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      Role of Cnot6l in maternal mRNA turnover

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          Abstract

          Mice lacking Cnot6l, a deadenylase component of the CCR4–NOT complex, are viable, but females have ∼40% smaller litters. Cnot6l is a maternal-effect gene acting in maternal mRNA degradation.

          Abstract

          Removal of poly(A) tail is an important mechanism controlling eukaryotic mRNA turnover. The major eukaryotic deadenylase complex CCR4-NOT contains two deadenylase components, CCR4 and CAF1, for which mammalian CCR4 is encoded by Cnot6 or Cnot6l paralogs. We show that Cnot6l apparently supplies the majority of CCR4 in the maternal CCR4-NOT in mouse, hamster, and bovine oocytes. Deletion of Cnot6l yielded viable mice, but Cnot6l −/− females exhibited ∼40% smaller litter size. The main onset of the phenotype was post-zygotic: fertilized Cnot6l −/− eggs developed slower and arrested more frequently than Cnot6l +/− eggs, suggesting that maternal CNOT6L is necessary for accurate oocyte-to-embryo transition. Transcriptome analysis revealed major transcriptome changes in Cnot6l −/− ovulated eggs and one-cell zygotes. In contrast, minimal transcriptome changes in preovulatory Cnot6l −/− oocytes were consistent with reported Cnot6l mRNA dormancy. A minimal overlap between transcripts sensitive to decapping inhibition and Cnot6l loss suggests that decapping and CNOT6L-mediated deadenylation selectively target distinct subsets of mRNAs during oocyte-to-embryo transition in mouse.

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          In silico prediction of protein-protein interactions in human macrophages

          Background: Protein-protein interaction (PPI) network analyses are highly valuable in deciphering and understanding the intricate organisation of cellular functions. Nevertheless, the majority of available protein-protein interaction networks are context-less, i.e. without any reference to the spatial, temporal or physiological conditions in which the interactions may occur. In this work, we are proposing a protocol to infer the most likely protein-protein interaction (PPI) network in human macrophages. Results: We integrated the PPI dataset from the Agile Protein Interaction DataAnalyzer (APID) with different meta-data to infer a contextualized macrophage-specific interactome using a combination of statistical methods. The obtained interactome is enriched in experimentally verified interactions and in proteins involved in macrophage-related biological processes (i.e. immune response activation, regulation of apoptosis). As a case study, we used the contextualized interactome to highlight the cellular processes induced upon Mycobacterium tuberculosis infection. Conclusion: Our work confirms that contextualizing interactomes improves the biological significance of bioinformatic analyses. More specifically, studying such inferred network rather than focusing at the gene expression level only, is informative on the processes involved in the host response. Indeed, important immune features such as apoptosis are solely highlighted when the spotlight is on the protein interaction level.
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            BigWig and BigBed: enabling browsing of large distributed datasets

            Summary: BigWig and BigBed files are compressed binary indexed files containing data at several resolutions that allow the high-performance display of next-generation sequencing experiment results in the UCSC Genome Browser. The visualization is implemented using a multi-layered software approach that takes advantage of specific capabilities of web-based protocols and Linux and UNIX operating systems files, R trees and various indexing and compression tricks. As a result, only the data needed to support the current browser view is transmitted rather than the entire file, enabling fast remote access to large distributed data sets. Availability and implementation: Binaries for the BigWig and BigBed creation and parsing utilities may be downloaded at http://hgdownload.cse.ucsc.edu/admin/exe/linux.x86_64/. Source code for the creation and visualization software is freely available for non-commercial use at http://hgdownload.cse.ucsc.edu/admin/jksrc.zip, implemented in C and supported on Linux. The UCSC Genome Browser is available at http://genome.ucsc.edu Contact: ann@soe.ucsc.edu Supplementary information: Supplementary byte-level details of the BigWig and BigBed file formats are available at Bioinformatics online. For an in-depth description of UCSC data file formats and custom tracks, see http://genome.ucsc.edu/FAQ/FAQformat.html and http://genome.ucsc.edu/goldenPath/help/hgTracksHelp.html
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              Genetic programs in human and mouse early embryos revealed by single-cell RNA sequencing.

