QTL identification and KASP marker development for productive tiller and fertile spikelet numbers in two high-yielding hard white spring wheat cultivars

Quantitative trait loci detection for three tiller-related traits and the effects on wheat (Triticum aestivum L.) yields

KEY MESSAGE

A total of 38 putative additive QTLs and 55 pairwise putative epistatic QTLs for tiller-related traits were reported, and the candidate genes underlying qMtn-KJ-5D, a novel major and stable QTL for maximum tiller number, were characterized. Tiller-related traits play an important role in determining the yield potential of wheat. Therefore, it is important to elucidate the genetic basis for tiller number when attempting to use genetic improvement as a tool for enhancing wheat yields. In this study, a quantitative trait locus (QTL) analysis of three tiller-related traits was performed on the recombinant inbred lines (RILs) of a mapping population, referred to as KJ-RILs, that was derived from a cross between the Kenong 9204 (KN9204) and Jing 411 (J411) lines. A total of 38 putative additive QTLs and 55 pairwise putative epistatic QTLs for spike number per plant (SNPP), maximum tiller number (MTN), and ear-bearing tiller rate (EBTR) were detected in eight different environments. Among these QTLs with additive effects, three major and stable QTLs were first documented herein. Almost all but two pairwise epistatic QTLs showed minor interaction effects accounting for no more than 3.0% of the phenotypic variance. The genetic effects of two colocated major and stable QTLs, i.e., qSnpp-KJ-5D.1 and qMtn-KJ-5D, for yield-related traits were characterized. The breeding selection effect of the beneficial allele for the two QTLs was characterized, and its genetic effects on yield-related traits were evaluated. The candidate genes underlying qMtn-KJ-5D were predicted based on multi-omics data, and TraesKN5D01HG00080 was identified as a likely candidate gene. Overall, our results will help elucidate the genetic architecture of tiller-related traits and can be used to develop novel wheat varieties with high yields.

A chromosome arm from Thinopyrum intermedium × Thinopyrum ponticum hybrid confers increased tillering and yield potential in wheat

Tiller number is a key component of wheat plant architecture having a direct impact on grain yield. Because of their viability, biotic resistance, and abiotic stress tolerance, wild relative species are a valuable gene source for increasing wheat genetic diversity, including yield potential. Agropyron glael, a perennial hybrid of Thinopyrum intermedium and Th. ponticum, was created in the 1930s. Recent genome analyses identified five evolutionarily distinct subgenomes (J, Jst, Jvs, Jr, and St), making A. glael an important gene source for transferring useful agronomical traits into wheat. During a bread wheat × A. glael crossing program, a genetically stable translocation line, WT153397, was developed. Sequential in situ hybridizations (McGISH) with J-, St-, and D-genomic DNA probes and pSc119.2, Afa family, pTa71, and (GAA)7 DNA repeats, as well as molecular markers specific for the wheat 6D chromosome, revealed the presence of a 6DS.6Jvs Robertsonian translocation in the genetic line. Field trials in low-input and high-input breeding nurseries over four growing seasons demonstrated the Agropyron chromosome arm's high compensating ability for the missing 6DL, as spike morphology and fertility of WT153397 did not differ significantly from those of wheat parents, Mv9kr1 and 'Mv Karizma.' Moreover, the introgressed 6Jvs chromosome arm significantly increased the number of productive tillers, resulting in a significantly higher grain yield potential compared to the parental wheat cultivars. The translocated chromosome could be highly purified by flow cytometric sorting due to the intense fluorescent labeling of (GAA)7 clusters on the Thinopyrum chromosome arm, providing an opportunity to use chromosome genomics to identify Agropyron gene variant(s) responsible for the tillering capacity. The translocation line WT153397 is an important genetic stock for functional genetic studies of tiller formation and useful breeding material for increasing wheat yield potential. The study also discusses the use of the translocation line in wheat breeding.

Supplementary information

The online version contains supplementary material available at 10.1007/s11032-024-01439-y.

Identification and validation of quantitative trait loci for fertile spikelet number per spike and grain number per fertile spikelet in bread wheat (Triticum aestivum L.)

