摘要：For systematic identification of transcription signatures of human cell aging, we carried out Weighted Gene Co-expression Network Analysis (WGCNA) with the RNA-sequencing data generated with young to old human dermal fibroblasts. By relating the modules to the donor's traits, we uncovered the natural aging- and premature aging disease-associated modules. The STRING functional association networks built with the core module memberships provided a systematic overview of genome-wide transcriptional changes upon aging. We validated the selected candidates via quantitative reverse transcription PCR (RT-qPCR) assay with young and aged human fibroblasts, and uncovered several genes involved in ECM, cell, and nuclear mechanics as a potential aging biomarker. Collectively, our study not only provides a snapshot of functional changes during human fibroblast aging but also presents potential aging markers that are relevant to cell mechanics.
其他摘要：Abstract For systematic identification of transcription signatures of human cell aging, we carried out Weighted Gene Co-expression Network Analysis (WGCNA) with the RNA-sequencing data generated with young to old human dermal fibroblasts. By relating the modules to the donor's traits, we uncovered the natural aging- and premature aging disease-associated modules. The STRING functional association networks built with the core module memberships provided a systematic overview of genome-wide transcriptional changes upon aging. We validated the selected candidates via quantitative reverse transcription PCR (RT-qPCR) assay with young and aged human fibroblasts, and uncovered several genes involved in ECM, cell, and nuclear mechanics as a potential aging biomarker. Collectively, our study not only provides a snapshot of functional changes during human fibroblast aging but also presents potential aging markers that are relevant to cell mechanics.
