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      The Prolactin Gene: A Paradigm of Tissue-Specific Gene Regulation with Complex Temporal Transcription Dynamics

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          Abstract

          Transcription of numerous mammalian genes is highly pulsatile, with bursts of expression occurring with variable duration and frequency. The presence of this stochastic or ‘noisy’ expression pattern has been relatively unexplored in tissue systems. The prolactin gene provides a model of tissue-specific gene regulation resulting in pulsatile transcription dynamics in both cell lines and endocrine tissues. In most cell culture models, prolactin transcription appears to be highly variable between cells, with differences in transcription pulse duration and frequency. This apparently stochastic transcription is constrained by a transcriptional refractory period, which may be related to cycles of chromatin remodelling. We propose that prolactin transcription dynamics result from the summation of oscillatory cellular inputs and by regulation through chromatin remodelling cycles. Observations of transcription dynamics in cells within pituitary tissue show reduced transcriptional heterogeneity and can be grouped into a small number of distinct patterns. Thus, it appears that the tissue environment is able to reduce transcriptional noise to enable coordinated tissue responses to environmental change. We review the current knowledge on the complex tissue-specific regulation of the prolactin gene in pituitary and extra-pituitary sites, highlighting differences between humans and rodent experimental animal models. Within this context, we describe the transcription dynamics of prolactin gene expression and how this may relate to specific processes occurring within the cell.

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          Most cited references115

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          Nature, nurture, or chance: stochastic gene expression and its consequences.

          Gene expression is a fundamentally stochastic process, with randomness in transcription and translation leading to cell-to-cell variations in mRNA and protein levels. This variation appears in organisms ranging from microbes to metazoans, and its characteristics depend both on the biophysical parameters governing gene expression and on gene network structure. Stochastic gene expression has important consequences for cellular function, being beneficial in some contexts and harmful in others. These situations include the stress response, metabolism, development, the cell cycle, circadian rhythms, and aging.
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            Genome-wide mapping of HATs and HDACs reveals distinct functions in active and inactive genes.

            Histone acetyltransferases (HATs) and deacetylases (HDACs) function antagonistically to control histone acetylation. As acetylation is a histone mark for active transcription, HATs have been associated with active and HDACs with inactive genes. We describe here genome-wide mapping of HATs and HDACs binding on chromatin and find that both are found at active genes with acetylated histones. Our data provide evidence that HATs and HDACs are both targeted to transcribed regions of active genes by phosphorylated RNA Pol II. Furthermore, the majority of HDACs in the human genome function to reset chromatin by removing acetylation at active genes. Inactive genes that are primed by MLL-mediated histone H3K4 methylation are subject to a dynamic cycle of acetylation and deacetylation by transient HAT/HDAC binding, preventing Pol II from binding to these genes but poising them for future activation. Silent genes without any H3K4 methylation signal show no evidence of being bound by HDACs.
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              Transcriptome-wide noise controls lineage choice in mammalian progenitor cells.

              Phenotypic cell-to-cell variability within clonal populations may be a manifestation of 'gene expression noise', or it may reflect stable phenotypic variants. Such 'non-genetic cell individuality' can arise from the slow fluctuations of protein levels in mammalian cells. These fluctuations produce persistent cell individuality, thereby rendering a clonal population heterogeneous. However, it remains unknown whether this heterogeneity may account for the stochasticity of cell fate decisions in stem cells. Here we show that in clonal populations of mouse haematopoietic progenitor cells, spontaneous 'outlier' cells with either extremely high or low expression levels of the stem cell marker Sca-1 (also known as Ly6a; ref. 9) reconstitute the parental distribution of Sca-1 but do so only after more than one week. This slow relaxation is described by a gaussian mixture model that incorporates noise-driven transitions between discrete subpopulations, suggesting hidden multi-stability within one cell type. Despite clonality, the Sca-1 outliers had distinct transcriptomes. Although their unique gene expression profiles eventually reverted to that of the median cells, revealing an attractor state, they lasted long enough to confer a greatly different proclivity for choosing either the erythroid or the myeloid lineage. Preference in lineage choice was associated with increased expression of lineage-specific transcription factors, such as a >200-fold increase in Gata1 (ref. 10) among the erythroid-prone cells, or a >15-fold increased PU.1 (Sfpi1) (ref. 11) expression among myeloid-prone cells. Thus, clonal heterogeneity of gene expression level is not due to independent noise in the expression of individual genes, but reflects metastable states of a slowly fluctuating transcriptome that is distinct in individual cells and may govern the reversible, stochastic priming of multipotent progenitor cells in cell fate decision.
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                Author and article information

                Journal
                J Neuroendocrinol
                J. Neuroendocrinol
                jne
                Journal of Neuroendocrinology
                Blackwell Publishing Ltd (Oxford, UK )
                0953-8194
                1365-2826
                July 2012
                : 24
                : 7
                : 977-990
                Affiliations
                [* ]Developmental Biomedicine Research Group, Faculty of Medical and Human Sciences, University of Manchester Manchester, UK
                []Systems Biology Centre, Faculty of Life Sciences, University of Manchester Manchester, UK.
                Author notes
                Correspondence to: Karen Featherstone, Endocrinology and Diabetes Group, Developmental Biomedicine Research Group, AV Hill Building, Oxford Road, University of Manchester, Manchester M13 9PT, UK (e-mail: karen.featherstone@ 123456manchester.ac.uk ).
                Article
                10.1111/j.1365-2826.2012.02310.x
                3505372
                22420298
                bc3347dc-6f8a-4b0f-83a5-1f14b3a47237
                © 2012 The Authors. Journal of Neuroendocrinology © 2012 Blackwell Publishing Ltd

                Re-use of this article is permitted in accordance with the Creative Commons Deed, Attribution 2.5, which does not permit commercial exploitation.

                History
                : 16 January 2012
                : 09 March 2012
                : 10 March 2012
                Categories
                Review Article

                Endocrinology & Diabetes
                dynamics,transcription,prolactin,chromatin,pituitary
                Endocrinology & Diabetes
                dynamics, transcription, prolactin, chromatin, pituitary

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