Kernel-related Traits Research Articles

Genetic architecture of kernel-related traits in sweet and waxy maize revealed by genome-wide association analysis.

Maize (Zea mays L.) is one of the most important crops worldwide, the kernel size-related traits are the major components of maize grain yield. To dissect the genetic architecture of four kernel-related traits of 100-kernel weight, kernel length, kernel width, and kernel diameter, a genome-wide association study (GWAS) was conducted in the waxy and sweet maize panel comprising of 447 maize inbred lines re-sequenced at the 5× coverage depth. GWAS analysis was carried out with the mixed linear model using 1,684,029 high-quality SNP markers. In total, 49 SNPs significantly associated with the four kernel-related traits were identified, including 46 SNPs on chromosome 3, two SNPs on chromosome 4, and one SNP on chromosome 7. Haplotype regression analysis identified 338 haplotypes that significantly affected these four kernel-related traits. Genomic selection (GS) results revealed that a set of 10,000 SNPs and a training population size of 30% are sufficient for the application of GS in waxy and sweet maize breeding for kernel weight and kernel size. Forty candidate genes associated with the four kernel-related traits were identified, including both Zm00001d000707 and Zm00001d044139 expressed in the kernel development tissues and stages with unknown functions. These significant SNPs and important haplotypes provide valuable information for developing functional markers for the implementation of marker-assisted selection in breeding. The molecular mechanism of Zm00001d000707 and Zm00001d044139 regulating these kernel-related traits needs to be investigated further.

Mapping QTLs with additive and epistatic effects for awn length and their effects on kernel-related traits in common wheat.

Wheat awns are crucial determinants of wheat yield due to their capacity to photosynthesize and exchange gas. Understanding the genetic basis of awn length (AL) is essential for improving wheat yield in molecular breeding programs. In this study, quantitative trait loci (QTLs) of AL were analyzed using recombinant inbred line (RIL) mapping population referred to as YY-RILs, which was derived from a cross between Yannong 15 (YN15) and Yannong 1212 (YN1212). Seven putative additive QTLs and 30 pairwise epistatic QTLs for AL were identified. Among them, five novel additive QTLs (except qAl-2A and qAl-5A.2) and 30 novel pairwise epistatic QTLs were identified. qAl-5A.1 was repeatedly identified in all five environment datasets, which was considered to be one novel stable QTL for AL with minor additive effects. eqAl-2B.2-2 significantly interacted with eight loci and could be of great importance in regulating awn development. The genes associated with the major stable QTL of qAl-5A.2 and the minor stable QTL of qAl-2A were B1 and WFZP-A, respectively. Awn lengths exhibited significant genetic correlations with kernel weight and kernels per spike, which could affect grain protein content to a lesser extent. This study enhances our understanding of the genetic basis of awn development and identifies novel genes as well as markers for future genetic improvement of wheat yield.

QTL mapping for kernel-related traits in a durum wheat x T. dicoccum segregating population.

Durum wheat breeding relies on grain yield improvement to meet its upcoming demand while coping with climate change. Kernel size and shape are the determinants of thousand kernel weight (TKW), which is a key component of grain yield, and the understanding of the genetic control behind these traits supports the progress in yield potential. The present study aimed to dissect the genetic network responsible for kernel size components (length, width, perimeter, and area) and kernel shape traits (width-to-length ratio and formcoefficient) as well as their relationships with kernel weight, plant height, and heading date in durum wheat. Quantitative Trait Locus (QTL) mapping was performed on a segregating population of 110 recombinant inbred lines, derived from a cross between the domesticated emmer wheat accession MG5323 and the durum wheat cv. Latino, evaluated in four different environments. A total of 24 QTLs stable across environments were found and further grouped in nine clusters on chromosomes 2A, 2B, 3A, 3B, 4B, 6B, and 7A. Among them, a QTL cluster on chromosome 4B was associated with kernel size traits and TKW, where the parental MG5323 contributed the favorable alleles, highlighting its potential to improve durum wheat germplasm. The physical positions of the clusters, defined by the projection on the T. durum reference genome, overlapped with already known genes (i.e., BIG GRAIN PROTEIN 1 on chromosome 4B). These results might provide genome-based guidance for the efficient exploitation of emmer wheat diversity in wheat breeding, possibly through yield-related molecular markers.

Breeding effects on durum wheat traits detected using GWAS and haplotype block analysis.

