Kernel morphometric traits in hexaploid wheat (Triticum aestivum L.) are modulated by intricate QTL × QTL and genotype × environment interactions

Genome-wide association analysis of spike and kernel traits in the U.S. hard winter wheat

A better understanding of the genetic control of spike and kernel traits that have higher heritability can help in the development of high-yielding wheat varieties. Here, we identified the marker-trait associations (MTAs) for various spike- and kernel-related traits in winter wheat (Triticum aestivum L.) through genome-wide association studies (GWAS). An association mapping panel comprising 297 hard winter wheat accessions from the U.S. Great Plains was evaluated for eight spike- and kernel-related traits in three different environments. A GWAS using 15,590 single-nucleotide polymorphisms (SNPs) identified a total of 53 MTAs for seven spike- and kernel-related traits, where the highest number of MTAs were identified for spike length (16) followed by the number of spikelets per spike (15) and spikelet density (11). Out of 53 MTAs, 14 were considered to represent stable quantitative trait loci (QTL) as they were identified in multiple environments. Five multi-trait MTAs were identified for various traits including the number of spikelets per spike (NSPS), spikelet density (SD), kernel width (KW), and kernel area (KA) that could facilitate the pyramiding of yield-contributing traits. Further, a significant additive effect of accumulated favorable alleles on the phenotype of four spike-related traits suggested that breeding lines and cultivars with a higher number of favorable alleles could be a valuable resource for breeders to improve yield-related traits. This study improves the understanding of the genetic basis of yield-related traits in hard winter wheat and provides reliable molecular markers that will facilitate marker-assisted selection (MAS) in wheat breeding programs.

Identification of quantitative trait loci (QTL) and meta-QTL analysis for kernel size-related traits in wheat (Triticum aestivum L.)

BACKGROUND

Kernel size-related traits, including kernel length (KL), kernel width (KW), kernel diameter ratio (KDR) and kernel thickness (KT), are critical determinants for wheat kernel weight and yield and highly governed by a type of quantitative genetic basis. Genome-wide identification of major and stable quantitative trait loci (QTLs) and functional genes are urgently required for genetic improvement in wheat kernel yield. A hexaploid wheat population consisting of 120 recombinant inbred lines was developed to identify QTLs for kernel size-related traits under different water environments. The meta-analysis and transcriptome evaluation were further integrated to identify major genomic regions and putative candidate genes.

RESULTS

The analysis of variance (ANOVA) revealed more significant genotypic effects for kernel size-related traits, indicating the moderate to high heritability of 0.61-0.89. Thirty-two QTLs for kernel size-related traits were identified, explaining 3.06%-14.2% of the phenotypic variation. Eleven stable QTLs were detected in more than three water environments. The 1103 original QTLs from the 34 previous studies and the present study were employed for the MQTL analysis and refined into 58 MQTLs. The average confidence interval of the MQTLs was 3.26-fold less than that of the original QTLs. The 1864 putative candidate genes were mined within the regions of 12 core MQTLs, where 70 candidate genes were highly expressed in spikes and kernels by comprehensive analysis of wheat transcriptome data. They were involved in various metabolic pathways, such as carbon fixation in photosynthetic organisms, carbon metabolism, mRNA surveillance pathway, RNA transport and biosynthesis of secondary metabolites.

CONCLUSIONS

Major genomic regions and putative candidate genes for kernel size-related traits in wheat have been revealed by an integrative strategy with QTL linkage mapping, meta-analysis and transcriptomic assessment. The findings provide a novel insight into understanding the genetic determinants of kernel size-related traits and will be useful for the marker-assisted selection of high yield in wheat breeding.

Colored wheat and derived products: key to global nutritional security

Ensuring food and nutritional security of fast-growing population will pose a huge challenge in future. An estimated one-half population who does not go hungry, nonetheless suffers the debilitating effects of unhealthy diets. In view of the nutritional awareness, when the major wheat breeding programs have started shifting to quality, instead of quantity in wheat, the colored wheats give a novel twist of targeting the malnutrition by enhancing the antioxidants such as anthocyanin, carotenoids, flavonoids, polyphenols etc. Moreover, changing consumer demands have picked the trend to prefer a nutritionally balanced diet over the conventional high energy diets and thus, colored wheat has opened up a hidden avenue for providing additional value to the wheat-based products. Besides providing nutrition, these pigments have the potential to replace the synthetic dyes and food colorants prevalent in the market. The review summarizes the genetics and biochemistry of the pigments of colored wheat along with their product development, nutritional status and consumer preference. The review also sheds light on the environmental effect on color accumulation and the effect of increased colorants on other quality traits of wheat.

