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Article

Identification and Validation of Quantitative Trait Loci for Grain Size in Bread Wheat (Triticum aestivum L.)

by
Wenjing Hu
1,2,
Sen Liao
2,
Die Zhao
2,
Jizeng Jia
1,2,3,
Weigang Xu
1,4 and
Shunhe Cheng
2,*
1
College of Agronomy & Center for Crop Genome Engineering, Henan Agricultural University, Zhengzhou 450046, China
2
Key Laboratory of Wheat Biology and Genetic Improvement for Low & Middle Yangtze Valley, Ministry of Agriculture and Rural Affairs, Lixiahe Institute of Agricultural Sciences, Yangzhou 225007, China
3
Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing 100081, China
4
Institute of Crop Molecular Breeding, National Engineering Laboratory of Wheat, Key Laboratory of Wheat Biology and Genetic Breeding in Central Huanghuai Area, Ministry of Agriculture, Henan Key Laboratory of Wheat Germplasm Resources Innovation and Improvement, Henan Academy of Agricultural Sciences, Zhengzhou 450002, China
*
Author to whom correspondence should be addressed.
Agriculture 2022, 12(6), 822; https://doi.org/10.3390/agriculture12060822
Submission received: 16 May 2022 / Revised: 1 June 2022 / Accepted: 5 June 2022 / Published: 8 June 2022
(This article belongs to the Special Issue Molecular Markers and Marker-Assisted Breeding in Wheat)
Browse Figures
Review Reports Versions Notes

Abstract

:
Grain width (GW) and grain length (GL) are crucial components affecting grain weight. Dissection of their genetic control is essential for improving yield potential in wheat breeding. Yangmai 12 (YM12) and Yanzhan 1 (YZ1) are two elite cultivars released in the Middle and Lower Yangtze Valleys Wheat Zone (MLYVWZ) and the Yellow-Huai River Valleys Wheat Zone (YRVWZ), respectively. One biparental population derived from YM12/YZ1 cross was employed to perform QTL mapping based on the data from four environments over two years to detect quantitative trait loci (QTL) for GW and GL. A total of eight QTL were identified on chromosomes 1B, 2D, 3B, 4B, 5A, and 6B. Notably, QGW.yz.2D was co-located with QGL.yz.2D, and QGW.yz.4B was co-located with QGL.yz.4B, respectively. QGW.yz.2D and QGL.yz.2D, with the increasing GW/GL allele from YZ1, explained 12.36–18.27% and 13.69–26.53% of the phenotypic variations for GW and GL, respectively. QGW.yz.4B and QGL.yz.4B, with the increasing GW/GL allele from YM12, explained 10.34–11.95% and 10.35–16.04% of the phenotypic variation for GW and GL, respectively. QGL.yz.5A, with the increasing GL allele from YM12, explained 10.04–12.48% of the phenotypic variation for GL. Moreover, the positive alleles of these three QTL regions could significantly increase thousand-grain weight, and QGW.yz.4B/QGL.yz.4B and QGL.yz.5A did not show significant negative effects on grain number per spike. QGL.yz.2D, QGW.yz.4B/QGL.yz.4B, and QGL.yz.5A have not been reported. These three QTL regions were then further validated using Kompetitive Allele-Specific PCR (KASP) markers in 159 wheat cultivars/lines from MLYVWZ and YRVWZ. Combining the positive alleles of the major QTL significantly increased GW and GL. Eleven candidate genes associated with encoding ethylene-responsive transcription factor, oleosin, osmotin protein, and thaumatin protein were identified. Three major QTL and KASP markers reported here will be helpful in developing new wheat cultivars with high and stable yields.

1. Introduction

Wheat (Triticum aestivum L.) is one of the world’s major staple crops, providing 20% of the total caloric demands of humans [1]. The demand for wheat production has been increasing rapidly due to farmland loss, climate change, and population increase [2,3]. Therefore, it is important to improve grain yield by breeding high-yield wheat cultivars. Wheat grain yield comprises three main components, viz., spike number per unit area, kernel number per spike, and thousand-grain weight (TGW). Among them, TGW with relatively high heritability is determined mainly by grain size, including grain width (GW) and grain length (GL) [4,5]. In the past decade, many studies have been conducted to identify quantitative trait loci (QTL) for wheat grain size [5] (Guan et al. 2020). Of those detected QTL, few had been further validated and fine-mapped [5,6,7,8,9,10,11]. Since rice and wheat have a conserved genetic network in regulating grain size, a translational genomics approach appears to be an effective method to identify and map candidate genes for grain size in the wheat genome [12]. Most of the candidate genes for grain weight in wheat have been cloned through homology-based cloning approaches, such as TaGW2 [13], TaCKX6-D1 [14], TaCwi-A1 [15], TaGS-D1 [16], 6-SFT-A2 [17], TaTGW6 [18], TaTPP-6AL1 [19], TaGW8 [20], TaBT1 [21], and TaGW7 [22]. Moreover, several genes for grain size in wheat, such as TaGL3.3-5B [23] and TaPGS1 [24] have been characterized. The functions of several orthologous genes associated with grain size and weight had been further confirmed by the RNAi approach, TILLING (targeting induced local lesions in genomes), and clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) genome editing technology [21,22,25,26,27]. However, few QTL/genes for grain size have been used in marker-assisted selection (MAS) in breeding programs, due to their unstable effects on corresponding traits in different genetic backgrounds and environments. Therefore, detecting novel QTL for grain size and validating them is still critical for yield-breeding. SSR and SNP markers are common molecular markers that are based on polymerase chain reaction (PCR) [28]. Recent progress on wheat genome sequencing and availability of high-throughput chip-based markers have accelerated QTL analysis and MAS in breeding programs. Kompetitive Allele-Specific PCR (KASP) assay, which using the specific commercial master-mix without compromising data throughput, has been an excellent breeding toolkit for high-throughput, cost-effective tracing functional genes/QTL for agronomic traits, pre-harvest sprouting resistance and biotic stress resistance in wheat [29,30].
Yangmai 12 (YM12) was a leading cultivar in the Middle and Lower Yangtze Valleys Wheat Zone (MLYVWZ) released with a peak planting area of 0.14 Mha in 2006 [31], which has been used extensively as an important parent with good disease resistance and excellent agronomic traits in many breeding programs. Yangzhan 1 (YZ1) is a high-yield and good-quality winter wheat variety released in the Yellow-Huai River Valleys Wheat Zone (YRVWZ) [32]. The genetic basis of grain size for YM12 and YZ1 is unclear. Thus, the objectives of this study were to (1) understand the genetic basis of YM12 and YZ1 for GW and GL using a recombinant inbred line (RIL) population; (2) highlight the critical chromosomal regions harboring stable QTL; (3) develop breeder-friendly molecular markers tightly linked to the target QTL regions and evaluate the effects of stable QTL intervals on the related traits in different backgrounds; and (4) identify candidate genes for map-based cloning of the major QTL.