A major and stable QTL for fertile spikelet number per spike and grain number per fertile spikelet identified in a 4.96-Mb interval on chromosome 2A was validated in different genetic backgrounds. Fertile spikelet number per spike (FSN) and grain number per fertile spikelet (GNFS) contribute greatly to wheat yield improvement. To detect quantitative trait loci (QTL) associated with FSN and GNFS, we used a recombinant inbred line population crossed by Zhongkemai 13F10 and Chuanmai 42 in eight environments. Two Genomic regions associated with FSN were detected on chromosomes 2A and 6A using bulked segregant exome sequencing analysis. After the genetic linkage maps were constructed, four QTL QFsn.cib-2A, QFsn.cib-6A, QGnfs.cib-2A and QGnfs.cib-6A were identified in three or more environments. Among them, two major QTL QFsn.cib-2A (LOD = 4.67-9.34, PVE = 6.66-13.05%) and QGnfs.cib-2A (LOD = 5.27-11.68, PVE = 7.95-16.71%) were detected in seven and six environments, respectively. They were co-located in the same region, namely QFsn/Gnfs.cib-2A. The developed linked Kompetitive Allele Specific PCR (KASP) markers further validated this QTL in a different genetic background. QFsn/Gnfs.cib-2A showed pleiotropic effects on grain number per spike (GNS) and spike compactness (SC), and had no effect on grain weight. Since QFsn/Gnfs.cib-2A might be a new locus, it and the developed KASP markers can be used in wheat breeding. According to haplotype analysis, QFsn/Gnfs.cib-2A was identified as a target of artificial selection during wheat improvement. Based on haplotype analysis, sequence differences, spatiotemporal expression patterns, and gene annotation, the potential candidate genes for QFsn/Gnfs.cib-2A were predicted. These results provide valuable information for fine mapping and cloning gene(s) underlying QFsn/Gnfs.cib-2A.

Domestication of newly evolved hexaploid wheat—A journey of wild grass to cultivated wheat

Domestication of wheat started with the dawn of human civilization. Since then, improvement in various traits including resistance to diseases, insect pests, saline and drought stresses, grain yield, and quality were improved through selections by early farmers and then planned hybridization after the discovery of Mendel’s laws. In the 1950s, genetic variability was created using mutagens followed by the selection of superior mutants. Over the last 3 decades, research was focused on developing superior hybrids, initiating marker-assisted selection and targeted breeding, and developing genetically modified wheat to improve the grain yield, tolerance to drought, salinity, terminal heat and herbicide, and nutritive quality. Acceptability of genetically modified wheat by the end-user remained a major hurdle in releasing into the environment. Since the beginning of the 21st century, changing environmental conditions proved detrimental to achieving sustainability in wheat production particularly in developing countries. It is suggested that high-tech phenotyping assays and genomic procedures together with speed breeding procedures will be instrumental in achieving food security beyond 2050.

Identification and validation of QTLs for kernel number per spike and spike length in two founder genotypes of wheat

BACKGROUND

Kernel number per spike (KNS) and spike length (SL) are important spike-related traits in wheat variety improvement. Discovering genetic loci controlling these traits is necessary to elucidate the genetic basis of wheat yield traits and is very important for marker-assisted selection breeding.

RESULTS

In the present study, we used a recombinant inbred line population with 248 lines derived from the two founder genotypes of wheat, Bima4 and BainongAK58, to construct a high-density genetic map using wheat 55 K genotyping assay. The final genetic linkage map consists of 2356 bin markers (14,812 SNPs) representing all 21 wheat chromosomes, and the entire map spanned 4141.24 cM. A total of 7 and 18 QTLs were identified for KNS and SL, respectively, and they were distributed on 11 chromosomes. The allele effects of the flanking markers for 12 stable QTLs, including four QTLs for KNS and eight QTLs for SL, were estimated based on phenotyping data collected from 15 environments in a diverse wheat panel including 384 elite cultivars and breeding lines. The positive alleles at seven loci, namely, QKns.his-7D2-1, QKns.his-7D2-2, QSl.his-4A-1, QSl.his-5D1, QSl.his-4D2-2, QSl.his-5B and QSl.his-5A-2, significantly increased KNS or SL in the diverse panel, suggesting they are more universal in their effects and are valuable for gene pyramiding in breeding programs. The transmission of Bima4 allele indicated that the favorite alleles at five loci (QKns.his-7D2-1, QSl.his-5A-2, QSl.his-2D1-1, QSl.his-3A-2 and QSl.his-3B) showed a relatively high frequency or an upward trend following the continuity of generations, suggesting that they underwent rigorous selection during breeding. At two loci (QKns.his-7D2-1 and QSl.his-5A-2) that the positive effects of the Bima4 alleles have been validated in the diverse panel, two and one kompetitive allele-specific PCR (KASP) markers were further developed, respectively, and they are valuable for marker-assisted selection breeding.

