Many human genes are transcribed from both strands and produce sense-antisense gene pairs. Sense-antisense (SAS) chimeric transcripts are produced upon the coalescing of exons/introns from both sense and antisense transcripts of the same gene. SAS chimera was first reported in prostate cancer cells. Subsequently, numerous SAS chimeras have been reported in the ChiTaRS-2.1 database. However, the landscape of their expression in human cells and functional aspects are still unknown. We found that longer palindromic sequences are a unique feature of SAS chimeras. Structural analysis indicates that a long hairpin-like structure formed by many consecutive Watson-Crick base pairs appears because of these long palindromic sequences, which possibly play a similar role as double-stranded RNA (dsRNA), interfering with gene expression. RNA–RNA interaction analysis suggested that SAS chimeras could significantly interact with their parental mRNAs, indicating their potential regulatory features. Here, 267 SAS chimeras were mapped in RNA-seq data from 16 healthy human tissues, revealing their expression in normal cells. Evolutionary analysis suggested the positive selection favoring sense-antisense fusions that significantly impacted the evolution of their function and structure. Overall, our study provides detailed insight into the expression landscape of SAS chimeras in human cells and identifies potential regulatory features.

Chimeric RNA transcripts are formed when exons from two genes fuse together, often due to chromosomal translocations, transcriptional errors or trans-splicing effect. While these chimeric RNAs produce functional proteins only in certain cases, they play a significant role in disease phenotyping and progression. ChiTaRS 5.0 (http://chitars.md.biu.ac.il/) is the latest and most comprehensive chimeric transcript repository, with 111 582 annotated entries from eight species, including 23 167 known human cancer breakpoints. The database includes unique information correlating chimeric breakpoints with 3D chromatin contact maps, generated from public datasets of chromosome conformation capture techniques (Hi–C). In this update, we have added curated information on druggable fusion targets matched with chimeric breakpoints, which are applicable to precision medicine in cancers. The introduction of a new section that lists chimeric RNAs in various cell-lines is another salient feature. Finally, using text-mining techniques, novel chimeras in Alzheimer's disease, schizophrenia, dyslexia and other diseases were collected in ChiTaRS. Thus, this improved version is an extensive catalogue of chimeras from multiple species. It extends our understanding of the evolution of chimeric transcripts in eukaryotes and contributes to the analysis of 3D genome conformational changes and the functional role of chimeras in the etiopathogenesis of cancers and other complex diseases.

Cardiovascular diseases (CVDs) are of multifactorial origin and can be attributed to several genetic and environmental components. CVDs are the leading cause of mortality worldwide and they primarily damage the heart and the vascular system. Non-coding RNA (ncRNA) refers to functional RNA molecules, which have been transcribed into DNA but do not further get translated into proteins. Recent transcriptomic studies have identified the presence of thousands of ncRNA molecules across species. In humans, less than 2% of the total genome represents the protein-coding genes. While the role of many ncRNAs is yet to be ascertained, some long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) have been associated with disease progression, serving as useful diagnostic and prognostic biomarkers. A plethora of data repositories specialized in ncRNAs have been developed over the years using publicly available high-throughput data from next-generation sequencing and other approaches, that cover various facets of ncRNA research like basic and functional annotation, expressional profile, structural and molecular changes, and interaction with other biomolecules. Here, we provide a compendium of the current ncRNA databases relevant to cardiovascular research.

Single-cell and single-nuclei approaches are being extensively used to decipher the cellular heterogeneity of samples and to understand the genetic factors leading to various diseases. While single-cell RNA sequencing is quite straightforward, single-nuclei sequencing requires careful consideration in the isolation & processing of intact nuclei after dissociation. Numerous protocols have been developed for this purpose, but the size and morphology of cardiomyocytes make the process quite complicated.1-3 Previously described processes also included steps involving manual homogenization using a Dounce homogenizer and Fluorescence-activated Cell Sorting.2,4 These steps have an increased propensity to vary from user to user and also produce stress on the cells, which further alters the transcriptional profile of these nuclei. To this end, we devised a simple direct protocol for processing cardiac tissue into intact nuclei for downstream single-nuclei RNA sequencing using the gentleMACS Octo Dissociator. This protocol has been extensively tested with Engineered Heart Tissues (EHTs) and also works well with frozen or fresh cardiac tissues from human biopsies.

Funding Acknowledgements: Type of funding sources: Public grant(s) – EU funding. Main funding source(s): TRAIN-HEART Innovative Training Network, funded by the European Union’s Horizon 2020 research and innovation program (under the Marie Sklodowska-Curie grant agreement no. 813716) Characterizing Atrial fibrillation by Translating its Causes into Health Modifiers in the Elderly (CATCH ME), funded by the European Union’s Horizon 2020 research and innovation program (under the grant agreement no. 633196) Background: Atrial fibrillation (AF) is the most common cardiac arrhythmia and is associated with heart failure (HF) and stroke. Clinical and experimental data from previous studies suggest gender differences in mechanisms and phenotypes of AF: women may have more atrial fibrosis, worse outcomes after catheter ablation, and some women carry a higher risk for thromboembolic complications than men. The molecular mechanisms underlying these differences are still poorly understood. Methods: Gender-based transcriptional patterns were assessed using paired-end, directional RNA sequencing data generated from atrial tissue biopsies in 199 patients either in sinus rhythm or with paroxysmal or persistent AF as part of the CATCH-ME project. Transcript counts were compared between genders separately in the left and right atria using the DESeq2 package in R. The models were adjusted for potential sources of confounding (age, atrial fibrillation status, heart failure status and sequencing batch). Interaction models were implemented using DESeq2 to compare gender*morbidity interactions for persistent AF and HF. Significance was assessed using likelihood ratio tests comparing models with and without the interaction terms. Results with an adjusted P-value 0.05 were considered significant and utilized for subsequent downstream assessments. Differentially expressed (DE) genes were tested for enrichment of gene ontology (GO) terms and KEGG pathways using the WebGestalt toolkit. Results: Transcriptome-wide profiling across the cohort identified 33 sex-differentiated genes in the left atria and 51 in the right atrial samples, with 21 of these showing bilateral differences. Interestingly, 36 (44%) of the results from these analyses were comprised of non-coding transcripts, including long non-coding RNAs (lncRNAs), antisense RNAs and pseudogenes. GO and pathway enrichment analyses for these genes revealed their involvement in critical pathways such as the complement and coagulation cascades and RNA transport. Interaction analyses between gender and AF identified two genes (MPP2 & GNAS-AS1) that were differentially transcribed in the right atria and one gene (MYL2) that was DE in the left atria by gender in persistent AF samples. A similar analysis comparing gender*HF morbidity also revealed evidence of DE. Four transcripts (HLA-DQB1-AS1, EIF1AY, UTY and ZFY-AS1) showed gender-specific differences in expression by HF status in left atria, while HLA-DQB1-AS1 was differentially regulated by gender and HF status in right atrial samples. Conclusions: These RNA-seq analyses provide novel insights into gender-related differences in the transcriptional landscape of right and left adult human atrial appendages. Moreover, interaction analyses identified three genes DE in female atria in persistent AF and four DE genes in female atria in heart failure, providing a molecular anchor for the observed differences in atrial diseases phenotypes between men and women.