Maize gene atlas developed by RNA sequencing and comparative evaluation of transcriptomes based on RNA sequencing and microarrays

PLoS One. 2013 Apr 23;8(4):e61005. doi: 10.1371/journal.pone.0061005. Print 2013.


Transcriptome analysis is a valuable tool for identification and characterization of genes and pathways underlying plant growth and development. We previously published a microarray-based maize gene atlas from the analysis of 60 unique spatially and temporally separated tissues from 11 maize organs [1]. To enhance the coverage and resolution of the maize gene atlas, we have analyzed 18 selected tissues representing five organs using RNA sequencing (RNA-Seq). For a direct comparison of the two methodologies, the same RNA samples originally used for our microarray-based atlas were evaluated using RNA-Seq. Both technologies produced similar transcriptome profiles as evident from high Pearson's correlation statistics ranging from 0.70 to 0.83, and from nearly identical clustering of the tissues. RNA-Seq provided enhanced coverage of the transcriptome, with 82.1% of the filtered maize genes detected as expressed in at least one tissue by RNA-Seq compared to only 56.5% detected by microarrays. Further, from the set of 465 maize genes that have been historically well characterized by mutant analysis, 427 show significant expression in at least one tissue by RNA-Seq compared to 390 by microarray analysis. RNA-Seq provided higher resolution for identifying tissue-specific expression as well as for distinguishing the expression profiles of closely related paralogs as compared to microarray-derived profiles. Co-expression analysis derived from the microarray and RNA-Seq data revealed that broadly similar networks result from both platforms, and that co-expression estimates are stable even when constructed from mixed data including both RNA-Seq and microarray expression data. The RNA-Seq information provides a useful complement to the microarray-based maize gene atlas and helps to further understand the dynamics of transcription during maize development.

Publication types

  • Comparative Study
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Gene Expression Profiling*
  • Gene Regulatory Networks
  • Genes, Plant / genetics*
  • Oligonucleotide Array Sequence Analysis*
  • Sequence Analysis, RNA*
  • Zea mays / genetics*

Grant support

This work was supported by the Department of Energy Great Lakes Bioenergy Research Center (Department of Energy Biological and Environmental Research Office of Science grant no. DE–FC02–07ER64494). RB and CLM were partially supported by Grant DBI-0953881 and Grant IOS-1126950 from the National Science Foundation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.