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A high-density genetic map of hexaploid wheat (Triticum aestivum L.) from the cross Chinese Spring × SQ1 and its use to compare QTLs for grain yield across a range of environments

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Abstract

A population of 96 doubled haploid lines (DHLs) was prepared from F1 plants of the hexaploid wheat cross Chinese Spring × SQ1 (a high abscisic acid-expressing breeding line) and was mapped with 567 RFLP, AFLP, SSR, morphological and biochemical markers covering all 21 chromosomes, with a total map length of 3,522 cM. Although the map lengths for each genome were very similar, the D  genome had only half the markers of the other two genomes. The map was used to identify quantitative trait loci (QTLs) for yield and yield components from a combination of 24 site × treatment × year combinations, including nutrient stress, drought stress and salt stress treatments. Although yield QTLs were widely distributed around the genome, 17 clusters of yield QTLs from five or more trials were identified: two on group 1 chromosomes, one each on group 2 and group 3, five on group 4, four on group 5, one on group 6 and three on group 7. The strongest yield QTL effects were on chromosomes 7AL and 7BL, due mainly to variation in grain numbers per ear. Three of the yield QTL clusters were largely site-specific, while four clusters were largely associated with one or other of the stress treatments. Three of the yield QTL clusters were coincident with the dwarfing gene Rht-B1 on 4BS and with the vernalisation genes Vrn-A1 on 5AL and Vrn-D1 on 5DL. Yields of each DHL were calculated for trial mean yields of 6 g plant−1 and 2 g plant−1 (equivalent to about 8 t ha−1 and 2.5 t ha−1, respectively), representing optimum and moderately stressed conditions. Analyses of these yield estimates using interval mapping confirmed the group-7 effects on yield and, at 2 g plant−1, identified two additional major yield QTLs on chromosomes 1D and 5A. Many of the yield QTL clusters corresponded with QTLs already reported in wheat and, on the basis of comparative genetics, also in rice. The implications of these results for improving wheat yield stability are discussed.

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Acknowledgements

The authors acknowledge the following funding sources that allowed aspects of this research to be carried out: molecular marker work from the BC-MURST (Italy) programme (C. Calestani), EU FP4 Biotechnology programme for the EGRAM project (E. Waterman) and EU FP5 Sustainable agriculture SUSTAIN project no. QLK5-CT-2001-01461 (D. Z. Habash, J. Weyen, J. Schondelmaier); molecular marker work and field trials from the BBSRC RASP (Resource Allocation and Stress in Plants) programme (C. Chinoy, P. Farmer, L. Saker, D.T. Clarkson), EU INTAS programme (A. Abugalieva, M. Yessimbekova, Y. Turuspekov, S. Abugalieva, R. Tuberosa, M.-C. Sanguineti) and EU INCO-DC programme (N. Steele, P. Hollington, R. Aragüés, A. Royo). D. Dodig acknowledges financial support from the Serbian Ministry of Science and Technology. The John Innes Centre is supported by a grant-in-aid from the Biotechnological and Biological Sciences Research Council. The helpful comments on this manuscript of Professor John Snape are gratefully acknowledged.

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Quarrie, S.A., Steed, A., Calestani, C. et al. A high-density genetic map of hexaploid wheat (Triticum aestivum L.) from the cross Chinese Spring × SQ1 and its use to compare QTLs for grain yield across a range of environments. Theor Appl Genet 110, 865–880 (2005). https://doi.org/10.1007/s00122-004-1902-7

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