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      Understanding Tissue-Specific Gene Regulation

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          Summary

          Although all human tissues carry out common processes, tissues are distinguished by gene expression patterns, implying that distinct regulatory programs control tissue specificity. In this study, we investigate gene expression and regulation across 38 tissues profiled in the Genotype-Tissue Expression project. We find that network edges (transcription factor to target gene connections) have higher tissue specificity than network nodes (genes) and that regulating nodes (transcription factors) are less likely to be expressed in a tissue-specific manner as compared to their targets (genes). Gene set enrichment analysis of network targeting also indicates that the regulation of tissue-specific function is largely independent of transcription factor expression. In addition, tissue-specific genes are not highly targeted in their corresponding tissue network. However, they do assume bottleneck positions due to variability in transcription factor targeting and the influence of non-canonical regulatory interactions. These results suggest that tissue specificity is driven by context-dependent regulatory paths, providing transcriptional control of tissue-specific processes.

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          Most cited references23

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          Finding community structure in very large networks

          The discovery and analysis of community structure in networks is a topic of considerable recent interest within the physics community, but most methods proposed so far are unsuitable for very large networks because of their computational cost. Here we present a hierarchical agglomeration algorithm for detecting community structure which is faster than many competing algorithms: its running time on a network with n vertices and m edges is O(m d log n) where d is the depth of the dendrogram describing the community structure. Many real-world networks are sparse and hierarchical, with m ~ n and d ~ log n, in which case our algorithm runs in essentially linear time, O(n log^2 n). As an example of the application of this algorithm we use it to analyze a network of items for sale on the web-site of a large online retailer, items in the network being linked if they are frequently purchased by the same buyer. The network has more than 400,000 vertices and 2 million edges. We show that our algorithm can extract meaningful communities from this network, revealing large-scale patterns present in the purchasing habits of customers.
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            A multitude of genes expressed solely in meiotic or postmeiotic spermatogenic cells offers a myriad of contraceptive targets.

            Understanding mammalian spermatozoan development and the events surrounding fertilization has grown slowly, in part because of uncertainty about the number and identity of the cellular components involved. Determination of those transcripts expressed specifically by germ cells should provide an inclusive list of probable critical proteins. Here, total mouse testis transcript profiles were trimmed of transcripts found in cultures enriched in Sertoli or interstitial cells to yield a germ cell-enriched transcript profile. Monitoring of changes of this profile in the developing testis identified 1,652 genes whose transcript abundance increased markedly coincident with the onset of meiosis. Remarkably, 351 of these genes (approximately equal to 20%) appear to be expressed only in the male germline. Germ cell-specific transcripts are much less common earlier in testis development. Further analysis of the UniGene EST database coupled with quantitative PCR indicates that approximately 4% of the mouse genome is dedicated to expression in postmeiotic male germ cells. Most or many of the protein products of these transcripts are probably retained in mature spermatozoa. Targeted disruption of 19 of these genes has indicated that a majority have roles critical for normal fertility. Thus, we find an astonishing number of genes expressed specifically by male germ cells late in development. This extensive group provides a plethora of potential targets for germ cell-directed contraception and a staggering number of candidate proteins that could be critical for fertilization.
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              Tet1 regulates adult hippocampal neurogenesis and cognition.

              DNA hydroxylation catalyzed by Tet dioxygenases occurs abundantly in embryonic stem cells and neurons in mammals. However, its biological function in vivo is largely unknown. Here, we demonstrate that Tet1 plays an important role in regulating neural progenitor cell proliferation in adult mouse brain. Mice lacking Tet1 exhibit impaired hippocampal neurogenesis accompanied by poor learning and memory. In adult neural progenitor cells deficient in Tet1, a cohort of genes involved in progenitor proliferation were hypermethylated and downregulated. Our results indicate that Tet1 is positively involved in the epigenetic regulation of neural progenitor cell proliferation in the adult brain. Copyright © 2013 Elsevier Inc. All rights reserved.
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                Author and article information

                Journal
                101573691
                39703
                Cell Rep
                Cell Rep
                Cell reports
                2211-1247
                18 October 2017
                24 October 2017
                24 October 2018
                : 21
                : 4
                : 1077-1088
                Affiliations
                [1 ]Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, MA 02115, USA
                [2 ]Department of Medicine, Harvard Medical School, Boston, MA 02115, USA
                [3 ]Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
                [4 ]Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA
                [5 ]Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, Boston, MA 02115, USA
                [6 ]Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA
                Author notes
                [7]

                These authors contributed equally

                [8]

                Lead Contact

                Article
                NIHMS913856
                10.1016/j.celrep.2017.10.001
                5828531
                29069589
                d1f0c81c-d9e9-43e1-910b-24fa817a80d1

                This is an open access article under the CC BY-NC-ND license.

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                Cell biology
                Cell biology

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