The recent boosting of genomic data in durum wheat (Triticum turgidum subsp. durum) offers the opportunity to better understand the effects of breeding on the genetic structures that regulate the expression of traits of agronomic interest. Furthermore, the identification of DNA markers useful for marker-assisted selection could also improve the reliability of technical protocols used for variety protection and registration. Within this motivation context, 123 durum wheat accessions, classified into three groups: landraces (LR), ancient (OC) and modern cultivars (MC), were evaluated in two locations, for 34 agronomic traits, including UPOV descriptors, to assess the impact of changes that occurred during modern breeding. The association mapping analysis, performed with 4,241 SNP markers and six multi-locus-GWAS models, revealed 28 reliable Quantitative Trait Nucleotides (QTNs) related to plant morphology and kernel-related traits. Some important genes controlling flowering time and plant height were in linkage disequilibrium (LD) decay with QTNs identified in this study. A strong association for yellow berry was found on chromosome 6A (Q.Yb-6A) in a region containing the nadh-ubiquinone oxidoreductase subunit, a gene involved in starch metabolism. The Q.Kcp-2A harbored the PPO locus, with the associated marker (Ku_c13700_1196) in LD decay with Ppo-A1 and Ppo-A2. Interestingly, the Q.FGSGls-2B.1, identified by RAC875_c34512_685 for flag leaf glaucosity, mapped less than 1 Mb from the Epistatic inhibitors of glaucousness (Iw1), thus representing a good candidate for supporting the morphological DUS traits also with molecular markers. LD haplotype block approach revealed a higher diversity, richness and length of haploblocks in MC than OC and LR (580 in LR, 585 in OC and 612 in MC), suggesting a possible effect exerted by breeding programs on genomic regions associated with the agronomic traits. Our findings pave new ways to support the phenotypic characterization necessary for variety registration by using a panel of cost-effectiveness SNP markers associated also to the UPOV descriptors. Moreover, the panel of associated SNPs might represent a reservoir of favourable alleles to use in durum wheat breeding and genetics.

Phenotypic evolution in durum wheat (Triticum durum Desf.) based on SNPs, morphological traits, UPOV descriptors and kernel-related traits.

Durum wheat is a worldwide staple crop cultivated mainly in the Mediterranean basin. Progress in durum wheat breeding requires the exploitation of genetic variation among the gene pool enclosed in landraces, old cultivars and modern cultivars. The aim of this study was to provide a more comprehensive view of the genetic architecture evolution among 123 durum wheat accessions (41 landraces, 41 old cultivars and 41 modern cultivars), grown in replicated randomized complete block in two areas, Metaponto (Basilicata) and Foggia (Apulia), using the Illumina iSelect 15K wheat SNP array and 33 plant and kernel traits including the International Union for the Protection of new Varieties of Plants (UPOV) descriptors. Through DAPC and Bayesian population structure five groups were identified according to type of material data and reflecting the genetic basis and breeding strategies involved in their development. Phenotypic and genotypic coefficient of variation were low for kernel width (6.43%) and for grain protein content (1.03%). Highly significant differences between environments, genotypes and GEI (Genotype x Environment Interaction) were detected by mixed ANOVAs for agro-morphological-quality traits. Number of kernels per spike (h2 = 0.02) and grain protein content (h2 = 0.03) were not a heritability character and highly influenced by the environment. Nested ANOVAs revealed highly significant differences between DAPC clusters within environments for all traits except kernel roundness. Ten UPOV traits showed significant diversity for their frequencies in the two environments. By PCAmix multivariate analysis, plant height, heading time, spike length, weight of kernels per spike, thousand kernel weight, and the seed related traits had heavy weight on the differentiation of the groups, while UPOV traits discriminated moderately or to a little extent. The data collected in this study provide useful resources to facilitate management and use of wheat genetic diversity that has been lost due to selection in the last decades.

