Genetic and molecular bases of yield-associated traits: a translational biology approach between rice and wheat

Introgression of chromosome 5P from Agropyron cristatum enhances grain weight in a wheat background

KEY MESSAGE

A grain weight locus from Agropyron cristatum chromosome 5P increases grain weight in different wheat backgrounds and is localized to 5PL (bin 7-12). Thousand-grain weight is an important trait in wheat breeding, with a narrow genetic basis being the main factor limiting improvement. Agropyron cristatum, a wild relative of wheat, harbors many desirable genes for wheat improvement. Here, we found that the introduction of the 5P chromosome from A. cristatum into wheat significantly increased the thousand-grain weight by 2.55-7.10 g, and grain length was the main contributor to grain weight. An increase in grain weight was demonstrated in two commercial wheat varieties, indicating that the grain weight locus was not affected by the wheat background. To identify the chromosome segment harboring the grain weight locus, three A. cristatum 5P deletion lines, two wheat-A. cristatum 5P translocation lines and genetic populations of these lines were used to evaluate agronomic traits. We found that the translocation lines harboring the long arm of A. cristatum chromosome 5P (5PL) exhibited high grain weight and grain length, and the genetic locus associated with increased grain weight was mapped to 5PL (bin 7-12). An increase in grain weight did not adversely affect other agronomic traits in translocation line 5PT2, which is a valuable germplasm resource. Overall, we identified a grain weight locus from chromosome 5PL and provided valuable germplasm for improving wheat grain weight.

Negative regulators of grain yield and mineral contents in rice: potential targets for CRISPR-Cas9-mediated genome editing

Rice is a major global staple food crop, and improving its grain yield and nutritional quality has been a major thrust research area since last decades. Yield and nutritional quality are complex traits which are controlled by multiple signaling pathways. Sincere efforts during past decades of research have identified several key genetic and molecular regulators that governed these complex traits. The advent of clustered regularly interspaced short palindromic repeats (CRISPR)-CRISPR-associated protein 9 (Cas9)-mediated gene knockout approaches has accelerated the development of improved varieties; however, finding out target gene with negative regulatory function in particular trait without giving any pleiotropic effect remains a challenge. Here, we have reviewed past and recent literature and identified important negative regulators of grain yield and mineral contents which could be potential targets for CRISPR-Cas9-mediated gene knockout. Additionally, we have also compiled a list of microRNAs (miRNAs), which target positive regulators of grain yield, plant stress tolerance, and grain mineral contents. Knocking out these miRNAs could help to increase expression of such positive regulators and thus improve the plant trait. The knowledge presented in this review would help to further accelerate the CRISPR-Cas9-mediated trait improvement in rice.

Genetics of Plant Metabolism

This Special Issue is aimed to collect scientific papers that support holistic methodological approaches, both top-down and horizontal, for the correct application of various omics sciences because, when well-integrated, they can contribute to our understanding of the genotypic plasticity of plant species [...].

Breeding for Higher Yields of Wheat and Rice through Modifying Nitrogen Metabolism

Wheat and rice produce nutritious grains that provide 32% of the protein in the human diet globally. Here, we examine how genetic modifications to improve assimilation of the inorganic nitrogen forms ammonium and nitrate into protein influence grain yield of these crops. Successful breeding for modified nitrogen metabolism has focused on genes that coordinate nitrogen and carbon metabolism, including those that regulate tillering, heading date, and ammonium assimilation. Gaps in our current understanding include (1) species differences among candidate genes in nitrogen metabolism pathways, (2) the extent to which relative abundance of these nitrogen forms across natural soil environments shape crop responses, and (3) natural variation and genetic architecture of nitrogen-mediated yield improvement. Despite extensive research on the genetics of nitrogen metabolism since the rise of synthetic fertilizers, only a few projects targeting nitrogen pathways have resulted in development of cultivars with higher yields. To continue improving grain yield and quality, breeding strategies need to focus concurrently on both carbon and nitrogen assimilation and consider manipulating genes with smaller effects or that underlie regulatory networks as well as genes directly associated with nitrogen metabolism.

