{"database":"biostudies-arrayexpress","file_versions":[],"scores":null,"additional":{"submitter":[null],"organism":["Mus musculus"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/E-MTAB-13879"],"description":["To identify candidate predictive markers of obesity susceptibility, our study used two mouse models: one of them consists in Balb/c adult male mice whose susceptibility to obesity was programmed through maternal nutritional stresses. Transcriptomic analysis was performed on White adipose tissues sample from 14 mice."],"repository":["biostudies-arrayexpress"],"sample_protocol":["Sample Collection - Mice were euthanized by cervical dislocation under isoflurane anesthesia. Perigonadal WAT was collected prior to immediate freezing in liquid nitrogen and stored at −80 ◦C until analyses.","Sequencing - The libraries were sequenced using the Nextseq 500 (ILLUMINA®) to obtain 2 * 40 million 75-base pair fragments per sample.","Nucleic Acid Extraction - Total RNA was prepared using the RNeasy minikit (Qiagen)","Library Construction - Prepared RNAs sample were sent to the sequencing facility (IGENSEQ) at the ICM Institute (Paris, France), and their quality and concentration were checked using bioanalyzer. Libraries were prepared using the \\\\\"TruSeq Stranded mRNA\\\\\" kit (ILLUMINA®), allowing the construction of a library of polyadenylated RNAs (mRNA and polyadenylated non-coding RNAs such as lncRNA) from total RNAs. The libraries were prepared following the manufacturer's recommendations."],"figure_sub":["MINSEQE Score","Assays and Data","Processed Data","organisation","MAGE-TAB Files"],"data_protocol":["Data Transformation - For mouse RNA-Seq data, the standard edgeR (v3.40.2) [31] procedure was applied to clean and transform the data. Genes with a cpm transformed counts mean below 10 were first rejected from analysis as low expressed. Before differential analysis a TMM (trimmed mean of M values) normalisation procedure was applied on filtered raw counts to compensate technical bias at the samples level. EdgeR quasi-likelihood F-test was then used to select significant genes with a Benjamini-Hochberg adjusted p-values below a 0.05 threshold. Further analysis were applied on log(cpm) transformed and thus linearised counts data."],"omics_type":["Metabolomics","Unknown","Transcriptomics","Genomics","Proteomics"],"instrument_platform":["NextSeq 500"],"study_type":["RNA-seq of coding RNA"],"species":["Mus musculus"],"pubmed_title":["Identification of a specific set of genes predicting obesity before phenotype appearance"],"additional_accession":["ERP158358"],"pubmed_authors":["Céline Jousse, Laurent Parry, Gwendal Cueff, Marion Brandolini-Bunlon, Jérémy Tournayre, Alain Bruhat, Anne-Catherine Maurin, Cyrielle Vituret, Julien Averous, Yuki Muranishi, and Pierre Fafournoux","Gwendal Cueff","Céline Jousse"]},"is_claimable":false,"name":"RNAseq of WAT from male offspring born to mothers subjected to various nutritional stress during gestation and/or lactation","description":"To identify candidate predictive markers of obesity susceptibility, our study used two mouse models: one of them consists in Balb/c adult male mice whose susceptibility to obesity was programmed through maternal nutritional stresses. Transcriptomic analysis was performed on White adipose tissues sample from 14 mice.","dates":{"release":"2025-04-15T00:00:00Z","modification":"2026-06-03T17:45:42.039Z","creation":"2024-03-05T21:22:52.723Z"},"accession":"E-MTAB-13879","cross_references":{"ENA":["ERP158358"],"EFO":["EFO_0002944","EFO_0004170","EFO_0005518","EFO_0003816","EFO_0003738","EFO_0004184"]}}