GEOapplication/xmlftp://ftp.ncbi.nlm.nih.gov/geo/series/GSE347nnn/GSE347079/primaryOK200TranscriptomicsMus musculus Non-coding RNA profiling by high throughput sequencingExpression profiling by high throughput sequencinghttps://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE347079GEOGSEfalseTGIRT-seq-based quantification of snoRNAs across 5 healthy mouse organsSmall nucleolar RNAs (snoRNAs) are structured non-coding RNAs that are frequently under-quantified by standard RNA-seq protocols, since their compact secondary structure impedes efficient reverse transcription. TGIRT-seq relies on a thermostable group II intron reverse transcriptase with high fidelity, processivity, and structure-tolerant activity, making it particularly well suited to accurately capture and quantify these RNA species. This dataset presents a TGIRT-seq atlas generated from ribodepleted total RNA of five healthy mouse organs (bone, colon, gonad, liver and lung), enabling accurate snoRNA quantification alongside mRNAs, lncRNAs and other structured non-coding RNAs (e.g. tRNAs), using a genome annotation supplemented with an updated murine snoRNA annotation and tRNA gene annotations from GtRNAdb.2026/09/13GSE347079GSM10045622GSM10045621GSM10045624GSM10045623GSM10045620GSM10045630GSM10045619GSM10045618GSM10045629GSM10045626GSM10045625GSM10045617GSM10045628GSM10045616GSM1004562737305347079Mus musculus