Literature DB >> 20668062

The association of multiple interacting genes with specific phenotypes in rice using gene coexpression networks.

Stephen P Ficklin1, Feng Luo, F Alex Feltus.   

Abstract

Discovering gene sets underlying the expression of a given phenotype is of great importance, as many phenotypes are the result of complex gene-gene interactions. Gene coexpression networks, built using a set of microarray samples as input, can help elucidate tightly coexpressed gene sets (modules) that are mixed with genes of known and unknown function. Functional enrichment analysis of modules further subdivides the coexpressed gene set into cofunctional gene clusters that may coexist in the module with other functionally related gene clusters. In this study, 45 coexpressed gene modules and 76 cofunctional gene clusters were discovered for rice (Oryza sativa) using a global, knowledge-independent paradigm and the combination of two network construction methodologies. Some clusters were enriched for previously characterized mutant phenotypes, providing evidence for specific gene sets (and their annotated molecular functions) that underlie specific phenotypes.

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Year:  2010        PMID: 20668062      PMCID: PMC2938148          DOI: 10.1104/pp.110.159459

Source DB:  PubMed          Journal:  Plant Physiol        ISSN: 0032-0889            Impact factor:   8.340


  45 in total

Review 1.  Network biology: understanding the cell's functional organization.

Authors:  Albert-László Barabási; Zoltán N Oltvai
Journal:  Nat Rev Genet       Date:  2004-02       Impact factor: 53.242

2.  Hierarchical organization of modularity in metabolic networks.

Authors:  E Ravasz; A L Somera; D A Mongru; Z N Oltvai; A L Barabási
Journal:  Science       Date:  2002-08-30       Impact factor: 47.728

3.  From single genes to co-expression networks: extracting knowledge from barley functional genomics.

Authors:  P Faccioli; P Provero; C Herrmann; A M Stanca; C Morcia; V Terzi
Journal:  Plant Mol Biol       Date:  2005-07       Impact factor: 4.076

4.  Identifying biological themes within lists of genes with EASE.

Authors:  Douglas A Hosack; Glynn Dennis; Brad T Sherman; H Clifford Lane; Richard A Lempicki
Journal:  Genome Biol       Date:  2003-09-11       Impact factor: 13.583

5.  RiceArrayNet: a database for correlating gene expression from transcriptome profiling, and its application to the analysis of coexpressed genes in rice.

Authors:  Tae-Ho Lee; Yeon-Ki Kim; Thu Thi Minh Pham; Sang Ik Song; Ju-Kon Kim; Kyu Young Kang; Gynheung An; Ki-Hong Jung; David W Galbraith; Minkyun Kim; Ung-Han Yoon; Baek Hie Nahm
Journal:  Plant Physiol       Date:  2009-07-15       Impact factor: 8.340

Review 6.  Identification of cis-regulatory elements in gene co-expression networks using A-GLAM.

Authors:  Leonardo Mariño-Ramírez; Kannan Tharakaraman; Olivier Bodenreider; John Spouge; David Landsman
Journal:  Methods Mol Biol       Date:  2009

7.  Large-scale analysis of Arabidopsis transcription reveals a basal co-regulation network.

Authors:  Osnat Atias; Benny Chor; Daniel A Chamovitz
Journal:  BMC Syst Biol       Date:  2009-09-03

8.  Systematic survey reveals general applicability of "guilt-by-association" within gene coexpression networks.

Authors:  Cecily J Wolfe; Isaac S Kohane; Atul J Butte
Journal:  BMC Bioinformatics       Date:  2005-09-14       Impact factor: 3.169

9.  ATTED-II provides coexpressed gene networks for Arabidopsis.

Authors:  Takeshi Obayashi; Shinpei Hayashi; Motoshi Saeki; Hiroyuki Ohta; Kengo Kinoshita
Journal:  Nucleic Acids Res       Date:  2008-10-25       Impact factor: 16.971