2. Materials and Methods

2.1. Plant Materials

A biparental population (205 F10 RILs) derived from the cross of YM12 and YZ1 was used for QTL detection. YM12 has a bigger grain size than YZ1. A panel of 159 wheat cultivars/lines, including 64 cultivars and 95 advanced breeding lines, was used for the validation of the major QTL. In the 95 advanced breeding lines, 25 lines were from Yangmai 15/Zhoumai 18 cross, 16 lines were from Yangmai 16/Ningmai 22 cross, and 22 lines were from Yangmai 18/Zhengmai 7698 cross.

2.2. Field Trials and Phenotypic Evaluation

Field trials were carried out at Yangzhou Experimental Station (YZ) (altitude 10–20 m, latitude 32.24°N, longitude 119.26° E, annual rainfall 1020 mm) and Sihong Experimental Station (SH) (altitude 35–45 m, latitude 33.46° N, longitude 118.22° E, annual rainfall 910 mm) in Jiangsu Province, respectively. The YM12/YZ1 RIL population was planted in wheat cropping seasons 2019–2020 and 2020–2021, respectively (2020YZ, 2020SH, 2021YZ, and 2021SH). Field trials were conducted in randomized complete blocks with two replications. Each plot had three 2.5-m rows spaced 0.3 m apart. Fifty seeds for each RIL and parental cultivar were sown in each row. Weed control, fungicide treatment, and other field managements were in accordance with local standard practices. At maturity, 20 plants of each RIL and parental cultivar with similar growth stages and without disease infection were selected and marked. The mean grain number per spike (GNS) was measured as the mean grain number of 20 main-stem spikes. The selected plants were harvested and manually threshed for evaluating GW and GL with SC-G software (Wanshen Technology Company, Hangzhou, Zhejiang, China). TGW was calculated from the mean weight of three independent samples of 500 grains. GNS and TGW were used to validate the effect of the target QTL on the corresponding traits. One hundred and fifty-nine wheat cultivars/lines were planted in the yield evaluation nurseries from 2019–2020 and 2020–2021 cropping seasons at YZ for measuring GW and GL using the same protocol as RILs. Yangmai 20 (YM20) and Yanzhan 4110 (YZ4110) were used as the control for GW, GL, and TGW in the validation populations.

2.3. Statistical Analysis

All analyses were performed in Microsoft Excel 2019 and SPSS software (Chicago, IL, USA). Broad-sense heritability (HB2) for GW and GL was calculated using the formula HB2 = σ2𝐺/(σ2𝐺 + σ2 𝐺×𝐸/E + σ2e/ER), where E and R represent the number of environments and replicates, respectively; σ2𝐺 represents the genotypic variance; σ2𝐺×𝐸 represents genotype-by-environment interaction; and σ2e represents residual variance. Best linear unbiased estimator (BLUE) values and HB2 were estimated using the ANOVA function in IciMapping v4.1 [33].

2.4. Genotyping, Linkage Map Construction, and QTL Analysis

A whole-genome genetic map of the YM12/YZ1 population was previously constructed from Wheat 55 K SNP array data (unpublished). The linkage map including 1468 bin markers spanned a total length of 3610.67 cM, with 26 linkage groups assigned to 21 chromosomes with a mean distance of 2.62 cM/marker; chromosomes 1A, 6B, 1D, 2D, 3D, and 5D each had two linkage groups. Twelve Kompetitive Allele-Specific PCR (KASP) markers and eight SSR markers that are associated with known genes including Vrn-B1, Ppd-B1, Rht-B1, Rht-D1, Rht8, and Qfhb-2DL were selected for genotyping the parental cultivars and RILs [34,35,36,37]. The 660K SNP array containing 660,011 SNPs was used to scan parents YM12 and YZ1 and the SNPs corresponding to the target interval of stable and major QTL for grain size on chromosome 2D were converted into KASP markers. Then, the KASP markers were merged with other markers to construct a new linkage map of 2D (unpublished). QTL analysis was conducted using the inclusive composite interval mapping algorithm and the LOD threshold value was set at 2.5 in IciMapping V4.0 software, with walking step = 0.001 cM and PIN = 0.0005 [36,37,38]. QTL identified for the same trait situated within overlapping confidence intervals were considered to be the same one. Physical positions of linked markers were used to compare the QTL identified in the current study with the previous QTL (http://202.194.139.32/blast/blast.html) (accessed on 3 December 2021) (http://202.194.139.32/genes/) (accessed on 1 February 2022).

