Transcriptional Regulation of Rod Photoreceptor Homeostasis Revealed by In Vivo NRL Targetome Analysis
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{"title"=>"Transcriptional regulation of rod photoreceptor homeostasis revealed by in vivo NRL targetome analysis", "type"=>"journal", "authors"=>[{"first_name"=>"Hong", "last_name"=>"Hao", "scopus_author_id"=>"50161561400"}, {"first_name"=>"Douglas S.", "last_name"=>"Kim", "scopus_author_id"=>"55603091800"}, {"first_name"=>"Bernward", "last_name"=>"Klocke", "scopus_author_id"=>"6701374980"}, {"first_name"=>"Kory R.", "last_name"=>"Johnson", "scopus_author_id"=>"25936343700"}, {"first_name"=>"Kairong", "last_name"=>"Cui", "scopus_author_id"=>"8785222500"}, {"first_name"=>"Norimoto", "last_name"=>"Gotoh", "scopus_author_id"=>"7006670313"}, {"first_name"=>"Chongzhi", "last_name"=>"Zang", "scopus_author_id"=>"24448859500"}, {"first_name"=>"Janina", "last_name"=>"Gregorski", "scopus_author_id"=>"53979534400"}, {"first_name"=>"Linn", "last_name"=>"Gieser", "scopus_author_id"=>"6602869139"}, {"first_name"=>"Weiqun", "last_name"=>"Peng", "scopus_author_id"=>"35337480300"}, {"first_name"=>"Yang", "last_name"=>"Fann", "scopus_author_id"=>"55977835400"}, {"first_name"=>"Martin", "last_name"=>"Seifert", "scopus_author_id"=>"55765293700"}, {"first_name"=>"Keji", "last_name"=>"Zhao", "scopus_author_id"=>"7202071783"}, {"first_name"=>"Anand", "last_name"=>"Swaroop", "scopus_author_id"=>"57200407963"}], "year"=>2012, "source"=>"PLoS Genetics", "identifiers"=>{"pui"=>"364739035", "sgr"=>"84860572048", "pmid"=>"22511886", "scopus"=>"2-s2.0-84860572048", "isbn"=>"1553-7404 (Electronic)\\r1553-7390 (Linking)", "doi"=>"10.1371/journal.pgen.1002649", "issn"=>"15537390"}, "id"=>"2e5f931a-9982-3024-aaf7-db5fd3c628b9", "abstract"=>"A stringent control of homeostasis is critical for functional maintenance and survival of neurons. In the mammalian retina, the basic motif leucine zipper transcription factor NRL determines rod versus cone photoreceptor cell fate and activates the expression of many rod-specific genes. Here, we report an integrated analysis of NRL-centered gene regulatory network by coupling chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-Seq) data from Illumina and ABI platforms with global expression profiling and in vivo knockdown studies. We identified approximately 300 direct NRL target genes. Of these, 22 NRL targets are associated with human retinal dystrophies, whereas 95 mapped to regions of as yet uncloned retinal disease loci. In silico analysis of NRL ChIP-Seq peak sequences revealed an enrichment of distinct sets of transcription factor binding sites. Specifically, we discovered that genes involved in photoreceptor function include binding sites for both NRL and homeodomain protein CRX. Evaluation of 26 ChIP-Seq regions validated their enhancer functions in reporter assays. In vivo knockdown of 16 NRL target genes resulted in death or abnormal morphology of rod photoreceptors, suggesting their importance in maintaining retinal function. We also identified histone demethylase Kdm5b as a novel secondary node in NRL transcriptional hierarchy. Exon array analysis of flow-sorted photoreceptors in which Kdm5b was knocked down by shRNA indicated its role in regulating rod-expressed genes. Our studies identify candidate genes for retinal dystrophies, define cis-regulatory module(s) for photoreceptor-expressed genes and provide a framework for decoding transcriptional regulatory networks that dictate rod homeostasis.", "link"=>"http://www.mendeley.com/research/transcriptional-regulation-rod-photoreceptor-homeostasis-revealed-vivo-nrl-targetome-analysis", "reader_count"=>54, "reader_count_by_academic_status"=>{"Professor > Associate Professor"=>5, "Student > Doctoral Student"=>4, "Researcher"=>13, "Student > Ph. D. Student"=>12, "Student > Postgraduate"=>4, "Student > Master"=>5, "Student > Bachelor"=>6, "Professor"=>5}, "reader_count_by_user_role"=>{"Professor > Associate Professor"=>5, "Student > Doctoral Student"=>4, "Researcher"=>13, "Student > Ph. D. Student"=>12, "Student > Postgraduate"=>4, "Student > Master"=>5, "Student > Bachelor"=>6, "Professor"=>5}, "reader_count_by_subject_area"=>{"Engineering"=>2, "Unspecified"=>1, "Biochemistry, Genetics and Molecular Biology"=>8, "Agricultural and Biological Sciences"=>34, "Medicine and Dentistry"=>4, "Neuroscience"=>2, "Business, Management and Accounting"=>1, "Social Sciences"=>1, "Computer Science"=>1}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>2}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>4}, "Neuroscience"=>{"Neuroscience"=>2}, "Social Sciences"=>{"Social Sciences"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>34}, "Computer Science"=>{"Computer Science"=>1}, "Business, Management and Accounting"=>{"Business, Management and Accounting"=>1}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>8}, "Unspecified"=>{"Unspecified"=>1}}, "reader_count_by_country"=>{"United States"=>4, "Denmark"=>1, "Portugal"=>1}, "group_count"=>1}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/654964"], "description"=>"<p>Twenty-six NRL peak regions were cloned into pGL3-promoter vector in front of a SV40 basal promoter and a luciferase reporter. The constructs were transfected in HEK293T cells together with mouse <i>Nrl</i> (m<i>Nrl</i>) expression plasmid (in pC4C vector) or empty pC4C vector. The y-axis is fold change (Fc) of normalized luciferase readings. Control: enhancer constructs co-transfected with empty pC4C vector. Five non-peak regions served as additional negative controls. The experiments were performed three times. Representative results are shown as mean ± SD. P<0.05 for all by Student's t test.</p>", "links"=>[], "tags"=>["nrl", "regions", "transfected", "hek293t"], "article_id"=>325440, "categories"=>["Biotechnology", "Biochemistry", "Developmental Biology", "Medicine", "Biological Sciences", "Neuroscience", "Genetics"], "users"=>["Hong Hao", "Douglas S. Kim", "Bernward Klocke", "Kory R. Johnson", "Kairong Cui", "Norimoto Gotoh", "Chongzhi Zang", "Janina Gregorski", "Linn Gieser", "Weiqun Peng", "Yang Fann", "Martin Seifert", "Keji Zhao", "Anand Swaroop"], "doi"=>"https://dx.doi.org/10.1371/journal.pgen.1002649.g005", "stats"=>{"downloads"=>1, "page_views"=>14, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Enhancer_function_of_NRL_ChIP_8211_Seq_regions_in_transfected_HEK293T_cells_/325440", "title"=>"Enhancer function of NRL ChIP–Seq regions in transfected HEK293T cells.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-04-12 01:30:40"}
  • {"files"=>["https://ndownloader.figshare.com/files/654369"], "description"=>"<p>(A) Analysis workflow. Raw sequence reads from Illumina or ABI/SOLiD were mapped to the mouse genome (NCBI build 37) using the Genomatix Mining Station (GMS) and the reads mapped to unique genomic locations (uniquely mapped reads) were used for further analyses. ChIP–Seq peaks were called using NGS Analyzer (Genomatix) or MACS (Zhang et al., 2008), and the common peaks were used for further analyses. The NRL ChIP–Seq peaks were compared to the CRX ChIP–Seq peaks for overlapping using GenomeInspector (Genomatix) software. The ChIP–Seq peaks were assigned to the nearest gene. Transcription profile analyses of flow-sorted photoreceptors of WT and <i>Nrl</i><sup>−/−</sup> were performed using ChipInsepector program (Genomatix) and 1.5 fold expression change was used as a criterion for NRL target genes. TF motif enrichment analyses were performed on the NRL ChIP–Seq peak regions that were associated with NRL target genes. Comparison was made between CRX-overlapping and non CRX-overlapping NRL ChIP–Seq peaks. Gene regulatory network was constructed based on TF enrichment analysis. (B) Correlation of ChIP–Seq peaks by Illumina and ABI. The number of correlations (y-axis) was plotted to