Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Deciphering the Developmental Dynamics of the Mouse Liver Transcriptome

ABSTRACT: This study uses Whole Transcriptome Shotgun Sequencing (RNA-Seq) data to interrogate the developmental dynamics of the C57BL/6 mouse liver transcriptome. We analyze gene expression patterns in the developing mouse liver over 12 distinct time points from late embryonic stage (2 days before birth) to maturity (60 days after birth). Biological functions deemed significant at different developmental stages are identified and their leverage is mapped over time. Upstream regulators modulating these gene expression patterns are determined and their regulatory networks are described along with putative transcriptional modules associated with gene regulation. Several genes that were alternatively spliced over time were identified. Previously uncharacterized isoforms were found for several genes. We analyze gene expression patterns in the developing mouse liver over 12 distinct time points from late embryonic stage (2 days before birth) to maturity (60 days after birth). Three replicates per time point.

ORGANISM(S): Mus musculus

SUBMITTER: Curtis Klaassen

PROVIDER: E-GEOD-58827 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Ontogeny of hepatic energy metabolism genes in mice as revealed by RNA-sequencing.

Renaud Helen J HJ Cui Yue Julia YJ Lu Hong H Zhong Xiao-bo XB Klaassen Curtis D CD

PloS one 20140807 8

The liver plays a central role in metabolic homeostasis by coordinating synthesis, storage, breakdown, and redistribution of nutrients. Hepatic energy metabolism is dynamically regulated throughout different life stages due to different demands for energy during growth and development. However, changes in gene expression patterns throughout ontogeny for factors important in hepatic energy metabolism are not well understood. We performed detailed transcript analysis of energy metabolism genes dur ...[more]

PMID: 25102070

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Project description:Over the past decade, genome-wide assays have underscored the broad sweep of circadian gene expression. A substantial fraction of the transcriptome undergoes oscillations in many organisms and tissues, which governs the many biochemical, physiological and behavioral functions under circadian control. Based predominantly on the transcription feedback loops important for core circadian timekeeping, it is commonly assumed that this widespread mRNA cycling reflects circadian transcriptional cycling. To address this issue, we directly measured dynamic changes in mouse liver transcription using Nascent-Seq. Many genes are rhythmically transcribed over the 24h day, which include precursors of several non-coding RNAs as well as the expected set of core clock genes. Surprisingly however, nascent RNA rhythms overlap poorly with mRNA abundance rhythms assayed by RNA-seq. This is because most mouse liver genes with rhythmic mRNA expression manifest poor transcriptional rhythms, indicating a prominent role of post-transcriptional regulation in setting mRNA cycling amplitude. To gain further insight into circadian transcriptional regulation, we also characterized the rhythmic transcription of liver genes targeted by the transcription factors CLOCK and BMAL1; they directly target other core clock genes and sit at the top of the molecular circadian clock hierarchy in mammals. CLK:BMAL1 rhythmically bind at the same discrete phase of the circadian cycle to all target genes, which not surprisingly have a much higher percentage of rhythmic transcription than the genome as a whole. However, there is a surprisingly heterogeneous set of cycling transcription phases of direct target genes, which even include core clock genes. This indicates a disconnect between rhythmic DNA binding and the peak of transcription, which is likely due to other transcription factors that collaborate with CLK:BMAL1. In summary, the application of Nascent-Seq to a mammalian tissue provides surprising insights into the rhythmic control of gene expression and should have broad applications beyond the analysis of circadian rhythms. Mouse liver nascent RNA profile over 6 time points of the 24h light:dark cycle, in duplicate, sequenced using Ilumina GAII (Nascent-Seq); Mouse liver mRNA profile over 6 time points of the 24h light:dark cycle, in duplicate, sequenced using Ilumina HiSeq2000 (RNA-Seq); CLK and BMAL1 DNA binding profile in the mouse liver at ZT8, sequenced along an Input sample using GAII (ChIP-Seq); Mouse liver strand-specific nascent RNA profile over 6 time points of the 24h light:dark cycle, in duplicate, sequenced using Ilumina HiSeq2000 (Strand-specific Nascent-Seq); Supplementary file RNASeq_Mouse_Liver_NormalizedGeneSignal.txt represents mRNA abundance (reads per base pair) for each sample.

Dataset Information

Deciphering the Developmental Dynamics of the Mouse Liver Transcriptome

Publications

Ontogeny of hepatic energy metabolism genes in mice as revealed by RNA-sequencing.

Similar Datasets

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