Genome-Wide Analysis of the GW2-Like Genes in Gossypium and Functional Characterization of the Seed Size Effect of GhGW2-2D

Cotton is one of the most economically important crops worldwide. Seed size is a vital trait for plants connected with yield and germination. GW2 encodes a RING_Ubox E3 ubiquitin ligase that controls seed development by affecting cell growth. Here, are few reports on GW2-like genes in cotton, and the function of GW2 in cotton is poorly understood. In the present study, a genome-wide analysis identified 6 and 3 GW2-like genes in each of the two cultivated tetraploids (Gossypium hirsutum and G. barbadense) and each of their diploid ancestral species (G. arboreum, G. raimondii), respectively. GhGW2-2D has the same functional domain and high sequence similarity with AtDA2 in Arabidopsis. Overexpression of GhGW2-2D in Arabidopsis significantly reduced seed and seedling size, suggesting GhGW2-2D is a potential target for regulating cotton seed size. These results provided information on the genetic and molecular basis of GW2-like genes in cotton, thus establishing a foundation for functional studies of cotton seeds.

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

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

Wheat omics: Classical breeding to new breeding technologies

Wheat is an important cereal crop, and its significance is more due to compete for dietary products in the world. Many constraints facing by the wheat crop due to environmental hazardous, biotic, abiotic stress and heavy matters factors, as a result, decrease the yield. Understanding the molecular mechanism related to these factors is significant to figure out genes regulate under specific conditions. Classical breeding using hybridization has been used to increase the yield but not prospered at the desired level. With the development of newly emerging technologies in biological sciences i.e., marker assisted breeding (MAB), QTLs mapping, mutation breeding, proteomics, metabolomics, next-generation sequencing (NGS), RNA_sequencing, transcriptomics, differential expression genes (DEGs), computational resources and genome editing techniques i.e. (CRISPR cas9; Cas13) advances in the field of omics. Application of new breeding technologies develops huge data; considerable development is needed in bioinformatics science to interpret the data. However, combined omics application to address physiological questions linked with genetics is still a challenge. Moreover, viroid discovery opens the new direction for research, economics, and target specification. Comparative genomics important to figure gene of interest processes are further discussed about considering the identification of genes, genomic loci, and biochemical pathways linked with stress resilience in wheat. Furthermore, this review extensively discussed the omics approaches and their effective use. Integrated plant omics technologies have been used viroid genomes associated with CRISPR and CRISPR-associated Cas13a proteins system used for engineering of viroid interference along with high-performance multidimensional phenotyping as a significant limiting factor for increasing stress resistance in wheat.

Dissection of Molecular Processes and Genetic Architecture Underlying Iron and Zinc Homeostasis for Biofortification: From Model Plants to Common Wheat

The micronutrients iron (Fe) and zinc (Zn) are not only essential for plant survival and proliferation but are crucial for human health. Increasing Fe and Zn levels in edible parts of plants, known as biofortification, is seen a sustainable approach to alleviate micronutrient deficiency in humans. Wheat, as one of the leading staple foods worldwide, is recognized as a prioritized choice for Fe and Zn biofortification. However, to date, limited molecular and physiological mechanisms have been elucidated for Fe and Zn homeostasis in wheat. The expanding molecular understanding of Fe and Zn homeostasis in model plants is providing invaluable resources to biofortify wheat. Recent advancements in NGS (next generation sequencing) technologies coupled with improved wheat genome assembly and high-throughput genotyping platforms have initiated a revolution in resources and approaches for wheat genetic investigations and breeding. Here, we summarize molecular processes and genes involved in Fe and Zn homeostasis in the model plants Arabidopsis and rice, identify their orthologs in the wheat genome, and relate them to known wheat Fe/Zn QTL (quantitative trait locus/loci) based on physical positions. The current study provides the first inventory of the genes regulating grain Fe and Zn homeostasis in wheat, which will benefit gene discovery and breeding, and thereby accelerate the release of Fe- and Zn-enriched wheats.

