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A molecular map of long non-coding RNA expression, isoform switching and alternative splicing in osteoarthritis.

ABSTRACT: Osteoarthritis is a prevalent joint disease and a major cause of disability worldwide with no curative therapy. Development of disease-modifying therapies requires a better understanding of the molecular mechanisms underpinning disease. A hallmark of osteoarthritis is cartilage degradation. To define molecular events characterizing osteoarthritis at the whole transcriptome level, we performed deep RNA sequencing in paired samples of low- and high-osteoarthritis grade knee cartilage derived from 124 patients undergoing total joint replacement. We detected differential expression between low- and high-osteoarthritis grade articular cartilage for 365 genes and identified a 38-gene signature in osteoarthritis cartilage by replicating our findings in an independent dataset. We also found differential expression for 25 novel long non-coding RNA genes (lncRNAs) and identified potential lncRNA interactions with RNA-binding proteins in osteoarthritis. We assessed alterations in the relative usage of individual gene transcripts and identified differential transcript usage for 82 genes, including ABI3BP, coding for an extracellular matrix protein, AKT1S1, a negative regulator of the mTOR pathway and TPRM4, coding for a transient receptor potential channel. We further assessed genome-wide differential splicing, for the first time in osteoarthritis, and detected differential splicing for 209 genes, which were enriched for extracellular matrix, proteoglycans and integrin surface interactions terms. In the largest study of its kind in osteoarthritis, we find that isoform and splicing changes, in addition to extensive differences in both coding and non-coding sequence expression, are associated with disease and demonstrate a novel layer of genomic complexity to osteoarthritis pathogenesis.

SUBMITTER: Katsoula G

PROVIDER: S-EPMC9239745 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:The continuously prolonged human lifespan is accompanied by increase in neurodegenerative diseases incidence, calling for the development of inexpensive blood-based diagnostics. Analyzing blood cell transcripts by RNA-Seq is a robust means to identify novel biomarkers that rapidly becomes a commonplace. However, there is lack of tools to discover novel exons, junctions and splicing events and to precisely and sensitively assess differential splicing through RNA-Seq data analysis and across RNA-Seq platforms. Here, we present a new and comprehensive computational workflow for whole-transcriptome RNA-Seq analysis, using an updated version of the software AltAnalyze, to identify both known and novel high-confidence alternative splicing events, and to integrate them with both protein-domains and microRNA binding annotations. We applied the novel workflow on RNA-Seq data from Parkinson's disease (PD) patients' leukocytes pre- and post- Deep Brain Stimulation (DBS) treatment and compared to healthy controls. Disease-mediated changes included decreased usage of alternative promoters and N-termini, 5'-end variations and mutually-exclusive exons. The PD regulated FUS and HNRNP A/B included prion-like domains regulated regions. We also present here a workflow to identify and analyze long non-coding RNAs (lncRNAs) via RNA-Seq data. We identified reduced lncRNA expression and selective PD-induced changes in 13 of over 6,000 detected leukocyte lncRNAs, four of which were inversely altered post-DBS. These included the U1 spliceosomal lncRNA and RP11-462G22.1, each entailing sequence complementarity to numerous microRNAs. Analysis of RNA-Seq from PD and unaffected controls brains revealed over 7,000 brain-expressed lncRNAs, of which 3,495 were co-expressed in the leukocytes including U1, which showed both leukocyte and brain increases. Furthermore, qRT-PCR validations confirmed these co-increases in PD leukocytes and two brain regions, the amygdala and substantia-nigra, compared to controls. This novel workflow allows deep multi-level inspection of RNA-Seq datasets and provides a comprehensive new resource for understanding disease transcriptome modifications in PD and other neurodegenerative diseases.

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A molecular map of long non-coding RNA expression, isoform switching and alternative splicing in osteoarthritis.

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