Selecting the superior late-leafing genotypes of Persian walnut (Juglans regia L.) using morphological and pomological evaluations

BackgroundLate-spring frost is one of the major factors limiting and reducing yield of Persian walnut (Juglans regia L.) in temperate regions, including Iran. Therefore, in the present study, seedling-originated genotypes of walnut were investigated to identify late-leafing genotypes with high-quality kernels for direct cultivation in orchards or as parents in breeding programs. In the first step, the variation of the selected trees was investigated in terms of traits related to phenology, vegetation, and fruit. In the second step, late-leafing trees were identified and their traits related to kernel quality were investigated to identify superior genotypes.ResultsStrong variabilities were exhibited among the studied genotypes based on the traits recorded. The genotypes showed high variation based on dates of leafing, full male flowering date, and full female flowering date, including very early, early, moderate, and late. After recording the leafing date, 21 late-leaf genotypes were identified and evaluated to select the superiors among them in terms of kernel quantity and quality. Among them, the values of nut-related traits ranged as follows: nut length: 30.12–49.74 mm, nut width: 29.31–37.17 mm, nut weight: 8.77–16.47 g, and shell thickness: 1.15–2.25 mm. The values of kernel-related traits ranged as follows: kernel length: 22.35–35.73 mm, kernel width: 21.79–29.03 mm, kernel weight: 3.22–8.17 g, and kernel percentage: 35.08–53.95%.ConclusionsAccording to the ideal values and situations of commercial characteristics of walnut, twelve promising late-leafing genotypes (No. 9, 13, 32, 33, 72, 77, 78, 82, 83, 86, 92, and 98) were identified and are recommended for cultivation in orchards.

Performance and Stability Analysis of Selected Durum Wheat Genotypes Differing in Their Kernel Characteristics.

Breeding of high-yielding and stable durum wheat varieties with improved kernel characteristics is needed for dry regions around the globe. The aim of this study was to investigate the performance and stability of eight durum wheat genotypes varying in their kernel characteristics across 15 contrasting environments. The tested material included three recombinant inbred lines (NUR-072, NUR-106 and NUR-238) derived from a cross between Norsi, a Jordanian landrace with special kernel characteristics and UC1113 Yr36+Gpc-B1, an elite line from USA. Field trials were carried out for three constitutive growing seasons under rainfed conditions, except for three environments where supplementary irrigation was provided. After the harvest, grain yield (GY), total yield (TW), and harvest index (HI) were recorded. Additionally, several kernel-related traits, including thousand kernel weight (TKW), kernel area (KA), kernel width (KW), kernel length (KL), kernel circularity (KC), and kernel length-width ratio (KL:KW) were evaluated. Analysis of variance for all tested traits revealed high significant variations (p ≤ 0.01) between the genotype (except for TW) and the genotype × environment (G × E) interaction. Genotype effect contributed to substantial percentage of variation (>75%) for KA, KL, KC and KL:KW, whereas KW showed a lower percentage similar to GY. Regarding the G × E effect, explained variation was highest for the TW (67.79%), and lowest for KL (6.47%). For GY, Norsi produced significantly the lowest mean value (249.99 g.m-2) while, Bolenga produced the highest mean value (377.85 g.m-2) although no significant differences were observed with the remaining genotypes. On the other hand, Norsi, NUR-072 and NUR-106 showed best performance for TKW and kernel-related traits with NUR-106 producing the highest mean value for KL (9.07 mm). The GGE biplot and AMMI analysis of GY identified Bolenga, Um Qais and NUR-106 as good performers across several environments, while Norsi exhibited the poorest performance. For TKW, Norsi was the best performer across different environments followed by NUR-106, which showed excellent performance under irrigated and saline conditions. For stability analysis, NUR-106 emerged as the most stable genotype in this study for GY and several kernel-related traits, particularly for KL and KC. In conclusion, the results of this study offer valuable insights for durum wheat breeders seeking to develop high-yielding and stable varieties with special kernel characteristics suitable for cultivation in dry areas.

Evaluating the Genetic Background Effect on Dissecting the Genetic Basis of Kernel Traits in Reciprocal Maize Introgression Lines.

Maize yield is mostly determined by its grain size. Although numerous quantitative trait loci (QTL) have been identified for kernel-related traits, the application of these QTL in breeding programs has been strongly hindered because the populations used for QTL mapping are often different from breeding populations. However, the effect of genetic background on the efficiency of QTL and the accuracy of trait genomic prediction has not been fully studied. Here, we used a set of reciprocal introgression lines (ILs) derived from 417F × 517F to evaluate how genetic background affects the detection of QTLassociated with kernel shape traits. A total of 51 QTL for kernel size were identified by chromosome segment lines (CSL) and genome-wide association studies (GWAS) methods. These were subsequently clustered into 13 common QTL based on their physical position, including 7 genetic-background-independent and 6 genetic-background-dependent QTL, respectively. Additionally, different digenic epistatic marker pairs were identified in the 417F and 517F ILs. Therefore, our results demonstrated that genetic background strongly affected not only the kernel size QTL mapping via CSL and GWAS but also the genomic prediction accuracy and epistatic detection, thereby enhancing our understanding of how genetic background affects the genetic dissection of grain size-related traits.