Appraising the Genetic Architecture of Kernel Traits in Hexaploid Wheat Using GWAS

Kernel morphology is one of the major yield traits of wheat, the genetic architecture of which is always important in crop breeding. In this study, we performed a genome-wide association study (GWAS) to appraise the genetic architecture of the kernel traits of 319 wheat accessions using 22,905 single nucleotide polymorphism (SNP) markers from a wheat 90K SNP array. As a result, 111 and 104 significant SNPs for Kernel traits were detected using four multi-locus GWAS models (mrMLM, FASTmrMLM, FASTmrEMMA, and pLARmEB) and three single-locus models (FarmCPU, MLM, and MLMM), respectively. Among the 111 SNPs detected by the multi-locus models, 24 SNPs were simultaneously detected across multiple models, including seven for kernel length, six for kernel width, six for kernels per spike, and five for thousand kernel weight. Interestingly, the five most stable SNPs (RAC875_29540_391, Kukri_07961_503, tplb0034e07_1581, BS00074341_51, and BobWhite_049_3064) were simultaneously detected by at least three multi-locus models. Integrating these newly developed multi-locus GWAS models to unravel the genetic architecture of kernel traits, the mrMLM approach detected the maximum number of SNPs. Furthermore, a total of 41 putative candidate genes were predicted to likely be involved in the genetic architecture underlining kernel traits. These findings can facilitate a better understanding of the complex genetic mechanisms of kernel traits and may lead to the genetic improvement of grain yield in wheat.

Genetic architecture underpinning yield component traits in wheat

Genetic atlas, reliable QTL and candidate genes of yield component traits in wheat were figured out, laying concrete foundations for map-based gene cloning and dissection of regulatory mechanisms underlying yield. Mining genetic loci for yield is challenging due to the polygenic nature, large influence of environment and complex relationship among yield component traits (YCT). Many genetic loci related to wheat yield have been identified, but its genetic architecture and key genetic loci for selection are largely unknown. Wheat yield potential can be determined by three YCT, thousand kernel weight, kernel number per spike and spike number. Here, we summarized the genetic loci underpinning YCT from QTL mapping, association analysis and homology-based gene cloning. The major loci determining yield-associated agronomic traits, such as flowering time and plant height, were also included in comparative analyses with those for YCT. We integrated yield-related genetic loci onto chromosomes based on their physical locations. To identify the major stable loci for YCT, 58 QTL-rich clusters (QRC) were defined based on their distribution on chromosomes. Candidate genes in each QRC were predicted according to gene annotation of the wheat reference genome and previous information on validation of those genes in other species. Finally, a technological route was proposed to take full advantage of the resultant resources for gene cloning, molecular marker-assisted breeding and dissection of molecular regulatory mechanisms underlying wheat yield.

From markers to genome-based breeding in wheat

Recent technological advances in wheat genomics provide new opportunities to uncover genetic variation in traits of breeding interest and enable genome-based breeding to deliver wheat cultivars for the projected food requirements for 2050. There has been tremendous progress in development of whole-genome sequencing resources in wheat and its progenitor species during the last 5 years. High-throughput genotyping is now possible in wheat not only for routine gene introgression but also for high-density genome-wide genotyping. This is a major transition phase to enable genome-based breeding to achieve progressive genetic gains to parallel to projected wheat production demands. These advances have intrigued wheat researchers to practice less pursued analytical approaches which were not practiced due to the short history of genome sequence availability. Such approaches have been successful in gene discovery and breeding applications in other crops and animals for which genome sequences have been available for much longer. These strategies include, (i) environmental genome-wide association studies in wheat genetic resources stored in genbanks to identify genes for local adaptation by using agroclimatic traits as phenotypes, (ii) haplotype-based analyses to improve the statistical power and resolution of genomic selection and gene mapping experiments, (iii) new breeding strategies for genome-based prediction of heterosis patterns in wheat, and (iv) ultimate use of genomics information to develop more efficient and robust genome-wide genotyping platforms to precisely predict higher yield potential and stability with greater precision. Genome-based breeding has potential to achieve the ultimate objective of ensuring sustainable wheat production through developing high yielding, climate-resilient wheat cultivars with high nutritional quality.

Paleogenomics: reconstruction of plant evolutionary trajectories from modern and ancient DNA

How contemporary plant genomes originated and evolved is a fascinating question. One approach uses reference genomes from extant species to reconstruct the sequence and structure of their common ancestors over deep timescales. A second approach focuses on the direct identification of genomic changes at a shorter timescale by sequencing ancient DNA preserved in subfossil remains. Merged within the nascent field of paleogenomics, these complementary approaches provide insights into the evolutionary forces that shaped the organization and regulation of modern genomes and open novel perspectives in fostering genetic gain in breeding programs and establishing tools to predict future population changes in response to anthropogenic pressure and global warming.

