Transcriptome profile of barley aleurone differs between total and polysomal RNAs: implications for proteome modeling
- 121 Downloads
Microarray analysis of mRNA populations is routinely conducted with total RNA. However, such analyses would probably represent the translated genome (proteome) more accurately if conducted with polysomal RNA. An accurate assessment of the proteome is essential where microarray analysis is used to produce molecular markers for breeding programs. In order to determine whether significant variation occurs between these two RNA populations, the relative abundance of transcripts was analyzed in barley aleurones of intact 3.5 day old germinated seedlings, comparing total and polysomal RNAs. A total of 13,744 transcripts was detected among both populations. Of these, 714 were detected only in total RNA, and 1,541 were detected only in polysomal RNA. A surprising number of transcripts detected in both populations (6,312 gene calls or 46% of the compared transcripts) differed significantly between populations. Almost half of these (2,987) were more abundant by at least two-fold, depending on the RNA source, and expression was often biased toward specific functional classes of genes. Transcripts encoding hydrolytic enzymes for the mobilization of stored seed macromolecules were more highly represented in total RNA, rather than polysomal RNA. These included proteinases, nucleases and carbohydrases. Genes for ribonucleoprotein complexes, nucleic acid binding and components of ribosomes were more abundant in polysomal RNA. Among genes with signal intensities of 1,000 or more, hydrolases were greatly over-represented in total RNA, whereas ubiquitin, histone and kinase related genes were mainly represented in polysomal RNA.
KeywordsAleurone Barley seed Microarray Polysomal mRNA Transcriptional profiling Proteome
The pM/C clone was generously provided by John Rogers (Washington State Univ.). The 18S barley rRNA was cloned in our lab by John Herbst. This material is based upon work supported by the U.S. Department of Agriculture. Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the view of the U.S. Department of Agriculture. Mention of trade names or commercial products in this article is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the U.S. Dept. of Agriculture.
- Bamforth CW, Barclay AHP (1993) Malting technology and the uses of malt. In: MacGregor AW, Bhatty RS (eds) Barley: chemistry and technology. American Assoc. of Cereal Chemists, Inc., St. Paul, MNGoogle Scholar
- Briggs DE (1978) Barley. Chapman and Hall, London, pp 208–215Google Scholar
- Carrari F, Baxter C, Usadel B, Urbanczyk-Wochniac E, Zanor AN, Nikiforova V, Centero D, Ratzka A, Pauly M et al (2006) Integrated analysis of metabolite and transcript levels reveals the metabolic shifts that underlie tomato fruit development and highlight regulatory aspects of metabolic network behavior. Plant Physiol 142:1380–1396PubMedCrossRefGoogle Scholar
- Hayes PM, Castro A, Marquez-Cedillo, Corey A, Henson C, Jones B, Kling J, Mather D, Matus I, Rossi C, Sato K (2003) Genetic diversity for quantitatively inherited agronomic and malting quality traits. In: Roland von Bothmer et al. (eds) Diversity in barley (Hordeum vulgare). Elsevier Science B.VGoogle Scholar
- Shen L, Gong J, Caldo RA, Nettleton D, Cook D, Wise RP, Dickerson JA (2005) BarleyBase-an expression profiling database for plant genomics. Nucleic Acids Res 33: Database issueGoogle Scholar