the distance of ABI ChIP–Seq peaks to Illumina ChIP–Seq peaks (x-axis). The Venn diagram (inset) calculated the percentage of ABI and Illumina peaks within 500 bp of each other: 88% of Illumina peaks are within 500 bp of ABI peaks and 49% of ABI peaks are within 500 bp of Illumina peaks. (C) Correlation of ChIP–Seq peaks to promoters. The number of correlation (y-axis) was plotted to the distance of ABI ChIP–Seq peaks (green graph) or Illumina ChIP–Seq peaks (blue graph) to the transcription start site (TSS) (x-axis). The Venn diagram (inset) calculated the percentage of ABI (75%) or Illumina (72%) peaks within 10,000 bp from the TSS. (D) Genomic distribution of NRL ChIP–Seq peaks relative to the nearest annotated genes. Promoters and exons account for 2.3% and 5.4% of the mouse genome, respectively.</p>", "links"=>[], "tags"=>["occupancy", "nrl", "revealed", "illumina", "sequencing"], "article_id"=>324845, "categories"=>["Biotechnology", "Biochemistry", "Developmental Biology", "Medicine", "Biological Sciences", "Neuroscience", "Genetics"], "users"=>["Hong Hao", "Douglas S. Kim", "Bernward Klocke", "Kory R. Johnson", "Kairong Cui", "Norimoto Gotoh", "Chongzhi Zang", "Janina Gregorski", "Linn Gieser", "Weiqun Peng", "Yang Fann", "Martin Seifert", "Keji Zhao", "Anand Swaroop"], "doi"=>"https://dx.doi.org/10.1371/journal.pgen.1002649.g001", "stats"=>{"downloads"=>1, "page_views"=>20, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Genome_wide_Occupancy_of_NRL_revealed_by_ChIP_8211_Seq_using_Illumina_and_ABI_SOLiD_sequencing_platforms_/324845", "title"=>"Genome-wide Occupancy of NRL revealed by ChIP–Seq using Illumina and ABI/SOLiD sequencing platforms.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-04-12 01:20:45"}
  • {"files"=>["https://ndownloader.figshare.com/files/654811"], "description"=>"<p>ChIP-qPCR was performed to validate NRL binding to 26 ChIP–Seq peak regions (left panel), and 5 non-peak regions (right panel) served as negative controls. The amount of ChIP DNA was measured by qPCR in triplicates using primers flanking the regions of interest. Normal IgG served as an antibody control when ChIP was performed using WT retinas (white bars). White bars (NRL Ab/IgG) represent fold change (FC) of qPCR signals comparing NRL ChIP DNA to the IgG control ChIP DNA. A separate set of ChIP assays was performed using NRL antibody to compare signals from WT retina to signals from <i>Nrl</i><sup>−/−</sup> retina (tissue control). Black bars (WT/<i>Nrl</i><sup>−/−</sup>) represent fold increase (Fc) of qPCR signals comparing NRL ChIP DNA from wild type C57BL/6 mouse retina to NRL ChIP DNA from <i>Nrl<sup>−/</sup></i><sup>−</sup> mouse retina. The ChIP-qPCR assays were performed twice. The representative results were shown as mean ± SD. P<0.01 for all by Student's t test.</p>", "links"=>[], "tags"=>["nrl", "binding", "corresponding", "regions"], "article_id"=>325278, "categories"=>["Biotechnology", "Biochemistry", "Developmental Biology", "Medicine", "Biological Sciences", "Neuroscience", "Genetics"], "users"=>["Hong Hao", "Douglas S. Kim", "Bernward Klocke", "Kory R. Johnson", "Kairong Cui", "Norimoto Gotoh", "Chongzhi Zang", "Janina Gregorski", "Linn Gieser", "Weiqun Peng", "Yang Fann", "Martin Seifert", "Keji Zhao", "Anand Swaroop"], "doi"=>"https://dx.doi.org/10.1371/journal.pgen.1002649.g004", "stats"=>{"downloads"=>1, "page_views"=>9, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Validation_of_NRL_binding_to_corresponding_peak_regions_by_ChIP_8211_qPCR_/325278", "title"=>"Validation of NRL binding to corresponding peak regions by ChIP–qPCR.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-04-12 01:27:58"}