Genetic analysis of multi-environmental spring wheat trials identifies genomic regions for locus-specific trade-offs for grain weight and grain number

GWAS on multi-environment data identified genomic regions associated with trade-offs for grain weight and grain number. Grain yield (GY) can be dissected into its components thousand grain weight (TGW) and grain number (GN), but little has been achieved in assessing the trade-off between them in spring wheat. In the present study, the Wheat Association Mapping Initiative (WAMI) panel of 287 elite spring bread wheat lines was phenotyped for GY, GN, and TGW in ten environments across different wheat growing regions in Mexico, South Asia, and North Africa. The panel genotyped with the 90 K Illumina Infinitum SNP array resulted in 26,814 SNPs for genome-wide association study (GWAS). Statistical analysis of the multi-environmental data for GY, GN, and TGW observed repeatability estimates of 0.76, 0.62, and 0.95, respectively. GWAS on BLUPs of combined environment analysis identified 38 loci associated with the traits. Among them four loci-6A (85 cM), 5A (98 cM), 3B (99 cM), and 2B (96 cM)-were associated with multiple traits. The study identified two loci that showed positive association between GY and TGW, with allelic substitution effects of 4% (GY) and 1.7% (TGW) for 6A locus and 0.2% (GY) and 7.2% (TGW) for 2B locus. The locus in chromosome 6A (79-85 cM) harbored a gene TaGW2-6A. We also identified that a combination of markers associated with GY, TGW, and GN together explained higher variation for GY (32%), than the markers associated with GY alone (27%). The marker-trait associations from the present study can be used for marker-assisted selection (MAS) and to discover the underlying genes for these traits in spring wheat.

TaFlo2-A1, an ortholog of rice Flo2, is associated with thousand grain weight in bread wheat (Triticum aestivum L.)

BACKGROUND

The Flo2 gene is a member of a conserved gene family in plants. This gene has been found to be related to thousand grain weight (TGW) in rice. Its orthologs in hexaploid wheat were cloned, and the haplotype variation in TaFlo2-A1 was tested for association with TGW.

RESULTS

The cloned sequences of TaFlo2-A1, TaFlo2-B1 and TaFlo2-D1 contained 23, 23 and 24 exons, respectively. The deduced proteins of TaFlo2-A1 (1734 aa), TaFlo2-B1 (1698 aa) and TaFlo2-D1 (1682 aa) were highly similar (>94%) and exhibited >77% similarity with the rice FLO2 protein. Like the rice FLO2 protein, four tetratricopeptide repeat (TPR) motifs were observed in the deduced TaFLO2 protein. An 8-bp InDel (-10 to -17 bp) in the promoter region and five SNPs in first intron of TaFlo2-A1 together formed two haplotypes, TaFlo2-A1a and TaFlo2-A1b, in bread wheat. TaFlo2 was located on homeologous group 2 chromosomes. TaFlo2-A1 was inferred to be located on deletion bin '2AL1-0.85-1.00'. The TaFlo2-A1 haplotypes were characterized in the Chinese Micro Core Collection (MCC) and Pakistani wheat collection using the molecular marker TaFlo2-Indel8. TaFlo2-A1 was found to be associated with TGW but not with grain number per spike (GpS) in both the MCC and Pakistani wheat collections. The frequency of TaFlo2-A1b (positive haplotype) was low in commercial wheat cultivars; thus this haplotype can be selected to improve grain weight without negatively affecting GpS. The expression level of TaFlo2-A1 in developing grains at 5 DAF (days after flowering) was positively correlated with TGW in cultivars carrying the positive haplotype.

CONCLUSION

This study will likely lead to additional investigations to understand the regulatory mechanism of the Flo2 gene in hexaploid wheat. Furthermore, the newly developed molecular marker 'TaFlo2-InDel8' could be incorporated into the kit of wheat breeders for use in marker-assisted selection.

