Genetic control of grain yield and grain physical characteristics in a bread wheat population grown under a range of environmental conditions
- 1.1k Downloads
Genetic analysis of the yield and physical quality of wheat revealed complex genetic control, including strong effects of photoperiod-sensitivity loci.
Environmental conditions such as moisture deficit and high temperatures during the growing period affect the grain yield and grain characteristics of bread wheat (Triticum aestivum L.). The aim of this study was to map quantitative trait loci (QTL) for grain yield and grain quality traits using a Drysdale/Gladius bread wheat mapping population grown under a range of environmental conditions in Australia and Mexico. In general, yield and grain quality were reduced in environments exposed to drought and/or heat stress. Despite large effects of known photoperiod-sensitivity loci (Ppd-B1 and Ppd-D1) on crop development, grain yield and grain quality traits, it was possible to detect QTL elsewhere in the genome. Some of these QTL were detected consistently across environments. A locus on chromosome 6A (TaGW2) that is known to be associated with grain development was associated with grain width, thickness and roundness. The grain hardness (Ha) locus on chromosome 5D was associated with particle size index and flour extraction and a region on chromosome 3B was associated with grain width, thickness, thousand grain weight and yield. The genetic control of grain length appeared to be largely independent of the genetic control of the other grain dimensions. As expected, effects on grain yield were detected at loci that also affected yield components. Some QTL displayed QTL-by-environment interactions, with some having effects only in environments subject to water limitation and/or heat stress.
KeywordsQuantitative Trait Locus Simple Sequence Repeat Marker Quantitative Trait Locus Analysis DArT Marker Test Weight
This work was funded by the New South Wales Government through its BioFirst initative (D2985-8), by the Australian Research Council (PFG002008), and the Grains Research and Development Corporation (ACP0002) and by scholarships awarded to the first author by the University of Adelaide and the Australian Centre for Plant Functional Genomics. The authors thank Howard Eagles for providing information about the allele combinations of the parents, and Paul Eckermann for advice on linkage mapping.
Conflict of interest
The authors declare that they have no conflict of interest.
The experiments reported here comply with the current laws of the countries in which they were performed.
- AACC (1999) Approved methods of the AACC. Association of Cereal Chemists, St. PaulGoogle Scholar
- Akbari M, Wenzl P, Caig V, Carling J, Xia L, Yang S, Uszynski G, Mohler V, Lehmensiek A, Kuchel H, Hayden M, Howes N, Sharp P, Vaughan P, Rathmell B, Huttner E, Kilian A (2006) Diversity arrays technology (DArT) for high-throughput profiling of the hexaploid wheat genome. Theor Appl Genet 113:1409–1420PubMedCrossRefGoogle Scholar
- Berman M, Bason ML, Ellison F, Peden G, Wrigley CW (1996) Image analysis of whole grains to screen for flour-milling yield in wheat breeding. Cereal Chem 73:323–327Google Scholar
- Díaz A, Zikhali M, Turner AS, Isaac P, Laurie DA (2012) Copy number variation affecting the Photoperiod-B1 and Vernalization-A1 genes is associated with altered flowering time in wheat (Triticum aestivum). PLoS One 7:e33234. doi: 10.1371/journal.pone.0033234 PubMedCentralPubMedCrossRefGoogle Scholar
- Griffiths S, Simmonds J, Leverington M, Wang Y, Fish L, Sayers L, Alibert L, Orford S, Wingen L, Herry L, Faure S, Laurie D, Bilham L, Snape J (2009) Meta-QTL analysis of the genetic control of ear emergence in elite European winter wheat germplasm. Theor Appl Genet 119:383–395PubMedCrossRefGoogle Scholar
- Isidore E, van Os H, Andrzejewski S, Bakker J, Barrena I, Bryan GJ, Caromel B, van Eck H, Ghareeb B, de Jong W, van Koert P, Lefebvre V, Milbourne D, Ritter E, van der Voort JR, Rousselle-Bourgeois F, van Vliet J, Waugh R (2003) Toward a marker-dense meiotic map of the potato genome: lessons from linkage group I. Genetics 165:2107–2116PubMedCentralPubMedGoogle Scholar
- McIntyre C, Mathews K, Rattey A, Chapman S, Drenth J, Ghaderi M, Reynolds M, Shorter R (2010) Molecular detection of genomic regions associated with grain yield and yield-related components in an elite bread wheat cross evaluated under irrigated and rainfed conditions. Theor Appl Genet 120:527–541PubMedCrossRefGoogle Scholar
- Payne RW, Murray DA, Harding SA, Baird DB, Soutar DM (2009) GenStat for Windows, 12th edn. Introduction, VSN International, Hemel HempsteadGoogle Scholar
- RACI-CCD CHK (2010) Official testing methods of the Cereal Chemistry division, 4th edn. NSW, AustraliaGoogle Scholar
- Wang G, Leonard J, Ross A, Peterson CJ, Zemetra R, Garland Campbell K, Riera-Lizarazu O (2012) Identification of genetic factors controlling kernel hardness and related traits in a recombinant inbred population derived from a soft × ‘extra-soft’ wheat (Triticum aestivum L.) cross. Theor Appl Genet 124:207–221PubMedCrossRefGoogle Scholar