2.5. Marker Development and QTL Validation in Different Genetic Backgrounds

Genomic DNA was extracted from fresh leaves according to Ma and Sorrells [39] The flanking markers of the peak position for the major QTL were converted into KASP markers. KASP markers were designed following the protocols described by Xu et al. [36]. KASP assays were performed in 384-well PCR plates in a 5 μL volume with 2.5 μL of KASP 2× Reaction Mix, 0.056 μL of KASP primer mix, and 2.5 μL of genomic DNA at 30 ng/μL. Fluorescence detection of PCR products was performed with PHERAstar (BMG LABTECH, Ortenberg, Germany). KlusterCaller software (LGC Genomics, Beverly, MA, USA) was used to analyze the fluorescence results [38]. The KASP markers were remapped in the RIL population to integrate maps. To further validate these major QTL in different genetic backgrounds, the developed KASP markers were used to trace the target QTL in a panel of 64 cultivars and 95 advanced breeding lines.

2.6. Prediction of Candidate Genes for Major QTL

The primer sequence of the marker flanking each QTL was BLAST-searched against pseudomolecules of ‘Chinese Spring’ (CS) v2.1 (http://202.194.139.32/blast/blast.html) (accessed on 1 February 2022) to find their physical positions. Genes within the mapping intervals were extracted from CS v2.1 annotation (http://202.194.139.32/jbrowse-1.12.3-release) (accessed on 2 February 2022) and used in homolog searches in the UniProt database (http://www.uniprot.org/) (accessed on 2 February 2022) for functional annotation. Spatiotemporal expression patterns of candidate genes were analyzed in the Wheat Expression Browser (http://www.wheat-expression.com/) (accessed on 5 February 2022). Expression pattern analyses were conducted following Borrill et al. [40] and Li et al. [41].

3. Results

3.1. Phenotypic Variation and Correlation Analysis

Significant differences (P < 0.01) in GW and GL between YM12 and YZ1 were observed from all environments as well as the combined BLUE dataset (Table 1, Figure 1a). Broad-sense heritabilities (HB2) for GW and GL were 0.71 and 0.79, respectively (Table 1). The phenotype values of all traits based on the BLUE dataset of all trials for the YM12/YZ1 population displayed a continuous distribution and obvious transgressive segregation, suggesting the existence of polygenic inheritance (Table 1, Figure 1b). The datasets of GW and GL in all environments and BLUE values were employed to assess their correlations (Table S1). GW showed very significant positive correlations with GL from the same trial (p < 0.01) and significant positive correlations with GL from different trials (p < 0.05) (Table S1). BLUE datasets of GW and GL also had very significant positive correlations with each other (p < 0.01) (Table S1).

3.2. QTL for GW and GL

Four QTL for GW were identified on chromosomes 2D, 3B, 4B, and 6B (Table 2), respectively. Among them, QGW-yz-3B and QGW-yz-4B were associated with increasing GW alleles from YM12, whereas QGW-yz-2D and QGW-yz-6B were related to increasing GW alleles from YZ1 (Table 2). QGW-yz-2D and QGW-yz-6B were detected in all trials and the BLUE datasets, explaining 12.36–18.27% and 4.57–7.88% of the phenotypic variance, respectively (Table 2). QGW-yz-3B and QGW-yz-4B were identified in three trials and the BLUE values, explaining 4.60–9.17% and 10.34–11.95% of the phenotypic variances, respectively (Table 2).
Four QTL were identified for GL on chromosomes 1B, 2D, 4B, and 5A (Table 2), respectively. QGL-yz-1B, QGL-yz-4B, and QGL-yz-5A were associated with the increasing GL effect from YM12, whereas QGL-yz-2D had the increasing SC effect from YZ1 (Table 2). Both QGL-yz-2D and QGL-yz-4B could be identified in four trials and the BLUE values, explaining 13.69–26.53% and 10.35–16.04% of the phenotypic variances, respectively (Table 2). QGL-yz-5A was detected in three trials and the BLUE values, explaining 10.04–12.48% of the phenotypic variances (Table 2). QGL-yz-1B was identified in two trials and the BLUE dataset, explaining 3.17–4.57% of the phenotypic variances (Table 2).

3.3. Effect of Major QTL QGW.yz.2D/QGL.yz.2D, QGW.yz.4B/QGL.yz.4B and QGL-yz-5A on GNS and TGW in the Mapping Population

AX109059601, AX108819885, and AX110003317 flanking the peak intervals of the major QTL QGW.yz.2D/QGL.yz.2D, QGW.yz.4B/QGL.yz.4B, and QGL-yz-5A, were used to evaluate the effects of these regions on GNS and TGW with the BLUE dataset from four environments. The YZ1 allele at QGW.yz.2D/QGL.yz.2D had an extremely significant negative effect on GNS (p < 0.001), while it increased 5.77% of TGW (Figure 2). The YM12 allele at QGW.yz.4B/QGL.yz.4B increased 4.02% of TGW, and the YM12 allele at QGL-yz-5A increased 2.10% of TGW (Figure 3 and Figure 4). These two alleles did not have significant negative effect on GNS (Figure 3 and Figure 4).

3.4. Additive Effects of the Major QTL

Different major QTL for GW and GL showed additive effects with lines without any of the positive alleles that had the lowest GW and GL (p < 0.01) (Figure 5). For GW, lines with one of the positive alleles increased GW by 1.18–2.66% and lines with both positive alleles increased GW by 4.44% (p < 0.01) (Figure 5a). For GL, lines with one of the positive alleles for GL increased GL by 3.73%, 3.27%, or 1.56%, respectively; lines with positive alleles at two loci increased GL by 6.22–8.56%; and lines with positive alleles at all three loci increased GL by 10.26% (Figure 5b).

