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Genome Research Papers Focus on Gene Functions, Aging Transcriptomic, Diabetes Models

Investigators from Canada and Oman track down post-zygotic mutations that might contribute to the development of type 1 diabetes or related conditions in a mouse model of disease. Reasoning that autoreactive CD4+ and CD8+ T cells in non-obese diabetic mice can lash out at pancreatic beta cells in a manner similar to that observed in T1D, the team did comparative genomic hybridization on CD4+ T cells from more than two dozen of these non-obese diabetic mice, validating potential copy number mosaic events with multiplex ligation-dependent probe amplification. Results from these and other experiments point to the presence of "lymphocyte-exclusive mosaic somatic copy number aberrations with highly non-random, independent involvement of the same gene(s) across different mice, some with an autoimmunity association," the authors report, adding that future studies of human T cells "will enable the further delineation of driver genes to target for functional studies."

A team from the California biotech company Calico Life Sciences shares findings from a single-cell RNA sequencing study of mammalian aging in a mouse model. Using scRNA-seq data for more than 50,000 individual cells obtained from three aged mice that were nearly two years old and four youthful mice closer to seven months old, the researchers looked for age-related features within and across three tissue types: kidney, lung, and spleen. In particular, the authors note that "changes in protein localization gene sets and increased inflammatory gene expression occur across cell identities, whereas other changes are more specific to individual cell identities."

Researchers in Switzerland and the US outline an analytical toolkit dubbed GeneBridge. The method brings together two previous computational strategies to impute gene functions, connected modules, and corresponding biological process, the team explains, the "Gene Module Association Determination," or G-MAD method, and a "Module-Module Association Determination," or M-MAD. When the authors used GeneBridge to assess available gene expression data for more than 300,000 human, mouse, rat, fly, worm, or yeast samples, for example, they predicted new functions or tissue-specific activity for known genes, along with previously unappreciated module members. "The GeneBridge tools, together with the expression compendia, are available as an open resource," they write, "which will facilitate the identification of connections linking genes, modules, phenotypes, and diseases."