A Genome-Wide Association Study of Wheat Spike Related Traits in China

Discovering novel genomic regions explaining adaptation of bread wheat to conservation agriculture through GWAS

To sustainably increase wheat yield to meet the growing world population's food demand in the face of climate change, Conservation Agriculture (CA) is a promising approach. Still, there is a lack of genomic studies investigating the genetic basis of crop adaptation to CA. To dissect the genetic architecture of 19 morpho-physiological traits that could be involved in the enhanced adaptation and performance of genotypes under CA, we performed GWAS to identify MTAs under four contrasting production regimes viz., conventional tillage timely sown (CTTS), conservation agriculture timely sown (CATS), conventional tillage late sown (CTLS) and conservation agriculture late sown (CALS) using an association panel of 183 advanced wheat breeding lines along with 5 checks. Traits like Phi2 (Quantum yield of photosystem II; CATS:0.37, CALS: 0.31), RC (Relative chlorophyll content; CATS:55.51, CALS: 54.47) and PS1 (Active photosystem I centers; CATS:2.45, CALS: 2.23) have higher mean values in CA compared to CT under both sowing times. GWAS identified 80 MTAs for the studied traits across four production environments. The phenotypic variation explained (PVE) by these QTNs ranged from 2.15 to 40.22%. Gene annotation provided highly informative SNPs associated with Phi2, NPQ (Quantum yield of non-photochemical quenching), PS1, and RC which were linked with genes that play crucial roles in the physiological adaptation under both CA and CT. A highly significant SNP AX94651261 (9.43% PVE) was identified to be associated with Phi2, while two SNP markers AX94730536 (30.90% PVE) and AX94683305 (16.99% PVE) were associated with NPQ. Identified QTNs upon validation can be used in marker-assisted breeding programs to develop CA adaptive genotypes.

Genome-wide association study and genomic selection of spike-related traits in bread wheat

KEY MESSAGE

Identification of 337 stable MTAs for wheat spike-related traits improved model accuracy, and favorable alleles of MTA259 and MTA64 increased grain weight and yield per plant. Wheat (Triticum aestivum L.) is one of the three primary global, staple crops. Improving spike-related traits in wheat is crucial for optimizing spike and plant morphology, ultimately leading to increased grain yield. Here, we performed a genome-wide association study using a dataset of 24,889 high-quality unique single-nucleotide polymorphisms (SNPs) and phenotypic data from 314 wheat accessions across eight diverse environments. In total, 337 stable and significant marker-trait associations (MTAs) related to spike-related traits were identified. MTA259 and MTA64 were consistently detected in seven and six environments, respectively. The presence of favorable alleles associated with MTA259 and MTA64 significantly reduced wheat spike exsertion length and spike length, while enhancing thousand kernel weight and yield per plant. Combined gene expression and network analyses identified TraesCS6D03G0692300 and TraesCS6D03G0692700 as candidate genes for MTA259 and TraesCS2D03G0111700 and TraesCS2D03G0112500 for MTA64. The identified MTAs significantly improved the prediction accuracy of each model compared with using all the SNPs, and the random forest model was optimal for genome selection. Additionally, the eight stable and major MTAs, including MTA259, MTA64, MTA66, MTA94, MTA110, MTA165, MTA180, and MTA164, were converted into cost-effective and efficient detection markers. This study provided valuable genetic resources and reliable molecular markers for wheat breeding programs.

Characterization of a wheat stable QTL for spike length and its genetic effects on yield-related traits

Spike length (SL) is one of the most important agronomic traits affecting yield potential and stability in wheat. In this study, a major stable quantitative trait locus (QTL) for SL, i.e., qSl-2B, was detected in multiple environments in a recombinant inbred line (RIL) mapping population, KJ-RILs, derived from a cross between Kenong 9204 (KN9204) and Jing 411 (J411). The qSl-2B QTL was mapped to the 60.06-73.06 Mb region on chromosome 2B and could be identified in multiple mapping populations. An InDel molecular marker in the target region was developed based on a sequence analysis of the two parents. To further clarify the breeding use potential of qSl-2B, we analyzed its genetic effects and breeding selection effect using both the KJ-RIL population and a natural mapping population, which consisted of 316 breeding varieties/advanced lines. The results showed that the qSl-2B alleles from KN9204 showed inconsistent genetic effects on SL in the two mapping populations. Moreover, in the KJ-RILs population, the additive effects analysis of qSl-2B showed that additive effect was higher when both qSl-2D and qSl-5A harbor negative alleles under LN and HN. In China, a moderate selection utilization rate for qSl-2B was found in the Huanghuai winter wheat area and the selective utilization rate for qSl-2B continues to increase. The above findings provided a foundation for the genetic improvement of wheat SL in the future via molecular breeding strategies.

Construction of a high-density genetic map and mapping of a spike length locus for rye

Genetic maps provide the foundation for QTL mapping of important traits of crops. As a valuable food and forage crop, rye (Secale cereale L., RR) is also one of the tertiary gene sources of wheat, especially wild rye, Secale cereale subsp. segetale, possessing remarkable stress tolerance, tillering capacity and numerous valuable traits. In this study, based on the technique of specific-locus amplified fragment sequencing (SLAF-seq), a high-density single nucleotide polymorphism (SNP) linkage map of the cross-pollinated (CP) hybrid population crossed by S. cereale L (female parent) and S. cereale subsp. segetale (male parent) was successfully constructed. Following preprocessing, the number of 1035.11 M reads were collected and 2425800 SNP were obtained, of which 409134 SNP were polymorphic. According to the screening process, 9811 SNP markers suitable for constructing linkage groups (LGs) were selected. Subsequently, all of the markers with MLOD values lower than 3 were filtered out. Finally, an integrated map was constructed with 4443 markers, including 1931 female mapping markers and 3006 male mapping markers. A major quantitative trait locus (QTL) linked with spike length (SL) was discovered at 73.882 cM on LG4, which explained 25.29% of phenotypic variation. Meanwhile two candidate genes for SL, ScWN4R01G329300 and ScWN4R01G329600, were detected. This research presents the first high-quality genetic map of rye, providing a substantial number of SNP marker loci that can be applied to marker-assisted breeding. Additionally, the finding could help to use SLAF marker mapping to identify certain QTL contributing to important agronomic traits. The QTL and the candidate genes identified through the high-density genetic map above may provide diverse potential gene resources for the genetic improvement of rye.