3.5. Development and Evaluation of Breeder-Friendly KASP Markers for Major QTL and Validation of These QTL in 159 Wheat Cultivars/Lines

Among the QTL detected for GW and GL, QGW-yz-2D/QGL-yz-2D, QGW-yz-4B/QGL-yz-4B, and QGL-yz-5A had larger effects on GW or GL. We converted the SNP markers AX109059601, AX108819885, and AX110003317, which flanked the peak intervals of QGW-yz-2D/QGL-yz-2D, QGW-yz-4B/QGL-yz-4B, and QGL-yz-5A, into KASP markers KASP_2D, KASP_4B, and KASP_5A (Figure 6a–c and Table S2). A collection of 159 wheat cultivars and lines were evaluated for GW and GL and surveyed using the three KASP markers. The list of 159 wheat cultivars/lines and their genotypes and phenotypes were shown in Table S3. To compare the additive allelic effects of “QGW-yz-2D + QGW-yz-4B” on GW and “QGL-yz-2D + QGL-yz-4B + QGL-yz-5A” on GL, all cultivars/lines in the panel was divided into four and eight groups based on their allele combinations. For GW, the group carrying the YZ1 allele at QGW-yz-2D and the YM12 allele at QGW-yz-4B showed 7.12% higher GW than cultivars/lines without positive alleles. The group carrying the YZ allele at QGW-yz-2D and the YZ allele at QGW-yz-4B had similar GW to those with the YM12 allele at QGW-yz-2D or YM12 allele at QGW-yz-4B, increasing GW by 4.64–5.26% (Figure 6d). GL of the group with the three positive alleles was 6.95 mm, 6.60% longer than cultivars/lines without positive alleles (P < 0.05) (Figure 6e). Lines with a positive allele for GL at one of QGL.yz.2D, QGL.yz.4B, or QGL-yz-5A increased GL by 1.84–2.91% (Figure 6e). The groups that carried two positive allele combinations had 3.22–5.37% longer GL than cultivars/lines without positive alleles (Figure 6e).

3.6. Potential Candidate Genes for QGW-yz-2D/QGL-yz-2D, QGW-yz-4B/QGL-yz-4B, and QGL-yz-5A

We attempted to predict potential candidate genes for the three major QTL. In the QGW-yz-2D/QGL-yz-2D interval on the CS genome, there are 59 annotated high-confidence genes (Table S4). Expression pattern analyses showed that 16 genes were expressed in grain and two of them were expressed more highly in grain than in root, leaf, stem, and spike (Figure 2d). Gene annotation analysis indicated that TraesCS2D03G0934600 and TraesCS2D03G0935700 are likely associated with encoding the ethylene-responsive transcription factor and oleosin, respectively (Table S4). In the QGW-yz-4B/QGL-yz-4B interval on the CS genome, there are 66 annotated high-confidence genes (Table S4). Thirty-one genes were expressed in grain and only TraesCS4B03G0630100 was expressed more highly in grain than in root, leaf, stem, and spike. However, TraesCS4B03G0630100 does not have annotation (Figure 3d, Table S4). In the QGL-yz-5A interval on the CS genome, there are 59 annotated high-confidence genes (Table S4). Twenty-four genes were expressed in grain and eight of them had higher expression levels in grain than in root, leaf, stem, and spike (Figure 4d). Among the eight genes, TraesCS5A03G0044100 is likely to be associated with encoding osmotin protein while TraesCS5A03G0043700, TraesCS5A03G0044700, TraesCS5A03G0044900, TraesCS5A03G0045000, TraesCS5A03G0045100, and TraesCS5A03G0045200 are probably involved in encoding thaumatin protein. Moreover, TraesCS5A03G0045900 does not have annotation (Table S4).

4. Discussion

4.1. Comparison of QTL for GW and GL with Those in Previous Studies

A previous QTL cluster QW-1B.1 (49.93–53.25 Mb), consisting of QTL for grain area (GA), grain diameter (GD), grain perimeter (GP), GL, and thousand-grain weight [21], was mapped distal to QGL-yz-1B (697.54–698.30Mb) detected in the current study. Another two QTL clusters QKw/l.caas-1B.1 and QKw/l.caas-1B.2 were mapped at the locus of 634.96 Mb and 673.08 Mb on chromosome 1B, respectively [42], and were also mapped distal from QGL-yz-1B. Thus, QGL-yz-1B is likely a new QTL for GL (Table 2). QGW-yz-2D (526.61–530.23 Mb) was co-located with QGL-yz-2D (528.04–530.23 Mb) (Figure 2). Several QTL for GW (QGw, 546.76–580.68 Mb, [43]) or TGW (QTKW-2D-AN, 502.38 Mb, [44]; Q.TKW.ui-2D-1, 553.73 Mb, [45]; qTKW-2D.4, 582.64 Mb, [46]) were identified distal from QGW-yz-2D/QGL-yz-2D. No previous QTL for GL was identified at this genomic region of 2D. Whether QGW-yz-2D is a novel QTL still needs to be verified by fine mapping and gene cloning. QW-3B (28.00–29.36 Mb, [21]) was detected for GW via nested association mapping and overlapped with QGW.yz.3B (25.76–28.27 Mb) detected in the current study (Table 2). QGw.cib-4B.2 and QTgw.cib-4B were mapped at the interval of 604.91 to 612.03 Mb [41]. Rht-B1 (30.86Mb) was reported to be associated with grain size and weight [5]. QGW-yz-4B and QGL-yz-4B were co-located, corresponding to 470.98–490.23 Mb on chromosome 4B (Figure 3), which were physically separated from QGw.cib-4B.2, QTgw.cib-4B, QGl.cau-4B-1, QGl.cau-4B-2, and QGw.cau-4B [5,41,47]. Jia et al. [48] identified a QTL for TGW named QGw.nau-4B flanked by SSR marker GWM495, which also flanked with QGW-yz-4B/QGL-yz-4B detected in the current study. In this study, QGW-yz-4B and QGL-yz-4B contributed to the increasing GW and GL effects from YM12, which had been crossed with Zhoumai 16 into two elite cultivars Luxuan 66 and Luxuan 166 released in YRVWZ. A polymorphism survey was also carried out using KASP_4B; we found that Zhoumai 16 lacked the increasing GW/GL allele from YM12, while Luxuan 66 and Luxuan 166 contained the increasing GW/GL allele from YM12, indicating that YM12 allele of QGW-yz-4B/QGL-yz-4B is probably to be retained due to its great value for yield improvement. QGL-yz-5A was located at the interval of 11.89–14.20 Mb on chromosome 5A (Figure 4), differently from two GL associated genes TaARF25-5A (35.63 Mb, [49]) and TaGL3.3-5A (571.78–571.79 Mb, [50]). QGL-yz-5A detected in the current study is likely to be a novel QTL for GL [41,49,50]. QGW-yz-6B (212.74–477.22 Mb) was located at the overlapped interval of QKw/l.caas-6B (404.98 Mb) identified by Xiao et al. [42] (Table 2).