CONCLUSION

Important chromosome regions controlling KNS and SL were identified in the founder parents. Our results are useful for knowing the molecular mechanisms of founder parents and future molecular breeding in wheat.

Applications of Genomic Tools in Plant Breeding: Crop Biofortification

Crop breeding has mainly been focused on increasing productivity, either directly or by decreasing the losses caused by biotic and abiotic stresses (that is, incorporating resistance to diseases and enhancing tolerance to adverse conditions, respectively). Quite the opposite, little attention has been paid to improve the nutritional value of crops. It has not been until recently that crop biofortification has become an objective within breeding programs, through either conventional methods or genetic engineering. There are many steps along this long path, from the initial evaluation of germplasm for the content of nutrients and health-promoting compounds to the development of biofortified varieties, with the available and future genomic tools assisting scientists and breeders in reaching their objectives as well as speeding up the process. This review offers a compendium of the genomic technologies used to explore and create biodiversity, to associate the traits of interest to the genome, and to transfer the genomic regions responsible for the desirable characteristics into potential new varieties. Finally, a glimpse of future perspectives and challenges in this emerging area is offered by taking the present scenario and the slow progress of the regulatory framework as the starting point.

Unravelling consensus genomic regions conferring leaf rust resistance in wheat via meta-QTL analysis

Leaf rust, caused by the fungus Puccinia triticina Erikss (Pt), is a destructive disease affecting wheat (Triticum aestivum L.) and a threat to food security. Developing resistant cultivars represents a useful method of disease control, and thus, understanding the genetic basis for leaf rust resistance is required. To this end, a comprehensive bibliographic search for leaf rust resistance quantitative trait loci (QTL) was performed, and 393 QTL were collected from 50 QTL mapping studies. Afterward, a consensus map with a total length of 4,567 cM consisting of different types of markers (simple sequence repeat [SSR], diversity arrays technology [DArT], chip-based single-nucleotide polymorphism [SNP] markers, and SNP markers from genotyping-by-sequencing) was used for QTL projection, and meta-QTL (MQTL) analysis was performed on 320 QTL. A total of 75 MQTL were discovered and refined to 15 high-confidence MQTL (hcmQTL). The candidate genes discovered within the hcmQTL interval were then checked for differential expression using data from three transcriptome studies, resulting in 92 differentially expressed genes (DEGs). The expression of these genes in various leaf tissues during wheat development was explored. This study provides insight into leaf rust resistance in wheat and thereby provides an avenue for developing resistant cultivars by incorporating the most important hcmQTL.

Four-Year and Five-Developing-Stage Dynamic QTL Mapping for Tiller Number in the Hybrid Population of Agropyron Gaertn