Quick mapping and characterization of a co-located kernel length and thousand-kernel weight-related QTL in wheat

A co-located KL and TKW-related QTL with no negative effect on PH and AD was rapidly identified using BSA and wheat 660 K SNP array. Its effect was validated in a panel of 218 wheat accessions. Kernel length (KL) and thousand-kernel weight (TKW) of wheat (Triticum aestivum L.) contribute significantly to kernel yield. In the present study, a recombinant inbred line (RIL) population derived from the cross between the wheat line S849-8 with larger kernels and more spikelets per spike and the line SY95-71 was developed. Further, of both the bulked segregant analysis (BSA) and the wheat 660 K single nucleotide polymorphism (SNP) array were used to rapidly identify genomic regions for kernel-related traits from this RIL population. Kompetitive Allele Specific PCR markers were further developed in the SNP-enriched region on the 2D chromosome to construct a genetic map. Both QKL.sicau-SSY-2D for KL and QTKW.sicau-SSY-2D for TKW were identified at multiple environments on chromosome arm 2DL. These two QTLs explained 9.68-23.02% and 6.73-18.32% of the phenotypic variation, respectively. The effects of this co-located QTL were successfully verified in a natural population consisting of 218 Sichuan wheat accessions. Interestingly, the major QTL was significantly and positively correlated with spike length, but did not negatively affect spikelet number per spike (SNS), plant height, or anthesis date. These results indicated that it is possible to synchronously improve kernel weight and SNS by using this QTL. Additionally, several genes associated with kernel development and filling rate were predicted and sequenced in the QTL-containing physical intervals of reference genomes of 'Chinese spring' and Aegilops tauschii. Collectively, these results provide a QTL with great breeding potential and its linked markers which should be helpful for fine mapping and molecular breeding.

GWAS for main effects and epistatic interactions for grain morphology traits in wheat

In the present study in wheat, GWAS was conducted for identification of marker trait associations (MTAs) for the following six grain morphology traits: (1) grain cross-sectional area (GCSA), (2) grain perimeter (GP), (3) grain length (GL), (4) grain width (GWid), (5) grain length-width ratio (GLWR) and (6) grain form-density (GFD). The data were recorded on a subset of spring wheat reference set (SWRS) comprising 225 diverse genotypes, which were genotyped using 10,904 SNPs and phenotyped for two consecutive years (2017-2018, 2018-2019). GWAS was conducted using five different models including two single-locus models (CMLM, SUPER), one multi-locus model (FarmCPU), one multi-trait model (mvLMM) and a model for Q x Q epistatic interactions. False discovery rate (FDR) [P value -log10(p) ≥ 5] and Bonferroni correction [P value -log10(p) ≥ 6] (corrected p value < 0.05) were applied to eliminate false positives due to multiple testing. This exercise gave 88 main effect and 29 epistatic MTAs after FDR and 13 main effect and 6 epistatic MTAs after Bonferroni corrections. MTAs obtained after Bonferroni corrections were further utilized for identification of 55 candidate genes (CGs). In silico expression analysis of CGs in different tissues at different parts of the seed at different developmental stages was also carried out. MTAs and CGs identified during the present study are useful addition to available resources for MAS to supplement wheat breeding programmes after due validation and also for future strategic basic research.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12298-022-01164-w.

Genetic dissection of quantitative trait loci for grain size and weight by high-resolution genetic mapping in bread wheat (Triticum aestivum L.)

Six major QTLs for wheat grain size and weight were identified on chromosomes 4A, 4B, 5A and 6A across multiple environments, and were validated in different genetic backgrounds. Grain size and weight are crucial components of wheat yield. Dissection of their genetic control is thus essential for the improvement of yield potential in wheat breeding. We used a doubled haploid (DH) population to detect quantitative trait loci (QTLs) for grain width (GW), grain length (GL), and thousand grain weight (TGW) in five environments. Six major QTLs, QGw.cib-4B.2, QGl.cib-4A, QGl.cib-5A.1, QGl.cib-6A, QTgw.cib-4B, and QTgw.cib-5A, were consistently identified in at least three individual environments and in best linear unbiased prediction (BLUP) datasets, and explained 5.65-34.06% of phenotypic variation. QGw.cib-4B.2, QTgw.cib-4B, QGl.cib-5A.1 and QGl.cib-6A had no effect on grain number per spike (GNS). In addition to QGl.cib-4A, the other major QTLs were further validated by using Kompetitive Allele Specific PCR (KASP) markers in different genetic backgrounds. Moreover, significant interactions between the three major GL QTLs and two major TGW QTLs were observed. Comparison analysis showed that QGl.cib-5A.1 and QGl.cib-6A are likely new loci. Notably, QGw.cib-4B.2 and QTgw.cib-4B were co-located on chromosome 4B and improved TGW by increasing only GW, unlike nearby or overlapped loci reported previously. Three genes associated with grain development within the QGw.cib-4B.2/QTgw.cib-4B interval were identified by searches on sequence similarity, spatial expression patterns, and orthologs. The major QTLs and KASP markers reported here will be useful for elucidating the genetic architecture of grain size and weight and for developing new wheat cultivars with high and stable yield.