  • {"files"=>["https://ndownloader.figshare.com/files/655548"], "description"=>"<p>(A) Experimental workflow. CD-1 mouse retinas were transfected at P0 with Ub-GFP and shRNA against <i>Gapdh</i> or <i>Kdm5b</i> by sub-retinal injection and <i>in vivo</i> electroporation. Retinas were dissociated at P20 and shRNA-transfected retinal cells were isolated by flow-sorting. The effect of <i>Kdm5b</i> shRNA on transcriptional profile was measured by microarray analysis. (B) Ontology analysis of common targets of KDM5b and NRL. <i>Kdm5b</i> shRNA up: genes that are up-regulated in retinal cells electroporated with <i>Kdm5b</i> shRNA. <i>Kdm5b</i> shRNA down: genes that are down-regulated in retinal cells electroporated with <i>Kdm5b</i> shRNA. <i>Nrl-</i>ko up: genes that are up-regulated in <i>Nrl</i><sup>−/−</sup> photoreceptor cells. <i>Nrl-</i>ko down: genes that are down-regulated in <i>Nrl</i><sup>−/−</sup> photorceptor cells.</p>", "links"=>[], "tags"=>["flow-sorted", "photoreceptors", "vivo"], "article_id"=>326025, "categories"=>["Biotechnology", "Biochemistry", "Developmental Biology", "Medicine", "Biological Sciences", "Neuroscience", "Genetics"], "users"=>["Hong Hao", "Douglas S. Kim", "Bernward Klocke", "Kory R. Johnson", "Kairong Cui", "Norimoto Gotoh", "Chongzhi Zang", "Janina Gregorski", "Linn Gieser", "Weiqun Peng", "Yang Fann", "Martin Seifert", "Keji Zhao", "Anand Swaroop"], "doi"=>"https://dx.doi.org/10.1371/journal.pgen.1002649.g008", "stats"=>{"downloads"=>1, "page_views"=>14, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Microarray_analysis_of_flow_sorted_photoreceptors_after_in_vivo_Kdm5b_knockdown_/326025", "title"=>"Microarray analysis of flow-sorted photoreceptors after <i>in vivo Kdm5b</i> knockdown.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-04-12 01:40:25"}
  • {"files"=>["https://ndownloader.figshare.com/files/655135"], "description"=>"<p>CD-1 mouse retinas were transfected at P0 with Ub-GFP and shRNA against <i>Gapdh</i> or NRL target genes by sub-retinal injection followed by <i>in vivo</i> electroporation (A–F). Retina were harvested at P20 and examined for GFP fluorescence (green), Rho immuno-reactivity (red) and DAPI staining (blue). At least 3 biological replicate retinas were collected and imaged. (A). ONL: outer nuclear layer. INL: inner nuclear layer. GCL: ganglion cell layer. Scale bar: 20 µM. (B) Higher magnification images of (A). OS: outer segment. OONL: outer portion of the outer nuclear layer. IONL: inner portion of the outer nuclear layer. Scale bar: 15 µM. GFP positive (+) cells in ONL were counted in sections of retinas electroporated with shRNA targeting <i>Gapdh</i> or NRL target genes (C, F). Distribution of electroporated cell bodies in the retina (D). Fraction of GFP positive cells in the retinal outer nuclear layer is calculated. OONL, outer portion of outer nuclear layer; IONL, inner portion of outer nuclear layer. Average outer segment (OS) length of electroporated cells was measured (E). Data are represented as mean ± SD. (C, D, E) *P<0.001, **P<0.0001 by Student's t test (n = 6 electroporated retinas). (F) *P<0.01 by Student's t test (n = 3 electroporated retinas).</p>", "links"=>[], "tags"=>["knockdown", "nrl", "targets", "shrna", "sub-retinal", "injection"], "article_id"=>325607, "categories"=>["Biotechnology", "Biochemistry", "Developmental Biology", "Medicine", "Biological Sciences", "Neuroscience", "Genetics"], "users"=>["Hong Hao", "Douglas S. Kim", "Bernward Klocke", "Kory R. Johnson", "Kairong Cui", "Norimoto Gotoh", "Chongzhi Zang", "Janina Gregorski", "Linn Gieser", "Weiqun Peng", "Yang Fann", "Martin Seifert", "Keji Zhao", "Anand Swaroop"], "doi"=>"https://dx.doi.org/10.1371/journal.pgen.1002649.g006", "stats"=>{"downloads"=>2, "page_views"=>20, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_In_vivo_knockdown_of_NRL_targets_by_shRNA_sub_retinal_injection_and_in_vivo_electroporation_/325607", "title"=>"<i>In vivo</i> knockdown of NRL targets by shRNA sub-retinal injection and <i>in vivo</i> electroporation.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-04-12 01:33:27"}