              Mammalian pre-implantation development is a complex process involving dramatic changes in the transcriptional architecture. We report here a comprehensive analysis of transcriptome dynamics from oocyte to morula in both human and mouse embryos, using single-cell RNA sequencing. Based on single-nucleotide variants in human blastomere messenger RNAs and paternal-specific single-nucleotide polymorphisms, we identify novel stage-specific monoallelic expression patterns for a significant portion of polymorphic gene transcripts (25 to 53%). By weighted gene co-expression network analysis, we find that each developmental stage can be delineated concisely by a small number of functional modules of co-expressed genes. This result indicates a sequential order of transcriptional changes in pathways of cell cycle, gene regulation, translation and metabolism, acting in a step-wise fashion from cleavage to morula. Cross-species comparisons with mouse pre-implantation embryos reveal that the majority of human stage-specific modules (7 out of 9) are notably preserved, but developmental specificity and timing differ between human and mouse. Furthermore, we identify conserved key members (or hub genes) of the human and mouse networks. These genes represent novel candidates that are likely to be key in driving mammalian pre-implantation development. Together, the results provide a valuable resource to dissect gene regulatory mechanisms underlying progressive development of early mammalian embryos.
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                Author and article information

                Journal
                Life Sci Alliance
                Life Sci Alliance
                lsa
                lsa
                Life Science Alliance
                Life Science Alliance LLC
                2575-1077
                16 July 2018
                August 2018
                16 July 2018
                : 1
                : 4
                : e201800084
                Affiliations
                [1 ]Institute of Molecular Genetics of the Czech Academy of Sciences, Prague, Czech Republic
                [2 ]Bioinformatics Group, Division of Molecular Biology, Department of Biology, Faculty of Science, University of Zagreb, Zagreb, Croatia
                [3 ]Institute of Animal Science, Prague, Czech Republic
                [4 ]Department of Biology, University of Pennsylvania, Philadelphia, PA, USA
                [5 ]Department of Anatomy, Physiology, and Cell Biology, School of Veterinary Medicine, University of California, Davis, CA, USA
                [6 ]Czech Centre for Phenogenomics and Laboratory of Transgenic Models of Diseases, Institute of Molecular Genetics of the Czech Academy of Sciences, v. v. i., Vestec, Czech Republic
                Author notes

                Radek Jankele’s present address is Swiss Institute for Experimental Cancer Research (ISREC), School of Live Sciences, Swiss Federal Institute of Technology Lausanne (EPFL), Lausanne, Switzerland.

                [*]

                Filip Horvat, Helena Fulka, and Radek Jankele contributed equally to this work.

                Author information
                https://orcid.org/0000-0002-1896-7645
                https://orcid.org/0000-0002-6783-1146
                https://orcid.org/0000-0002-5705-2464
                https://orcid.org/0000-0002-4370-3705
                Article
                LSA-2018-00084
                10.26508/lsa.201800084
                6238536
                30456367
                c7863dd4-26fe-4bda-a76b-9bbe288df124
                © 2018 Horvat et al.

                This article is available under a Creative Commons License (Attribution 4.0 International, as described at https://creativecommons.org/licenses/by/4.0/).

                History
                : 5 May 2018
                : 4 July 2018
                : 5 July 2018
                Funding
                Funded by: Czech Science Foundation;
                Award ID: P305/12/G034
                Funded by: Ministry of Education, Youth, and Sports;
                Funded by: CSF;
                Award ID: 17-08605S
                Award Recipient :
                Funded by: Czech Centre for Phenogenomics;
                Award ID: LM2015040
                Funded by: Biotechnology and Biomedicine Centre of the Academy of Sciences and Charles University;
                Award ID: CZ.1.05/1.1.00/02.0109
                Funded by: MEYS;
                Award ID: CZ.1.05/2.1.00/19.0395
                Funded by: Academy of Sciences of the Czech Republic;
                Award ID: RVO 68378050
                Award Recipient :
                Funded by: European Structural and Investment Funds;
                Award Recipient :
                Funded by: Croatian National Centre of Research Excellence;
                Award Recipient :
                Funded by: Croatian Science Foundation;
                Award ID: IP-2014-09-6400
                Award Recipient :
                Funded by: National Institutes of Health;
                Award ID: HD022681
                Award Recipient :
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