4.2. Pyramiding of Major QTL for GW and GL Improvement

Pyramiding the favorable alleles from elite cultivars/lines is an effective method to obtain desired ideal cultivars with improved yield [41,51]. Utilizing accessions derived from a different ecological area can be an effective way to broaden the genetic diversity of local breeding materials for breeders. Dissection of the effects of major QTL on corresponding traits in the mapping population indicated that YZ1 allele at QGW.yz.2D/QGL.yz.2D and QGW.yz.4B/QGL.yz.4B and the YM12 allele at QGL-yz-5A had positive effects on improving TGW as well as GW or GL. The significant additive effect indicated that pyramiding of the major loci facilitated by using the developed KASP markers could be utilized as applicable strategy to optimize grain size in wheat breeding. YZ1 and YM12 are two elite cultivars released in YRVWZ and the MLYVWZ, respectively. The KASP markers developed in this study could be utilized to efficiently pyramid these loci through MAS. Among the validated population, 71 cultivars/lines are suitable for planting in MLYVWZ, and 88 cultivars/lines are suitable for planting in YRVWZ (Table S3). For QGW.yz.2D/QGL.yz.2D, only 29.58% of the cultivars/lines from MLYVWZ have positive alleles, while 81.82% of the cultivars/lines from YRVWZ carry positive alleles. For QGW.yz.4B/QGL.yz.4B, 46.48% of the cultivars/lines from MLYVWZ have positive alleles, while 75% of the cultivars/lines from YRVWZ carry positive alleles. For QGL-yz-5A, 54.93% of the cultivars/lines from MLYVWZ have positive alleles, while 69.32% of the cultivars/lines from YRVWZ carry positive alleles. All of the above results suggest that these three positive alleles have been used more frequently in wheat breeding programs in YRVWZ, which was consistent with the finding that the average GW and GL of the cultivars/lines from YRVWZ are 3.40 mm and 6.86 mm, which are 1.20% and 2.85% higher than those from MLYVWZ. For YZ1 allele from QGW.yz.2D/QGL.yz.2D, due to its negative effect on the GNS, it mainly exists in the cultivars/lines in YRVWZ and has been used with difficulty in wheat breeding programs in MLYVWZ. Further fine-mapping and map-based cloning of QGW.yz.2D/QGL.yz.2D for grain size would facilitate better use of this QTL in wheat breeding. There are only 12.58% of the 159 cultivars/lines simultaneously harboring these three positive alleles, indicating that the combining of the three favorable alleles has great potential for breeding programs.

4.3. Potential Candidate Genes for QGW-yz-2D/QGL-yz-2D, QGW-yz-4B/QGL-yz-4B, and QGL-yz-5A

Among the genes in the intervals of the major QTL identified in the current study, a total of eleven genes showed significantly higher expression levels in grain than in root, leaf, stem, and spike, indicating that they are likely associated with grain growth and developmental processes. Gene annotation and ortholog analysis showed that TraesCS2D03G0934600 acts as a transcriptional activator, binding to the GCC-box pathogenesis-related promoter element and is involved in the regulation of gene expression by stress factors and by components of stress signal transduction pathways in Arabidopsis thaliana [52,53]. TraesCS2D03G0935700 might have a structural role to stabilize the lipid body during desiccation of the seed by preventing coalescence of the oil and probably interacting with both lipid and phospholipid moieties of lipid bodies in Rye brome (https://www.uniprot.org/uniprot/Q96543) (accessed on 2 March 2022). TraesCS5A03G0044100 encodes the osmotin protein OSML13 involved in response to stress, a change in state or activity of a cell or an organism as a result of some stressful conditions (https://www.uniprot.org/uniprot/P50701) (accessed on 2 March 2022). TraesCS5A03G0043700 encodes thaumatin protein in Actinidia deliciosa (kiwi). TraesCS5A03G0044700, TraesCS5A03G0044900, TraesCS5A03G0045000, TraesCS5A03G0045100, and TraesCS5A03G0045200 are associated with the thaumatin protein in rice [54]. Os12g0629600 is the ortholog gene of these five candidate genes [51], indicating that these five genes are homologous and have the conserved site. Moreover, TraesCS4B03G0630100 and TraesCS5A03G0045900 do not have annotation in Chinese Spring genome (http://wheat.cau.edu.cn/TGT/ann_db/) (accessed on 5 March 2022). The function of these candidate genes in the growth of grain would be elucidated by cloning and gene editing.