  • {"files"=>["https://ndownloader.figshare.com/files/655372"], "description"=>"<p>CD-1 mice were transfected at P0 with Ub-GFP and shRNA against <i>Gapdh</i>, <i>Lman1 or Wisp1</i> by sub-retinal injection and <i>in vivo</i> electroporation. shRNA-resistant degenerate cDNA (dcDNA) was co-injected together with shRNA against <i>Gapdh</i>, <i>Lman1 or Wisp1</i> for rescue experiments. Retinas were harvested at P20 and examined for GFP fluorescence (green), Rho immuno-reactivity (red) and DAPI staining (blue). Three biological replicate retinas were collected and imaged. (A, C). Scale bar: 20 µM. (B, D) Higher magnification images of (A, C). OS: outer segment. OONL: outer portion of the outer nuclear layer. IONL: inner portion of the outer nuclear layer. Scale bar: 10 µM. GFP positive (+) cells were counted in sections of retina electroporated with shRNA targeting <i>Gapdh</i> or NRL target genes (E, H). Distribution of electroporated cell bodies in the retina (F). Fraction of GFP positive cells in the retinal outer nuclear layer is counted. OONL, outer region of outer nuclear layer; IONL, inner region of outer nuclear layer. Average outer segment (OS) lengths of electroporated cells were measured (G). Data are represented as mean ± SD. (E–H) *P<0.01, **P<0.001 by Student's t test (n = 3 electroporated retinas).</p>", "links"=>[], "tags"=>["ophthalmology", "genetics and genomics", "Computational biology", "biotechnology", "neuroscience", "developmental biology", "Biochemistry"], "article_id"=>325845, "categories"=>["Biotechnology", "Biochemistry", "Developmental Biology", "Medicine", "Biological Sciences", "Neuroscience", "Genetics"], "users"=>["Hong Hao", "Douglas S. Kim", "Bernward Klocke", "Kory R. Johnson", "Kairong Cui", "Norimoto Gotoh", "Chongzhi Zang", "Janina Gregorski", "Linn Gieser", "Weiqun Peng", "Yang Fann", "Martin Seifert", "Keji Zhao", "Anand Swaroop"], "doi"=>"https://dx.doi.org/10.1371/journal.pgen.1002649.g007", "stats"=>{"downloads"=>2, "page_views"=>18, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Rescue_of_shRNA_8211_knockdown_with_shRNA_8211_resistant_dcDNA_/325845", "title"=>"Rescue of shRNA–knockdown with shRNA–resistant dcDNA.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-04-12 01:37:25"}
  • {"files"=>["https://ndownloader.figshare.com/files/336430", "https://ndownloader.figshare.com/files/336452", "https://ndownloader.figshare.com/files/336466", "https://ndownloader.figshare.com/files/336491", "https://ndownloader.figshare.com/files/336513", "https://ndownloader.figshare.com/files/336539", "https://ndownloader.figshare.com/files/336555", "https://ndownloader.figshare.com/files/336579", "https://ndownloader.figshare.com/files/336601", "https://ndownloader.figshare.com/files/336626", "https://ndownloader.figshare.com/files/336637"], "description"=>"<div><p>A stringent control of homeostasis is critical for functional maintenance and survival of neurons. In the mammalian retina, the basic motif leucine zipper transcription factor NRL determines rod versus cone photoreceptor cell fate and activates the expression of many rod-specific genes. Here, we report an integrated analysis of NRL-centered gene regulatory network by coupling chromatin immunoprecipitation followed by high-throughput sequencing (ChIP–Seq) data from Illumina and ABI platforms with global expression profiling and <em>in vivo</em> knockdown studies. We identified approximately 300 direct NRL target genes. Of these, 22 NRL targets are associated with human retinal dystrophies, whereas 95 mapped to regions of as yet uncloned retinal disease loci. <em>In silico</em> analysis of NRL ChIP–Seq peak sequences revealed an enrichment of distinct sets of transcription factor binding sites. Specifically, we discovered that genes involved in photoreceptor function include binding sites for both NRL and homeodomain protein CRX. Evaluation of 26 ChIP–Seq regions validated their enhancer functions in reporter assays. <em>In vivo</em> knockdown of 