10.  High-throughput functional annotation and data mining with the Blast2GO suite.

Authors:  Stefan Götz; Juan Miguel García-Gómez; Javier Terol; Tim D Williams; Shivashankar H Nagaraj; María José Nueda; Montserrat Robles; Manuel Talón; Joaquín Dopazo; Ana Conesa
Journal:  Nucleic Acids Res       Date:  2008-04-29       Impact factor: 16.971

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  44 in total

1.  Identification of altered metabolic pathways of γ-irradiated rice mutant via network-based transcriptome analysis.

Authors:  Sun-Goo Hwang; Dong Sub Kim; Jung Eun Hwang; Hyeon Mi Park; Cheol Seong Jang
Journal:  Genetica       Date:  2015-09-11       Impact factor: 1.082

2.  Coexpression network analysis associated with call of rice seedlings for encountering heat stress.

Authors:  Neelam K Sarkar; Yeon-Ki Kim; Anil Grover
Journal:  Plant Mol Biol       Date:  2013-08-24       Impact factor: 4.076

3.  PlaNet: combined sequence and expression comparisons across plant networks derived from seven species.

Authors:  Marek Mutwil; Sebastian Klie; Takayuki Tohge; Federico M Giorgi; Olivia Wilkins; Malcolm M Campbell; Alisdair R Fernie; Björn Usadel; Zoran Nikoloski; Staffan Persson
Journal:  Plant Cell       Date:  2011-03-25       Impact factor: 11.277

4.  Gene coexpression network alignment and conservation of gene modules between two grass species: maize and rice.

Authors:  Stephen P Ficklin; F Alex Feltus
Journal:  Plant Physiol       Date:  2011-05-23       Impact factor: 8.340

5.  Maize source leaf adaptation to nitrogen deficiency affects not only nitrogen and carbon metabolism but also control of phosphate homeostasis.

Authors:  Urte Schlüter; Martin Mascher; Christian Colmsee; Uwe Scholz; Andrea Bräutigam; Holger Fahnenstich; Uwe Sonnewald
Journal:  Plant Physiol       Date:  2012-09-12       Impact factor: 8.340

6.  Suppressive effect of microRNA319 expression on rice plant height.

Authors:  Wei-Ting Liu; Peng-Wen Chen; Li-Chi Chen; Chia-Chun Yang; Shu-Yun Chen; GuanFu Huang; Tzu Che Lin; Hsin-Mei Ku; Jeremy J W Chen
Journal:  Theor Appl Genet       Date:  2017-05-03       Impact factor: 5.699

7.  Genetic dissection of the biotic stress response using a genome-scale gene network for rice.

Authors:  Insuk Lee; Young-Su Seo; Dusica Coltrane; Sohyun Hwang; Taeyun Oh; Edward M Marcotte; Pamela C Ronald
Journal:  Proc Natl Acad Sci U S A       Date:  2011-10-31       Impact factor: 11.205

8.  A developmental transcriptional network for maize defines coexpression modules.

Authors:  Gregory S Downs; Yong-Mei Bi; Joseph Colasanti; Wenqing Wu; Xi Chen; Tong Zhu; Steven J Rothstein; Lewis N Lukens
Journal:  Plant Physiol       Date:  2013-02-06       Impact factor: 8.340

9.  Inference of Longevity-Related Genes from a Robust Coexpression Network of Seed Maturation Identifies Regulators Linking Seed Storability to Biotic Defense-Related Pathways.

Authors:  Karima Righetti; Joseph Ly Vu; Sandra Pelletier; Benoit Ly Vu; Enrico Glaab; David Lalanne; Asher Pasha; Rohan V Patel; Nicholas J Provart; Jerome Verdier; Olivier Leprince; Julia Buitink
Journal:  Plant Cell       Date:  2015-09-26       Impact factor: 11.277

10.  Coexpression network revealing the plasticity and robustness of population transcriptome during the initial stage of domesticating energy crop Miscanthus lutarioriparius.

Authors:  Shilai Xing; Chengcheng Tao; Zhihong Song; Wei Liu; Juan Yan; Lifang Kang; Cong Lin; Tao Sang
Journal:  Plant Mol Biol       Date:  2018-07-13       Impact factor: 4.076

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