QTL mapping and comparative genome analysis of agronomic traits including grain yield in winter rye

Genetic diversity in elite rye germplasm as well as F _2:3 testcross design enables fast QTL mapping to approach genes controlling grain yield, grain weight, tiller number and heading date in rye hybrids. Winter rye (Secale cereale L.) is a multipurpose cereal crop closely related to wheat, which offers the opportunity for a sustainable production of food and feed and which continues to emerge as a renewable energy source for the production of bioethanol and biomethane. Rye contributes to increase agricultural crop species diversity particularly in Central and Eastern Europe. In contrast to other small grain cereals, knowledge on the genetic architecture of complex inherited, agronomic important traits is yet limited for the outbreeding rye. We have performed a QTL analysis based on a F_2:3 design and testcross performance of 258 experimental hybrids in multi-environmental field trials. A genetic linkage map covering 964.9 cM based on SSR, conserved-orthologous set (COS), and mixed-phase dominant DArT markers allowed to describe 22 QTL with significant effects for grain yield, heading date, tiller number, and thousand grain weight across seven environments. Using rye COS markers, orthologous segments for these traits have been identified in the rice genome, which carry cloned and functionally characterized rice genes. The initial genome scan described here together with the existing knowledge on candidate genes provides the basis for subsequent analyses of the genetic and molecular mechanisms underlying agronomic important traits in rye.

Crop Breeding Chips and Genotyping Platforms: Progress, Challenges, and Perspectives

There is a rapidly rising trend in the development and application of molecular marker assays for gene mapping and discovery in field crops and trees. Thus far, more than 50 SNP arrays and 15 different types of genotyping-by-sequencing (GBS) platforms have been developed in over 25 crop species and perennial trees. However, much less effort has been made on developing ultra-high-throughput and cost-effective genotyping platforms for applied breeding programs. In this review, we discuss the scientific bottlenecks in existing SNP arrays and GBS technologies and the strategies to develop targeted platforms for crop molecular breeding. We propose that future practical breeding platforms should adopt automated genotyping technologies, either array or sequencing based, target functional polymorphisms underpinning economic traits, and provide desirable prediction accuracy for quantitative traits, with universal applications under wide genetic backgrounds in crops. The development of such platforms faces serious challenges at both the technological level due to cost ineffectiveness, and the knowledge level due to large genotype-phenotype gaps in crop plants. It is expected that such genotyping platforms will be achieved in the next ten years in major crops in consideration of (a) rapid development in gene discovery of important traits, (b) deepened understanding of quantitative traits through new analytical models and population designs, (c) integration of multi-layer -omics data leading to identification of genes and pathways responsible for important breeding traits, and (d) improvement in cost effectiveness of large-scale genotyping. Crop breeding chips and genotyping platforms will provide unprecedented opportunities to accelerate the development of cultivars with desired yield potential, quality, and enhanced adaptation to mitigate the effects of climate change.

Source-sink interaction: a century old concept under the light of modern molecular systems biology

Many approaches to engineer source strength have been proposed to enhance crop yield potential. However, a well-co-ordinated source-sink relationship is required finally to realize the promised increase in crop yield potential in the farmer's field. Source-sink interaction has been intensively studied for decades, and a vast amount of knowledge about the interaction in different crops and under different environments has been accumulated. In this review, we first introduce the basic concepts of source, sink and their interactions, then summarize current understanding of how source and sink can be manipulated through both environmental control and genetic manipulations. We show that the source-sink interaction underlies the diverse responses of crops to the same perturbations and argue that development of a molecular systems model of source-sink interaction is required towards a rational manipulation of the source-sink relationship for increased yield. We finally discuss both bottom-up and top-down routes to develop such a model and emphasize that a community effort is needed for development of this model.

Major genes determining yield-related traits in wheat and barley

Current development of advanced biotechnology tools allows us to characterize the role of key genes in plant productivity. The implementation of this knowledge in breeding strategies might accelerate the progress in obtaining high-yielding cultivars. The achievements of the Green Revolution were based on a specific plant ideotype, determined by a single gene involved in gibberellin signaling or metabolism. Compared with the 1950s, an enormous increase in our knowledge about the biological basis of plant productivity has opened new avenues for novel breeding strategies. The large and complex genomes of diploid barley and hexaploid wheat represent a great challenge, but they also offer a large reservoir of genes that can be targeted for breeding. We summarize examples of productivity-related genes/mutants in wheat and barley, identified or characterized by means of modern biology. The genes are classified functionally into several groups, including the following: (1) transcription factors, regulating spike development, which mainly affect grain number; (2) genes involved in metabolism or signaling of growth regulators-cytokinins, gibberellins, and brassinosteroids-which control plant architecture and in consequence stem hardiness and grain yield; (3) genes determining cell division and proliferation mainly impacting grain size; (4) floral regulators influencing inflorescence architecture and in consequence seed number; and (5) genes involved in carbohydrate metabolism having an impact on plant architecture and grain yield. The implementation of selected genes in breeding programs is discussed, considering specific genotypes, agronomic and climate conditions, and taking into account that many of the genes are members of multigene families.