16 NRL target genes resulted in death or abnormal morphology of rod photoreceptors, suggesting their importance in maintaining retinal function. We also identified histone demethylase Kdm5b as a novel secondary node in NRL transcriptional hierarchy. Exon array analysis of flow-sorted photoreceptors in which <em>Kdm5b</em> was knocked down by shRNA indicated its role in regulating rod-expressed genes. Our studies identify candidate genes for retinal dystrophies, define <em>cis</em>-regulatory module(s) for photoreceptor-expressed genes and provide a framework for decoding transcriptional regulatory networks that dictate rod homeostasis.</p> </div>", "links"=>[], "tags"=>["transcriptional", "photoreceptor", "homeostasis", "revealed", "nrl", "targetome"], "article_id"=>126484, "categories"=>["Biotechnology", "Biochemistry", "Developmental Biology", "Medicine", "Biological Sciences", "Neuroscience", "Genetics"], "users"=>["Hong Hao", "Douglas S. Kim", "Bernward Klocke", "Kory R. Johnson", "Kairong Cui", "Norimoto Gotoh", "Chongzhi Zang", "Janina Gregorski", "Linn Gieser", "Weiqun Peng", "Yang Fann", "Martin Seifert", "Keji Zhao", "Anand Swaroop"], "doi"=>["https://dx.doi.org/10.1371/journal.pgen.1002649.s001", "https://dx.doi.org/10.1371/journal.pgen.1002649.s002", "https://dx.doi.org/10.1371/journal.pgen.1002649.s003", "https://dx.doi.org/10.1371/journal.pgen.1002649.s004", "https://dx.doi.org/10.1371/journal.pgen.1002649.s005", "https://dx.doi.org/10.1371/journal.pgen.1002649.s006", "https://dx.doi.org/10.1371/journal.pgen.1002649.s007", "https://dx.doi.org/10.1371/journal.pgen.1002649.s008", "https://dx.doi.org/10.1371/journal.pgen.1002649.s009", "https://dx.doi.org/10.1371/journal.pgen.1002649.s010", "https://dx.doi.org/10.1371/journal.pgen.1002649.s011"], "stats"=>{"downloads"=>23, "page_views"=>37, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Transcriptional_Regulation_of_Rod_Photoreceptor_Homeostasis_Revealed_by_In_Vivo_NRL_Targetome_Analysis/126484", "title"=>"Transcriptional Regulation of Rod Photoreceptor Homeostasis Revealed by <em>In Vivo</em> NRL Targetome Analysis", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2012-04-12 01:48:04"}
  • {"files"=>["https://ndownloader.figshare.com/files/654522"], "description"=>"<p>(A) Identification of direct NRL transcriptional target genes by ChIP–Seq and transcription profiling. ABI ChIP–Seq peaks and Illumina ChIP–Seq peaks were assigned to the nearest genes (ABI and Illumina). Transcriptional profiling of flow-sorted photoreceptors of WT or <i>Nrl</i><sup>−/−</sup> mice was generated using microarrays. Up: genes up-regulated in <i>Nrl</i><sup>−/−</sup> photoreceptors. Down: genes down-regulated in <i>Nrl</i><sup>−/−</sup> photoreceptors. (B) Correlation of NRL ChIP–Seq peaks to the promoters of its target genes. The number of correlation (y-axis) was plotted to the distance (x-axis) of ABI ChIP–Seq peaks (green graph) or Illumina ChIP–Seq peaks (blue graph) to the promoters of the genes that were down-regulated (top) or up-regulated (bottom) in the <i>Nrl</i><sup>−/−</sup> photoreceptors. (C) TF enrichment and TF binding site (TFBS) positional bias analysis. NRL ChIP–Seq peak regions were analyzed for TF enrichment using Genomatix RegionMiner. The positional bias of TFBS (P) was calculated and plotted as −log(P) (y-axis) to the distance of TFBS to the peak center (x-axis). Positions where TFBS are overrepresented appear as peaks in these plots. * significantly enriched. (D) Correlation of NRL ChIP–Seq peaks with CRX ChIP–Seq peaks. The number of correlation (y-axis) was plotted to the distance of NRL ChIP–Seq peaks to CRX ChIP–Seq peaks (x-axis). The Venn diagram (inset) calculated the percentage of NRL ChIP–Seq peaks (Illumina and ABI) within 500 bp of CRX peaks: 65% of Illumina peaks and 48% of ABI peaks are within 500 bp of CRX peaks.