5. Conclusions

In the current study, four QTL for GW and four QTL for GL were identified in the YM12/YZ1 population. Among them, QGW.yz.2D/QGL.yz.2D, QGW.yz.4B/QGL.yz.4B, and QGL-yz-5A were three major QTL regions. QGL.yz.2D, QGW.yz.4B/QGL.yz.4B, and QGL-yz-5A are more likely novel QTL. The additive effects of the positive alleles of the major QTL on corresponding traits in the validation population are significant. Eleven potential candidate genes in the interval of the major QTL were expressed significantly more highly in grain than root, leaf, stem, and spike by spatial expression patterns. These results lay a foundation for further fine-mapping and map-based cloning of these major QTL for grain size. In addition, three breeder-friendly markers KASP_2D, KASP_4B, and KASP_5A for QGW.yz.2D/QGL.yz.2D, QGW.yz.4B/QGL.yz.4B, and QGL-yz-5A, respectively, would be useful for marker-assisted selection in wheat breeding programs.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/agriculture12060822/s1. Table S1: Pearson’s correlation coefficients among traits of different environments in the Yangmai 12/Yanzhan 1 population; Table S2: Primers for Kompetitive Allele Specific PCR markers KASP_2D, KASP_4B, and KASP_5A; Table S3: Distribution of detected QTL related with grain width and grain length in 117 cultivars and advanced lines planted in the yield evaluation nursery; Table S4: Prediction of candidate genes for the genomic regions of QGW.yz.2D/QGL.yz.2D, QGW.yz.4B/QGL.yz.4B, and QGL.yz.5A.