Reconciling the evolutionary origin of bread wheat (Triticum aestivum)

The origin of bread wheat (Triticum aestivum; AABBDD) has been a subject of controversy and of intense debate in the scientific community over the last few decades. In 2015, three articles published in New Phytologist discussed the origin of hexaploid bread wheat (AABBDD) from the diploid progenitors Triticum urartu (AA), a relative of Aegilops speltoides (BB) and Triticum tauschii (DD). Access to new genomic resources since 2013 has offered the opportunity to gain novel insights into the paleohistory of modern bread wheat, allowing characterization of its origin from its diploid progenitors at unprecedented resolution. We propose a reconciled evolutionary scenario for the modern bread wheat genome based on the complementary investigation of transposable element and mutation dynamics between diploid, tetraploid and hexaploid wheat. In this scenario, the structural asymmetry observed between the A, B and D subgenomes in hexaploid bread wheat derives from the cumulative effect of diploid progenitor divergence, the hybrid origin of the D subgenome, and subgenome partitioning following the polyploidization events.

Identification of QTL for Grain Size and Shape on the D Genome of Natural and Synthetic Allohexaploid Wheats with Near-Identical AABB Genomes

Grain size and shape associated with yield and milling quality are important traits in wheat domestication and breeding. To reveal the genetic factors on the D genome that control grain size and shape variation, we conducted analysis of quantitative trait loci (QTL) using the F₂ and F_2:3 populations derived from a common allohexaploid wheat line TAA10 and a synthetic allohexaploid wheat XX329, which have near-identical AABB genomes and different DD genomes. Based on genotyping using wheat 660K single nucleotide polymorphism (SNP) array, TAA10 and XX329 exhibited 96.55, 98.10, and 66.26% genetic similarities of A, B, and D genomes, respectively. Phenotypic evaluation revealed that XX329 had higher thousand grain weight (TGW), grain length, width, area and perimeter than TAA10 across all environments, and the grain yield per plot of XX329 increased by 17.43-30.36% compared with that of TAA10 in two environments. A total of nine environmentally stable QTL associated with grain size and shape were mapped on chromosomes 2D and 7D and verified using near isogenic lines (NILs), with the synthetic allohexaploid wheat XX329 contributing favorable alleles. Notably, a novel QTL QTgw.cau-2D controlling grain weight was first identified from the synthetic allohexaploid wheat, which may be a more desirable target for genetic improvement in wheat breeding. Collectively, these results provide further insights into the genetic factors that shaped the grain morphology during wheat evolution and domestication.

Combined Genomic and Genetic Data Integration of Major Agronomical Traits in Bread Wheat (Triticum aestivum L.)

The high resolution integration of bread wheat genetic and genomic resources accumulated during the last decades offers the opportunity to unveil candidate genes driving major agronomical traits to an unprecedented scale. We combined 27 public quantitative genetic studies and four genetic maps to deliver an exhaustive consensus map consisting of 140,315 molecular markers hosting 221, 73, and 82 Quantitative Trait Loci (QTL) for respectively yield, baking quality, and grain protein content (GPC) related traits. Projection of the consensus genetic map and associated QTLs onto the wheat syntenome made of 99,386 genes ordered on the 21 chromosomes delivered a complete and non-redundant repertoire of 18, 8, 6 metaQTLs for respectively yield, baking quality and GPC, altogether associated to 15,772 genes (delivering 28,630 SNP-based makers) including 37 major candidates. Overall, this study illustrates a translational research approach in transferring information gained from grass relatives to dissect the genomic regions hosting major loci governing key agronomical traits in bread wheat, their flanking markers and associated candidate genes to be now considered as a key resource for breeding programs.