</p>", "links"=>[], "tags"=>["nrl", "genes", "co-regulatory", "transcription", "factors", "transcriptional"], "article_id"=>324990, "categories"=>["Biotechnology", "Biochemistry", "Developmental Biology", "Medicine", "Biological Sciences", "Neuroscience", "Genetics"], "users"=>["Hong Hao", "Douglas S. Kim", "Bernward Klocke", "Kory R. Johnson", "Kairong Cui", "Norimoto Gotoh", "Chongzhi Zang", "Janina Gregorski", "Linn Gieser", "Weiqun Peng", "Yang Fann", "Martin Seifert", "Keji Zhao", "Anand Swaroop"], "doi"=>"https://dx.doi.org/10.1371/journal.pgen.1002649.g002", "stats"=>{"downloads"=>0, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Identification_of_NRL_target_genes_and_co_regulatory_transcription_factors_by_ChIP_8211_Seq_and_transcriptional_profiling_/324990", "title"=>"Identification of NRL target genes and co-regulatory transcription factors by ChIP–Seq and transcriptional profiling.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-04-12 01:23:10"}
  • {"files"=>["https://ndownloader.figshare.com/files/655868"], "description"=>"<p>ChIP–Seq libraries were prepared according to manufacture's instructions and sequenced by Illumina 1G Genome Analyzer or ABI/SOLiD platform. Uniquely mapped reads: reads mapped to unique genomic locations.</p>", "links"=>[], "tags"=>["peaks", "illumina"], "article_id"=>326351, "categories"=>["Biotechnology", "Biochemistry", "Developmental Biology", "Medicine", "Biological Sciences", "Neuroscience", "Genetics"], "users"=>["Hong Hao", "Douglas S. Kim", "Bernward Klocke", "Kory R. Johnson", "Kairong Cui", "Norimoto Gotoh", "Chongzhi Zang", "Janina Gregorski", "Linn Gieser", "Weiqun Peng", "Yang Fann", "Martin Seifert", "Keji Zhao", "Anand Swaroop"], "doi"=>"https://dx.doi.org/10.1371/journal.pgen.1002649.t001", "stats"=>{"downloads"=>5, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Comparison_of_ChIP_8211_Seq_peaks_by_Illumina_and_ABI_/326351", "title"=>"Comparison of ChIP–Seq peaks by Illumina and ABI.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-04-12 01:45:51"}
  • {"files"=>["https://ndownloader.figshare.com/files/654696"], "description"=>"<p>NRL and CRX ChIP–Seq peaks for known and novel NRL target genes were visualized with the UCSC genome browser. NRL peaks (in blue), IgG peaks (in black) and CRX peaks (in black) represent the numbers of sequence tags detected at each location and the numbers are the peak-summit count. Exon (Black box) and intron (black line) structure are shown below peaks. Species conservation is shown at the bottom. NRL_ABI and NRL_Illumina: NRL ChIP–Seq using ABI sequencing platform and illumina sequencing platform, respectively. IgG_ABI and IgG_Illumina: IgG control ChIP–Seq using ABI sequencing platform and illumina sequencing platform, respectively. CRX_1 and CRX_2: duplicate CRX ChIP–Seq data using Illumina sequencing platform.</p>", "links"=>[], "tags"=>["nrl", "peaks", "crx"], "article_id"=>325170, "categories"=>["Biotechnology", "Biochemistry", "Developmental Biology", "Medicine", "Biological Sciences", "Neuroscience", "Genetics"], "users"=>["Hong Hao", "Douglas S. Kim", "Bernward Klocke", "Kory R. Johnson", "Kairong Cui", "Norimoto Gotoh", "Chongzhi Zang", "Janina Gregorski", "Linn Gieser", "Weiqun Peng", "Yang Fann", "Martin Seifert", "Keji Zhao", "Anand Swaroop"], "doi"=>"https://dx.doi.org/10.1371/journal.pgen.1002649.g003", "stats"=>{"downloads"=>1, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Visualization_of_NRL_ChIP_8211_Seq_peaks_and_CRX_ChIP_8211_Seq_peaks_/325170", "title"=>"Visualization of NRL ChIP–Seq peaks and CRX ChIP–Seq peaks.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-04-12 01:26:10"}
