The genetic gain in yield and quality are two major targets of wheat breeding programs around the world. In this study, a high density genetic map consisting of 10,172 SNP markers identified a total ...of 43 genomic regions associated with three quality traits, three yield traits and two agronomic traits in hard red spring wheat (HRSW). When compared with six grain shape and size traits, the quality traits showed mostly independent genetic control (~18% common loci), while the yield traits showed moderate association (~53% common loci). Association of genomic regions for grain area (GA) and thousand-grain weight (TGW), with yield suggests that targeting an increase in GA may help enhancing wheat yield through an increase in TGW. Flour extraction (FE), although has a weak positive phenotypic association with grain shape and size, they do not share any common genetic loci. A major contributor to plant height was the Rht8 locus and the reduced height allele was associated with significant increase in grains per spike (GPS) and FE, and decrease in number of spikes per square meter and test weight. Stable loci were identified for almost all the traits. However, we could not find any QTL in the region of major known genes like GPC-B1, Ha, Rht-1, and Ppd-1. Epistasis also played an important role in the genetics of majority of the traits. In addition to enhancing our knowledge about the association of wheat quality and yield with grain shape and size, this study provides novel loci, genetic information and pre-breeding material (combining positive alleles from both parents) to enhance the cultivated gene pool in wheat germplasm. These resources are valuable in facilitating molecular breeding for wheat quality and yield improvement.
The objective of this paper is to review progress made in wheat breeding for Fusarium head blight (FHB) resistance in China, the United States of America (USA), and Canada. In China, numerous Chinese ...landraces possessing high levels of FHB resistance were grown before the 1950s. Later, pyramiding multiple sources of FHB resistance from introduced germplasm such as Mentana and Funo and locally adapted cultivars played a key role in combining satisfactory FHB resistance and high yield potential in commercial cultivars. Sumai 3, a Chinese spring wheat cultivar, became a major source of FHB resistance in the USA and Canada, and contributed to the release of more than 20 modern cultivars used for wheat production, including the leading hard spring wheat cultivars Alsen, Glenn, Barlow and SY Ingmar from North Dakota, Faller and Prosper from Minnesota, and AAC Brandon from Canada. Brazilian wheat cultivar Frontana, T. dicoccoides and other local germplasm provided additional sources of resistance. The FHB resistant cultivars mostly relied on stepwise accumulation of favorable alleles of both genes for FHB resistance and high yield, with marker-assisted selection being a valuable complement to phenotypic selection. With the Chinese Spring reference genome decoded and resistance gene Fhb1 now cloned, new genomic tools such as genomic selection and gene editing will be available to breeders, thus opening new possibilities for development of FHB resistant cultivars.
Among the biotic constraints to wheat (Triticum aestivum L.) production, fusarium head blight (FHB), caused by Fusarium graminearum, leaf rust (LR), caused by Puccinia triticina, and stripe rust (SR) ...caused by Puccinia striiformis are problematic fungal diseases worldwide. Each can significantly reduce grain yield while FHB causes additional food and feed safety concerns due to mycotoxin contamination of grain. Genetic resistance is the most effective and sustainable approach for managing wheat diseases. In the past 20 years, over 500 quantitative trait loci (QTLs) conferring small to moderate effects for the different FHB resistance types have been reported in wheat. Similarly, 79 Lr-genes and more than 200 QTLs and 82 Yr-genes and 140 QTLs have been reported for seedling and adult plant LR and SR resistance, respectively. Most QTLs conferring rust resistance are race-specific generally conforming to a classical gene-for-gene interaction while resistance to FHB exhibits complex polygenic inheritance with several genetic loci contributing to one resistance type. Identification and deployment of additional genes/QTLs associated with FHB and rust resistance can expedite wheat breeding through marker-assisted and/or genomic selection to combine small-effect QTL in the gene pool. LR disease has been present in the southeast United States for decades while SR and FHB have become increasingly problematic in the past 20 years, with FHB arguably due to increased corn acreage in the region. Currently, QTLs on chromosome 1B from Jamestown, 1A, 1B, 2A, 2B, 2D, 4A, 5A, and 6A from W14, Ning7840, Ernie, Bess, Massey, NC-Neuse, and Truman, and 3B (Fhb1) from Sumai 3 for FHB resistance, Lr9, Lr10, Lr18, Lr24, Lr37, LrA2K, and Lr2K38 genes for LR resistance, and Yr17 and YrR61 for SR resistance have been extensively deployed in southeast wheat breeding programs. This review aims to disclose the current status of FHB, LR, and SR diseases, summarize the genetics of resistance and breeding efforts for the deployment of FHB and rust resistance QTL on soft red winter wheat cultivars, and present breeding strategies to achieve sustainable management of these diseases in the southeast US.
