Mapping Quantitative Trait Loci for 1000-Grain Weight in a Double Haploid Population of Common Wheat.
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ABSTRACT:
SUBMITTER: Liu T
PROVIDER: S-EPMC7311974 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Statistical power calculations are a critical part of any study design for gene mapping. Most calculations assume that the locus of interest is biallelic. However, there are common situations in human genetics such as X-linked loci in males where the locus is haploid. The purpose of this work is to mathematically derive the biometric model for haploid loci, and to compute power for QTL mapping when the loci are haploid.We have derived the biometric model for power calculations for haploid loci and have developed software to perform these calculations. We have verified our calculations with independent mathematical methods.Our results fill a need in power calculations for QTL mapping studies. Furthermore, failure to appropriately model haploid loci may cause underestimation of power.
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Project description:Cadmium (Cd) is as an extremely toxic metal that can contaminate agricultural soils. To reduce the risk of Cd intake in food cereals, the development of cultivars with low grain Cd concentration (GCC) is an effective countermeasure. We analyzed quantitative trait loci (QTLs) for GCC in a doubled haploid (DH) common wheat (Triticum aestivum L.) population derived from 'Chugoku 165' (low GCC) × 'Chukei 10-22' (high GCC). We found novel loci for low GCC on the short arm of chromosome 4B and on the long arm of chromosome 6B. These QTLs accounted for 9.4%-25.4% (4B) and 9.0%-17.8% (6B) of the phenotypic variance in the DH population. An association analysis with 43 cultivars identified 3 loci at these QTLs: QCdc.4B-kita, QCdc.6B-kita1, and QCdc.6B-kita2. In contrast to durum wheat and barley, no QTL was detected on the chromosomes of homeologous group 5 for heavy metal P1B-type ATPase 3. These results will contribute to marker-assisted selection for low GCC in breeding of common wheat.
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Project description:Quantitative trait loci (QTLs) mapped in different genetic populations are of great significance for marker-assisted breeding. In this study, an F2:3 population were developed from the crossing of two maize inbred lines SG-5 and SG-7 and applied to QTL mapping for seven yield-related traits. The seven traits included 100-kernel weight, ear length, ear diameter, cob diameter, kernel row number, ear weight, and grain weight per plant. Based on an ultra-high density linkage map, a total of thirty-three QTLs were detected for the seven studied traits with composite interval mapping (CIM) method, and fifty-four QTLs were indentified with genome-wide composite interval mapping (GCIM) methods. For these QTLs, Fourteen were both detected by CIM and GCIM methods. Besides, eight of the thirty QTLs detected by CIM were identical to those previously mapped using a F2 population (generating from the same cross as the mapping population in this study), and fifteen were identical to the reported QTLs in other recent studies. For the fifty-four QTLs detected by GCIM, five of them were consistent with the QTLs mapped in the F2 population of SG-5 × SG-7, and twenty one had been reported in other recent studies. The stable QTLs associated with grain weight were located on maize chromosomes 2, 5, 7, and 9. In addition, differentially expressed genes (DEGs) between SG-5 and SG-7 were obtained from the transcriptomic profiling of grain at different developmental stages and overlaid onto the stable QTLs intervals to predict candidate genes for grain weight in maize. In the physical intervals of confirmed QTLs qKW-7, qEW-9, qEW-10, qGWP-6, qGWP-8, qGWP-10, qGWP-11 and qGWP-12, there were 213 DEGs in total. Finally, eight genes were predicted as candidate genes for grain size/weight. In summary, the stable QTLs would be reliable and the candidate genes predicted would be benefit for maker assisted breeding or cloning.
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Project description:KEY MESSAGE:The quantitative trait loci (QTLs) for grain morphological traits were identified via nested association mapping and validated in a natural wheat population via haplotype analysis. Grain weight, one of the three most important components of crop yield, is largely determined by grain morphological traits. Dissecting the genetic bases of grain morphology could facilitate the improvement of grain weight and yield production. In this study, four wheat recombinant inbred line populations constructed by crossing the modern variety Yanzhan 1 with three semi-wild wheat varieties (i.e., Chayazheda, Yutiandaomai, and Yunnanxiaomai from Xinjiang, Tibet, and Yunnan, respectively) and one exotic accession Hussar from Great Britain were investigated for grain weight and eight morphological traits in seven environments. Eighty-eight QTLs for all measured traits were totally identified through nested association mapping utilizing 14,643 high-quality polymorphic single nucleotide polymorphism (SNP) markers generated by 90 K SNP array. Among them, 64 (72.7%) QTLs have the most favorable alleles donated by semi-wild wheat varieties. For 14 QTL clusters affecting at least two grain morphological traits, nine QTL clusters were located in similar position with known genes/QTL, and the other five were novel. Three important novel QTLs (i.e., qTGW-1B.1, qTGW-1B.2, and qTGW-1A.1) were further validated in a natural wheat population via haplotype analysis. The favorable haplotypes for these three QTLs might be used in marker-assisted selection for the improvement of wheat yield by modifying morphological traits.