Major and stably expressed QTL for traits related to the mature wheat embryo independent of kernel size

Two major and stably expressed QTL for traits related to mature wheat embryo independent of kernel size were identified and validated in a natural population that contained 171 Sichuan wheat accessions and 49 Sichuan wheat landraces. As the juvenile of a highly differentiated plant, mature wheat (Triticum aestivum L.) embryos are highly significant to agricultural production. To understand the genetic basis of traits related to wheat embryo size, the embryo of mature kernels in a recombination inbred line that contained 126 lines from four environments was measured. The genetic loci of embryo size, including embryo length (EL), embryo width (EW), embryo area (EA), embryo length/kernel length (EL/KL), embryo width/kernel width (EW/KW), and EL/EW, were identified based on a genetic linkage map constructed based on PCR markers and the Wheat 55K single nucleotide polymorphism (SNP) array. A total of 50 quantitative trait loci (QTL) for traits related to wheat embryo size were detected. Among them, QEL.sicau-2SY-4A for EL and QEW.sicau-2SY-7B for EW were major and stably expressed and were genetically independent of KL and KW, respectively. Their effects were further verified in a natural population that contained 171 Sichuan wheat accessions and 49 Sichuan wheat landraces. Further analysis showed that TraesCS4A02G343300 and TraesCS7B02G006800 could be candidate genes for QEL.sicau-2SY-4A and QEW.sicau-2SY-7B, respectively. In addition, significant positive correlations between EL and kernel-related traits and the 1,000-grain weight were detected. Collectively, this study broadens our understanding of the genetic basis of wheat embryo size and will be helpful for the further fine-mapping of interesting loci in the future.

QTL Analysis of Yield and End-Use Quality Traits in Texas Hard Red Winter Wheat

Genetic dissection of complex traits by quantitative trait locus (QTL) analysis permits the understanding of the genotypic effects of QTL, interactions between QTLs, and QTL-by-environment interactions in wheat. This study aimed to identify the QTL linked to yield, its components, end-use quality traits including kernel, flour, and dough rheology, and related agronomic traits under dryland and irrigated conditions. A mapping population of 179 F2:6 recombinant inbred lines (RILs) derived from ‘TAM 111’/‘TX05A001822’ was evaluated for these traits to investigate their genetic stability and phenotypic plasticity using 2658 single nucleotide polymorphisms (SNPs) with 35 linkage groups. Traits associated with chromosome regions were detected for individual and across-environment QTL by inclusive composite interval mapping. A total of 30 QTL regions were identified, including 14 consistent QTLs mapped on 11 chromosomes and six pleiotropic QTLs mapped on 5 chromosomes. Three consistent QTLs in chromosomes 1A, 3B, and 6D might be novel. Three major QTLs with both consistent and pleiotropic effects were co-localized with known genes. The first QTL for dough mixing properties was physically clustered around Glu-D1 and had an phenotypic variation explained (PVE) up to 31.3%. The second QTL for kernel-related traits was physically close to the TaCWI-4A (cell wall invertase) gene, which influences the thousand kernel weight, heading date, and harvest index, with a PVE of up to 12.3%. The third QTL, which was colocalized with the TaCWI-5D gene for kernel traits, was identified with a PVE of 6.7%. Epistasis was also detected, but major QTLs were not involved in significant epistasis or interactions with environmental effects. The current study provided new information that is useful for enhanced wheat breeding, which will benefit from the deployment of the favorable alleles for end-use quality, yield, and other agronomic traits in wheat-breeding programs through marker-assisted selection.

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.

QTL mapping of yield components and kernel traits in wheat cultivars TAM 112 and Duster.

