Transcriptome analysis of grain development in hexaploid wheat

• Main Authors: Mills Clare, Gooding Mike J, Welham Sue, Feeney Kevin, Toscano-Underwood Claudia, Huttly Alison K, Poole Rebecca L, Wan Yongfang, Edwards Keith J, Shewry Peter R, Mitchell Rowan AC
• Format: Article
• Language: English
• Published: BMC 2008-03-01
• Series: BMC Genomics
• Online Access: http://www.biomedcentral.com/1471-2164/9/121

<p>Abstract</p> <p>Background</p> <p>Hexaploid wheat is one of the most important cereal crops for human nutrition. Molecular understanding of the biology of the developing grain will assist the improvement of yield and quality traits for different environments. High quality transcriptomics is a powerful method to increase this understanding.</p> <p>Results</p> <p>The transcriptome of developing caryopses from hexaploid wheat (<it>Triticum aestivum</it>, cv. Hereward) was determined using Affymetrix wheat GeneChip^®oligonucleotide arrays which have probes for 55,052 transcripts. Of these, 14,550 showed significant differential regulation in the period between 6 and 42 days after anthesis (daa). Large changes in transcript abundance were observed which were categorised into distinct phases of differentiation (6–10 daa), grain fill (12–21 daa) and desiccation/maturation (28–42 daa) and were associated with specific tissues and processes. A similar experiment on developing caryopses grown with dry and/or hot environmental treatments was also analysed, using the profiles established in the first experiment to show that most environmental treatment effects on transcription were due to acceleration of development, but that a few transcripts were specifically affected. Transcript abundance profiles in both experiments for nine selected known and putative wheat transcription factors were independently confirmed by real time RT-PCR. These expression profiles confirm or extend our knowledge of the roles of the known transcription factors and suggest roles for the unknown ones.</p> <p>Conclusion</p> <p>This transcriptome data will provide a valuable resource for molecular studies on wheat grain. It has been demonstrated how it can be used to distinguish general developmental shifts from specific effects of treatments on gene expression and to diagnose the probable tissue specificity and role of transcription factors.</p>