Tiller number (TN) is an important agronomic trait affecting gramineous crop yield. To understand the static and dynamic information of quantitative trait locus (QTLs) controlling TN of Agropyron Gaertn., both the unconditional and conditional quantitative trait loci (QTL) mapping of TN were conducted using a cross-pollinated (CP) hybrid population with a total of 113 plant lines from the cross between Agropyron cristatum (L.) Gaertn. Z1842 and Allium mongolicum Keng Z2098, based on the phenotypic data of TN at five developmental stages [i.e., recovering stage (RS), jointing stage (JS), heading stage (HS), flowering stage (FS), and maturity stage (MS)] in 4 years (i.e., 2017, 2018, 2020, and 2021) and the genetic map constructed of 1,023 single-nucleotide polymorphism (SNP) markers. Thirty-seven QTLs controlling TN were detected using two analysis methods in 4 years, which were distributed in six linkage groups. Each QTL explained 2.96-31.11% of the phenotypic variation, with a logarithum of odds (LOD) value of 2.51-13.95. Nine of these loci detected both unconditional and conditional QTLs. Twelve unconditional major QTLs and sixteen conditional major QTLs were detected. Three relatively major stable conditional QTLs, namely, cQTN1-3, cQTN1-5, and cQTN4-1, were expressed in 2020 and 2021. Meantime, two pairs of major QTLs cQTN1-5 and qTN1-4 and also cQTN2-4 and qTN2-3 were located at the same interval but in different years. Except for qTN2-2 and qTN3-5/cQTN3-5, other thirty-four QTLs were first detected in this study. This study provides a better interpretation of genetic factors that selectively control tiller at different developmental stages and a reference for molecular marker-assisted selection in the related plant improvement.

A Major Quantitative Trait Loci Cluster Controlling Three Components of Yield and Plant Height Identified on Chromosome 4B of Common Wheat

Wheat yield is not only affected by three components of yield, but also affected by plant height (PH). Identification and utilization of the quantitative trait loci (QTL) controlling these four traits is vitally important for breeding high-yielding wheat varieties. In this work, we conducted a QTL analysis using the recombinant inbred lines (RILs) derived from a cross between two winter wheat varieties of China, "Nongda981" (ND981) and "Nongda3097" (ND3097), exhibiting significant differences in spike number per unit area (SN), grain number per spike (GNS), thousand grain weight (TGW), and PH. A total of 11 environmentally stable QTL for these four traits were detected. Among them, four major and stable QTLs (QSn.cau-4B-1.1, QGns.cau-4B-1, QTgw.cau-4B-1.1, and QPh.cau-4B-1.2) explaining the highest phenotypic variance for SN, GNS, TGW, and PH, respectively, were mapped on the same genomic region of chromosome 4B and were considered a QTL cluster. The QTL cluster spanned a genetic distance of about 12.3 cM, corresponding to a physical distance of about 8.7 Mb. Then, the residual heterozygous line (RHL) was used for fine mapping of the QTL cluster. Finally, QSn.cau-4B-1.1, QGns.cau-4B-1, and QPh.cau-4B-1.2 were colocated to the physical interval of about 1.4 Mb containing 31 annotated high confidence genes. QTgw.cau-4B-1.1 was divided into two linked QTL with opposite effects. The elite NILs of the QTL cluster increased SN and PH by 55.71-74.82% and 14.73-23.54%, respectively, and increased GNS and TGW by 29.72-37.26% and 5.81-11.24% in two environments. Collectively, the QTL cluster for SN, GNS, TGW, and PH provides a theoretical basis for improving wheat yield, and the fine-mapping result will be beneficial for marker-assisted selection and candidate genes cloning.

Identification and Validation of a Novel Locus Controlling Spikelet Number in Bread Wheat (Triticum aestivum L.)