In the Southern Great Plains, wheat cultivars have been selected for a combination of outstanding yield and drought tolerance as a long-term breeding goal. To understand the underlying genetic mechanisms, this study aimed to dissect the quantitative trait loci (QTL) associated with yield components and kernel traits in two wheat cultivars `TAM 112' and `Duster' under both irrigated and dryland environments. A set of 182 recombined inbred lines (RIL) derived from the cross of TAM 112/Duster were planted in 13 diverse environments for evaluation of 18 yield and kernel related traits. High-density genetic linkage map was constructed using 5,081 single nucleotide polymorphisms (SNPs) from genotyping-by-sequencing (GBS). QTL mapping analysis detected 134 QTL regions on all 21 wheat chromosomes, including 30 pleiotropic QTL regions and 21 consistent QTL regions, with 10 QTL regions in common. Three major pleiotropic QTL on the short arms of chromosomes 2B (57.5 - 61.6 Mbps), 2D (37.1 - 38.7 Mbps), and 7D (66.0 - 69.2 Mbps) colocalized with genes Ppd-B1, Ppd-D1, and FT-D1, respectively. And four consistent QTL associated with kernel length (KLEN), thousand kernel weight (TKW), plot grain yield (YLD), and kernel spike-1 (KPS) (Qklen.tamu.1A.325, Qtkw.tamu.2B.137, Qyld.tamu.2D.3, and Qkps.tamu.6A.113) explained more than 5% of the phenotypic variation. QTL Qklen.tamu.1A.325 is a novel QTL with consistent effects under all tested environments. Marker haplotype analysis indicated the QTL combinations significantly increased yield and kernel traits. QTL and the linked markers identified in this study will facilitate future marker-assisted selection (MAS) for pyramiding the favorable alleles and QTL map-based cloning.

Traditional and Conditional QTL Analysis of Kernel Size- and Shape-Related Traits in Wheat (Triticum aestivum L.)

Optimal kernel size and shape were critical in improving the wheat yield potential and processing quality. A traditional and conditional QTL analysis for kernel-related traits was performed using 152 recombinant inbred lines derived from a cross between Zhongkemai 138 (ZKM138) and Kechengmai 2, whose kernel size showed significant differences. A total of 48 traditional QTLs (LOD: 3.69–14.20) were identified, with twenty-six QTLs distributed across five genomic regions. Each had at least one major stable QTL for kernel-related traits. We deduced from the co-location and conditional QTL analysis results that R3D and R4B.1 primarily controlled kernel shape, while R4D, R6A, and R6D2 primarily contributed to kernel size and the final thousand-kernel weight, potentially providing the genetic basis for the ZKM138’s high TKW and large-kernel performance. R4D may be involved with Rht2, and the possible regulatory effects of the other four QTL clusters are more likely to be influenced by unknown genes. The KASP markers validated their effect on kernel-related traits, and they were used to analyze the transmissibility and distribution of superior genotypes in ZKM138 derivatives and global wheat cultivars, respectively. These findings may serve as a reference for future genetic improvement of the ideal kernel morphology.

Whole-genome analysis of hard winter wheat germplasm identifies genomic regions associated with spike and kernel traits.

Genetic dissection of yield component traits including spike and kernel characteristics is essential for the continuous improvement in wheat yield. Genome-wide association studies (GWAS) have been frequently used to identify genetic determinants for spike and kernel-related traits in wheat, though none have been employed in hard winter wheat (HWW) which represents a major class in US wheat acreage. Further, mostof these studies relied on assembled diversity panels instead of adapted breeding lines, limiting the transferability of results to practicalwheat breeding. Here we assembled a population of advanced/elite breeding lines and well-adapted cultivars and evaluated over four environments for phenotypic analysis of spike and kernel traits. GWAS identified 17 significant multi-environment marker-trait associations (MTAs) for various traits, representing 12 putative quantitative trait loci (QTLs), with five QTLs affecting multiple traits. Four of these QTLs mapped on three chromosomes 1A, 5B, and 7A for spike length, number of spikelets per spike (NSPS), and kernel length are likely novel. Further, a highly significant QTL was detected on chromosome 7AS that has not been previously associated with NSPS and putative candidate genes were identified in this region. The allelic frequencies of important quantitative trait nucleotides (QTNs)were deduced in a larger set of 1,124 accessions which revealed the importance of identified MTAs in the US HWW breeding programs. The results from this study could be directly used by thebreeders to select the lines with favorable alleles for making crosses, and reported markers will facilitate marker-assisted selection of stable QTLs for yield components in wheat breeding.

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 660K 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 660K 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.

