Plant Regulomics: a data‐driven interface for retrieving upstream regulators from plant multi‐omics data

Summary High‐throughput technology has become a powerful approach for routine plant research. Interpreting the biological significance of high‐throughput data has largely focused on the functional characterization of a large gene list or genomic loci that involves the following two aspects: the func...

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Veröffentlicht in:The Plant journal : for cell and molecular biology 2020-01, Vol.101 (1), p.237-248
Hauptverfasser: Ran, Xiaojuan, Zhao, Fei, Wang, Yuejun, Liu, Jian, Zhuang, Yili, Ye, Luhuan, Qi, Meifang, Cheng, Jingfei, Zhang, Yijing
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container_issue 1
container_start_page 237
container_title The Plant journal : for cell and molecular biology
container_volume 101
creator Ran, Xiaojuan
Zhao, Fei
Wang, Yuejun
Liu, Jian
Zhuang, Yili
Ye, Luhuan
Qi, Meifang
Cheng, Jingfei
Zhang, Yijing
description Summary High‐throughput technology has become a powerful approach for routine plant research. Interpreting the biological significance of high‐throughput data has largely focused on the functional characterization of a large gene list or genomic loci that involves the following two aspects: the functions of the genes or loci and how they are regulated as a whole, i.e. searching for the upstream regulators. Traditional platforms for functional annotation largely help resolving the first issue. Addressing the second issue is essential for a global understanding of the regulatory mechanism, but is more challenging, and requires additional high‐throughput experimental evidence and a unified statistical framework for data‐mining. The rapid accumulation of ’omics data provides a large amount of experimental data. We here present Plant Regulomics, an interface that integrates 19 925 transcriptomic and epigenomic data sets and diverse sources of functional evidence (58 112 terms and 695 414 protein−protein interactions) from six plant species along with the orthologous genes from 56 whole‐genome sequenced plant species. All pair‐wise transcriptomic comparisons with biological significance within the same study were performed, and all epigenomic data were processed to genomic loci targeted by various factors. These data were well organized to gene modules and loci lists, which were further implemented into the same statistical framework. For any input gene list or genomic loci, Plant Regulomics retrieves the upstream factors, treatments, and experimental/environmental conditions regulating the input from the integrated ’omics data. Additionally, multiple tools and an interactive visualization are available through a user‐friendly web interface. Plant Regulomics is available at http://bioinfo.sibs.ac.cn/plant-regulomics. Significance Statement Plant Regulomics is a data‐driven interface for deciphering the upstream regulators of genes and genomic loci, this is achieved via systematic integration of epigenomic and transcriptomic data from 62 plant species, which were further unified into the same statistical framework. For any input gene list or genomic loci, Plant Regulomics retrieves the upstream factors, treatments, and experimental/environmental conditions regulating the input, providing useful resources and tools for data‐mining and hypothesis generation from high‐throughput data.
doi_str_mv 10.1111/tpj.14526
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Interpreting the biological significance of high‐throughput data has largely focused on the functional characterization of a large gene list or genomic loci that involves the following two aspects: the functions of the genes or loci and how they are regulated as a whole, i.e. searching for the upstream regulators. Traditional platforms for functional annotation largely help resolving the first issue. Addressing the second issue is essential for a global understanding of the regulatory mechanism, but is more challenging, and requires additional high‐throughput experimental evidence and a unified statistical framework for data‐mining. The rapid accumulation of ’omics data provides a large amount of experimental data. We here present Plant Regulomics, an interface that integrates 19 925 transcriptomic and epigenomic data sets and diverse sources of functional evidence (58 112 terms and 695 414 protein−protein interactions) from six plant species along with the orthologous genes from 56 whole‐genome sequenced plant species. All pair‐wise transcriptomic comparisons with biological significance within the same study were performed, and all epigenomic data were processed to genomic loci targeted by various factors. These data were well organized to gene modules and loci lists, which were further implemented into the same statistical framework. For any input gene list or genomic loci, Plant Regulomics retrieves the upstream factors, treatments, and experimental/environmental conditions regulating the input from the integrated ’omics data. Additionally, multiple tools and an interactive visualization are available through a user‐friendly web interface. Plant Regulomics is available at http://bioinfo.sibs.ac.cn/plant-regulomics. Significance Statement Plant Regulomics is a data‐driven interface for deciphering the upstream regulators of genes and genomic loci, this is achieved via systematic integration of epigenomic and transcriptomic data from 62 plant species, which were further unified into the same statistical framework. For any input gene list or genomic loci, Plant Regulomics retrieves the upstream factors, treatments, and experimental/environmental conditions regulating the input, providing useful resources and tools for data‐mining and hypothesis generation from high‐throughput data.