Spikelet number is an important target trait for wheat yield improvement. Thus, the identification and verification of novel quantitative trait locus (QTL)/genes controlling spikelet number are essential for dissecting the underlying molecular mechanisms and hence for improving grain yield. In the present study, we constructed a high-density genetic map for the Kechengmai1/Chuanmai42 doubled haploid (DH) population using 13,068 single-nucleotide polymorphism (SNP) markers from the Wheat 55K SNP array. A comparison between the genetic and physical maps indicated high consistence of the marker orders. Based on this genetic map, a total of 27 QTLs associated with total spikelet number per spike (TSN) and fertile spikelet number per spike (FSN) were detected on chromosomes 1B, 1D, 2B, 2D, 3D, 4A, 4D, 5A, 5B, 5D, 6A, 6B, and 7D in five environments. Among them, five QTLs on chromosome 2D, 3D, 5A, and 7D were detected in multiple environments and combined QTL analysis, explaining the phenotypic variance ranging from 3.64% to 23.28%. Particularly, QTsn/Fsn.cib-3D for TSN and FSN [phenotypic variation explained (PVE) = 5.97-23.28%, limit of detection (LOD) = 3.73-18.51] is probably a novel locus and located in a 4.5-cM interval on chromosome arm 3DL flanking by the markers AX-110914105 and AX-109429351. This QTL was further validated in other two populations with different genetic backgrounds using the closely linked Kompetitive Allele-Specific PCR (KASP) marker KASP_AX-110914105. The results indicated that QTsn/Fsn.cib-3D significantly increased the TSN (5.56-7.96%) and FSN (5.13-9.35%), which were significantly correlated with grain number per spike (GNS). We also preliminary analyzed the candidate genes within this locus by sequence similarity, spatial expression patterns, and collinearity analysis. These results provide solid foundation for future fine mapping and cloning of QTsn/Fsn.cib-3D. The developed and validated KASP markers could be utilized in molecular breeding aiming to increase the grain yield in wheat.

QTL Mapping for Seed Germination Response to Drought Stress in Brassica napus

Drought stress is one of the most environmental abiotic stresses affecting seed germination and crop growth. In the present study, the genetic characteristics of seed germination under drought stress in a Brassica napus double haploid population were analyzed. Five germination-related indexes, including germination percentage (GP), root length (RL), shoot length (SL), fresh weight (FW), and root-to-shoot length ratio (R/S) under control and drought stress, were calculated, and the drought stress index (DSI), including DSI-GP, DSI-RL, DSI-SL, DSI-FW, and DSI-R/S, was determined using the quantitative trait loci (QTLs) analysis based on high-density genetic linkage map. The phenotypic analysis indicated that the R/S is an effective morphological trait in the determination of drought tolerance in the seedling stage. Thirty-nine identified QTLs were observed for these traits and then integrated into 36 consensus QTLs, in which 18 QTLs were found to affect the DSI of four traits (GP, RL, SL, and R/S). Based on the co-linearity between genetic and physical maps of B. napus, 256 candidate genes were detected, and 128 genes have single-nucleotidepolymorphisms/insertion-deletion (SNP/InDel) variations between two parents, some of which were associated with the drought stress tolerance (for example, BnaC03g32780D, BnaC03g37030D, and BnaC09g27300D). The present results laid insights into drought tolerance and its genetic bases in B. napus.

Fingerprint identification of white clover cultivars based on SSR molecular markers

White clover (Trifolium repens L.) is an important perennial legume forage with high productivity and quality. To strengthen the basic research on the genetic characteristics, fingerprint identification and adaptability of white clover germplasm resources, Simple sequence repeat (SSR) molecular markers were applied to 10 white clover cultivars to assess the genetic diversity and related lines of white clover at the molecular level in order to lay a theoretical foundation for the selection of high-quality seeds and cultivars of white clover. A total of 120 different bands were amplified by 29 pairs of SSR primers with good polymorphism, of which 103 (89.5%) were polymorphic. Meanwhile, the PIC of each primer was 0.181-0.588, with an average of 0.329. Analysis of molecular variance revealed that 57% of the genetic variation occurred within cultivars and 43% occurred among cultivars. The results of cluster analysis and the principal coordinate analysis revealed that the parental relationships of the 10 cultivars, with the 'Purple' cultivar very distantly related to the other 9 cultivars and the closest parental relationship between 'Ladino' and 'Sulky'. The fingerprints constructed by three representative primers (gtrs679, gtrs319, and gtrs678) have a strong identification ability. In summary, the SSR markers had good polymorphism and could be used for DNA fingerprint analysis of white clover cultivars.

