Loss of β-cell identity and diabetic phenotype in mice caused by disruption of CNOT3-dependent mRNA deadenylation

Pancreatic β-cells are responsible for production and secretion of insulin in response to increasing blood glucose levels. Defects in β-cell function lead to hyperglycemia and diabetes mellitus. Here, we show that CNOT3, a CCR4–NOT deadenylase complex subunit, is dysregulated in islets in diabetic db/db mice, and that it is essential for murine β cell maturation and identity. Mice with β cell-specific Cnot3 deletion (Cnot3βKO) exhibit impaired glucose tolerance, decreased β cell mass, and they gradually develop diabetes. Cnot3βKO islets display decreased expression of key regulators of β cell maturation and function. Moreover, they show an increase of progenitor cell markers, β cell-disallowed genes, and genes relevant to altered β cell function. Cnot3βKO islets exhibit altered deadenylation and increased mRNA stability, partly accounting for the increased expression of those genes. Together, these data reveal that CNOT3-mediated mRNA deadenylation and decay constitute previously unsuspected post-transcriptional mechanisms essential for β cell identity.


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Policy information about availability of data All manuscripts must include a data availability statement. This statement should provide the following information, where applicable: -Accession codes, unique identifiers, or web links for publicly available datasets -A list of figures that have associated raw data -A description of any restrictions on data availability Tadashi Yamamoto Jul 7, 2020 doesn't apply RNA sequencing data analysis: Paired-end RNA-seq data were mapped to the Mus musculus reference strain mm10 UCSC using Strand NGS, next generation sequencing analysis software. Counts for each sample were imported into the RStudio (v.1.1.453). Genes without an expression level of at least one read per million mapped reads in at least three samples were removed before differential gene expression testing between control, and Cnot3"KO islet RNA replicates, using the edgeR function in the Bioconductor package edgeR. GO analysis using DAVID annotation tool (https://david.ncifcrf.gov/). Softwares for statistical analysis: GraphPad Prism (GraphPad Software v.8.0), and GSEA (v.4.0.1) developed by Broad Institute (http://software.broadinstitute.org/gsea/index.jsp). Softwares for images analysis and processing: Fiji (www.fiji.sc) and Imaris (v.2.9) softwares, respectively.

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All studies must disclose on these points even when the disclosure is negative. We used at least 3 biological replicates for each experiment. Only bulk poly (A) tail experiment was done once on RNA extracted from WT and KO islets each pooled from 4 mice per group. We didn't repeat the experiment as the results were consistent with previous reports and each sample was pooled from 4 biological replicates.
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