Mapping of QTL for total spikelet number per spike on chromosome 2D in wheat using a high-density genetic map

Deng, Mei; Wu, Fangkun; Zhou, Wanlin; Li, Jing; Shi, Haoran; Wang, Zhiqiang; Lin, Yu; Yang, Xilan; Wei, Yuming; Zheng, Youliang; Liu, Yaxi

doi:10.1590/1678-4685-gmb-2018-0122

Cited by 15 publications

(4 citation statements)

References 34 publications

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“…Grain yield is a complex trait affected by multiple agronomic and yield-related traits, environments, and G × E interactions, and QTL × QTL interactions (epistasis) (Wu et al 2012;Xing et al 2014). Chromosome 2D harbors multiple QTLs associated with spike number and agronomic traits (Zhang et al 2015;Perez-Lara et al 2016;Deng et al 2019;Ma et al 2020) as well as the photoperiodism response Ppd-D1gene. However, none of the previously reported QTLs are located within the same physical interval of QYld.dms-2D identified in the present study.…”

Section: Discussionmentioning

confidence: 99%

Quantitative trait locus mapping of rust resistance and agronomic traits in spring wheat

et al. 2022

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Marker-assisted selection requires the identification of molecular markers associated with major genes and quantitative trait loci (QTL). In this study, we used 167 doubled haploid (DH) lines derived from two unregistered spring wheat (Triticum aestivum L.) parental lines that belong to the Canada Western Special Purpose (CWSP) class to map QTLs associated with five traits using inclusive composite interval mapping (ICIM). Using ICIM, the least square means phenotype data across 3-4 environments, and a genetic map of 2,676 SNPs out of the wheat 90K SNP array, we identified ten QTLs associated with days to maturity (4A and 5B), plant lodging (4B, 5A, 5D, and 7D), grain yield (2D), leaf rust (4A) and stem rust (1A and 2B). Each QTL individually explained 6.0-22.3% of the phenotypic variance and together accounted for 8.6-38.2% of the total variance per trait. Two of the QTLs associated with rusts (QLr.dms-4A and QSr.dms-1A) had a minor effect (6.0-9.0%) whereas the second QTL for stem rust (QSr.dms-2B) had a major effect (22.3%). Although chromosome 2B harbors multiple disease resistance QTLs, the physical location of QSr.dms-2B has not been reported in previous studies. Results from this study provide additional valuable information to wheat researchers, in particular, the area on chromosome 2B should be considered for future analyses.

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Section: Discussionmentioning

confidence: 99%

Quantitative trait locus mapping of rust resistance and agronomic traits in spring wheat

et al. 2022

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“…QTL mapping for SLU was detected using the inclusive composite interval mapping [35] in IciMapping 4.2 [36]. To increase the authenticity and reliability of the QTL detected, the threshold was set as LOD scores ≥3, and the loci that were detected in only one environment or only using BLUP values were removed [37][38][39]. QTL were named according to the rules that were established by the International Rules of Genetic Nomenclature (http://wheat.pw.usda.gov/ggpages/wgc/ 98/Intro.htm (accessed on 12 September 2021)).…”

Section: Genotyping Map Construction Qtl Mappingmentioning

confidence: 99%

Identification and Validation of Quantitative Trait Loci Mapping for Spike-Layer Uniformity in Wheat

Zhou

Lin

Jiang

et al. 2022

IJMS

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Spike-layer uniformity (SLU), the consistency of the spike distribution in the vertical space, is an important trait. It directly affects the yield potential and appearance. Revealing the genetic basis of SLU will provide new insights into wheat improvement. To map the SLU-related quantitative trait loci (QTL), 300 recombinant inbred lines (RILs) that were derived from a cross between H461 and Chinese Spring were used in this study. The RILs and parents were tested in fields from two continuous years from two different pilots. Phenotypic analysis showed that H461 was more consistent in the vertical spatial distribution of the spike layer than in Chinese Spring. Based on inclusive composite interval mapping, four QTL were identified for SLU. There were two major QTL on chromosomes 2BL and 2DL and two minor QTL on chromosomes 1BS and 2BL that were identified. The additive effects of QSlu.sicau-1B, Qslu.sicau-2B-2, and QSlu.sicau-2D were all from the parent, H461. The major QTL, QSlu.sicau-2B-2 and QSlu.sicau-2D, were detected in each of the conducted trials. Based on the best linear unbiased prediction values, the two loci explained 23.97% and 15.98% of the phenotypic variation, respectively. Compared with previous studies, the two major loci were potentially novel and the two minor loci were overlapped. Based on the kompetitive allele-specific PCR (KASP) marker, the genetic effects for QSlu.sicau-2B-2 were validated in an additional RIL population. The genetic effects ranged from 26.65% to 32.56%, with an average value of 30.40%. In addition, QSlu.sicau-2B-2 showed a significant (p < 0.01) and positive influence on the spike length, spikelet number, and thousand kernel weight. The identified QTL and the developed KASP marker will be helpful for fine-mapping these loci, finally contributing to wheat breeding programs in a marker-assisted selection way.

