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Abstract Background MicroRNAs (miRNAs) are small, non-coding RNAs that regulate gene expression and play a critical role in development, homeostasis, and disease. Despite their demonstrated roles in age-associated pathologies, little is known about the role of miRNAs in human aging and longevity. Results We employed massively parallel sequencing technology to identify miRNAs expressed in B-cells from Ashkenazi Jewish centenarians, i.e., those living to a hundred and a human model of exceptional longevity, and younger controls without a family history of longevity. With data from 26.7 million reads comprising 9.4 × 108 bp from 3 centenarian and 3 control individuals, we discovered a total of 276 known miRNAs and 8 unknown miRNAs ranging several orders of magnitude in expression levels, a typical characteristics of saturated miRNA-sequencing. A total of 22 miRNAs were found to be significantly upregulated, with only 2 miRNAs downregulated, in centenarians as compared to controls. Gene Ontology analysis of the predicted and validated targets of the 24 differentially expressed miRNAs indicated enrichment of functional pathways involved in cell metabolism, cell cycle, cell signaling, and cell differentiation. A cross sectional expression analysis of the differentially expressed miRNAs in B-cells from Ashkenazi Jewish individuals between the 50th and 100th years of age indicated that expression levels of miR-363* declined significantly with age. Centenarians, however, maintained the youthful expression level. This result suggests that miR-363* may be a candidate longevity-associated miRNA. Conclusion Our comprehensive miRNA data provide a resource for further studies to identify genetic pathways associated with aging and longevity in humans.

Abstract Background Systematic, high-throughput studies of mouse phenotypes have been hampered by the inability to analyze individual animal data from a multitude of sources in an integrated manner. Studies generally make comparisons at the level of genotype or treatment thereby excluding associations that may be subtle or involve compound phenotypes. Additionally, the lack of integrated, standardized ontologies and methodologies for data exchange has inhibited scientific collaboration and discovery. Results Here we introduce a Mouse Phenotype Analysis System (MPHASYS), a platform for integrating data generated by studies of mouse models of human biology and disease such as aging and cancer. This computational platform is designed to provide a standardized methodology for working with animal data; a framework for data entry, analysis and sharing; and ontologies and methodologies for ensuring accurate data capture. We describe the tools that currently comprise MPHASYS, primarily ones related to mouse pathology, and outline its use in a study of individual animal-specific patterns of multiple pathology in mice harboring a specific germline mutation in the DNA repair and transcription-specific gene Xpd. Conclusion MPHASYS is a system for analyzing multiple data types from individual animals. It provides a framework for developing data analysis applications, and tools for collecting and distributing high-quality data. The software is platform independent and freely available under an open-source license 1.