Fine mapping and validation of a major QTL for grain weight on chromosome 5B in bread wheat

A major QTL QTgw.caas-5B for thousand grain weight in wheat was fine mapped on chromosome 5B, and TraesCS5B02G044800 was predicted to be the candidate gene. Thousand grain weight (TGW), determined by grain length and width, and is an important yield component in wheat; understanding of the underlying genes and molecular mechanisms remains limited. A stable QTL QTgw.caas-5B for TGW was identified previously in a RIL population developed from a cross between Zhongmai 871 (ZM871) and a sister line Zhongmai 895 (ZM895), and the aim of this study was to perform fine mapping and validate the genetic effect of the QTL. It was delimited to an interval of approximately 2.0 Mb flanked by markers Kasp_5B29 and Kasp_5B31 (49.6-51.6 Mb) using 12 heterozygous recombinant plants obtained by selfing a residual BC₁F₆ line selected from the ZM871/ZM895//ZM871 population. A candidate gene was predicted following sequencing and differential expression analyses. Marker Kasp_5B_Tgw based on a SNP in TraesCS5B02G044800, the QTgw.caas-5B candidate, was developed and validated in a diversity panel of 166 cultivars. The precise mapping of QTgw.caas-5B laid a foundation for cloning of a predicted causal gene and provides a molecular marker for improving grain yield in wheat.

Genetic identification and characterization of chromosomal regions for kernel length and width increase from tetraploid wheat

BACKGROUND

Improvement of wheat gercTriticum aestivum L.) yield could relieve global food shortages. Kernel size, as an important component of 1000-kernel weight (TKW), is always a significant consideration to improve yield for wheat breeders. Wheat related species possesses numerous elite genes that can be introduced into wheat breeding. It is thus vital to explore, identify, and introduce new genetic resources for kernel size from wheat wild relatives to increase wheat yield.

RESULTS

In the present study, quantitative trait loci (QTL) for kernel length (KL) and width (KW) were detected in a recombinant inbred line (RIL) population derived from a cross between a wild emmer accession 'LM001' and a Sichuan endemic tetraploid wheat 'Ailanmai' using the Wheat 55 K single nucleotide polymorphism (SNP) array-based constructed linkage map and phenotype from six different environments. We identified eleven QTL for KL and KW including two major ones QKL.sicau-AM-3B and QKW.sicau-AM-4B, the positive alleles of which were from LM001 and Ailanmai, respectively. They explained 17.57 to 44.28% and 13.91 to 39.01% of the phenotypic variance, respectively. For these two major QTL, Kompetitive allele-specific PCR (KASP) markers were developed and used to successfully validate their effects in three F3 populations and two natural populations containing a panel of 272 Chinese wheat landraces and that of 300 Chinese wheat cultivars, respectively. QKL.sicau-AM-3B was located at 675.6-695.4 Mb on chromosome arm 3BL. QKW.sicau-AM-4B was located at 444.2-474.0 Mb on chromosome arm 4BL. Comparison with previous studies suggested that these two major QTL were likely new loci. Further analysis indicated that the positive alleles of QKL.sicau-AM-3B and QKW.sicau-AM-4B had a great additive effect increasing TKW by 6.01%. Correlation analysis between KL and other agronomic traits showed that KL was significantly correlated to spike length, length of uppermost internode, TKW, and flag leaf length. KW was also significantly correlated with TKW. Four genes, TRIDC3BG062390, TRIDC3BG062400, TRIDC4BG037810, and TRIDC4BG037830, associated with kernel development were predicted in physical intervals harboring these two major QTL on wild emmer and Chinese Spring reference genomes.

CONCLUSIONS

Two stable and major QTL for KL and KW across six environments were detected and verified in three biparental populations and two natural populations. Significant relationships between kernel size and yield-related traits were identified. KASP markers tightly linked the two major QTL could contribute greatly to subsequent fine mapping. These results suggested the application potential of wheat related species in wheat genetic improvement.

Mapping QTL for seedling morphological and physiological traits under normal and salt treatments in a RIL wheat population

The genetic basis of 27 seedling traits under normal and salt treatments was fully analyzed in a RIL wheat population, and seven QTL intervals were validated in two other genetic populations. Soil salinity seriously constrains wheat (Triticum aestivum L.) production globally by influencing its growth and development. To explore the genetic basis of salt tolerance in wheat, a recombinant inbred line (RIL) population derived from a cross between high-yield wheat cultivar Zhongmai 175 (ZM175) and salt-tolerant cultivar Xiaoyan 60 (XY60) was used to map QTL for seedling traits under normal and salt treatments based on a high-density genetic linkage map. A total of 158 stable additive QTL for 27 morphological and physiological traits were identified and distributed on all wheat chromosomes except 3A and 4D. They explained 2.35-46.43% of the phenotypic variation with a LOD score range of 2.61-40.38. The alleles from XY60 increased corresponding traits for 100 QTL, while the alleles from ZM175 had positive effects for the other 58 QTL. Nearly half of the QTL (78/158) were mapped in nine QTL clusters on chromosomes 2A, 2B, 2D, 4B, 5A, 5B, 5D, and 7D (2), respectively. To prove the reliability and potentiality in molecular marker-assisted selection (MAS), seven QTL intervals were validated in two other genetic populations. Besides additive QTL, 94 pairs of loci were detected with significant epistatic effect and 20 QTL were found to interact with treatment. This study provides a full elucidation of the genetic basis of seedling traits (especially root system-related traits) associated with salt tolerance in wheat, and the developed kompetitive allele-specific PCR markers closely linked to stable QTL would supply strong supports to MAS in salt-tolerant wheat breeding.

