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Linking promoters to functional transcripts in small samples with nanoCAGE and CAGEscan.

ABSTRACT: Large-scale sequencing projects have revealed an unexpected complexity in the origins, structures and functions of mammalian transcripts. Many loci are known to produce overlapping coding and noncoding RNAs with capped 5' ends that vary in size. Methods to identify the 5' ends of transcripts will facilitate the discovery of new promoters and 5' ends derived from secondary capping events. Such methods often require high input amounts of RNA not obtainable from highly refined samples such as tissue microdissections and subcellular fractions. Therefore, we developed nano-cap analysis of gene expression (nanoCAGE), a method that captures the 5' ends of transcripts from as little as 10 ng of total RNA, and CAGEscan, a mate-pair adaptation of nanoCAGE that captures the transcript 5' ends linked to a downstream region. Both of these methods allow further annotation-agnostic studies of the complex human transcriptome.

SUBMITTER: Plessy C

PROVIDER: S-EPMC2906222 | biostudies-literature | 2010 Jul

REPOSITORIES: biostudies-literature

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Linking promoters to functional transcripts in small samples with nanoCAGE and CAGEscan.

Plessy Charles C Bertin Nicolas N Takahashi Hazuki H Simone Roberto R Salimullah Md M Lassmann Timo T Vitezic Morana M Severin Jessica J Olivarius Signe S Lazarevic Dejan D Hornig Nadine N Orlando Valerio V Bell Ian I Gao Hui H Dumais Jacqueline J Kapranov Philipp P Wang Huaien H Davis Carrie A CA Gingeras Thomas R TR Kawai Jun J Daub Carsten O CO Hayashizaki Yoshihide Y Gustincich Stefano S Carninci Piero P

Nature methods 20100613 7

Large-scale sequencing projects have revealed an unexpected complexity in the origins, structures and functions of mammalian transcripts. Many loci are known to produce overlapping coding and noncoding RNAs with capped 5' ends that vary in size. Methods to identify the 5' ends of transcripts will facilitate the discovery of new promoters and 5' ends derived from secondary capping events. Such methods often require high input amounts of RNA not obtainable from highly refined samples such as tissu ...[more]

PMID: 20543846

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Project description:Given the central metabolic role of the liver, hepatic metabolites and transcripts reflect the organismal physiological state. Biochemical-clinical plasma biomarkers, hepatic metabolites, transcripts, and single nucleotide polymorphism (SNP) genotypes of some 300 pigs were integrated by weighted correlation networks and genome-wide association analyses. Network-based approaches of transcriptomic and metabolomics data revealed linked of transcripts and metabolites of the pentose phosphate pathway (PPP). This finding was evidenced by using a NADP/NADPH assay and HDAC4 and G6PD transcript quantification with the latter coding for first limiting enzyme of this pathway and by RNAi knockdown experiments of HDAC4. Other transcripts including ARG2 and SLC22A7 showed link to amino acids and biomarkers. The amino acid metabolites were linked with transcripts of immune or acute phase response signaling, whereas the carbohydrate metabolites were highly enrich in cholesterol biosynthesis transcripts. Genome-wide association analyses revealed 180 metabolic quantitative trait loci (mQTL) (p < 10-4). Trans-4-hydroxy-L-proline (p = 6 × 10-9), being strongly correlated with plasma creatinine (CREA), showed strongest association with SNPs on chromosome 6 that had pleiotropic effects on PRODH2 expression as revealed by multivariate analysis. Consideration of shared marker association with biomarkers, metabolites, and transcripts revealed 144 SNPs associated with 44 metabolites and 69 transcripts that are correlated with each other, representing 176 mQTL and expression quantitative trait loci (eQTL). This is the first work to report genetic variants associated with liver metabolite and transcript levels as well as blood biochemical-clinical parameters in a healthy porcine model. The identified associations provide links between variation at the genome, transcriptome, and metabolome level molecules with clinically relevant phenotypes. This approach has the potential to detect novel biomarkers displaying individual variation and promoting predictive biology in medicine and animal breeding.

Dataset Information

Linking promoters to functional transcripts in small samples with nanoCAGE and CAGEscan.

Publications

Linking promoters to functional transcripts in small samples with nanoCAGE and CAGEscan.

Similar Datasets

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