Annotating Transcriptional Effects of Genetic Variants in Disease-Relevant Tissue: Transcriptome-Wide Allelic Imbalance in Osteoarthritic Cartilage

Objective. Multiple single-nucleotide polymorphisms (SNPs) conferring susceptibility to osteoarthritis (OA) mark imbalanced expression of positional genes in articular cartilage, reflected by unequally expressed alleles among heterozygotes (allelic imbalance [AI]). We undertook this study to explore the articular cartilage transcriptome from OA patients for AI events to identify putative disease-driving genetic variation. Methods. AI was assessed in 42 preserved and 5 lesioned OA cartilage samples (from the Research Arthritis and Articular Cartilage study) for which RNA sequencing data were available. The count fraction of the alternative alleles among the alternative and reference alleles together (φ) was determined for heterozygous individuals. A meta-analysis was performed to generate a meta-φ and P value for each SNP with a false discovery rate (FDR) correction for multiple comparisons. To further validate AI events, we explored them as a function of multiple additional OA features. Results. We observed a total of 2,070 SNPs that consistently marked AI of 1,031 unique genes in articular cartilage. Of these genes, 49 were found to be significantly differentially expressed (fold change 2, FDR <0.05) between preserved and paired lesioned cartilage, and 18 had previously been reported to confer susceptibility to OA and/or related phenotypes. Moreover, we identified notable highly significant AI SNPs in the CRLF1, WWP2, and RPS3 genes that were related to multiple OA features. Conclusion. We present a framework and resulting data set for researchers in the OA research field to probe for disease-relevant genetic variation that affects gene expression in pivotal disease-affected tissue. This likely includes putative novel compelling OA risk genes such as CRLF1, WWP2, and RPS3

Symposium on the Scottish labour market

In the post-war period, up to the late 1960s, Britain enjoyed a modicum of unemployment and government policies which were geared to producing Full Employment were considered a success. It was simple - boost demand and more people would find work. But the mid 1970s the economic regency enjoyed by those advocating demand sided policies fell into disrepute as the OPEC nations raised prices dramatically and brought in a new era of both rising prices and unemployment. The laws of economics, which previously had viewed policy decisions as the choice between lower unemployment and higher inflation were now redundant. Both unemployment and inflation were moving in the same direction. The era of stagflation had begun

Transcriptome and genome sequencing uncovers functional variation in humans

Summary Genome sequencing projects are discovering millions of genetic variants in humans, and interpretation of their functional effects is essential for understanding the genetic basis of variation in human traits. Here we report sequencing and deep analysis of mRNA and miRNA from lymphoblastoid cell lines of 462 individuals from the 1000 Genomes Project – the first uniformly processed RNA-seq data from multiple human populations with high-quality genome sequences. We discovered extremely widespread genetic variation affecting regulation of the majority of genes, with transcript structure and expression level variation being equally common but genetically largely independent. Our characterization of causal regulatory variation sheds light on cellular mechanisms of regulatory and loss-of-function variation, and allowed us to infer putative causal variants for dozens of disease-associated loci. Altogether, this study provides a deep understanding of the cellular mechanisms of transcriptome variation and of the landscape of functional variants in the human genome

Lessons from non-canonical splicing

Recent improvements in experimental and computational techniques that are used to study the transcriptome have enabled an unprecedented view of RNA processing, revealing many previously unknown non-canonical splicing events. This includes cryptic events located far from the currently annotated exons and unconventional splicing mechanisms that have important roles in regulating gene expression. These non-canonical splicing events are a major source of newly emerging transcripts during evolution, especially when they involve sequences derived from transposable elements. They are therefore under precise regulation and quality control, which minimizes their potential to disrupt gene expression. We explain how non-canonical splicing can lead to aberrant transcripts that cause many diseases, and also how it can be exploited for new therapeutic strategies

Non-sequential and multi-step splicing of the dystrophin transcript

Molecular Technology and Informatics for Personalised Medicine and HealthFunctional Genomics of Muscle, Nerve and Brain Disorder

SplicePie: a novel analytical approach for the detection of alternative, non-sequential and recursive splicing

Molecular Technology and Informatics for Personalised Medicine and Healt

PROBING THE ARTICULAR CARTILAGE TRANSCRIPTOME FOR GENETIC OSTEOARTHRITIS SUSCEPTIBLITY

Optimising joint reconstruction management in arthritis and bone tumour patient

Probing the articular cartilage transcriptome for genetic osteoarthritis susceptiblity

Optimising joint reconstruction management in arthritis and bone tumour patient

miR-10b-5p is a novel Th17 regulator present in Th17 cells from Ankylosing Spondylitis

Objective: to determine the microRNA (miR) signature in ankylosing spondylitis (AS) Th17 cells.Methods: IL-17A-producing CD4+ T cells from AS patients and healthy controls were FACS-sorted for miR RNA sequencing and qPCR validation. miR-10b function was determined by miR mimic expression followed by cytokine measurement, transcriptome analysis, qPCR and luciferase assays. Results: AS Th17 cells exhibited a miR signature characterized by upregulation of miR-155-5p, miR- 210-3p and miR-10b. miR-10b has not been described previously in Th17 cells and was selected for further characterization. miR-10b is transiently induced in in-vitro differentiated Th17 cells. Transcriptome, qPCR and luciferase assays suggest that MAP3K7 is targeted by miR-10b. Both miR-10b over-expression and MAP3K7 silencing inhibited production of IL-17A by both total CD4 and differentiating Th17 cells. Conclusions: AS Th17 cells have a specific miR signature and upregulate miR-10b in vitro. Our data suggest that miR-10b is upregulated by pro-inflammatory cytokines and may act as a feedback loop to suppress IL-17A by targeting MAP3K7. miR-10b is a potential therapeutic candidate to suppress pathogenic Th17 cell function in AS patients.</p

Annotating Transcriptional Effects of Genetic Variants in Disease-Relevant Tissue: Transcriptome-Wide Allelic Imbalance in Osteoarthritic Cartilage

OBJECTIVE: Multiple single-nucleotide polymorphisms (SNPs) conferring susceptibility to osteoarthritis (OA) mark imbalanced expression of positional genes in articular cartilage, reflected by unequally expressed alleles among heterozygotes (allelic imbalance [AI]). We undertook this study to explore the articular cartilage transcriptome from OA patients for AI events to identify putative disease-driving genetic variation. METHODS: AI was assessed in 42 preserved and 5 lesioned OA cartilage samples (from the Research Arthritis and Articular Cartilage study) for which RNA sequencing data were available. The count fraction of the alternative alleles among the alternative and reference alleles together (phi) was determined for heterozygous individuals. A meta-analysis was performed to generate a meta-phi and P value for each SNP with a false discovery rate (FDR) correction for multiple comparisons. To further validate AI events, we explored them as a function of multiple additional OA features. RESULTS: We observed a total of 2,070 SNPs that consistently marked AI of 1,031 unique genes in articular cartilage. Of these genes, 49 were found to be significantly differentially expressed (fold change 2, FDR <0.05) between preserved and paired lesioned cartilage, and 18 had previously been reported to confer susceptibility to OA and/or related phenotypes. Moreover, we identified notable highly significant AI SNPs in the CRLF1, WWP2, and RPS3 genes that were related to multiple OA features. CONCLUSION: We present a framework and resulting data set for researchers in the OA research field to probe for disease-relevant genetic variation that affects gene expression in pivotal disease-affected tissue. This likely includes putative novel compelling OA risk genes such as CRLF1, WWP2, and RPS3