Pluto Bioinformatics

GSE153222: Temporal Transcriptomic Landscape of Interorgan Crosstalk between Islets and Liver in High-fat Diet Model

Bulk RNA sequencing

Purpose: Hyperinsulinemia and insulin resistance are co-existing characteristics of type 2 diabetes, whereas the forerunner initiating the deleterious cycle remains elusive. The temporal transcriptomic landscape of islets (responsible for hyperinsulinemia) and liver (involved in insulin resistance) could provide new insights.; Methods: C57BL/6N mice were fed a 60% high-fat diet (HFD) or control diet (CD) for 24 weeks. RNA-sequencing of islet and liver samples were respectively performed in quadruplicates at six consecutive time points of diet treatments (week 4, 8, 12, 16, 20 and 24), using BGISEQ-500 sequencing platform by the Beijing Genomics Institute (Shenzhen, China).The sequencing raw reads were filtered for low-quality, adaptor-polluted, high content of unknown base reads by SOAPnuke (v1.5.2). We used Trinity (v2.0.6) to perform de novo assembly, and Tgicl (v2.0.6) on cluster transcripts to remove redundancy and get unigenes. The high-quality clean reads were then mapped to the mouse reference genome (GRCm38) via HISAT2 (v2.0.4) and full-length transcriptome database via Bowtie2 (v2.2.5). The gene expression levels were then quantified by RSEM (v1.1.12) and were normalized by the method of fragments per kilobase of exon model per million reads mapped (FPKM). To interpret the functional significance of differentially expressed genes (DEGs), pathway analyses was conducted to determine enriched canonical pathways.; Results: Combined analyses of all 96 samples yielded the identification of 21990 annotated genes. Differentially expressed genes (DEGs) between the two groups (HFD vs. CD) at each time point were identified using the criteria of fold change 2 and adjusted P-value 0.05. In total, 3844 DEGs were found in islets, of which 33 were shared among all six time points. With regard to liver, 4101 DEGs were discovered throughout 24 weeks of feeding, of which 39 were overlapped. Our islet and liver RNA-sequencing datasets outlined the impact of HFD on dynamics of molecular network at different stages. Correlation analyses of islet and liver modules with metabolic phenotypes illustrated that these two tissues jointly program -cell adaption to irreversible impairment. Top scored networks combining islet and liver transcriptomes showed potential interactions of genes implicated in cell cycle during week 4, organismal development around week 12, and immune cell trafficking at week 24.; Conclusions: Our data provide a comprehensive landscape of crosstalk between islets and liver in diet-induced diabetes, linking to the development of islet dysfunction and insulin resistance. SOURCE: Rui Gao ( - Churchill Hospital

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