Project description:We present a survey of longevity effects for compounds suggested by a previously published computational prediction set using the comprehensive, multi-species approach utilized by the Caenorhabditis Intervention Testing Program (CITP). The compound all-trans retinoic acid extended lifespan in the nematode Caenorhabditis elegans. Given the dependency of lifespan extension under atRA treatment, we used RNA-seq to assess transcriptional changes under atRA treatment in wildtype N2 animals. In order to further dissect transcriptional response in detail, we repeated our transcriptional analysis in hsf-1(sy441) and aak-2(ok524) mutants.
2024-10-22 | GSE272535 | GEO
Project description:Wormwood transcriptome testing program
Project description:Sulforaphane (SFN), an organosulfur isothiocyanate derived from cruciferous vegetables, has been shown to inhibit inflammation, oxidative stress, and cancer cell growth; it has also been shown to increase the lifespan of the C. elegans nematode strain N2. Here, we tested the lifespan effects of SFN following the standard experimental procedures of the Caenorhabditis Intervention Testing Program (CITP). The CITP, a multi-institute research consortium, aims to identify chemical interventions that can robustly and reproducibly promote health and lifespan. To investigate the functional targets of SFN, we employed bulk RNA-Seq at a variety of ages to create a “transcriptional aging clock” using control individuals and then tested how global patterns of gene expression are altered under SFN treatment. Multi-dimensional scaling analysis of the transcriptome revealed transcriptional age under SFN treatment was similar to control individuals approximately four days younger, representing a nearly 20% shift relative to overall lifespan. These results support the idea that robust longevity-extending interventions can act via global effects across the organism, as revealed at a functional level via changes in gene expression.
Project description:Cancer cell lines can provide robust and facile biological models for the generation and testing of hypothesis in the early stages of drug development and caner biology. Although clinical trials remain the ultimate scientific testing ground for anticancer therapies, the use of appropriate model systems to explore the molecular basis of drug activity and to identify predictive biomarkers during their development can have a profound effect on the design, cost and ultimate success of new cancer drug development. In order to capture the high degree of genomic diversity in cancer and to identify rare molecular subtypes, we have assembled a collection of >1000 cancer cell lines. These lines have been characterised using whole exome sequencing, genome wide analysis of copy number, mRNA gene expression profiling and DNA methylation analysis (http://cancer.sanger.ac.uk/cell_lines). To further characterise this panel of cell lines we have now compiled data for RNA sequencing. The current study represent data for ~450 of the cell lines in the panel, data for the remaining lines can be accessed via the CGHUB data browser hosted at UCSC. <br>This ArrayExpress record contains only meta-data. Raw data files have been archived at the European Genome-Phenome Archive (EGA, www.ebi.ac.uk/ega) by the consortium, with restricted access to protect sample donors' identity. The relevant accessions of the EGA data set is EGAD00001001357 under EGA study accession EGAS00001000828.