Development and validation of KASP assays for genes underpinning key economic traits in bread wheat

We developed and validated a robust marker toolkit for high-throughput and cost-effective screening of a large number of functional genes in wheat. Functional markers (FMs) are the most valuable markers for crop breeding programs, and high-throughput genotyping for FMs could provide an excellent opportunity to effectively practice marker-assisted selection while breeding cultivars. Here we developed and validated kompetitive allele-specific PCR (KASP) assays for genes that underpin economically important traits in bread wheat including adaptability, grain yield, quality, and biotic and abiotic stress resistances. In total, 70 KASP assays either developed in this study or obtained from public databases were validated for reliability in application. The validation of KASP assays were conducted by (a) comparing the assays with available gel-based PCR markers on 23 diverse wheat accessions, (b) validation of the derived allelic information using phenotypes of a panel comprised of 300 diverse cultivars from China and 13 other countries, and (c) additional testing, where possible, of the assays in four segregating populations. All KASP assays being reported were significantly associated with the relevant phenotypes in the cultivars panel and bi-parental populations, thus revealing potential application in wheat breeding programs. The results revealed 45 times superiority of the KASP assays in speed than gel-based PCR markers. KASP has recently emerged as single-plex high-throughput genotyping technology; this is the first report on high-throughput screening of a large number of functional genes in a major crop. Such assays could greatly accelerate the characterization of crossing parents and advanced lines for marker-assisted selection and can complement the inflexible, high-density SNP arrays. Our results offer a robust and reliable molecular marker toolkit that can contribute towards maximizing genetic gains in wheat breeding programs.

Considering causal genes in the genetic dissection of kernel traits in common wheat

Genetic factors controlling thousand-kernel weight (TKW) were characterized for their association with other seed traits, including kernel width, kernel length, ratio of kernel width to kernel length (KW/KL), kernel area, and spike number per m² (SN). For this purpose, a genetic map was established utilizing a doubled haploid population derived from a cross between German winter wheat cultivars Pamier and Format. Association studies in a diversity panel of elite cultivars supplemented genetic analysis of kernel traits. In both populations, genomic signatures of 13 candidate genes for TKW and kernel size were analyzed. Major quantitative trait loci (QTL) for TKW were identified on chromosomes 1B, 2A, 2D, and 4D, and their locations coincided with major QTL for kernel size traits, supporting the common belief that TKW is a function of other kernel traits. The QTL on chromosome 2A was associated with TKW candidate gene TaCwi-A1 and the QTL on chromosome 4D was associated with dwarfing gene Rht-D1. A minor QTL for TKW on chromosome 6B coincided with TaGW2-6B. The QTL for kernel dimensions that did not affect TKW were detected on eight chromosomes. A major QTL for KW/KL located at the distal tip of chromosome arm 5AS is being reported for the first time. TaSus1-7A and TaSAP-A1, closely linked to each other on chromosome 7A, could be related to a minor QTL for KW/KL. Genetic analysis of SN confirmed its negative correlation with TKW in this cross. In the diversity panel, TaSus1-7A was associated with TKW. Compared to the Pamier/Format bi-parental population where TaCwi-A1a was associated with higher TKW, the same allele reduced grain yield in the diversity panel, suggesting opposite effects of TaCwi-A1 on these two traits.

Advanced phenotyping and phenotype data analysis for the study of plant growth and development

Due to an increase in the consumption of food, feed, fuel and to meet global food security needs for the rapidly growing human population, there is a necessity to breed high yielding crops that can adapt to the future climate changes, particularly in developing countries. To solve these global challenges, novel approaches are required to identify quantitative phenotypes and to explain the genetic basis of agriculturally important traits. These advances will facilitate the screening of germplasm with high performance characteristics in resource-limited environments. Recently, plant phenomics has offered and integrated a suite of new technologies, and we are on a path to improve the description of complex plant phenotypes. High-throughput phenotyping platforms have also been developed that capture phenotype data from plants in a non-destructive manner. In this review, we discuss recent developments of high-throughput plant phenotyping infrastructure including imaging techniques and corresponding principles for phenotype data analysis.