Dissection of Genetic Basis Underpinning Kernel Weight-Related Traits in Common Wheat

Genetic dissection kernel weight-related traits is of great significance for improving wheat yield potential. As one of the three major yield components of wheat, thousand kernel weight (TKW) was mainly affected by grain length (GL) and grain width (GW). To uncover the key loci for these traits, we carried out a quantitative trait loci (QTL) analysis of an F₆ recombinant inbred lines (RILs) population derived from a cross of Henong 5290 (small grain) and 06Dn23 (big grain) with a 50 K single nucleotide polymorphism (SNP) array. A total of 17 stable and big effect QTL, including 5 for TKW, 8 for GL and 4 for GW, were detected on the chromosomes 1B, 2A, 2B, 2D, 4B, 5A, 6A and 6D, respectively. Among these, there were two co-located loci for three traits that were mapped on the chromosome 4BS and 6AL. The QTL on 6AL was the most stable locus and explained 15.4–24.8%, 4.1–8.8% and 15.7–24.4% of TKW, GW and GL variance, respectively. In addition, two more major QTL of GL were located on chromosome arm 2BL and 2DL, accounting for 9.7–17.8% and 13.6–19.8% of phenotypic variance, respectively. In this study, we found one novel co-located QTL associated with GL and TKW in 2DL, QGl.haaf-2DL.2/QTkw.haaf-2DL.2, which could explain 13.6–19.8% and 9.8–10.7% phenotypic variance, respectively. Genetic regions and linked markers of these stable QTL will help to further refine mapping of the corresponding loci and marker-assisted selection (MAS) breeding for wheat grain yield potential improvement.

Utilization of a Wheat55K SNP array-derived high-density genetic map for high-resolution mapping of quantitative trait loci for important kernel-related traits in common wheat

This study mapped QTLs associated with kernel-related traits by high-density genetic map. Five new major and stable QTLs for KL, KDR, SN, and KWPS were mapped in multiple environments. In the present study, a recombinant inbred line population including 371 lines derived from the cross of Chuannong18 and T1208 was genotyped using the Wheat55K single nucleotide polymorphism array. A novel high-density genetic map consisting of 11,583 markers spanning 4192.62 cM and distributed across 21 wheat chromosomes was constructed. QTLs for important kernel-related traits were mapped in multiple environments. A total of 96 and 151 QTLs were mapped by using the ICIM method and the MET method, respectively. And a total of 114 digenic epistatic QTLs were also detected across 21 chromosomes, and the epistatic effects of each trait were analyzed. BLAST analysis showed that 23 QTLs for different kernel-related traits were first time mapped and five of them were major and stable QTLs for kernel diameter ratio (121.34-126.83 cM on 4BS), spike number per square meter (71.32-73.84 cM on 2DS), kernel weight per spike (71.32-75.26 cM on 2DS), and kernel length (16.78-31.64 cM on 6A and 51.63-58.40 cM on 3D), respectively. Fifteen QTL clusters that contained 58 QTLs were also detected, and all most stable QTLs were contained in these QTL clusters. Significant correlations between different traits were detected and discussed. These results lay the foundation for fine mapping and cloning of the gene(s) underlying the stable QTLs detected in this study.

Genetic Mapping and Validation of Loci for Kernel-Related Traits in Wheat (Triticum aestivum L.)

Kernel size (KS) and kernel weight play a key role in wheat yield. Phenotypic data from six environments and a Wheat55K single-nucleotide polymorphism array-based constructed genetic linkage map from a recombinant inbred line population derived from the cross between the wheat line 20828 and the line SY95-71 were used to identify quantitative trait locus (QTL) for kernel length (KL), kernel width (KW), kernel thickness (KT), thousand-kernel weight (TKW), kernel length-width ratio (LWR), KS, and factor form density (FFD). The results showed that 65 QTLs associated with kernel traits were detected, of which the major QTLs QKL.sicau-2SY-1B, QKW.sicau-2SY-6D, QKT.sicau-2SY-2D, and QTKW.sicau-2SY-2D, QLWR.sicau-2SY-6D, QKS.sicau-2SY-1B/2D/6D, and QFFD.sicau-2SY-2D controlling KL, KW, KT, TKW, LWR, KS, and FFD, and identified in multiple environments, respectively. They were located on chromosomes 1BL, 2DL, and 6DS and formed three QTL clusters. Comparison of genetic and physical interval suggested that only QKL.sicau-2SY-1B located on chromosome 1BL was likely a novel QTL. A Kompetitive Allele Specific Polymerase chain reaction (KASP) marker, KASP-AX-109379070, closely linked to this novel QTL was developed and used to successfully confirm its effect in two different genetic populations and three variety panels consisting of 272 Chinese wheat landraces, 300 Chinese wheat cultivars most from the Yellow and Huai River Valley wheat region, and 165 Sichuan wheat cultivars. The relationships between kernel traits and other agronomic traits were detected and discussed. A few predicted genes involved in regulation of kernel growth and development were identified in the intervals of these identified major QTL. Taken together, these stable and major QTLs provide valuable information for understanding the genetic composition of kernel yield and provide the basis for molecular marker-assisted breeding.

