Transcriptome dynamics

David A. Carter, Steven L. Coon, Yoav Gothilf, Charles K. Hwang, Leming Shi, P. Michael Iuvone, Stephen Hartley, James C. Mullikin, Peter Munson, Cong Fu, Samuel J. Clokie, David C. Klein

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

For almost 30 years, we have known that dynamic changes in the expression of individual gene transcripts are involved in adaptive neuroendocrine responses. Now, our detailed knowledge of mammalian genomes has been applied experimentally using new RNA technologies to show that physiological changes in gene expression are, in fact, manifold, demanding a more global consideration of ‘transcriptome dynamics.' This term is appropriate because our studies have shown that a major proportion of cellular transcripts (multiple thousands of genes) are dynamically regulated as part of daily changes in the functional activity of a neuroendocrine gland, the pineal. The regulated pool of transcripts includes both protein-coding and non-coding RNAs. To begin to understand transcriptome dynamics in the context of neuroendocrine system physiology, we first need to know the genomic-level mechanisms that coordinate these changes, and secondly, the functional relationships between individual genes and groups of genes. We have obtained insights into pineal gland transcriptome dynamics by combining multiple approaches: in vivo and in vitro experimental paradigms, bioinformatics and also comparative analysis of transcriptomes across different species including rodents (rat and mouse), birds (chicken), and fish (zebrafish). In these non-mammalian species, an endogenous clock controls rhythmic expression, whereas in the rat we have identified a dominant norepinephrine-cAMP pathway that drives rhythmic pineal gene expression. Analysis of individual gene dynamics in the rat has revealed diverse gene-specific temporal expression patterns that highlight gene-specific components of the dynamic, tailored to discrete functional actions. Our focused analysis of specific genes has begun to characterize these subcomponents of the overall transcriptome dynamic with subgroups of genes being organized into restricted regulatory hierarchies. Future analysis of transcriptome data sets will involve the development of new bioinformatic approaches coupled with more sophisticated gene targeting. Addressing fundamental knowledge gaps in this research area will provide us with a deeper understanding of neuroendocrine control mechanisms that will be more apposite for advancing health and wellbeing.

Original languageEnglish
Title of host publicationMolecular Neuroendocrinology
Subtitle of host publicationFrom Genome to Physiology
Publisherwiley
Pages57-74
Number of pages18
ISBN (Electronic)9781118760369
ISBN (Print)9781118760376
DOIs
StatePublished - 1 Jan 2016

Keywords

  • Circadian
  • LncRNA
  • Microarray
  • Pineal
  • Pituitary
  • RNA-Seq
  • Transcriptome
  • mRNA
  • miRNA

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