genomic regions (e.g., enhancer or TFBS). In a cohort of patients (n = 50) with dilated cardiomyopathy (DCM), 80,635 non‐protein‐coding elements of the genome are deleted or duplicated by SVs, containing 3,758 long non‐coding RNAs and 1,756 protein‐coding transcripts. 65.3% of the SV‐eQTLs do not harbor a significant SNV‐eQTL, and for the regions with both classes of association, we find similar effect sizes. In case of deleted protein‐coding exons, we find downregulation of the associated transcripts, duplication events, however, do not show significant changes over all events. In summary, we are first to describe the genomic variability associated with SVs in heart failure due to DCM and dissect their impact on the transcriptome. Overall, SVs explain up to 7.5% of the variation of cardiac gene expression, underlining the importance to study human myocardial gene expression in the context of the individual genome. This has immediate implications for studies on basic mechanisms of cardiac maladaptation, biomarkers, and (gene) therapeutic studies alike.

Antisense Transcription in Loci Associated to Hereditary Neurodegenerative Diseases

Natural antisense transcripts are common features of mammalian genes providing additional regulatory layers of gene expression. A comprehensive description of antisense transcription in loci associated to familial neurodegenerative diseases may identify key players in gene regulation and provide tools for manipulating gene expression. We take advantage of the FANTOM5 sequencing datasets that represent the largest collection to date of genome-wide promoter usage in almost 2000 human samples. Transcription start sites (TSSs) are mapped at high resolution by the use of a modified protocol of cap analysis of gene expression (CAGE) for high-throughput single molecule next-generation sequencing with Helicos (hCAGE). Here we present the analysis of antisense transcription at 17 loci associated to hereditary Alzheimer’s disease, Frontotemporal Dementia, Parkinson’s disease, Amyotrophic Lateral Sclerosis, and Huntington’s disease. We focused our analysis on libraries derived from brain tissues and primary cells. We also screened libraries from total blood and blood cell populations in the quest for peripheral biomarkers of neurodegenerative diseases. We identified 63 robust promoters in antisense orientation to genes associated to familial neurodegeneration. When applying a less stringent cutoff, this number increases to over 400. A subset of these promoters represents alternative TSSs for 24 FANTOM5 annotated long noncoding RNA (lncRNA) genes, in antisense orientation to 13 of the loci analyzed here, while the remaining contribute to the expression of additional transcript variants. Intersection with GWAS studies, sample ontology, and dynamic expression reveals association to specific genetic traits as well as cell and tissue types, not limited to neurodegenerative diseases. Antisense transcription was validated for a subset of genes, including those encoding for Microtubule-Associated Protein Tau, α-synuclein, Parkinsonism-associated deglycase DJ-1, and Leucin-Rich Repeat Kinase 2. This work provides evidence for the existence of additional regulatory mechanisms of the expression of neurodegenerative disease-causing genes by previously not-annotated and/or not-validated antisense long noncoding RNAs.

Intronic CNVs and gene expression variation in human populations

Introns can be extraordinarily large and they account for the majority of the DNA sequence in human genes. However, little is known about their population patterns of structural variation and their functional implication. By combining the most extensive maps of CNVs in human populations, we have found that intronic losses are the most frequent copy number variants (CNVs) in protein-coding genes in human, with 12,986 intronic deletions, affecting 4,147 genes (including 1,154 essential genes and 1,638 disease-related genes). This intronic length variation results in dozens of genes showing extreme population variability in size, with 40 genes with 10 or more different sizes and up to 150 allelic sizes. Intronic losses are frequent in evolutionarily ancient genes that are highly conserved at the protein sequence level. This result contrasts with losses overlapping exons, which are observed less often than expected by chance and almost exclusively affect primate-specific genes. An integrated analysis of CNVs and RNA-seq data showed that intronic loss can be associated with significant differences in gene expression levels in the population (CNV-eQTLs). These intronic CNV-eQTLs regions are enriched for intronic enhancers and can be associated with expression differences of other genes showing long distance intron-promoter 3D interactions. Our data suggests that intronic structural variation of protein-coding genes makes an important contribution to the variability of gene expression and splicing in human populations.

Identification of Potential Prostate Cancer-Related Pseudogenes Based on Competitive Endogenous RNA Network Hypothesis

BACKGROUND Long noncoding RNAs (lncRNAs) have been revealed to function as competing endogenous RNAs (ceRNAs), which can seclude the common microRNAs (miRNAs) and hence prevent the miRNAs from binding to their ancestral gene. Nonetheless, the role of lncRNA-mediated ceRNAs in prostate cancer has not yet been elucidated. MATERIAL AND METHODS Using The Cancer Genome Atlas (TCGA) database, lncRNA, miRNA, and mRNA profiles from 499 prostate cancer tissues and 52 normal prostate tissues were analyzed with the R package "DESeq" to identify the differentially expressed RNAs. GO and KEGG pathway analyses were performed using "DAVID6.8" and R packages "Clusterprofile." The ceRNA network in prostate cancer was constructed using miRDB, miRTarBase, and TargetScan databases. Survival analysis was performed with Kaplan-Meier analysis. RESULTS A total of 376 lncRNAs, 33 miRNAs, and 687 mRNAs were identified as significant factors in tumorigenesis. Based on the hypothesis that the ceRNA network (lncRNA-miRNA-mRNA regulatory axis) is involved in prostate cancer and forms competitive interrelations between miRNA and mRNA or lncRNA, we constructed a ceRNA network that included 23 lncRNAs, 6 miRNAs, and 2 mRNAs that were differentially expressed in prostate cancer. Only 3 lncRNAs (LINC00308, LINC00355, and OSTN-AS1) had a significant association with survival (P<0.05). The 3 prostate cancer-specific lncRNA were validated in prostate cancer cell lines PC3 and DU145 using qRT-PCR. CONCLUSIONS We demonstrated the differential lncRNA expression profiles in prostate cancer, which provides new insights for future studies of the ceRNA network and its regulatory mechanisms in prostate cancer.