QTL Mapping and Validation for Kernel Area and Circumference in Common Wheat via High-Density SNP-Based Genotyping

As an important component, 1,000 kernel weight (TKW) plays a significant role in the formation of yield traits of wheat. Kernel size is significantly positively correlated to TKW. Although numerous loci for kernel size in wheat have been reported, our knowledge on loci for kernel area (KA) and kernel circumference (KC) remains limited. In the present study, a recombinant inbred lines (RIL) population containing 371 lines genotyped using the Wheat55K SNP array was used to map quantitative trait loci (QTLs) controlling the KA and KC in multiple environments. A total of 54 and 44 QTLs were mapped by using the biparental population or multienvironment trial module of the inclusive composite interval mapping method, respectively. Twenty-two QTLs were considered major QTLs. BLAST analysis showed that major and stable QTLs QKc.sau-6A.1 (23.12-31.64 cM on 6A) for KC and QKa.sau-6A.2 (66.00-66.57 cM on 6A) for KA were likely novel QTLs, which explained 22.25 and 20.34% of the phenotypic variation on average in the 3 year experiments, respectively. Two Kompetitive allele-specific PCR (KASP) markers, KASP-AX-109894590 and KASP-AX-109380327, were developed and tightly linked to QKc.sau-6A.1 and QKa.sau-6A.2, respectively, and the genetic effects of the different genotypes in the RIL population were successfully confirmed. Furthermore, in the interval where QKa.sau-6A.2 was located on Chinese Spring and T. Turgidum ssp. dicoccoides reference genomes, only 11 genes were found. In addition, digenic epistatic QTLs also showed a significant influence on KC and KA. Altogether, the results revealed the genetic basis of KA and KC and will be useful for the marker-assisted selection of lines with different kernel sizes, laying the foundation for the fine mapping and cloning of the gene(s) underlying the stable QTLs detected in this study.

Genetic dissection of stem WSC accumulation and remobilization in wheat (Triticum aestivum L.) under terminal drought stress

BACKGROUND

The accumulation and remobilization of stem water soluble carbohydrates (WSC) are determinant physiological traits highly influencing yield potential in wheat against drought stress. However, knowledge gains of the genetic control are still limited. A hexaploid wheat population of 120 recombinant inbred lines were developed to identify quantitative trait loci (QTLs) and to dissect the genetic basis underlying eight traits related to stem WSC under drought stress (DS) and well-watered (WW) conditions across three environments.

RESULTS

Analysis of variance (ANOVA) revealed larger environmental and genotypic effects on stem WSC-related traits, indicating moderate heritabilities of 0.51-0.72. A total of 95 additive and 88 pairs of epistatic QTLs were identified with significant additive and epistatic effects, as well as QTL× water environmental interaction (QEI) effects. Most of additive QTLs and additive QEIs associated with drought-stressed environments functioned genetic effects promoting pre-anthesis WSC levels and stem WSC remobilization to developing grains. Compared to other genetic components, both genetic effects were performed exclusive contributions to phenotypic variations in stem WSC-related traits. Nineteen QTL clusters were identified on chromosomes 1B, 2A, 2B, 2D, 3B, 4B, 5A, 6A, 6B and 7A, suggestive of the genetic linkage or pleiotropy. Thirteen additive QTLs were detectable repeatedly across two of the three water environments, indicating features of stable expressions. Some loci were consistent with those reported early and were further discussed.

CONCLUSION

Stem WSC-related traits were inherited predominantly by additive and QEI effects with a moderate heritability. QTL cluster regions were suggestive of tight linkage or pleiotropy in the inheritance of these traits. Some stable and common loci, as well as closely linked molecular markers, had great potential in marker-assisted selection to improve stem WSC-related traits in wheat, especially under drought-stressed environments.

QTL mapping for grain yield-related traits in bread wheat via SNP-based selective genotyping

We identified four chromosome regions harboring QTL for grain yield-related traits, and breeder-friendly KASP markers were developed and validated for marker-assisted selection. Identification of major stable quantitative trait loci (QTL) for grain yield-related traits is important for yield potential improvement in wheat breeding. In the present study, 266 recombinant inbred lines (RILs) derived from a cross between Zhongmai 871 (ZM871) and its sister line Zhongmai 895 (ZM895) were evaluated for thousand grain weight (TGW), grain length (GL), grain width (GW), and grain number per spike (GNS) in 10 environments and for grain filling rate in six environments. Sixty RILs, with 30 higher and 30 lower TGW, respectively, were genotyped using the wheat 660 K SNP array for preliminary QTL mapping. Four genetic regions on chromosomes 1AL, 2BS, 3AL, and 5B were identified to have a significant effect on TGW-related traits. A set of Kompetitive Allele Specific PCR markers were converted from the SNP markers on the above target chromosomes and used to genotype all 266 RILs. The mapping results confirmed the QTL named Qgw.caas-1AL, Qgl.caas-3AL, Qtgw.caas-5B, and Qgl.caas-5BS on the targeted chromosomes, explaining 5.0-20.6%, 5.7-15.7%, 5.5-17.3%, and 12.5-20.5% of the phenotypic variation for GW, GL, TGW, and GL, respectively. A novel major QTL for GNS on chromosome 5BS, explaining 5.2-15.2% of the phenotypic variation, was identified across eight environments. These QTL were further validated using BC₁F₄ populations derived from backcrosses ZM871/ZM895//ZM871 (121 lines) and ZM871/ZM895//ZM895 (175 lines) and 186 advanced breeding lines. Collectively, selective genotyping is a simple, economic, and effective approach for rapid QTL mapping and can be generally applied to genetic mapping studies for important agronomic traits.