In humid and temperate areas, Septoria nodorum blotch (SNB) is a major fungal disease of common wheat (Triticum aestivum L.) in which grain yield is reduced when the pathogen, Parastagonospora ...nodorum, infects leaves and glumes during grain filling. Foliar SNB susceptibility may be associated with sensitivity to P. nodorum necrotrophic effectors (NEs). Both foliar and glume susceptibility are quantitative, and the underlying genetics are not understood in detail. We genetically mapped resistance quantitative trait loci (QTL) to leaf and glume blotch using a double haploid (DH) population derived from the cross between the moderately susceptible cultivar AGS2033 and the resistant breeding line GA03185-12LE29. The population was evaluated for SNB resistance in the field in four successive years (2018-2021). We identified major heading date (HD) and plant height (PH) variants on chromosomes 2A and 2D, co-located with SNB escape mechanisms. Five QTL with small effects associated with adult plant resistance to SNB leaf and glume blotch were detected on 1A, 1B, and 6B linkage groups. These QTL explained a relatively small proportion of the total phenotypic variation, ranging from 5.6 to 11.8%. The small-effect QTL detected in this study did not overlap with QTL associated with morphological and developmental traits, and thus are sources of resistance to SNB.
Genetic variation in growth over the course of the season is a major source of grain yield variation in wheat, and for this reason variants controlling heading date and plant height are among the ...best-characterized in wheat genetics. While the major variants for these traits have been cloned, the importance of these variants in contributing to genetic variation for plant growth over time is not fully understood. Here we develop a biparental population segregating for major variants for both plant height and flowering time to characterize the genetic architecture of the traits and identify additional novel QTL. We find that additive genetic variation for both traits is almost entirely associated with major and moderate-effect QTL, including four novel heading date QTL and four novel plant height QTL. FT2 and Vrn-A3 are proposed as candidate genes underlying QTL on chromosomes 3A and 7A, while Rht8 is mapped to chromosome 2D. These mapped QTL also underlie genetic variation in a longitudinal analysis of plant growth over time. The oligogenic architecture of these traits is further demonstrated by the superior trait prediction accuracy of QTL-based prediction models compared to polygenic genomic selection models. In a population constructed from two modern wheat cultivars adapted to the southeast U.S., almost all additive genetic variation in plant growth traits is associated with known major variants or novel moderate-effect QTL. Major transgressive segregation was observed in this population despite the similar plant height and heading date characters of the parental lines. This segregation is being driven primarily by a small number of mapped QTL, instead of by many small-effect, undetected QTL. As most breeding populations in the southeast U.S. segregate for known QTL for these traits, genetic variation in plant height and heading date in these populations likely emerges from similar combinations of major and moderate effect QTL. We can make more accurate and cost-effective prediction models by targeted genotyping of key SNPs.
Wheat is the most important source of food, feed, and nutrition for humans and livestock around the world. The expanding population has increasing demands for various wheat products with different ...quality attributes requiring the development of wheat cultivars that fulfills specific demands of end-users including millers and bakers in the international market. Therefore, wheat breeding programs continually strive to meet these quality standards by screening their improved breeding lines every year. However, the direct measurement of various end-use quality traits such as milling and baking qualities requires a large quantity of grain, traits-specific expensive instruments, time, and an expert workforce which limits the screening process. With the advancement of sequencing technologies, the study of the entire plant genome is possible, and genetic mapping techniques such as quantitative trait locus mapping and genome-wide association studies have enabled researchers to identify loci/genes associated with various end-use quality traits in wheat. Modern breeding techniques such as marker-assisted selection and genomic selection allow the utilization of these genomic resources for the prediction of quality attributes with high accuracy and efficiency which speeds up crop improvement and cultivar development endeavors. In addition, the candidate gene approach through functional as well as comparative genomics has facilitated the translation of the genomic information from several crop species including wild relatives to wheat. This review discusses the various end-use quality traits of wheat, their genetic control mechanisms, the use of genetics and genomics approaches for their improvement, and future challenges and opportunities for wheat breeding.
