A novel transcriptomic approach to identify candidate genes for grain quality traits in wheat.
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.
Wan
Yongfang
Y
Rothamsted Research, Harpenden, Hertfordshire, UK.
Underwood
Claudia
C
Toole
Geraldine
G
Skeggs
Peter
P
Zhu
Tong
T
Leverington
Michelle
M
Griffiths
Simon
S
Wheeler
Tim
T
Gooding
Mike
M
Poole
Rebecca
R
Edwards
Keith J
KJ
Gezan
Salvador
S
Welham
Sue
S
Snape
John
J
Mills
E N Clare
EN
Mitchell
Rowan A C
RA
Shewry
Peter R
PR
D018556:Crops, Agricultural / Q000235:genetics; D003433:Crosses, Genetic; D020869:Gene Expression Profiling / Q000379:methods*; D018506:Gene Expression Regulation, Plant; D017343:Genes, Plant; D005838:Genotype; D006238:Haploidy; D019655:Quantitative Trait, Heritable; D018749:RNA, Plant / Q000235:genetics; D012639:Seeds / Q000235:genetics*; D014908:Triticum / Q000235:genetics*
D018749:RNA, Plant