Analysis of Morphological Variation, Grouping and Path Coefficient Studies in a Set of Maize Inbred Lines Local to North East Hill Region of India

In the current study a total of 191 maize inbred lines were set up in an augmented randomized complete block design to study the genetic variation and interrelationship of different yield contributing parameters. Observations were recorded on a total of nine phenological and ear / kernel related traits. Significant results for ANOVA indicated presence of substantial variation while the first three axes of PCA could explain 75.54% of the variation present. Ear and flowering traits were orthogonal to each other and the highest variation in PC1 could be attributed to total grain weight. This was also reflected in the Agglomerative Hierarchical Clustering which grouped the inbreds into five clusters primarily on the basis of total grain weight which accounted for the highest variation between the clusters. Substantial heritability genetic advance as percentage of mean were observed for total grain weight indicating that selection for grain weight would be fruitful. Association and path coefficient studies after adjustments for multi-collinearity using k constant method (0.05) revealed that total grain weight was highly and positively correlated with ear weight, number of grain kernel rows and seed index. Therefore, simultaneous selection for these traits would be useful. Overall, our studies go on to show presence of sufficient genetic variability in the inbreds under study and hybridization between inbred lines grouped in different clusters have a high chance of producing heterotic hybrids.

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.

Heterologous expression of ZmGS5 enhances organ size and seed weight by regulating cell expansion in Arabidopsis thaliana.

Maize ZmGS5 was reported to be positively associated with kernel-related traits, however, its regulatory mechanism on plant development and seed size remains unknown. In this study, ZmGS5 was demonstrated to be widely expressed in various maize tissues with the highest expression level in developing embryos, indicating its critical roles in early kernel development process. The ZmGS5 protein was subcellularly localized to both the nucleus and cytoplasm. Transgenic Arabidopsis plants overexpressing ZmGS5 under the control of either the constitutive maize Ubiquitin1 promotor or native ZmGS5 promoter resulted in increased plant size, biomass, seed size and weight, although no significant difference was observed between transgenic lines harboring the two constructs. In contrast, the antisense-ZmGS5 transgene resulted in opposite phenotypes. Our cytological data suggested that ZmGS5 enlarged petal size through enhancing cell expansion. Quantitative RT-PCR analysis indicated that ZmGS5 might enhance cell expansion and grain filling by upregulating expression levels of particular EXPA or SWEET genes. Collectively, these findings help us further understand the biological function and regulatory mechanism of ZmGS5 in improving organ size and seed weight, which imply its great potential for high-yield breeding in the future.

Fine mapping of a kernel length-related gene with potential value for maize breeding

A key candidate gene for maize kernel length was fine mapped to an interval of 942 kb; the locus significantly increases kernel length (KL) and hundred-kernel weight (HKW). Kernel size is a major determinant of yield in cereals. Kernel length, one of the determining factors of kernel size, is a target trait for both domestication and artificial breeding. However, there are few reports of fine mapping and quantitative trait loci (QTLs)/cloned genes for kernel length in maize. In this project, a novel major QTL, named qKL9, controlling maize kernel length was identified. We verified the authenticity and stability of qKL9 via BC2F2 and BC3F1 populations, respectively, and ultimately mapped qKL9 to an ~ 942-kb genomic interval by testing the progenies of recombination events derived from BC3F2 and BC4F2 populations in multiple environments. Additionally, one new line (McqKL9−A) containing the ~ 942-kb segment was screened from the BC4F2 population. Combining transcriptome analysis between McqKL9−A and Mc at 6, 9 and 14 days after pollination and candidate regional association mapping, Zm00001d046723 was preliminarily identified as the key candidate gene for qKL9. Importantly, the replacement in the Mc line of the Mc’s alleles by the V671’s alleles in the qKL9 region improved the performances of single-cross hybrids obtained with elite lines, illustrating the potential value of this QTL for the genetic improvement in maize kernel-related traits. These findings facilitate molecular breeding for kernel size and cloning of the gene underlying qKL9, shedding light on the genetic basis of kernel size in maize.

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 4192.62cM 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 23QTLs for different kernel-related traits were first time mapped and five of them were major and stable QTLs for kernel diameter ratio (121.34-126.83cM on 4BS), spike number per square meter (71.32-73.84cM on 2DS), kernel weight per spike (71.32-75.26cM on 2DS), and kernel length (16.78-31.64cM on 6A and 51.63-58.40cM on 3D), respectively. FifteenQTL 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.