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RNA-sequencing reveals genome-wide long non-coding RNAs profiling associated with early development of diabetic nephropathy.

ABSTRACT: Diabetic nephropathy (DN) seriously threatens the lives of patients, and the mechanism of DN remains largely unknown because of the complex regulation between long non-coding RNA (lncRNA) and protein-coding genes. In early development of diabetic nephropathy (DN), pathogenesis remains largely unknown.We used RNA-sequencing to profile protein-coding and lncRNA gene transcriptome of mouse kidney proximal tubular cells during early stage of DN at various time points. Over 7000 protein-coding and lncRNA genes were differentially expressed, and most of them were time-specific. Nearly 40% of lncRNA genes overlapped with functional element signals using CHIP-Seq data from ENCODE database. Disease progression was characterized by lncRNA expression patterns, rather than protein-coding genes, indicating that the lncRNA genes are potential biomarkers for DN. For gene ontologies related to kidney, enrichment was observed in protein-coding genes co-expressed with neighboring lncRNA genes. Based on protein-coding and lncRNA gene profiles, clustering analysis reveals dynamic expression patterns for kidney, suggesting that they are highly correlated during disease progression. To evaluate translation of mouse model to human conditions, we experimentally validated orthologous genes in human cells in vitro diabetic model. In mouse model, most gene expression patterns were repeated in human cell lines.These results define dynamic transcriptome and novel functional roles for lncRNAs in diabetic kidney cells; these roles may result in lncRNA-based diagnosis and therapies for DN.

SUBMITTER: Tang W

PROVIDER: S-EPMC5739683 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature

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Project description:The intergenic space of plant genomes encodes many functionally important yet unexplored RNAs. The genomic loci encoding these RNAs are often considered "junk", DNA as they are frequently associated with repeat-rich regions of the genome. The latter makes the annotations of these loci and the assembly of the corresponding transcripts using short RNAseq reads particularly challenging. Here, using long-read Nanopore direct RNA sequencing, we aimed to identify these "junk" RNA molecules, including long non-coding RNAs (lncRNAs) and transposon-derived transcripts expressed during early stages (10 days post anthesis) of seed development of triticale (AABBRR, 2n = 6x = 42), an interspecific hybrid between wheat and rye. Altogether, we found 796 lncRNAs and 20 LTR retrotransposon-related transcripts (RTE-RNAs) expressed at this stage, with most of them being previously unannotated and located in the intergenic as well as intronic regions. Sequence analysis of the lncRNAs provide evidence for the frequent exonization of Class I (retrotransposons) and class II (DNA transposons) transposon sequences and suggest direct influence of "junk" DNA on the structure and origin of lncRNAs. We show that the expression patterns of lncRNAs and RTE-related transcripts have high stage specificity. In turn, almost half of the lncRNAs located in Genomes A and B have the highest expression levels at 10-30 days post anthesis in wheat. Detailed analysis of the protein-coding potential of the RTE-RNAs showed that 75% of them carry open reading frames (ORFs) for a diverse set of GAG proteins, the main component of virus-like particles of LTR retrotransposons. We further experimentally demonstrated that some RTE-RNAs originate from autonomous LTR retrotransposons with ongoing transposition activity during early stages of triticale seed development. Overall, our results provide a framework for further exploration of the newly discovered lncRNAs and RTE-RNAs in functional and genome-wide association studies in triticale and wheat. Our study also demonstrates that Nanopore direct RNA sequencing is an indispensable tool for the elucidation of lncRNA and retrotransposon transcripts.

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RNA-sequencing reveals genome-wide long non-coding RNAs profiling associated with early development of diabetic nephropathy.

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