Author Contributions

W.H., formal analysis, writing—original draft, and writing—review and editing; S.C., conceptualization, project administration, resources, and supervision; S.L., D.Z., J.J. and W.X., investigation, methodology, and data curation. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Natural Science Foundation of China (31901544, 32071999), and the National Key Research and Development Program of Jiangsu (BE2021335). The APC was funded by the National Natural Science Foundation of China (31901544).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data that support the findings of this study are available in the main body of the paper.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. (a) Grain morphology of two parents in Sihong Experimental Station of 2020. The scale bar represents 3 mm; (b) Frequency distribution of the YM12/YZ1 population for grain width and grain length of the BLUE datasets in the YM12/YZ1 population. BLUE represents the best linear unbiased estimator. YM12 represents Yangmai 12, YZ1 represents Yanzhan 1, and YM12/YZ1 represents Yangmai 12/Yanzhan 1 population.
Figure 1. (a) Grain morphology of two parents in Sihong Experimental Station of 2020. The scale bar represents 3 mm; (b) Frequency distribution of the YM12/YZ1 population for grain width and grain length of the BLUE datasets in the YM12/YZ1 population. BLUE represents the best linear unbiased estimator. YM12 represents Yangmai 12, YZ1 represents Yanzhan 1, and YM12/YZ1 represents Yangmai 12/Yanzhan 1 population.
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Figure 2. Allelic effects (a), genetic maps (b), physical locations (c), and expression patterns of genes (d) in the physical interval of major quantitative trait loci (QTL) QGW.yz.2D/QGL.yz.2D. In allelic effects (a), A and B indicated the lines with the alleles from YM12 and YZ1, respectively; *** represents significance at p < 0.001; ns represents non-significance. In the genetic maps (b), the names of the markers are listed on the right side of the corresponding linkage group, and their genetic positions and QTL names are shown on the left (cM). The red rectangles at the chromosomes represent QTL regions. Blue blocks represent QTLs for grain width, and green blocks represent QTLs for grain length. In the expression patterns of genes (d), the red arrows represent the genes that were more highly expressed in grain or both in grain and whole endosperm than in root, leaf, stem, and spike. GW, grain width; GL, grain length; GNS, grain number per spike; TGW, thousand-grain weight. YM12, Yangmai 12; YZ1, Yangzhan 1.
Figure 2. Allelic effects (a), genetic maps (b), physical locations (c), and expression patterns of genes (d) in the physical interval of major quantitative trait loci (QTL) QGW.yz.2D/QGL.yz.2D. In allelic effects (a), A and B indicated the lines with the alleles from YM12 and YZ1, respectively; *** represents significance at p < 0.001; ns represents non-significance. In the genetic maps (b), the names of the markers are listed on the right side of the corresponding linkage group, and their genetic positions and QTL names are shown on the left (cM). The red rectangles at the chromosomes represent QTL regions. Blue blocks represent QTLs for grain width, and green blocks represent QTLs for grain length. In the expression patterns of genes (d), the red arrows represent the genes that were more highly expressed in grain or both in grain and whole endosperm than in root, leaf, stem, and spike. GW, grain width; GL, grain length; GNS, grain number per spike; TGW, thousand-grain weight. YM12, Yangmai 12; YZ1, Yangzhan 1.
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Figure 3. Allelic effects (a), genetic maps (b), physical locations (c), and expression patterns of genes (d) in the physical interval of major quantitative trait loci (QTL) QGW.yz.4B/QGL.yz.4B. In allelic effects (a), A and B indicated the lines with the alleles from YM12 and YZ1, respectively; *** represents significance at P < 0.001; ns represents non-significance. In the genetic maps (b), the names of the markers are listed on the right side of the corresponding linkage group, and their genetic positions and QTL names are shown on the left (cM). The red rectangles at the chromosomes represent QTL regions. Blue blocks represent QTLs for grain width, and green blocks represent QTLs for grain length. In the expression patterns of genes (d), the red arrows represent the genes that were more highly expressed in grain or both in grain and whole endosperm than in root, leaf, stem, and spike. GW, grain width; GL, grain length; GNS, grain number per spike; TGW, thousand-grain weight. YM12, Yangmai 12; YZ1, Yangzhan 1.
Figure 3. Allelic effects (a), genetic maps (b), physical locations (c), and expression patterns of genes (d) in the physical interval of major quantitative trait loci (QTL) QGW.yz.4B/QGL.yz.4B. In allelic effects (a), A and B indicated the lines with the alleles from YM12 and YZ1, respectively; *** represents significance at P < 0.001; ns represents non-significance. In the genetic maps (b), the names of the markers are listed on the right side of the corresponding linkage group, and their genetic positions and QTL names are shown on the left (cM). The red rectangles at the chromosomes represent QTL regions. Blue blocks represent QTLs for grain width, and green blocks represent QTLs for grain length. In the expression patterns of genes (d), the red arrows represent the genes that were more highly expressed in grain or both in grain and whole endosperm than in root, leaf, stem, and spike. GW, grain width; GL, grain length; GNS, grain number per spike; TGW, thousand-grain weight. YM12, Yangmai 12; YZ1, Yangzhan 1.
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Figure 4. Allelic effects (a), genetic maps (b), physical locations (c), and expression patterns of genes (d) in the physical interval of major quantitative trait loci (QTL) QGL.yz.5A. In allelic effects (a), A and B indicated the lines with the alleles from YM12 and YZ1, respectively; * represents significance at p < 0.05; ns represents non-significance. In the genetic maps (b), the names of the markers are listed on the right side of the corresponding linkage group, and their genetic positions and QTL names are shown on the left (cM). The red rectangles at the chromosomes represent QTL regions. Blue blocks represent QTLs for grain width, and green blocks represent QTLs for grain length. In the expression patterns of genes (d), the red arrows represent the genes that were more highly expressed in grain or both in grain and whole endosperm than in root, leaf, stem, and spike. GW, grain width; GL, grain length; GNS, grain number per spike; TGW, thousand-grain weight. YM12, Yangmai 12; YZ1, Yangzhan 1.
Figure 4. Allelic effects (a), genetic maps (b), physical locations (c), and expression patterns of genes (d) in the physical interval of major quantitative trait loci (QTL) QGL.yz.5A. In allelic effects (a), A and B indicated the lines with the alleles from YM12 and YZ1, respectively; * represents significance at p < 0.05; ns represents non-significance. In the genetic maps (b), the names of the markers are listed on the right side of the corresponding linkage group, and their genetic positions and QTL names are shown on the left (cM). The red rectangles at the chromosomes represent QTL regions. Blue blocks represent QTLs for grain width, and green blocks represent QTLs for grain length. In the expression patterns of genes (d), the red arrows represent the genes that were more highly expressed in grain or both in grain and whole endosperm than in root, leaf, stem, and spike. GW, grain width; GL, grain length; GNS, grain number per spike; TGW, thousand-grain weight. YM12, Yangmai 12; YZ1, Yangzhan 1.