Farinograph and mixograph-related parameters are key elements in wheat end-products quality. Understanding the genetic control of these traits and the influence of environmental factors such as heat ...stress, and their interaction are critical for developing cultivars with improved for those traits. To identify QTL for six farinograph and three mixograph traits, two double haploid (DH) populations (Yecora Rojo × Ksu106 and Klasic × Ksu105) were used in experiments conducted at Riyadh and Al Qassim locations under heat stress. Single nucleotide polymorphism (SNP) markers were used to determine the number of QTLs controlling these parameters. The genetic analysis of farinograph and mixograph-related traits showed considerable variation with transgressive segregation regardless of heat stress conditions in both locations. A total of 108 additive QTLs were detected for the six farinograph and three mixograph traits in the Yecora Rojo × Ksu106 population in both locations under heat treatments. These QTLs were distributed over all 21 wheat chromosomes except 3A. Similarly, in Klassic × Ksu105 population, there were an additional 68 QTLs identified over the two locations and were allocated on all chromosomes except 1D, 2A, 6A, and 6D. In population (Yecora Rojo × Ksu106), the QTL on chromosome 7A (
Excalibur_c62415_288
) showed significant effects for farinograph and mixograph traits (FDDT, FDST, FBD, M × h8, and M × t) under normal and heat stress condition at both locations. Interestingly, several QTLs that are related to farinograph and mixograph traits, which showed stable expression under both locations, were detected on chromosome 7A in population (Klassic × Ksu105). Results from this study show the quantitative nature of the genetic control of the studied traits and constitute a step toward identifying major QTLs that can be sued molecular-marker assisted breeding to develop new improved quality wheat cultivars.
Core Ideas
The emergence of new virulent Puccinia triticina races requires a continuous search for novel sources of resistance to combat leaf rust (LR) disease
Twenty‐two wheat genotypes resistant to ...four P. triticina races were identified in this study
A genome‐wide association study detected 11 quantitative trait loci for LR resistance; five of them were detected on genomic regions where no LR resistant genes have been detected.
Wheat (Triticum aestivum L.) production worldwide is being challenged by several biotic and abiotic factors. Leaf rust (LR), caused by Puccinia triticina, is a major biotic constraint of wheat production worldwide. Genetic resistance is the most efficient and cost‐effective way to control LR. Seventy‐nine LR resistance genes have been identified to date but the frequent emergence of new virulent P. triticina races every year demands a constant search for new sources of resistance with novel quantitative trait loci (QTL) or genes. The objectives of this study were to identify putative novel sources of effective resistance against the current prevalent races of P. triticina in the southeast United States and to map genomic loci associated with LR resistance via a genome‐wide association study (GWAS) approach. Evaluation of 331 diverse wheat genotypes against four prevalent P. triticina races (MFGKG, MBTNB, MCTNB, and TCRKG) revealed that the majority of the genotypes were susceptible and only 22 genotypes (6.6%) were resistant to all four P. triticina races. The GWAS detected 11 QTL on nine chromosomes for LR resistance. Of these, six QTL were identified in the vicinity of known genes or QTL; therefore, more studies are warranted to determine their relationship. Five QTL (QLr.uga‐1AL, QLr.uga‐4AS, QLu.uga‐5AS, QLr.uga‐5AL, and QLr.uga‐7AS) were identified on genomic regions where no LR resistance genes have been identified in wheat, representing potential novel loci for LR resistance. The highly resistant wheat genotypes and novel QTL reported in this study could be used in breeding programs to improve LR resistance.
Moderate heat stress accompanied by short episodes of extreme heat during the post-anthesis stage is common in most US wheat growing areas and causes substantial yield losses. Sink strength (grain ...number) is a key yield limiting factor in modern wheat varieties. Increasing spike fertility (SF) and improving the partitioning of assimilates can optimize sink strength which is essential to improve wheat yield potential under a hot and humid environment. A genome-wide association study (GWAS) allows identification of novel quantitative trait loci (QTLs) associated with SF and other partitioning traits that can assist in marker assisted breeding. In this study, GWAS was performed on a soft wheat association mapping panel (SWAMP) comprised of 236 elite lines using 27,466 single nucleotide polymorphisms (SNPs). The panel was phenotyped in two heat stress locations over 3 years. GWAS identified 109 significant marker-trait associations (MTAs) (p ≤ 9.99 x 10-5) related to eight phenotypic traits including SF (a major component of grain number) and spike harvest index (SHI, a major component of grain weight). MTAs detected on chromosomes 1B, 3A, 3B, and 5A were associated with multiple traits and are potentially important targets for selection. More than half of the significant MTAs (60 out of 109) were found in genes encoding different types of proteins related to metabolism, disease, and abiotic stress including heat stress. These MTAs could be potential targets for further validation study and may be used in marker-assisted breeding for improving wheat grain yield under post-anthesis heat stress conditions. This is the first study to identify novel QTLs associated with SF and SHI which represent the major components of grain number and grain weight, respectively, in wheat.
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