Identification of the quantitative trait loci controlling spike-related traits in hexaploid wheat (Triticum aestivum L.)

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 F_2:3 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 F_2:3 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.

Unraveling the genetic architecture of grain size in einkorn wheat through linkage and homology mapping and transcriptomic profiling

Understanding the genetic architecture of grain size is a prerequisite to manipulating grain development and improving the potential crop yield. In this study, we conducted a whole genome-wide quantitative trait locus (QTL) mapping of grain-size-related traits by constructing a high-density genetic map using 109 recombinant inbred lines of einkorn wheat. We explored the candidate genes underlying QTLs through homologous analysis and RNA sequencing. The high-density genetic map spanned 1873 cM and contained 9937 single nucleotide polymorphism markers assigned to 1551 bins on seven chromosomes. Strong collinearity and high genome coverage of this map were revealed by comparison with physical maps of wheat and barley. Six grain size-related traits were surveyed in five environments. In total, 42 QTLs were identified; these were assigned to 17 genomic regions on six chromosomes and accounted for 52.3-66.7% of the phenotypic variation. Thirty homologous genes involved in grain development were located in 12 regions. RNA sequencing identified 4959 genes differentially expressed between the two parental lines. Twenty differentially expressed genes involved in grain size development and starch biosynthesis were mapped to nine regions that contained 26 QTLs, indicating that the starch biosynthesis pathway plays a vital role in grain development in einkorn wheat. This study provides new insights into the genetic architecture of grain size in einkorn wheat; identification of the underlying genes enables understanding of grain development and wheat genetic improvement. Furthermore, the map facilitates quantitative trait mapping, map-based cloning, genome assembly, and comparative genomics in wheat taxa.

Unraveling the genetic architecture of grain size in einkorn wheat through linkage and homology mapping and transcriptomic profiling

Understanding the genetic architecture of grain size is a prerequisite to manipulating grain development and improving the potential crop yield. In this study, we conducted a whole genome-wide quantitative trait locus (QTL) mapping of grain-size-related traits by constructing a high-density genetic map using 109 recombinant inbred lines of einkorn wheat. We explored the candidate genes underlying QTLs through homologous analysis and RNA sequencing. The high-density genetic map spanned 1873 cM and contained 9937 single nucleotide polymorphism markers assigned to 1551 bins on seven chromosomes. Strong collinearity and high genome coverage of this map were revealed by comparison with physical maps of wheat and barley. Six grain size-related traits were surveyed in five environments. In total, 42 QTLs were identified; these were assigned to 17 genomic regions on six chromosomes and accounted for 52.3-66.7% of the phenotypic variation. Thirty homologous genes involved in grain development were located in 12 regions. RNA sequencing identified 4959 genes differentially expressed between the two parental lines. Twenty differentially expressed genes involved in grain size development and starch biosynthesis were mapped to nine regions that contained 26 QTLs, indicating that the starch biosynthesis pathway plays a vital role in grain development in einkorn wheat. This study provides new insights into the genetic architecture of grain size in einkorn wheat; identification of the underlying genes enables understanding of grain development and wheat genetic improvement. Furthermore, the map facilitates quantitative trait mapping, map-based cloning, genome assembly, and comparative genomics in wheat taxa.

Genomic Regions From an Iranian Landrace Increase Kernel Size in Durum Wheat

Kernel size and shape are important parameters determining the wheat profitability, being main determinants of yield and its technological quality. In this study, a segregating population of 118 recombinant inbred lines, derived from a cross between the Iranian durum landrace accession "Iran_249" and the Iranian durum cultivar "Zardak", was used to investigate durum wheat kernel morphology factors and their relationships with kernel weight, and to map the corresponding QTLs. A high density genetic map, based on wheat 90k iSelect Infinium SNP assay, comprising 6,195 markers, was developed and used to perform the QTL analysis for kernel length and width, traits related to kernel shape and weight, and heading date, using phenotypic data from three environments. Overall, a total of 31 different QTLs and 9 QTL interactions for kernel size, and 21 different QTLs and 5 QTL interactions for kernel shape were identified. The landrace Iran_249 contributed the allele with positive effect for most of the QTLs related to kernel length and kernel weight suggesting that the landrace might have considerable potential toward enhancing the existing gene pool for grain shape and size traits and for further yield improvement in wheat. The correlation among traits and co-localization of corresponding QTLs permitted to define 11 clusters suggesting causal relationships between simplest kernel size trait, like kernel length and width, and more complex secondary trait, like kernel shape and weight related traits. Lastly, the recent release of the T. durum reference genome sequence allowed to define the physical interval of our QTL/clusters and to hypothesize novel candidate genes inspecting the gene content of the genomic regions associated to target traits.

