RNA sequencing of blood in coronary artery disease: involvement of regulatory T cell imbalance.

BACKGROUND: Cardiovascular disease had a global prevalence of 523 million cases and 18.6 million deaths in 2019. The current standard for diagnosing coronary artery disease (CAD) is coronary angiography. Surprisingly, despite well-established clinical indications, up to 40% of the one million invasive cardiac catheterizations return a result of 'no blockage'. The present studies employed RNA sequencing of whole blood to identify an RNA signature in patients with angiographically confirmed CAD. METHODS: Whole blood RNA was depleted of ribosomal RNA (rRNA) and analyzed by single-molecule sequencing of RNA (RNAseq) to identify transcripts associated with CAD (TRACs) in a discovery group of 96 patients presenting for elective coronary catheterization. The resulting transcript counts were compared between groups to identify differentially expressed genes (DEGs). RESULTS: Surprisingly, 98% of DEGs/TRACs were down-regulated ~ 1.7-fold in patients with mild to severe CAD (> 20% stenosis). The TRACs were independent of comorbid risk factors for CAD, such as sex, hypertension, and smoking. Bioinformatic analysis identified an enrichment in transcripts such as FoxP1, ICOSLG, IKZF4/Eos, SMYD3, TRIM28, and TCF3/E2A that are likely markers of regulatory T cells (Treg), consistent with known reductions in Tregs in CAD. A validation cohort of 80 patients confirmed the overall pattern (92% down-regulation) and supported many of the Treg-related changes. TRACs were enriched for transcripts associated with stress granules, which sequester RNAs, and ciliary and synaptic transcripts, possibly consistent with changes in the immune synapse of developing T cells. CONCLUSIONS: These studies identify a novel mRNA signature of a Treg-like defect in CAD patients and provides a blueprint for a diagnostic test for CAD. The pattern of changes is consistent with stress-related changes in the maturation of T and Treg cells, possibly due to changes in the immune synapse.

Genome-Wide Analysis of A-to-I RNA Editing.

Adenosine (A)-to-inosine (I) RNA editing is a fundamental posttranscriptional modification that ensures the deamination of A-to-I in double-stranded (ds) RNA molecules. Intriguingly, the A-to-I RNA editing system is particularly active in the nervous system of higher eukaryotes, altering a plethora of noncoding and coding sequences. Abnormal RNA editing is highly associated with many neurological phenotypes and neurodevelopmental disorders. However, the molecular mechanisms underlying RNA editing-mediated pathogenesis still remain enigmatic and have attracted increasing attention from researchers. Over the last decade, methods available to perform genome-wide transcriptome analysis, have evolved rapidly. Within the RNA editing field researchers have adopted next-generation sequencing technologies to identify RNA-editing sites within genomes and to elucidate the underlying process. However, technical challenges associated with editing site discovery have hindered efforts to uncover comprehensive editing site datasets, resulting in the general perception that the collections of annotated editing sites represent only a small minority of the total number of sites in a given organism, tissue, or cell type of interest. Additionally to doubts about sensitivity, existing RNA-editing site lists often contain high percentages of false positives, leading to uncertainty about their validity and usefulness in downstream studies. An accurate investigation of A-to-I editing requires properly validated datasets of editing sites with demonstrated and transparent levels of sensitivity and specificity. Here, we describe a high signal-to-noise method for RNA-editing site detection using single-molecule sequencing (SMS). With this method, authentic RNA-editing sites may be differentiated from artifacts. Machine learning approaches provide a procedure to improve upon and experimentally validate sequencing outcomes through use of computationally predicted, iterative feedback loops. Subsequent use of extensive Sanger sequencing validations can generate accurate editing site lists. This approach has broad application and accurate genome-wide editing analysis of various tissues from clinical specimens or various experimental organisms is now a possibility.

Molecular mechanism underlying differential apoptosis between human melanoma cell lines UACC903 and UACC903(+6) revealed by mitochondria-focused cDNA microarrays.

Human malignant melanoma cell line UACC903 is resistant to apoptosis while chromosome 6-mediated suppressed cell line UACC903(+6) is sensitive. Here, we describe identification of differential molecular pathways underlying this difference. Using our recently developed mitochondria-focused cDNA microarrays, we identified 154 differentially expressed genes including proapoptotic (BAK1 [6p21.3], BCAP31, BNIP1, CASP3, CASP6, FAS, FDX1, FDXR, TNFSF10 and VDAC1) and antiapoptotic (BCL2L1, CLN3 and MCL1) genes. Expression of these pro- and anti-apoptotic genes was higher in UACC903(+6) than in UACC903 before UV treatment and was altered after UV treatment. qRT-PCR and Western blots validated microarray results. Our bioinformatic analysis mapped these genes to differential molecular pathways that predict resistance and sensitivity of UACC903 and UACC903(+6) to apoptosis respectively. The pathways were functionally confirmed by the FAS ligand-induced cell death and by siRNA knockdown of BAK1 protein. These results demonstrated the differential molecular pathways underlying survival and apoptosis of UACC903 and UACC903(+6) cell lines.