BioEnergy Research

, Volume 9, Issue 1, pp 172–180

Genome-Scale Identification of Cell-Wall-Related Genes in Switchgrass through Comparative Genomics and Computational Analyses of Transcriptomic Data

  • Xin Chen
  • Qin Ma
  • Xiaolan Rao
  • Yuhong Tang
  • Yan Wang
  • Gaoyang Li
  • Chi Zhang
  • Xizeng Mao
  • Richard A. Dixon
  • Ying Xu
Article

DOI: 10.1007/s12155-015-9674-2

Cite this article as:
Chen, X., Ma, Q., Rao, X. et al. Bioenerg. Res. (2016) 9: 172. doi:10.1007/s12155-015-9674-2

Abstract

Large numbers of plant cell-wall (CW)-related genes have been identified or predicted in several plant genomes such as Arabidopsis thaliana, Oryza sativa (rice), and Zea mays (maize), as results of intensive studies of these organisms in the past 2 decades. However, no such gene list has been identified in switchgrass (Panicum virgatum), a key bioenergy crop. Here, we present a computational study for prediction of CW genes in switchgrass using a two-step procedure: (i) homology mapping of all annotated CW genes in the fore-mentioned species to switchgrass, giving rise to a total of 991 genes, and (ii) candidate prediction of CW genes based on switchgrass genes co-expressed with the 991 genes under a large number of experimental conditions. Specifically, our co-expression analyses using the 991 genes as seeds led to the identification of 104 large clusters of co-expressed genes, each referred to as a co-expression module (CEM), covering 830 of the 991 genes plus 823 additional genes that are strongly co-expressed with some of the 104 CEMs. These 1653 genes represent our prediction of CW genes in switchgrass, 112 of which are homologous to predicted CW genes in Arabidopsis. Functional inference of these genes is conducted to derive the possible functional relations among these predicted CW genes. Overall, these data may offer a highly useful information source for cell-wall biologists of switchgrass as well as plants in general.

Keywords

Switchgrass Plant cell wall Homology mapping Co-expression analysis 

Supplementary material

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Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  1. 1.College of Computer Science and Technology, and School of Public HealthJilin UniversityChangchunChina
  2. 2.Computational Systems Biology Lab, Department of Biochemistry and Molecular Biology and Institute of BioinformaticsUniversity of GeorgiaAthensUSA
  3. 3.US Department of EnergyBioEnergy Science Center (BESC)Oak RidgeUSA
  4. 4.Department of Biological SciencesUniversity of North TexasDentonUSA
  5. 5.Plant Biology DivisionThe Samuel Roberts Noble FoundationArdmoreUSA
  6. 6.Department of Plant ScienceSouth Dakota State UniversityBrookingsUSA
  7. 7.Institute of Applied Cancer CenterMD Anderson Cancer CenterHoustonUSA
  8. 8.A110 Life Science buildingUniversity of GeorgiaAthensUSA

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