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“…Hundreds of QTL for GNS have been found to be distributed across the 21 wheat chromosomes (Börner et al, 2002 ; Huang et al, 2006 ; Narasimhamoorthy et al, 2006 ; Li et al, 2007 ; Ma et al, 2007 ; Wu et al, 2012 ; Jia et al, 2013 ; Zhang et al, 2016 ; Cui et al, 2017 ; Guan et al, 2018 ; Keeble-Gagnere et al, 2018 ; Onyemaobi et al, 2018 ; Su et al, 2018 ; Deng et al, 2019 ; Fan et al, 2019 ; Liu et al, 2019 ; Yao et al, 2019 ). Some genes related to GNS had been reported, such as homology-based cloned genes TaTAR2.1-3A (Shao et al, 2017 ), TaCWI-4A (Jiang et al, 2015 ), TaMOC1-7A (Zhang et al, 2015 ), TaSnRK2.9-5A (Rehman et al, 2019 ), TaAPO-A1 (Muqaddasi et al, 2019 ), TaGW8-B1 (Yan et al, 2019 ), TaPHR3-A1 (Zheng et al, 2020 ), the Q gene (Chuck et al, 1998 ; Debernardi et al, 2017 ; Xie et al, 2018 ), and genes GNI-A1 (Sakuma et al, 2019 ) and WFZP identified via map-based cloning (Du et al, 2021 ).…”

Section: Introductionmentioning

confidence: 99%

Analysis of Genetic Regions Related to Field Grain Number per Spike From Chinese Wheat Founder Parent Linfen 5064

Liao

Zhao

et al. 2022

Front. Plant Sci.

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Wheat founder parents have been important in the development of new wheat cultivars. Understanding the effects of specific genome regions on yield-related traits in founder variety derivatives can enable more efficient use of these genetic resources through molecular breeding. In this study, the genetic regions related to field grain number per spike (GNS) from the founder parent Linfen 5064 were analyzed using a doubled haploid (DH) population developed from a cross between Linfen 5064 and Nongda 3338. Quantitative trait loci (QTL) for five spike-related traits over nine experimental locations/years were identified, namely, total spikelet number per spike (TSS), base sterile spikelet number per spike (BSSS), top sterile spikelet number per spike (TSSS), fertile spikelet number per spike (FSS), and GNS. A total of 13 stable QTL explaining 3.91–19.51% of the phenotypic variation were found. The effect of six of these QTL, Qtss.saw-2B.1, Qtss.saw-2B.2, Qtss.saw-3B, Qfss.saw-2B.2, Qbsss.saw-5A.1, and Qgns.saw-1A, were verified by another DH population (Linfen 5064/Jinmai 47), which showed extreme significance (P < 0.05) in more than three environments. No homologs of reported grain number-related from grass species were found in the physical regions of Qtss.saw-2B.1 and Qtss.saw-3B, that indicating both of them are novel QTL, or possess novel-related genes. The positive alleles of Qtss.saw-2B.2 from Linfen 5064 have the larger effect on TSS (3.30%, 0.62) and have 66.89% in Chinese cultivars under long-term artificial selection. This study revealed three key regions for GNS in Linfen 5064 and provides insights into molecular marker-assisted breeding.

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Mapping of QTL for total spikelet number per spike on chromosome 2D in wheat using a high-density genetic map

Cited by 15 publications

References 34 publications

Quantitative trait locus mapping of rust resistance and agronomic traits in spring wheat

Quantitative trait locus mapping of rust resistance and agronomic traits in spring wheat

Identification and Validation of Quantitative Trait Loci Mapping for Spike-Layer Uniformity in Wheat

Analysis of Genetic Regions Related to Field Grain Number per Spike From Chinese Wheat Founder Parent Linfen 5064

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