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.
Subject(s)
Gene Expression Profiling/methods , Quantitative Trait, Heritable , Seeds/genetics , Triticum/genetics , Crops, Agricultural/genetics , Crosses, Genetic , Gene Expression Regulation, Plant , Genes, Plant , Genotype , Haploidy , RNA, Plant/geneticsABSTRACT
Variation in ear emergence time is critical for the adaptation of wheat (Triticum aestivum L.) to specific environments. The aim of this study was to identify genes controlling ear emergence time in elite European winter wheat germplasm. Four doubled haploid populations derived from the crosses: Avalon x Cadenza, Savannah x Rialto, Spark x Rialto, and Charger x Badger were selected which represent diversity in European winter wheat breeding programmes. Ear emergence time was recorded as the time from 1st May to heading in replicated field trials in the UK, France and Germany. Genetic maps based on simple sequence repeat (SSR) and Diversity Arrays Technology (DArT) markers were constructed for each population. One hundred and twenty-seven significant QTL were identified in the four populations. These effects were condensed into 19 meta-QTL projected onto a consensus SSR map of wheat. These effects are located on chromosomes 1B (2 meta-QTL), 1D, 2A (2 meta-QTL), 3A, 3B (2 meta-QTL), 4B, 4D, 5A (2 meta-QTL), 5B, 6A, 6B 7A (2 meta-QTL), 7B and 7D. The identification of environmentally robust earliness per se effects will facilitate the fine tuning of ear emergence in predictive wheat breeding programmes.