Detection of genomic regions associated with tiller number in Iranian bread wheat under different water regimes using genome-wide association study

Two of the important traits for wheat yield are tiller and fertile tiller number, both of which have been thought to increase cereal yield in favorable and unfavorable environments. A total of 6,349 single nucleotide polymorphism (SNP) markers from the 15 K wheat Infinium array were employed for genome-wide association study (GWAS) of tillering number traits, generating a physical distance of 14,041.6 Mb based on the IWGSC wheat genome sequence. GWAS analysis using Fixed and random model Circulating Probability Unification (FarmCPU) identified a total of 47 significant marker-trait associations (MTAs) for total tiller number (TTN) and fertile tiller number (FTN) in Iranian bread wheat under different water regimes. After applying a 5% false discovery rate (FDR) threshold, a total of 13 and 11 MTAs distributed on 10 chromosomes were found to be significantly associated with TTN and FTN, respectively. Linked single nucleotide polymorphisms for IWB39005 (2A) and IWB44377 (7A) were highly significantly associated (FDR < 0.01) with TTN and FTN traits. Moreover, to validate GWAS results, meta-analysis was performed and 30 meta-QTL regions were identified on 11 chromosomes. The integration of GWAS and meta-QTLs revealed that tillering trait in wheat is a complex trait which is conditioned by the combined effects of minor changes in multiple genes. The information provided by this study can enrich the currently available candidate genes and genetic resources pools, offering evidence for subsequent analysis of genetic adaptation of wheat to different climatic conditions of Iran and other countries.

Characterization of a major quantitative trait locus on the short arm of chromosome 4B for spike number per unit area in common wheat (Triticum aestivum L.)

An InDel marker closely linked with a major and stable quantitative trait locus (QTL) on chromosome 4BS, QSnpa.cau-4B, controlling spike number per unit area will benefit wheat yield improvement. Spike number per unit area (SNPA) is an essential yield-related trait, and analyzing its genetic basis is important for cultivar improvement in wheat (Triticum aestivum L.). In this study, we used the F₂ population derived from a cross between two wheat accessions displaying significant differences in SNPA to perform quantitative trait locus (QTL) analysis. Through bulked segregant analysis, a major and stable QTL that explained 18.11-82.11% of the phenotypic variation was identified on chromosome 4BS. The QTL interval was validated using F_4:5 and F_6:7 families and narrowed it to a 24.91-38.36 Mb region of chromosome 4BS according to the 'Chinese Spring' reference genome sequence. In this region, variations in 16 genes caused amino acid changes and three genes were present in only one parent. Among these, we annotated a gene orthologous to TB1 in maize (Zea mays), namely TraesCS4B01G042700, which carried a 44-bp deletion in its promoter in the higher-SNPA parent. An InDel marker based on the insertion/deletion polymorphism was designed and used to diagnose the allelic distribution within a natural population. The frequency of the 44-bp deletion allele associated with higher SNPA was relatively low (13.24%), implying that this favorable allele has not been widely utilized and could be valuable for wheat yield improvement. In summary, we identified a major and stable QTL for SNPA and developed a diagnostic marker for the more-spiked trait, which will be beneficial for molecular-assisted breeding 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.

Genetics of yield, abiotic stress tolerance and biofortification in wheat (Triticum aestivum L.)

A review of the available literature on genetics of yield and its component traits, tolerance to abiotic stresses and biofortification should prove useful for future research in wheat in the genomics era. The work reviewed in this article mainly covers the available information on genetics of some important quantitative traits including yield and its components, tolerance to abiotic stresses (heat, drought, salinity and pre-harvest sprouting = PHS) and biofortification (Fe/Zn and phytate contents with HarvestPlus Program) in wheat. Major emphasis is laid on the recent literature on QTL interval mapping and genome-wide association studies, giving lists of known QTL and marker-trait associations. Candidate genes for different traits and the cloned and characterized genes for yield traits along with the molecular mechanism are also described. For each trait, an account of the present status of marker-assisted selection has also been included. The details of available results have largely been presented in the form of tables; some of these tables are included as supplementary files.

