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10.1016/j.celrep.2017.03.045 http://scihub22266oqcxt.onion/10.1016/j.celrep.2017.03.045 C5400779!5400779 !28402863     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=28402863 &cmd=llinks): Failed to open stream: HTTP request failed! 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Biotagging of Specific Cell Populations in Zebrafish Reveals Gene Regulatory Logic Encoded in the Nuclear Transcriptome |pdf=|usr=}}{{28402863 }} gab.com Text Biotagging of Specific Cell Populations in Zebrafish Reveals Gene Regulatory Logic Encoded in the Nuclear Transcriptome JO: Cell Rep http://www.kidney.de/pget.php?&tw=1&pmid=28402863 #FOAvip Interrogation of gene regulatory circuits in complex organisms requires precise tools for the selection of individual cell types and robust methods for biochemical profiling of target proteins. We have developed a versatile, tissue-specific binary in vivo biotinylation system in zebrafish termed biotagging that uses genetically encoded components to biotinylate target proteins, enabling in-depth genome-wide analyses of their molecular interactions. Using tissue-specific drivers and cell-compartment-specific effector lines, we demonstrate the specificity of the biotagging toolkit at the biochemical, cellular, and transcriptional levels. We use biotagging to characterize the in vivo transcriptional landscape of migratory neural crest and myocardial cells in different cellular compartments (ribosomes and nucleus). These analyses reveal a comprehensive network of coding and non-coding RNAs and cis-regulatory modules, demonstrating that tissue-specific identity is embedded in the nuclear transcriptomes. By eliminating background inherent to complex embryonic environments, biotagging allows analyses of molecular interactions at high resolution. Twit Text FOAVip Biotagging of Specific Cell Populations in Zebrafish Reveals Gene Regulatory Logic Encoded in the Nuclear Transcriptome ????Cell Rep http://www.kidney.de/pget.php?&tw=1&pmid=28402863 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=28402863 #FOAvip English Wikipedia <ref>{{Cite pmid|28402863 }}</ref> Biotagging of Specific Cell Populations in Zebrafish Reveals Gene Regulatory Logic Encoded in the Nuclear Transcriptome #MMPMID28402863 Trinh LA ; Chong-Morrison V ; Gavriouchkina D ; Hochgreb-Hägele T ; Senanayake U ; Fraser SE ; Sauka-Spengler T Cell Rep 2017[Apr]; 19 (2 ): 425-440 PMID28402863 show ga Interrogation of gene regulatory circuits in complex organisms requires precise tools for the selection of individual cell types and robust methods for biochemical profiling of target proteins. We have developed a versatile, tissue-specific binary in vivo biotinylation system in zebrafish termed biotagging that uses genetically encoded components to biotinylate target proteins, enabling in-depth genome-wide analyses of their molecular interactions. Using tissue-specific drivers and cell-compartment-specific effector lines, we demonstrate the specificity of the biotagging toolkit at the biochemical, cellular, and transcriptional levels. We use biotagging to characterize the in vivo transcriptional landscape of migratory neural crest and myocardial cells in different cellular compartments (ribosomes and nucleus). These analyses reveal a comprehensive network of coding and non-coding RNAs and cis-regulatory modules, demonstrating that tissue-specific identity is embedded in the nuclear transcriptomes. By eliminating background inherent to complex embryonic environments, biotagging allows analyses of molecular interactions at high resolution. |Animals [MESH] |Cell Compartmentation/genetics [MESH] |Cell Lineage/genetics [MESH] |Conserved Sequence/genetics [MESH] |Gene Expression Regulation, Developmental [MESH] |Gene Regulatory Networks/genetics [MESH] |Neural Crest/*growth & development [MESH] |Organ Specificity/genetics [MESH] |Transcription Factors/*biosynthesis/genetics [MESH] |Transcriptome/*genetics [MESH]Biotagging of Specific Cell Populations in Zebrafish Reveals Gene Regu(epmc).pdf DeepDyve Pubget Overpricing