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Project description:Cadmium (Cd) is a heavy metal that can cause a variety of adverse effects on human health, including cancer. Wheat comprises approximately 20% of the human diet worldwide; therefore, reducing the concentrations of Cd in wheat grain will have significant impacts on the intake of Cd in food products. The tests for measuring the Cd content in grain are costly, and the content is affected significantly by soil pH. To facilitate breeding for low Cd content, this study sought to identify quantitative trait loci (QTL) and associated molecular markers that can be used in molecular breeding. One spring wheat population of 181 doubled haploid lines (DHLs), which was derived from a cross between two hard white spring wheat cultivars "UI Platinum" (UIP) and "LCS Star" (LCS), was assessed for the Cd content in grain in multiple field trials in Southeast Idaho, United States. Three major QTL regions, namely, QCd.uia2-5B, QCd.uia2-7B, and QCd.uia2-7D, were identified on chromosomes 5B, 7B, and 7D, respectively. All genes in these three QTL regions were identified from the NCBI database. However, three genes related to the uptake and transport of Cd were used in the candidate gene analysis. The sequences of TraesCS5B02G388000 (TaHMA3) in the QCd.uia2-5B region and TraesCS7B02G320900 (TaHMA2) and TraesCS7B02G322900 (TaMSRMK3) in the QCd.uia2-7B region were compared between UIP and LCS. TaHMA2 on 7B is proposed for the first time as a candidate gene for grain Cd content in wheat. A KASP marker associated with this gene was developed and it will be further validated in near-isogenic lines via a gene-editing system in future studies.
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Project description:Stable quantitative trait loci (QTL) are important for deployment in marker assisted selection in wheat (Triticum aestivum L.) and other crops. We reported QTL discovery in wheat using a population of 217 recombinant inbred lines and multiple statistical approach including multi-environment, multi-trait and epistatic interactions analysis. We detected nine consistent QTL linked to different traits on chromosomes 1A, 2A, 2B, 5A, 5B, 6A, 6B and 7A. Grain yield QTL were detected on chromosomes 2B.1 and 5B across three or four models of GenStat, MapQTL, and QTLNetwork while the QTL on chromosomes 5A.1, 6A.2, and 7A.1 were only significant with yield from one or two models. The phenotypic variation explained (PVE) by the QTL on 2B.1 ranged from 3.3-25.1% based on single and multi-environment models in GenStat and was pleiotropic or co-located with maturity (days to heading) and yield related traits (test weight, thousand kernel weight, harvest index). The QTL on 5B at 211 cM had PVE range of 1.8-9.3% and had no significant pleiotropic effects. Other consistent QTL detected in this study were linked to yield related traits and agronomic traits. The QTL on 1A was consistent for the number of spikes m-2 across environments and all the four analysis models with a PVE range of 5.8-8.6%. QTL for kernels spike-1 were found in chromosomes 1A, 2A.1, 2B.1, 6A.2, and 7A.1 with PVE ranged from 5.6-12.8% while QTL for thousand kernel weight were located on chromosomes 1A, 2B.1, 5A.1, 6A.2, 6B.1 and 7A.1 with PVEranged from 2.7-19.5%. Among the consistent QTL, five QTL had significant epistatic interactions (additive × additive) at least for one trait and none revealed significant additive × additive × environment interactions. Comparative analysis revealed that the region within the confidence interval of the QTL on 5B from 211.4-244.2 cM is also linked to genes for aspartate-semialdehyde dehydrogenase, splicing regulatory glutamine/lysine-rich protein 1 isoform X1, and UDP-glucose 6-dehydrogenase 1-like isoform X1. The stable QTL could be important for further validation, high throughput SNP development, and marker-assisted selection (MAS) in wheat.
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Project description:Grain weight, which is controlled by quantitative trait loci (QTLs), is one of the most important determinants of rice yield. Although many QTLs for grain weight have been identified, little is known about how different alleles in different QTLs coordinate to determine grain weight. In the present study, six grain-weight-QTLs were detected in seven mapping populations (two F2, one F3, and four recombinant inbred lines) developed by crossing 'Lemont', a United States japonica variety, with 'Yangdao 4', a Chinese indica variety. In each of the six loci, one allele from one parent increased grain weight and one allele from another parent decreased it. Thus, the 12 alleles at the six QTLs were subjected to regression analysis to examine whether they acted additively across loci leading to a linear relationship between the predicted breeding value of QTL and phenotype. Results suggested that a combination of the 12 alleles determined grain weight. In addition, plants carrying more grain-weight-increasing alleles had heavier grains than those carrying more grain-weight-decreasing alleles. This trend was consistent in the seven mapping populations. Thus, these six QTLs might be used in marker-assisted selection of grain weight, by stacking different grain-weight-increasing or -decreasing alleles.
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