Genome-wide association study revealed that the TaGW8 gene was associated with kernel size in Chinese bread wheat

Using Wheat 90 K SNP assay, kernel-related traits of Chinese bread wheat were used to perform association mapping in 14 environments by GWAS. Results indicated that 996 and 953 of 4417 and 3172 significant SNPs for kernel length and thousand-kernel weight were located on the chromosome 7B. Haplotype analysis of these SNPs on 7B generated the block containing the predicted TaGW8-B1 gene. TaGW8-B1 gene was further cloned by sequencing in bread wheat and a 276-bp InDel was found in the first intron. TaGW8-B1 without and with the 276-bp InDel were designated as TaGW8-B1a and TaGW8-B1b, respectively. Analysis of agronomic traits indicated that cultivars with TaGW8-B1a possessed significantly wider kernel width, significantly more kernel number per spike, longer kernel length, higher thousand-kernel weight and more spikelet number per spike than cultivars with TaGW8-B1b. Furthermore, cultivars with TaGW8-B1a possessed significantly higher yield than cultivars with TaGW8-B1b. Therefore, TaGW8-B1a was considered as a potentially superior allele. Meanwhile, TaGW8-B1a possessed a significantly higher expression level than TaGW8-B1b in mature seeds by qRT-PCR. It possibly suggested that the high expression of TaGW8-B1 was positively associated with kernel size in bread wheat. Distribution of TaGW8-B1 allele indicated that TaGW8-B1a has been positively selected in Chinese wheat.

QTL mapping for some grain traits in bread wheat (Triticum aestivum L.)

Grain traits are important agronomic attributes with the market value as well as milling yield of bread wheat. In the present study, quantitative trait loci (QTL) regulating grain traits in wheat were identified. Data for grain area size (GAS), grain width (GWid), factor form density (FFD), grain length-width ratio (GLWR), thousand grain weight (TGW), grain perimeter length (GPL) and grain length (GL) were recorded on a recombinant inbred line derived from the cross of NW1014 × HUW468 at Meerut and Varanasi locations. A linkage map of 55 simple sequence repeat markers for 8 wheat chromosomes was used for QTL analysis by Composite interval mapping. Eighteen QTLs distributed on 8 chromosomes were identified for seven grain traits. Of these, five QTLs for GLWR were found on chromosomes 1A, 6A, 2B, and 7B, three QTLs for GPL were located on chromosomes 4A, 5A and 7B and three QTLs for GAS were mapped on 5D and 7D. Two QTLs were identified on chromosomes 4A and 5A for GL and two QTLs for GWid were identified on chromosomes 7D and 6A. Similarly, two QTLs for FFD were found on chromosomes 1A and 5D. A solitary QTL for TGW was identified on chromosome 2B. For several traits, QTLs were also co-localized on chromosomes 2B, 4A, 5A, 6A, 5D, 7B and 7D. The QTLs detected in the present study may be validated for specific crosses and then used for marker-assisted selection to improve grain quality in bread wheat.

Mapping QTLs controlling kernel dimensions in a wheat inter-varietal RIL mapping population

Seven kernel dimension QTLs were identified in wheat, and kernel thickness was found to be the most important dimension for grain weight improvement. Kernel morphology and weight of wheat (Triticum aestivum L.) affect both yield and quality; however, the genetic basis of these traits and their interactions has not been fully understood. In this study, to investigate the genetic factors affecting kernel morphology and the association of kernel morphology traits with kernel weight, kernel length (KL), width (KW) and thickness (KT) were evaluated, together with hundred-grain weight (HGW), in a recombinant inbred line population derived from Nanda2419 × Wangshuibai, with data from five trials (two different locations over 3 years). The results showed that HGW was more closely correlated with KT and KW than with KL. A whole genome scan revealed four QTLs for KL, one for KW and two for KT, distributed on five different chromosomes. Of them, QKl.nau-2D for KL, and QKt.nau-4B and QKt.nau-5A for KT were newly identified major QTLs for the respective traits, explaining up to 32.6 and 41.5% of the phenotypic variations, respectively. Increase of KW and KT and reduction of KL/KT and KW/KT ratios always resulted in significant higher grain weight. Lines combining the Nanda 2419 alleles of the 4B and 5A intervals had wider, thicker, rounder kernels and a 14% higher grain weight in the genotype-based analysis. A strong, negative linear relationship of the KW/KT ratio with grain weight was observed. It thus appears that kernel thickness is the most important kernel dimension factor in wheat improvement for higher yield. Mapping and marker identification of the kernel dimension-related QTLs definitely help realize the breeding goals.

