Literature DB >> 23429212

Characterization of the rat developmental liver transcriptome.

Richard H Chapple1, Polyana C Tizioto, Kevin D Wells, Scott A Givan, JaeWoo Kim, Stephanie D McKay, Robert D Schnabel, Jeremy F Taylor.   

Abstract

Gene regulation and transcriptome studies have been enabled by the development of RNA-Seq applications for high-throughput sequencing platforms. Next generation sequencing is remarkably efficient and avoids many issues inherent in hybridization-based microarray methodologies including the exon-specific dependence of probe design. Biologically relevant transcripts including messenger and regulatory RNAs may now be quantified and annotated regardless of whether they have previously been observed. We used RNA-Seq to investigate global patterns of gene expression in early developing rat liver. Liver samples from timed-pregnant Lewis rats were collected at six fetal and neonatal stages [embryonic day (E)14, E16, E18, E20, postnatal day (P)1, P7], transcripts were sequenced using an Illumina HiSeq 2000, and data analysis was performed with the Tuxedo software suite. Genes and isoforms differing in abundance were queried for enrichment within functionally related gene groups using the Functional Annotation Tool of the DAVID Bioinformatics Database. While hematopoietic gene expression is initiated by E14, hepatocyte maturation is a gradual process involving clusters of genes responsible for response to nutrients and enzymes responsible for glycolysis and fatty acid catabolism. Following birth, a large cluster of differentially abundant genes was enriched for mitochondrial gene expression and cholesterol synthesis indicating that by 1 wk of age, the liver is engaged in lipid sensing and bile production. Clustering results for differentially abundant genes and isoforms were similar with the greatest difference for the E14/E16 comparison. Finally, a bioinformatic approach was used to annotate 1,307 novel liver transcripts assembled from sequences that aligned to intergenic regions of the rat genome.

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Mesh:

Year:  2013        PMID: 23429212      PMCID: PMC3633428          DOI: 10.1152/physiolgenomics.00128.2012

Source DB:  PubMed          Journal:  Physiol Genomics        ISSN: 1094-8341            Impact factor:   3.107


  18 in total

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