24 research outputs found

    Differences in 5'untranslated regions highlight the importance of translational regulation of dosage sensitive genes

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    Background: Untranslated regions (UTRs) are important mediators of post-transcriptional regulation. The length of UTRs and the composition of regulatory elements within them are known to vary substantially across genes, but little is known about the reasons for this variation in humans. Here, we set out to determine whether this variation, specifically in 5’UTRs, correlates with gene dosage sensitivity. Results: We investigate 5’UTR length, the number of alternative transcription start sites, the potential for alternative splicing, the number and type of upstream open reading frames (uORFs) and the propensity of 5’UTRs to form secondary structures. We explore how these elements vary by gene tolerance to loss-of-function (LoF; using the LOEUF metric), and in genes where changes in dosage are known to cause disease. We show that LOEUF correlates with 5’UTR length and complexity. Genes that are most intolerant to LoF have longer 5’UTRs, greater TSS diversity, and more upstream regulatory elements than their LoF tolerant counterparts. We show that these differences are evident in disease gene-sets, but not in recessive developmental disorder genes where LoF of a single allele is tolerated. Conclusions: Our results confirm the importance of post-transcriptional regulation through 5'UTRs in tight regulation of mRNA and protein levels, particularly for genes where changes in dosage are deleterious and lead to disease. Finally, to support gene-based investigation we release a web-based browser tool, VuTR, that supports exploration of the composition of individual 5'UTRs and the impact of genetic variation within them

    Whole-Genome Sequencing of Finnish Type 1 Diabetic Siblings Discordant for Kidney Disease Reveals DNA Variants associated with Diabetic Nephropathy

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    Background Several genetic susceptibility loci associated with diabetic nephropathy have been documented, but no causative variants implying novel pathogenetic mechanisms have been elucidated. Methods We carried out whole-genome sequencing of a discovery cohort of Finnish siblings with type 1 diabetes who were discordant for the presence (case) or absence (control) of diabetic nephropathy. Controls had diabetes without complications for 15-37 years. We analyzed and annotated variants at genome, gene, and single-nucleotide variant levels. We then replicated the associated variants, genes, and regions in a replication cohort from the Finnish Diabetic Nephropathy study that included 3531 unrelated Finns with type 1 diabetes. Results We observed protein-altering variants and an enrichment of variants in regions associated with the presence or absence of diabetic nephropathy. The replication cohort confirmed variants in both regulatory and protein-coding regions. We also observed that diabetic nephropathy-associated variants, when clustered at the gene level, are enriched in a core protein-interaction network representing proteins essential for podocyte function. These genes include protein kinases (protein kinase C isoforms epsilon and iota and protein tyrosine kinase 2. Conclusions Our comprehensive analysis of a diabetic nephropathy cohort of siblings with type 1 diabetes who were discordant for kidney disease points to variants and genes that are potentially causative or protective for diabetic nephropathy. This includes variants in two isoforms of the protein kinase C family not previously linked to diabetic nephropathy, adding support to previous hypotheses that the protein kinase C family members play a role in diabetic nephropathy and might be attractive therapeutic targets.Peer reviewe

    Translational control of cardiac fibrosis

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    Background Fibrosis is a common pathology in many cardiac disorders and is driven by the activation of resident fibroblasts. The global post-transcriptional mechanisms underlying fibroblast-to-myofibroblast conversion in the heart have not been explored. Methods Genome-wide changes of RNA transcription and translation during human cardiac fibroblast activation were monitored with RNA sequencing and ribosome profiling. We then used miRNA-and RNA-binding protein-based analyses to identify translational regulators of fibrogenic genes. To reveal post-transcriptional mechanisms in the human fibrotic heart, we then integrated our findings with cardiac ribosome occupancy levels of 30 dilated cardiomyopathy patients. Results We generated nucleotide-resolution translatome data during the TGFβ1-driven cellular transition of human cardiac fibroblasts to myofibroblasts. This identified dynamic changes of RNA transcription and translation at several time points during the fibrotic response, revealing transient and early-responder genes. Remarkably, about one-third of all changes in gene expression in activated fibroblasts are subject to translational regulation and dynamic variation in ribosome occupancy affects protein abundance independent of RNA levels. Targets of RNA-binding proteins were strongly enriched in post-transcriptionally regulated genes, suggesting genes such as MBNL2 can act as translational activators or repressors. Ribosome occupancy in the hearts of patients with dilated cardiomyopathy suggested an extensive post-transcriptional regulatory network underlying cardiac fibrosis. Key network hubs include RNA-binding proteins such as PUM2 and QKI that work in concert to regulate the translation of target transcripts in human diseased hearts. Conclusions We reveal widespread translational effects of TGFβ1 and define novel post-transcriptional events that control the fibroblast-to-myofibroblast transition. Regulatory networks that affect ribosome occupancy in fibroblasts are paralleled in human heart disease. Our findings show the central importance of translational control in fibrosis and highlight novel pathogenic mechanisms in heart failure

    MAPPING THE TRANSLATIONAL LANDSCAPE IN HUMAN CARDIAC FIBROSIS AND BEYOND

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    Ph.DDOCTOR OF PHILOSOPHY (DUKE

    Discovering microproteins: making the most of ribosome profiling data

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    10.1080/15476286.2023.2279845RNA Biology201943-95
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