Characterization of the temporal and spatial expression of wheat (Triticum aestivum L.) plant height at the QTL level and their influence on yield-related traits

The temporal and spatial expression patterns of stable QTL for plant height and their influences on yield were characterized. Plant height (PH) is a complex trait in wheat (Triticum aestivum L.) that includes the spike length (SL) and the internode lengths from the first to the fifth internode, which are counted from the top and abbreviated as FIRITL, SECITL, THIITL, FOUITL, and FIFITL, respectively. This study identified eight putative additive quantitative trait loci (QTL) for PH. In addition, unconditional and conditional QTL mapping were used to analyze the temporal and spatial expression patterns of five stable QTL for PH. qPh-3A mainly regulated SL, FIRITL, and FIFITL to affect PH during the booting-heading stage (BS-HS); qPh-3D regulated all internode lengths to affect PH, especially during the BS-HS; before HS, qPh-4B mainly affected FIRITL, SECITL, THIITL, and FOUITL and qPh-5A.1 mainly affected SECITL, THIITL, and FOUITL to regulate PH; and qPh-6B mainly regulated FIRITL to affect the PH after the booting stage (BS). qPhdv-4B, a QTL for the response of PH to nitrogen stress, was stable and co-localized with qPh-4B. All five stable QTL, except for qPh-3A, were related to the 1000 kernel weight and yield per plant. Regions of qPh-3A, qPh-3D, qPh-4B, qPh-5A.1, and qPh-6B showed synteny to parts of rice chromosomes 1, 1, 3, 9, and 2, respectively. Based on comparative genomics analysis, Rht-B1b was cloned and mapped in the CI of qPh-4B. This report provides useful information for fine mapping of the stable QTL for PH and the genetic improvement of wheat plant type.

Dissection of Genetic Factors underlying Wheat Kernel Shape and Size in an Elite × Nonadapted Cross using a High Density SNP Linkage Map

Wheat kernel shape and size has been under selection since early domestication. Kernel morphology is a major consideration in wheat breeding, as it impacts grain yield and quality. A population of 160 recombinant inbred lines (RIL), developed using an elite (ND 705) and a nonadapted genotype (PI 414566), was extensively phenotyped in replicated field trials and genotyped using Infinium iSelect 90K assay to gain insight into the genetic architecture of kernel shape and size. A high density genetic map consisting of 10,172 single nucleotide polymorphism (SNP) markers, with an average marker density of 0.39 cM/marker, identified a total of 29 genomic regions associated with six grain shape and size traits; ∼80% of these regions were associated with multiple traits. The analyses showed that kernel length (KL) and width (KW) are genetically independent, while a large number (∼59%) of the quantitative trait loci (QTL) for kernel shape traits were in common with genomic regions associated with kernel size traits. The most significant QTL was identified on chromosome 4B, and could be an ortholog of major rice grain size and shape gene or . Major and stable loci also were identified on the homeologous regions of Group 5 chromosomes, and in the regions of (6A) and (7A) genes. Both parental genotypes contributed equivalent positive QTL alleles, suggesting that the nonadapted germplasm has a great potential for enhancing the gene pool for grain shape and size. This study provides new knowledge on the genetic dissection of kernel morphology, with a much higher resolution, which may aid further improvement in wheat yield and quality using genomic tools.

Agriproteomics of Bread Wheat: Comparative Proteomics and Network Analyses of Grain Size Variation

Agriproteomics signifies the merging of agriculture research and proteomics systems science and is impacting plant research and societal development. Wheat is a frequently consumed foodstuff, has highly variable grain size that in effect contributes to wheat grain yield and the end-product quality. Very limited information is available on molecular basis of grain size due to complex multifactorial nature of this trait. Here, using liquid chromatography-mass spectrometry, we investigated the proteomics profiles from grains of wheat genotypes, Rye selection 111 (RS111) and Chinese spring (CS), which differ in their size. Significant differences in protein expression were found, including 33 proteins uniquely present in RS111 and 32 only in CS, while 54 proteins were expressed from both genotypes. Among differentially expressed proteins, 22 were upregulated, while 21 proteins were downregulated in RS111 compared to CS. Functional classification revealed their role in energy metabolism, seed storage, stress tolerance and transcription. Further, protein interactive network analysis was performed to predict the targets of identified proteins. Significantly different interactions patterns were observed between these genotypes with detection of proteins such as Cyp450, Sus2, and WRKY that could potentially affect seed size. The present study illustrates the potentials of agriproteomics as a veritable new frontier of plant omics research.

Genetic control of grain yield and grain physical characteristics in a bread wheat population grown under a range of environmental conditions

Genetic analysis of the yield and physical quality of wheat revealed complex genetic control, including strong effects of photoperiod-sensitivity loci. Environmental conditions such as moisture deficit and high temperatures during the growing period affect the grain yield and grain characteristics of bread wheat (Triticum aestivum L.). The aim of this study was to map quantitative trait loci (QTL) for grain yield and grain quality traits using a Drysdale/Gladius bread wheat mapping population grown under a range of environmental conditions in Australia and Mexico. In general, yield and grain quality were reduced in environments exposed to drought and/or heat stress. Despite large effects of known photoperiod-sensitivity loci (Ppd-B1 and Ppd-D1) on crop development, grain yield and grain quality traits, it was possible to detect QTL elsewhere in the genome. Some of these QTL were detected consistently across environments. A locus on chromosome 6A (TaGW2) that is known to be associated with grain development was associated with grain width, thickness and roundness. The grain hardness (Ha) locus on chromosome 5D was associated with particle size index and flour extraction and a region on chromosome 3B was associated with grain width, thickness, thousand grain weight and yield. The genetic control of grain length appeared to be largely independent of the genetic control of the other grain dimensions. As expected, effects on grain yield were detected at loci that also affected yield components. Some QTL displayed QTL-by-environment interactions, with some having effects only in environments subject to water limitation and/or heat stress.