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Consensus Coexpression Network Analysis Identifies Key Regulators of Flower and Fruit Development in Wild Strawberry.
Shahan, Rachel; Zawora, Christopher; Wight, Haley; Sittmann, John; Wang, Wanpeng; Mount, Stephen M; Liu, Zhongchi.
Afiliação
  • Shahan R; Department of Cell Biology and Molecular Genetics, University of Maryland, College Park, Maryland 20742.
  • Zawora C; Department of Cell Biology and Molecular Genetics, University of Maryland, College Park, Maryland 20742.
  • Wight H; Department of Cell Biology and Molecular Genetics, University of Maryland, College Park, Maryland 20742.
  • Sittmann J; Department of Cell Biology and Molecular Genetics, University of Maryland, College Park, Maryland 20742.
  • Wang W; Department of Cell Biology and Molecular Genetics, University of Maryland, College Park, Maryland 20742.
  • Mount SM; Department of Cell Biology and Molecular Genetics, University of Maryland, College Park, Maryland 20742.
  • Liu Z; Department of Cell Biology and Molecular Genetics, University of Maryland, College Park, Maryland 20742 zliu@umd.edu.
Plant Physiol ; 178(1): 202-216, 2018 09.
Article em En | MEDLINE | ID: mdl-29991484
The diploid strawberry, Fragaria vesca, is a developing model system for the economically important Rosaceae family. Strawberry fleshy fruit develops from the floral receptacle and its ripening is nonclimacteric. The external seed configuration of strawberry fruit facilitates the study of seed-to-fruit cross tissue communication, particularly phytohormone biosynthesis and transport. To investigate strawberry fruit development, we previously generated spatial and temporal transcriptome data profiling F. vesca flower and fruit development pre- and postfertilization. In this study, we combined 46 of our existing RNA-seq libraries to generate coexpression networks using the Weighted Gene Co-Expression Network Analysis package in R. We then applied a post-hoc consensus clustering approach and used bootstrapping to demonstrate consensus clustering's ability to produce robust and reproducible clusters. Further, we experimentally tested hypotheses based on the networks, including increased iron transport from the receptacle to the seed postfertilization and characterized a F. vesca floral mutant and its candidate gene. To increase their utility, the networks are presented in a web interface (www.fv.rosaceaefruits.org) for easy exploration and identification of coexpressed genes. Together, the work reported here illustrates ways to generate robust networks optimized for the mining of large transcriptome data sets, thereby providing a useful resource for hypothesis generation and experimental design in strawberry and related Rosaceae fruit crops.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Regulação da Expressão Gênica de Plantas / Regulação da Expressão Gênica no Desenvolvimento / Fragaria / Flores / Redes Reguladoras de Genes / Frutas Idioma: En Revista: Plant Physiol Ano de publicação: 2018 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Regulação da Expressão Gênica de Plantas / Regulação da Expressão Gênica no Desenvolvimento / Fragaria / Flores / Redes Reguladoras de Genes / Frutas Idioma: En Revista: Plant Physiol Ano de publicação: 2018 Tipo de documento: Article