Blog
About

8
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      NetMiner-an ensemble pipeline for building genome-wide and high-quality gene co-expression network using massive-scale RNA-seq samples

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Accurately reconstructing gene co-expression network is of great importance for uncovering the genetic architecture underlying complex and various phenotypes. The recent availability of high-throughput RNA-seq sequencing has made genome-wide detecting and quantifying of the novel, rare and low-abundance transcripts practical. However, its potential merits in reconstructing gene co-expression network have still not been well explored. Using massive-scale RNA-seq samples, we have designed an ensemble pipeline, called NetMiner, for building genome-scale and high-quality Gene Co-expression Network (GCN) by integrating three frequently used inference algorithms. We constructed a RNA-seq-based GCN in one species of monocot rice. The quality of network obtained by our method was verified and evaluated by the curated gene functional association data sets, which obviously outperformed each single method. In addition, the powerful capability of network for associating genes with functions and agronomic traits was shown by enrichment analysis and case studies. In particular, we demonstrated the potential value of our proposed method to predict the biological roles of unknown protein-coding genes, long non-coding RNA (lncRNA) genes and circular RNA (circRNA) genes. Our results provided a valuable and highly reliable data source to select key candidate genes for subsequent experimental validation. To facilitate identification of novel genes regulating important biological processes and phenotypes in other plants or animals, we have published the source code of NetMiner, making it freely available at https://github.com/czllab/NetMiner.

          Related collections

          Most cited references 43

          • Record: found
          • Abstract: found
          • Article: not found

          Integration of biological networks and gene expression data using Cytoscape.

          Cytoscape is a free software package for visualizing, modeling and analyzing molecular and genetic interaction networks. This protocol explains how to use Cytoscape to analyze the results of mRNA expression profiling, and other functional genomics and proteomics experiments, in the context of an interaction network obtained for genes of interest. Five major steps are described: (i) obtaining a gene or protein network, (ii) displaying the network using layout algorithms, (iii) integrating with gene expression and other functional attributes, (iv) identifying putative complexes and functional modules and (v) identifying enriched Gene Ontology annotations in the network. These steps provide a broad sample of the types of analyses performed by Cytoscape.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            A gene-coexpression network for global discovery of conserved genetic modules.

            To elucidate gene function on a global scale, we identified pairs of genes that are coexpressed over 3182 DNA microarrays from humans, flies, worms, and yeast. We found 22,163 such coexpression relationships, each of which has been conserved across evolution. This conservation implies that the coexpression of these gene pairs confers a selective advantage and therefore that these genes are functionally related. Many of these relationships provide strong evidence for the involvement of new genes in core biological functions such as the cell cycle, secretion, and protein expression. We experimentally confirmed the predictions implied by some of these links and identified cell proliferation functions for several genes. By assembling these links into a gene-coexpression network, we found several components that were animal-specific as well as interrelationships between newly evolved and ancient modules.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              PlantTFDB 3.0: a portal for the functional and evolutionary study of plant transcription factors

              With the aim to provide a resource for functional and evolutionary study of plant transcription factors (TFs), we updated the plant TF database PlantTFDB to version 3.0 (http://planttfdb.cbi.pku.edu.cn). After refining the TF classification pipeline, we systematically identified 129 288 TFs from 83 species, of which 67 species have genome sequences, covering main lineages of green plants. Besides the abundant annotation provided in the previous version, we generated more annotations for identified TFs, including expression, regulation, interaction, conserved elements, phenotype information, expert-curated descriptions derived from UniProt, TAIR and NCBI GeneRIF, as well as references to provide clues for functional studies of TFs. To help identify evolutionary relationship among identified TFs, we assigned 69 450 TFs into 3924 orthologous groups, and constructed 9217 phylogenetic trees for TFs within the same families or same orthologous groups, respectively. In addition, we set up a TF prediction server in this version for users to identify TFs from their own sequences.
                Bookmark

                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SoftwareRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – original draft
                Role: Writing – review & editing
                Role: Writing – review & editing
                Role: Writing – review & editing
                Role: Writing – review & editing
                Role: Funding acquisitionRole: Supervision
                Role: Funding acquisitionRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                9 February 2018
                2018
                : 13
                : 2
                Affiliations
                [1 ] Nantong Medical College and School of Pharmacy, Nantong University, Nantong, China
                [2 ] State Key Laboratory of Plant Genomics, Institute of Genetic and Developmental Biology, Chinese Academy of Sciences, Beijing, China
                [3 ] University of Chinese Academy of Sciences, Beijing, China
                [4 ] Nantong Polytechnic College, Nantong, China
                Kunming University of Science and Technology, CHINA
                Author notes

                Competing Interests: The authors declare no competing financial interests.

                [¤]

                Current address: Institute of Reproductive Medicine, Nantong Medical College and School of Pharmacy, Nantong University, Nantong, China

                Article
                PONE-D-17-30744
                10.1371/journal.pone.0192613
                5806890
                29425247
                © 2018 Yu et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                Page count
                Figures: 6, Tables: 1, Pages: 23
                Product
                Funding
                Funded by: The Strategic Priority Research Program of the Chinese Academy of Sciences
                Award ID: XDA08020302
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;
                Award ID: 21402101
                Award Recipient :
                Our work is financially supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (Grant No. XDA08020302) and National Natural Science Foundation of China (Grant No. 21402101). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Genetics
                Gene Identification and Analysis
                Genetic Networks
                Computer and Information Sciences
                Network Analysis
                Genetic Networks
                Biology and Life Sciences
                Organisms
                Eukaryota
                Plants
                Grasses
                Rice
                Research and Analysis Methods
                Experimental Organism Systems
                Plant and Algal Models
                Rice
                Biology and Life Sciences
                Computational Biology
                Gene Regulatory Networks
                Biology and Life Sciences
                Genetics
                Gene Regulatory Networks
                Biology and life sciences
                Biochemistry
                Nucleic acids
                RNA
                Non-coding RNA
                Long non-coding RNAs
                Research and Analysis Methods
                Experimental Organism Systems
                Model Organisms
                Arabidopsis Thaliana
                Research and Analysis Methods
                Model Organisms
                Arabidopsis Thaliana
                Biology and Life Sciences
                Organisms
                Eukaryota
                Plants
                Brassica
                Arabidopsis Thaliana
                Research and Analysis Methods
                Experimental Organism Systems
                Plant and Algal Models
                Arabidopsis Thaliana
                Biology and Life Sciences
                Genetics
                Gene Expression
                Biology and Life Sciences
                Agriculture
                Agronomy
                Biology and Life Sciences
                Cell Biology
                Cell Processes
                Cell Cycle and Cell Division
                Custom metadata
                All relevant data are within the paper and its Supporting Information files.

                Uncategorized

                Comments

                Comment on this article