Pei Cao1, Xiaona Liang1,2, Hong Zhao1,2, Bo Feng3, Enjun Xu1, Liming Wang4, Yuxin Hu5,6. 1. Key Laboratory of Plant Molecular Physiology, CAS Center for Excellence in Molecular Plant Sciences, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China. 2. University of Chinese Academy of Sciences, Beijing, 100049, China. 3. Chengdu Institute of Biology, Chinese Academy of Sciences, Chengdu, 610041, China. 4. Henan Science and Technology University, Luoyang, 471023, Henan, China. 5. Key Laboratory of Plant Molecular Physiology, CAS Center for Excellence in Molecular Plant Sciences, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China. huyuxin@ibcas.ac.cn. 6. National Center for Plant Gene Research, Beijing, 100093, China. huyuxin@ibcas.ac.cn.
Abstract
MAIN CONCLUSION: Totally, 48 loci responsible for six spike-related traits were identified in wheat, and a major locus QGl-4A for grain length was mapped and validated for marker-assisted selection in breeding. Wheat yield is determined by the number of spikes, number of grains per spike (GN), and one-thousand kernel weight (TKW), among which GN and TKW are greatly related to the spike development and thus the spike-related traits, including spike length (SL), number of spikelet per spike (SN), grain length (GL) and grain width (GW). To identify the key loci governing the spike-related traits (SL, SN, GN, TKW, GL and GW), we conducted the quantitative trait loci (QTL) analysis combined with wheat 660K SNP chip and Kompetitive allele-specific PCR (KASP) assay, using the F2 and F2:3 populations derived from Luohan6 (LH6) with big spike and grain and Zhengmai366 with small spike and grain, and identified a total of 48 QTLs on 18 chromosomes. Moreover, a major stable QTL for GL on chromosome 4A, designated as QGl-4A, was mapped into a 0.37 cM interval between KASP markers Xib4A-10 and Xib4A-12, corresponding to 20 Mb physical region in the Chinese Spring genome. This QTL explained 17.30% and 5.12% of the phenotypic variation for GL in the F2 and F2:3 populations. Further association analysis of flanking markers Xib4A-10 and Xib4A-12 in 192 wheat varieties showed that these two markers could be used for marker-assisted selection in breeding. These results provide valuable information for map-based cloning of the target genes involved in the regulation of spike-related traits in common wheat.
MAIN CONCLUSION: Totally, 48 loci responsible for six spike-related traits were identified in wheat, and a major locus QGl-4A for grain length was mapped and validated for marker-assisted selection in breeding. Wheat yield is determined by the number of spikes, number of grains per spike (GN), and one-thousand kernel weight (TKW), among which GN and TKW are greatly related to the spike development and thus the spike-related traits, including spike length (SL), number of spikelet per spike (SN), grain length (GL) and grain width (GW). To identify the key loci governing the spike-related traits (SL, SN, GN, TKW, GL and GW), we conducted the quantitative trait loci (QTL) analysis combined with wheat 660K SNP chip and Kompetitive allele-specific PCR (KASP) assay, using the F2 and F2:3 populations derived from Luohan6 (LH6) with big spike and grain and Zhengmai366 with small spike and grain, and identified a total of 48 QTLs on 18 chromosomes. Moreover, a major stable QTL for GL on chromosome 4A, designated as QGl-4A, was mapped into a 0.37 cM interval between KASP markers Xib4A-10 and Xib4A-12, corresponding to 20 Mb physical region in the Chinese Spring genome. This QTL explained 17.30% and 5.12% of the phenotypic variation for GL in the F2 and F2:3 populations. Further association analysis of flanking markers Xib4A-10 and Xib4A-12 in 192 wheat varieties showed that these two markers could be used for marker-assisted selection in breeding. These results provide valuable information for map-based cloning of the target genes involved in the regulation of spike-related traits in common wheat.
Authors: Jing Liu; Zhibin Xu; Xiaoli Fan; Qiang Zhou; Jun Cao; Fang Wang; Guangsi Ji; Li Yang; Bo Feng; Tao Wang Journal: Front Plant Sci Date: 2018-10-31 Impact factor: 5.753