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Figure 5. Additive effects of QGL.yz.2D and QGL.yz.4B on grain width (a) and additive effects of QGL.yz.2D, QGL.yz.4B, and QGL.yz.5A on grain length (b) based on the BLUE datasets in the YM12/YZ1 population. A and B indicated the lines with the alleles from YM12 and YZ1, respectively. The different letters are significant at p < 0.05. GW, grain width; GL, grain length; GNS, grain number per spike; TGW, thousand-grain weight. YM12, Yangmai 12; YZ1, Yangzhan 1.
Figure 5. Additive effects of QGL.yz.2D and QGL.yz.4B on grain width (a) and additive effects of QGL.yz.2D, QGL.yz.4B, and QGL.yz.5A on grain length (b) based on the BLUE datasets in the YM12/YZ1 population. A and B indicated the lines with the alleles from YM12 and YZ1, respectively. The different letters are significant at p < 0.05. GW, grain width; GL, grain length; GNS, grain number per spike; TGW, thousand-grain weight. YM12, Yangmai 12; YZ1, Yangzhan 1.
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Figure 6. Kompetitive Allele-Specific PCR array and additive effects of the major QTL in the validation population. (a) KASP_2D; (b) KASP_4B; (c) KASP_5A. Blue dots represent the YM12-like genotypes, red dots represent the YZ1-like genotypes, and black dots in (a–c) are water controls. YM12 represents Yangmai 12, YZ1 represents Yanzhan 1. (d) Additive effects of QGW.yz.2D/QGL.yz.2D and QGW.yz.4B/QGL.yz.4B on grain width; (e) Additive effects of QGW.yz.2D/QGL.yz.2D, QGW.yz.4B/QGL.yz.4B, and QGL.yz.5A on grain length. A and B indicated the lines with the alleles from YM12 and YZ1, respectively. The different letters are significant at p < 0.05. GW, grain width; GL, grain length; GNS, grain number per spike; TGW, thousand-grain weight. YM12, Yangmai 12; YZ1, Yangzhan 1.
Figure 6. Kompetitive Allele-Specific PCR array and additive effects of the major QTL in the validation population. (a) KASP_2D; (b) KASP_4B; (c) KASP_5A. Blue dots represent the YM12-like genotypes, red dots represent the YZ1-like genotypes, and black dots in (a–c) are water controls. YM12 represents Yangmai 12, YZ1 represents Yanzhan 1. (d) Additive effects of QGW.yz.2D/QGL.yz.2D and QGW.yz.4B/QGL.yz.4B on grain width; (e) Additive effects of QGW.yz.2D/QGL.yz.2D, QGW.yz.4B/QGL.yz.4B, and QGL.yz.5A on grain length. A and B indicated the lines with the alleles from YM12 and YZ1, respectively. The different letters are significant at p < 0.05. GW, grain width; GL, grain length; GNS, grain number per spike; TGW, thousand-grain weight. YM12, Yangmai 12; YZ1, Yangzhan 1.
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Table
Table 1. Phenotypic variation and heritability (HB2) of grain width and grain length for the parents and the derived RILs in different environments.
Table 1. Phenotypic variation and heritability (HB2) of grain width and grain length for the parents and the derived RILs in different environments.
TraitEnv aParents bPopulationHB2
Yangmai 12Yanzhan 1MinMaxMean
Grain width (mm)E13.483.26 **2.93 3.85 3.42 0.71
E23.513.34 **3.15 3.83 3.47
E33.463.28 **2.91 3.88 3.42
E43.593.40 **3.05 3.81 3.45
BLUE3.523.33 **3.04 3.76 3.44
Grain length (mm)E16.846.48 **5.97 7.56 6.71 0.79
E27.086.54 **6.09 7.99 6.90
E36.776.46 **5.17 7.64 6.49
E47.126.69 **6.05 7.83 6.90
BLUE7.056.53 **6.04 7.48 6.71
a E1, Yangzhou Experimental Station of 2020; E2, Sihong Experimental Station of 2020; E3, Yangzhou Experimental Station of 2021; E4, Sihong Experimental Station 2021; BLUE represents the best linear unbiased estimator; b ** indicates different between Yangmai 12 and Yanzhan 1 at p < 0.01.
Table
Table 2. QTL identified for grain width and grain length across multiple environments in the RIL population.
Table 2. QTL identified for grain width and grain length across multiple environments in the RIL population.
TraitQTLEnv aPhysical
Interval (Mb) b		Flanking MarkersLOD cPVE d (%)Add eQTL/Genes
Reported f
Grain widthQGW.yz.2DE1526.61–528.04AX109864938–KASP.AX1109824038.6512.36−0.06Not found
E2529.23–530.23AX109059601–AX1087673819.2115.41−0.06
E3529.23–530.23AX109059601–AX1087673819.8616.91−0.07
E4529.23–530.23AX109059601–AX10876738110.5818.27−0.06
BLUE529.23–530.23AX109059601–AX1087673819.1414.64−0.05
QGW.yz.3BE126.67–28.40AX108858972–AX1089067273.424.600.04Wang et al. (2019)
E225.76–26.67AX109430505–AX1088589725.235.780.04
E326.67–28.40AX108858972–AX1089067273.435.450.04
BLUE26.67–28.40AX108858972–AX1089067277.979.170.04
QGW.yz.4BE1482.02–490.23GWM495–AX1088198857.0711.950.06Not found
E2482.02–490.23GWM495–AX1088198858.1511.470.09
E4482.02–490.23GWM495–AX1088198857.3910.340.09
BLUE482.02–490.23GWM495–AX1088198856.7210.740.03
QGW.yz.6BE1212.74–477.22AX109290430–AX1105844163.785.10−0.04Xiao et al. (2011)
E2212.74–477.22AX109290430–AX1105844166.226.81−0.04
E3212.74–477.22AX109290430–AX1105844162.884.57−0.04
E4212.74–477.22AX109290430–AX1105844163.027.39−0.04
BLUE212.74–477.22AX109290430–AX1105844166.937.88−0.04
Grain lengthQGL.yz.1BE2697.54–698.30AX111622338–AX1109723944.94.570.07Xiao et al. (2011)
E3697.54–698.30AX111622338–AX1109723942.963.810.07
BLUE697.54–698.30AX111622338–AX1109723942.993.170.06
QGL.yz.2DE1528.04–529.23KASP.AX110982403–AX10905960112.5713.69−0.12Not found
E2528.04–529.23KASP.AX110982403–AX10905960123.926.53−0.18
E3529.23–530.23AX109059601–AX10876738111.4616.27−0.15
E4529.23–530.23AX109059601–AX10876738113.8320.62−0.12
BLUE528.04–529.23KASP.AX110982403–AX10905960118.3823.31−0.15
QGL.yz.4BE1470.98–482.02AX111115843–GWM4959.8310.350.11Not found
E2482.02–490.23GWM495–AX10881988512.4513.830.12
E3470.98–482.02AX111115843–GWM4957.9311.050.13
E4482.02–490.23GWM495–AX10881988510.5812.490.15
BLUE482.02–490.23GWM495–AX10881988513.3116.040.13
QGL.yz.5AE111.89–14.20AX109365651–AX1116484027.4510.040.12Not found
E214.20–19.08AX111648402–AX1100033176.6312.480.11
E411.89–14.20AX109365651–AX1116484025.2910.280.13
BLUE14.20–19.08AX111648402–AX1100033176.9111.580.09
a E1, Yangzhou Experimental Station of 2020; E2, Sihong Experimental Station of 2020; E3, Yangzhou Experimental Station of 2021; E4, Sihong Experimental Station 2021; BLUE represents the best linear unbiased estimator; b The physical location is based on the Chinese Spring 2.1 reference genome (RefSeq v2.1); c LOD, logarithm of odds; d PVE, phenotypic variation explained; e Add, additive effect (positive values indicate that alleles from Yangmai 12 are increasing the grain width and grain length, and negative values indicate that alleles from Yanzhan 1 are increasing the grain width and grain length); f QTL/genes reported, the reported QTL mapped near or in the overlapped interval of the QTL detected in the current study. Not found, the QTL detected in the current study does not overlapped with the previous QTL.
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Hu, W.; Liao, S.; Zhao, D.; Jia, J.; Xu, W.; Cheng, S. Identification and Validation of Quantitative Trait Loci for Grain Size in Bread Wheat (Triticum aestivum L.). Agriculture 2022, 12, 822. https://doi.org/10.3390/agriculture12060822

AMA Style

Hu W, Liao S, Zhao D, Jia J, Xu W, Cheng S. Identification and Validation of Quantitative Trait Loci for Grain Size in Bread Wheat (Triticum aestivum L.). Agriculture. 2022; 12(6):822. https://doi.org/10.3390/agriculture12060822

Chicago/Turabian Style

Hu, Wenjing, Sen Liao, Die Zhao, Jizeng Jia, Weigang Xu, and Shunhe Cheng. 2022. "Identification and Validation of Quantitative Trait Loci for Grain Size in Bread Wheat (Triticum aestivum L.)" Agriculture 12, no. 6: 822. https://doi.org/10.3390/agriculture12060822

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