</description><identifier>ISSN: 0960-7412</identifier><identifier>EISSN: 1365-313X</identifier><identifier>DOI: 10.1111/tpj.14526</identifier><identifier>PMID: 31494994</identifier><language>eng</language><publisher>England: Blackwell Publishing Ltd</publisher><subject>Annotations ; Data mining ; data‐driven ; Environmental conditions ; Environmental regulations ; Flowers &amp; plants ; Gene loci ; Genes ; Genomes ; interface ; omics data ; Plant Regulomics ; Plant species ; Protein interaction ; Proteins ; Regulatory mechanisms (biology) ; Statistics ; technical advance ; upstream regulators</subject><ispartof>The Plant journal : for cell and molecular biology, 2020-01, Vol.101 (1), p.237-248</ispartof><rights>2019 The Authors The Plant Journal © 2019 John Wiley &amp; Sons Ltd</rights><rights>2019 The Authors The Plant Journal © 2019 John Wiley &amp; Sons Ltd.</rights><rights>Copyright © 2020 John Wiley &amp; Sons Ltd and the Society for Experimental Biology</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3886-509636f944929fbc0c609274cb29ecfb1c87e7cff8aa00e61e6adc9336f064693</citedby><cites>FETCH-LOGICAL-c3886-509636f944929fbc0c609274cb29ecfb1c87e7cff8aa00e61e6adc9336f064693</cites><orcidid>0000-0001-9568-9389</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1111%2Ftpj.14526$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1111%2Ftpj.14526$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,780,784,1417,1433,27924,27925,45574,45575,46409,46833</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/31494994$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Ran, Xiaojuan</creatorcontrib><creatorcontrib>Zhao, Fei</creatorcontrib><creatorcontrib>Wang, Yuejun</creatorcontrib><creatorcontrib>Liu, Jian</creatorcontrib><creatorcontrib>Zhuang, Yili</creatorcontrib><creatorcontrib>Ye, Luhuan</creatorcontrib><creatorcontrib>Qi, Meifang</creatorcontrib><creatorcontrib>Cheng, Jingfei</creatorcontrib><creatorcontrib>Zhang, Yijing</creatorcontrib><title>Plant Regulomics: a data‐driven interface for retrieving upstream regulators from plant multi‐omics data</title><title>The Plant journal : for cell and molecular biology</title><addtitle>Plant J</addtitle><description>Summary High‐throughput technology has become a powerful approach for routine plant research. Interpreting the biological significance of high‐throughput data has largely focused on the functional characterization of a large gene list or genomic loci that involves the following two aspects: the functions of the genes or loci and how they are regulated as a whole, i.e. searching for the upstream regulators. Traditional platforms for functional annotation largely help resolving the first issue. Addressing the second issue is essential for a global understanding of the regulatory mechanism, but is more challenging, and requires additional high‐throughput experimental evidence and a unified statistical framework for data‐mining. The rapid accumulation of ’omics data provides a large amount of experimental data. We here present Plant Regulomics, an interface that integrates 19 925 transcriptomic and epigenomic data sets and diverse sources of functional evidence (58 112 terms and 695 414 protein−protein interactions) from six plant species along with the orthologous genes from 56 whole‐genome sequenced plant species. All pair‐wise transcriptomic comparisons with biological significance within the same study were performed, and all epigenomic data were processed to genomic loci targeted by various factors. These data were well organized to gene modules and loci lists, which were further implemented into the same statistical framework. For any input gene list or genomic loci, Plant Regulomics retrieves the upstream factors, treatments, and experimental/environmental conditions regulating the input from the integrated ’omics data. Additionally, multiple tools and an interactive visualization are available through a user‐friendly web interface. Plant Regulomics is available at http://bioinfo.sibs.ac.cn/plant-regulomics. Significance Statement Plant Regulomics is a data‐driven interface for deciphering the upstream regulators of genes and genomic loci, this is achieved via systematic integration of epigenomic and transcriptomic data from 62 plant species, which were further unified into the same statistical framework. 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subjects Annotations
Data mining
data‐driven
Environmental conditions
Environmental regulations
Flowers & plants
Gene loci
Genes
Genomes
interface
omics data
Plant Regulomics
Plant species
Protein interaction
Proteins
Regulatory mechanisms (biology)
Statistics
technical advance
upstream regulators
title Plant Regulomics: a data‐driven interface for retrieving upstream regulators from plant multi‐omics data
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