  • {"files"=>["https://ndownloader.figshare.com/files/655816"], "description"=>"<p>ChIP–Seq peaks were identified using MACS with p<10<sup>−6</sup> or NGS-Analyzer (Genomatix) with p<10<sup>−3</sup>.</p>", "links"=>[], "tags"=>["peaks", "illumina"], "article_id"=>326295, "categories"=>["Biotechnology", "Biochemistry", "Developmental Biology", "Medicine", "Biological Sciences", "Neuroscience", "Genetics"], "users"=>["Hong Hao", "Douglas S. Kim", "Bernward Klocke", "Kory R. Johnson", "Kairong Cui", "Norimoto Gotoh", "Chongzhi Zang", "Janina Gregorski", "Linn Gieser", "Weiqun Peng", "Yang Fann", "Martin Seifert", "Keji Zhao", "Anand Swaroop"], "doi"=>"https://dx.doi.org/10.1371/journal.pgen.1002649.t002", "stats"=>{"downloads"=>1, "page_views"=>66, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Comparison_of_ChIP_8211_Seq_peaks_by_Illumina_and_ABI_/326295", "title"=>"Comparison of ChIP–Seq peaks by Illumina and ABI.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-04-12 01:44:55"}
  • {"files"=>["https://ndownloader.figshare.com/files/655688"], "description"=>"<p>NRL acts synergistically with photoreceptor-specific transcription factors (such as CRX) and regulates the expression of rod and cone genes. Thin lines denote expression-based links, the dashed lines indicate links based on ChIP assays, and thick lines denote confirmed regulatory connections.</p>", "links"=>[], "tags"=>["simplified", "cone"], "article_id"=>326162, "categories"=>["Biotechnology", "Biochemistry", "Developmental Biology", "Medicine", "Biological Sciences", "Neuroscience", "Genetics"], "users"=>["Hong Hao", "Douglas S. Kim", "Bernward Klocke", "Kory R. Johnson", "Kairong Cui", "Norimoto Gotoh", "Chongzhi Zang", "Janina Gregorski", "Linn Gieser", "Weiqun Peng", "Yang Fann", "Martin Seifert", "Keji Zhao", "Anand Swaroop"], "doi"=>"https://dx.doi.org/10.1371/journal.pgen.1002649.g009", "stats"=>{"downloads"=>1, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_A_simplified_gene_regulatory_network_in_rod_and_cone_photoreceptors_/326162", "title"=>"A simplified gene regulatory network in rod and cone photoreceptors.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-04-12 01:42:42"}

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  • {"unique-ip"=>"18", "full-text"=>"24", "pdf"=>"2", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"5", "supp-data"=>"2", "cited-by"=>"0", "year"=>"2019", "month"=>"5"}

Relative Metric

{"start_date"=>"2012-01-01T00:00:00Z", "end_date"=>"2012-12-31T00:00:00Z", "subject_areas"=>[{"subject_area"=>"/Biology and life sciences", "average_usage"=>[322, 550, 671, 773, 864, 955, 1048, 1135, 1223, 1308, 1387, 1465, 1534, 1602, 1673, 1744, 1813, 1885, 1955, 2026, 2093, 2160, 2228, 2290, 2349]}, {"subject_area"=>"/Biology and life sciences/Anatomy", "average_usage"=>[308, 530, 649, 751, 844, 933, 1021, 1107, 1194, 1277, 1357, 1426, 1501, 1572, 1634, 1702, 1768, 1838, 1910, 1976, 2046, 2114, 2181, 2241, 2298]}, {"subject_area"=>"/Biology and life sciences/Anatomy and physiology", "average_usage"=>[307, 540, 660, 756, 847, 936, 1025, 1111, 1199, 1282, 1361, 1432]}, {"subject_area"=>"/Biology and life sciences/Biochemistry", "average_usage"=>[316, 541, 663, 766, 856, 950, 1041, 1128, 1218, 1302, 1382, 1456, 1526, 1593, 1657, 1729, 1796, 1862, 1930, 1999, 2065, 2132, 2202, 2261, 2319]}, {"subject_area"=>"/Biology and life sciences/Cell biology", "average_usage"=>[319, 556, 679, 785, 881, 970, 1062, 1149, 1236, 1323, 1402, 1474, 1545, 1617, 1681, 1754, 1822, 1892, 1963, 2031, 2099, 2165, 2233, 2299, 2359]}, {"subject_area"=>"/Biology and life sciences/Genetics", "average_usage"=>[333, 576, 707, 814, 908, 1004, 1104, 1197, 1280, 1370, 1449, 1531, 1603, 1673, 1742, 1817, 1886, 1954, 2025, 2098, 2171, 2234, 2304, 2365, 2431]}, {"subject_area"=>"/Medicine and health sciences", "average_usage"=>[312, 547, 668, 769, 861, 953, 1046, 1135, 1224, 1307, 1388, 1464, 1536, 1606, 1676, 1744, 1812, 1882, 1954, 2020, 2089, 2155, 2218, 2282, 2344]}, {"subject_area"=>"/Medicine and health sciences/Anatomy", "average_usage"=>[307, 529, 649, 751, 845, 936, 1025, 1113, 1197, 1284, 1360, 1432, 1501, 1570, 1632, 1697, 1765, 1834, 1904, 1972, 2041, 2107, 2170, 2231, 2292]}]}
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