Genome-wide association for grain yield under rainfed conditions in historical wheat cultivars from Pakistan

Genome-wide association studies (GWAS) were undertaken to identify SNP markers associated with yield and yield-related traits in 123 Pakistani historical wheat cultivars evaluated during 2011-2014 seasons under rainfed field conditions. The population was genotyped by using high-density Illumina iSelect 90K single nucleotide polymorphism (SNP) assay, and finally 14,960 high quality SNPs were used in GWAS. Population structure examined using 1000 unlinked markers identified seven subpopulations (K = 7) that were representative of different breeding programs in Pakistan, in addition to local landraces. Forty four stable marker-trait associations (MTAs) with -log p > 4 were identified for nine yield-related traits. Nine multi-trait MTAs were found on chromosomes 1AL, 1BS, 2AL, 2BS, 2BL, 4BL, 5BL, 6AL, and 6BL, and those on 5BL and 6AL were stable across two seasons. Gene annotation and syntey identified that 14 trait-associated SNPs were linked to genes having significant importance in plant development. Favorable alleles for days to heading (DH), plant height (PH), thousand grain weight (TGW), and grain yield (GY) showed minor additive effects and their frequencies were slightly higher in cultivars released after 2000. However, no selection pressure on any favorable allele was identified. These genomic regions identified have historically contributed to achieve yield gains from 2.63 million tons in 1947 to 25.7 million tons in 2015. Future breeding strategies can be devised to initiate marker assisted breeding to accumulate these favorable alleles of SNPs associated with yield-related traits to increase grain yield. Additionally, in silico identification of 454-contigs corresponding to MTAs will facilitate fine mapping and subsequent cloning of candidate genes and functional marker development.

Advanced phenotyping and phenotype data analysis for the study of plant growth and development

Due to an increase in the consumption of food, feed, fuel and to meet global food security needs for the rapidly growing human population, there is a necessity to breed high yielding crops that can adapt to the future climate changes, particularly in developing countries. To solve these global challenges, novel approaches are required to identify quantitative phenotypes and to explain the genetic basis of agriculturally important traits. These advances will facilitate the screening of germplasm with high performance characteristics in resource-limited environments. Recently, plant phenomics has offered and integrated a suite of new technologies, and we are on a path to improve the description of complex plant phenotypes. High-throughput phenotyping platforms have also been developed that capture phenotype data from plants in a non-destructive manner. In this review, we discuss recent developments of high-throughput plant phenotyping infrastructure including imaging techniques and corresponding principles for phenotype data analysis.

Analysis of main effect QTL for thousand grain weight in European winter wheat (Triticum aestivum L.) by genome-wide association mapping

Grain weight, an essential yield component, is under strong genetic control and at the same time markedly influenced by the environment. Genetic analysis of the thousand grain weight (TGW) by genome-wide association study (GWAS) was performed with a panel of 358 European winter wheat (Triticum aestivum L.) varieties and 14 spring wheat varieties using phenotypic data of field tests in eight environments. Wide phenotypic variations were indicated for the TGW with BLUEs (best linear unbiased estimations) values ranging from 35.9 to 58.2 g with a mean value of 45.4 g and a heritability of H(2) = 0.89. A total of 12 candidate genes for plant height, photoperiodism and grain weight were genotyped on all varieties. Only three candidates, the photoperiodism gene Ppd-D1, dwarfing gene Rht-B1and the TaGW-6A gene were significant explaining up to 14.4, 2.3, and 3.4% of phenotypic variation, respectively. For a comprehensive genome-wide analysis of TGW-QTL genotyping data from 732 microsatellite markers and a set of 7769 mapped SNP-markers genotyped with the 90k iSELECT array were analyzed. In total, 342 significant (-log10 (P-value) ≥ 3.0) marker trait associations (MTAs) were detected for SSR-markers and 1195 MTAs (-log10(P-value) ≥ 3.0) for SNP-markers in all single environments plus the BLUEs. After Bonferroni correction, 28 MTAs remained significant for SSR-markers (-log10 (P-value) ≥ 4.82) and 58 MTAs for SNP-markers (-log10 (P-value) ≥ 5.89). Apart from chromosomes 4B and 6B for SSR-markers and chromosomes 4D and 5D for SNP-markers, MTAs were detected on all chromosomes. The highest number of significant SNP-markers was found on chromosomes 3B and 1B, while for the SSRs most markers were significant on chromosomes 6D and 3D. Overall, TGW was determined by many markers with small effects. Only three SNP-markers had R(2) values above 6%.