Agronomic and Physiological Traits, and Associated Quantitative Trait Loci (QTL) Affecting Yield Response in Wheat (Triticum aestivum L.): A Review

Enhanced grain yield has been achieved in bread wheat (Triticum aestivum L.) through development and cultivation of superior genotypes incorporating yield-related agronomic and physiological traits derived from genetically diverse and complementary genetic pool. Despite significant breeding progress, yield levels in wheat have remained relatively low and stagnant under marginal growing environments. There is a need for genetic improvement of wheat using yield-promoting morpho-physiological attributes and desired genotypes under the target production environments to meet the demand for food and feed. This review presents breeding progress in wheat for yield gains using agronomic and physiological traits. Further, the paper discusses globally available wheat genetic resources to identify and select promising genotypes possessing useful agronomic and physiological traits to enhance water, nutrient-, and radiation-use efficiency to improve grain yield potential and tolerance to abiotic stresses (i.e. elevated CO2, high temperature, and drought stresses). Finally, the paper highlights quantitative trait loci (QTL) linked to agronomic and physiological traits to aid breeding of high-performing wheat genotypes.

Identification and assessment of two major QTLs for dwarf bunt resistance in winter wheat line 'IDO835'

Two major dwarf bunt resistance QTLs were mapped to a known Bt9 locus and a novel locus. The associated KASP markers were developed and validated in other two populations. Dwarf bunt (DB), caused by Tilletia controversa J.G. Kühn, and common bunt (CB), caused by T. caries and T. foetida, are two destructive diseases that reduce grain yield and quality in wheat. Breeding for bunt-resistant cultivars is important in many wheat production areas, especially where organic wheat is grown. However, few molecular markers have been used in selection of bunt resistance. In the present study, a doubled haploid (DH) population derived from the bunt-resistant line 'IDO835' and the susceptible cultivar 'Moreland' was evaluated for DB resistance in a field nursery in Logan, Utah, for four growing seasons. The population was genotyped with the Illumina 90 K SNP iSelect marker platform. Two major QTLs were consistently identified on chromosomes 6DL (Q.DB.ui-6DL) and 7AL (Q.DB.ui-7AL), explaining up to 53% and 38% of the phenotypic variation, respectively. Comparative study suggested that Q.DB.ui-6DL was located in the same region as the CB resistance gene Bt9, and Q.DB.ui-7AL was located at a novel locus for bunt resistance. Based on Chinese Spring reference sequence and annotations (IWGSC RefSeq v1.1), both resistance QTLs were mapped to disease resistance gene-rich (NBS-LRR and kinase genes) regions. To validate the identified QTL and design user-friendly markers for MAS, five SNPs were converted to Kompetitive Allele-Specific PCR (KASP) markers and used to genotype two validation panels, including a DH population and a diverse winter wheat population from USDA-ARS National Small Grain Collection, as well as a Bt gene investigation panel, consisting of 15 bunt differential lines and 11 resistant lines.

Genome-wide association study reveals new loci for yield-related traits in Sichuan wheat germplasm under stripe rust stress

BACKGROUND

As one of the most important food crops in the world, increasing wheat (Triticum aestivum L.) yield is an urgent task for global food security under the continuous threat of stripe rust (caused by Puccinia striiformis f. sp. tritici) in many regions of the world. Molecular marker-assisted breeding is one of the most efficient ways to increase yield. Here, we identified loci associated to multi-environmental yield-related traits under stripe rust stress in 244 wheat accessions from Sichuan Province through genome-wide association study (GWAS) using 44,059 polymorphic markers from the 55 K single nucleotide polymorphism (SNP) chip.

RESULTS

A total of 13 stable quantitative trait loci (QTLs) were found to be highly associating to yield-related traits, including 6 for spike length (SL), 3 for thousand-kernel weight (TKW), 2 for kernel weight per spike (KWPS), and 2 for both TKW and KWPS, in at least two test environments under stripe rust stress conditions. Of them, ten QTLs were overlapped or very close to the reported QTLs, three QTLs, QSL.sicau-1AL, QTKW.sicau-4AL, and QKWPS.sicau-4AL.1, were potentially novel through the physical location comparison with previous QTLs. Further, 21 candidate genes within three potentially novel QTLs were identified, they were mainly involved in the regulation of phytohormone, cell division and proliferation, meristem development, plant or organ development, and carbohydrate transport.

CONCLUSIONS

QTLs and candidate genes detected in our study for yield-related traits under stripe rust stress will facilitate elucidating genetic basis of yield-related trait and could be used in marker-assisted selection in wheat yield breeding.