A novel transcriptomic approach to identify candidate genes for grain quality traits in wheat

A - Papers appearing in refereed journals

Wan, Y., Toscano-Underwood, C., Toole, G., Skeggs, P., Zhu, T., Leverington, M., Griffiths, S., Wheeler, T., Gooding, M., Poole, R., Edwards, K. J., Gezan, S. A., Welham, S. J., Snape, J., Mills, E. N. C., Mitchell, R. A. C. and Shewry, P. R. 2009. A novel transcriptomic approach to identify candidate genes for grain quality traits in wheat. Plant Biotechnology Journal. 7 (5), pp. 401-410. https://doi.org/10.1111/j.1467-7652.2009.00405.x

AuthorsWan, Y., Toscano-Underwood, C., Toole, G., Skeggs, P., Zhu, T., Leverington, M., Griffiths, S., Wheeler, T., Gooding, M., Poole, R., Edwards, K. J., Gezan, S. A., Welham, S. J., Snape, J., Mills, E. N. C., Mitchell, R. A. C. and Shewry, P. R.
Abstract

A novel methodology is described in which transcriptomics is combined with the measurement of bread-making quality and other agronomic traits for wheat genotypes grown in different environments (wet and cool or hot and dry conditions) to identify transcripts associated with these traits. Seven doubled haploid lines from the Spark x Rialto mapping population were selected to be matched for development and known alleles affecting quality. These were grown in polytunnels with different environments applied 14 days post-anthesis, and the whole experiment was repeated over 2 years. Transcriptomics using the wheat Affymetrix chip was carried out on whole caryopsis samples at two stages during grain filling. Transcript abundance was correlated with the traits for approximately 400 transcripts. About 30 of these were selected as being of most interest, and markers were derived from them and mapped using the population. Expression was identified as being under cis control for 11 of these and under trans control for 18. These transcripts are candidates for involvement in the biological processes which underlie genotypic variation in these traits.

KeywordsBiotechnology & Applied Microbiology; Plant Sciences
Year of Publication2009
JournalPlant Biotechnology Journal
Journal citation7 (5), pp. 401-410
Digital Object Identifier (DOI)https://doi.org/10.1111/j.1467-7652.2009.00405.x
PubMed ID19490503
Open accessPublished as ‘gold’ (paid) open access
FunderInstitute of Food Research and John Innes Centre
Biotechnology and Biological Sciences Research Council
Funder project or codeCentre for Crop Genetic Improvement (CGI)
Centre for Mathematical and Computational Biology (MCB)
Publisher's version
PublisherWiley
Grant ID218/EGA17713
EGA17706
EGA17703
EGA17705
EGA17694
ISSN1467-7644

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