Comprehensive transcriptional landscape of aging mouse liver

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Abstract

Background: Mammalian aging is a highly complex process, a full mechanistic understanding of which is still lacking. One way to help understand the molecular changes underlying aging is through a comprehensive analysis of the transcriptome, the primary determinant of age-related phenotypic diversity. Previous studies have relied on microarray analysis to examine gene expression profiles in different tissues of aging organisms. However, studies have shown microarray-based transcriptional profiling is less accurate and not fully capable of capturing certain intricacies of the global transcriptome. Methods: Here, using directional whole transcriptome RNA-sequencing of aged mouse liver we have identified a comprehensive high-resolution profile of differentially expressed liver transcripts comprised of canonical protein-coding transcripts, transcript isoforms, and non-coding RNA transcripts, including pseudogenes, long non-coding RNAs and small RNA species. Results: Results show extensive age-related changes in every component of the mouse liver transcriptome and a pronounced increase in inter-individual variation. Functional annotation of the protein-coding mRNAs and isoforms indicated broad alterations in immune response, cell activation, metabolic processes, and RNA modification. Interestingly, multiple lncRNAs (Meg3, Rian, Mirg) from the Dlk-Dio3 microRNA locus were found up-regulated in aging liver, classifying this locus as a putative regulatory hotspot locus in aging liver. Moreover, integration of the altered non-coding RNAs and protein-coding transcripts into interaction networks of age-related change revealed inflammation, cellular proliferation, and metabolism as the dominant aging phenotypes in mouse liver. Conclusions: Our analyses provide the first comprehensive dissection of the transcriptional landscape in aging mouse liver.

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White, R. R., Milholland, B., MacRae, S. L., Lin, M., Zheng, D., & Vijg, J. (2015). Comprehensive transcriptional landscape of aging mouse liver. BMC Genomics, 16(1). https://doi.org/10.1186/s12864-015-2061-8

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