Genome-Wide Association Study of Asian and European Common Wheat Accessions for Yield-Related Traits and Stripe Rust Resistance

Identifying novel loci of yield-related traits and resistance to stripe rust (caused by Puccinia striiformis f. sp. tritici) in wheat will help in breeding wheat that can meet projected demands in diverse environmental and agricultural practices. We performed a genome-wide association study with 24,767 single nucleotide polymorphisms (SNPs) in 180 wheat accessions that originated in 16 Asian or European countries between latitudes 30°N and 45°N. We detected seven accessions with desirable yield-related traits and 42 accessions that showed stable, high degrees of stripe rust resistance in multienvironment field assessments. A marker-trait association analysis of yield-related traits detected 18 quantitative trait loci (QTLs) in at least two test environments and two QTLs related to stripe rust resistance in at least three test environments. Five of these QTLs were identified as potentially novel QTLs by comparing their physical locations with those of known QTLs in the Chinese Spring (CS) reference genome RefSeq v1.1 published by the International Wheat Genome Sequencing Consortium; two were for spike length, one was for grain number per spike, one was for spike number, and one was for stripe rust resistance at the adult plant stage. We also identified 14 candidate genes associated with the five novel QTLs. These QTLs and candidate genes will provide breeders with new germplasm and can be used to conduct marker-assisted selection in breeding wheat with improved yield and stripe rust resistance.

Deciphering genetic basis of developmental and agronomic traits by integrating high-throughput optical phenotyping and genome-wide association studies in wheat

Dissecting the genetic basis of complex traits such as dynamic growth and yield potential is a major challenge in crops. Monitoring the growth throughout growing season in a large wheat population to uncover the temporal genetic controls for plant growth and yield-related traits has so far not been explored. In this study, a diverse wheat panel composed of 288 lines was monitored by a non-invasive and high-throughput phenotyping platform to collect growth traits from seedling to grain filling stage and their relationship with yield-related traits was further explored. Whole genome re-sequencing of the panel provided 12.64 million markers for a high-resolution genome-wide association analysis using 190 image-based traits and 17 agronomic traits. A total of 8327 marker-trait associations were detected and clustered into 1605 quantitative trait loci (QTLs) including a number of known genes or QTLs. We identified 277 pleiotropic QTLs controlling multiple traits at different growth stages which revealed temporal dynamics of QTLs action on plant development and yield production in wheat. A candidate gene related to plant growth that was detected by image traits was further validated. Particularly, our study demonstrated that the yield-related traits are largely predictable using models developed based on i-traits and provide possibility for high-throughput early selection, thus to accelerate breeding process. Our study explored the genetic architecture of growth and yield-related traits by combining high-throughput phenotyping and genotyping, which further unravelled the complex and stage-specific contributions of genetic loci to optimize growth and yield in wheat.

Molecular and genetic perspectives of cold tolerance in wheat

Environmental variation is the most crucial problem as it is causing food insecurity and negatively impacts food availability, utilization, assessment, and stability. Wheat is the largest and extensively cultivated staple food crop for fulfilling global food requirements. Abiotic stresses including salinity, heavy metal toxicity, drought, extreme temperatures, and oxidative stresses being the primary cause of productivity loss are a serious threat to agronomy. Cold stress is a foremost ecological constraint that is extremely influencing plant development, and yield. It is extremely hampering the propagative development of plant life. The structure and function of plant cells depend on the cell's immune system. The stresses due to cold, affect fluid in the plasma membrane and change it into crystals or a solid gel phase. Plants being sessile in nature have evolved progressive systems that permit them to acclimatize the cold stress at the physiological as well as molecular levels. The phenomenon of acclimatisation of plants to cold stress has been investigated for the last 10 years. Studying cold tolerance is critical for extending the adaptability zones of perennial grasses. In the present review, we have elaborated the current improvement of cold tolerance in plants from molecular and physiological viewpoints, such as hormones, the role of the posttranscriptional gene, micro RNAs, ICE-CBF-COR signaling route in cold acclimatization and how they are stimulating the expression of underlying genes encoding osmoregulatory elements and strategies to improve cold tolerance in wheat.

Identification and validation of a major quantitative trait locus for spike length and compactness in the wheat (Triticum aestivum L.) line Chuanyu12D7

Spike length (SL) and spike compactness (SC) are crucial traits related to wheat (Triticum aestivum L.) yield potential. In this study, a backcrossed inbred lines (BILs) population segregating for SL/SC was developed by using a commercial variety chuanyu25 as recurrent parent and a backbone parent Chuanyu12D7. Bulked segregant analysis (BSA) combined with the Wheat 660K SNP array was performed to conduct quantitative trait locus (QTL) mapping. A major and stable SL/SC QTL (designated as QSl/Sc.cib-2D.1) was identified on chromosome 2DS, explaining 45.63-59.72% of the phenotypic variation. QSl/Sc.cib-2D.1 was mapped to a 102.29-Kb interval by flanking SNPs AX-110276364 and AX-111593853 using a BC₄F_2:3 population. Since QSl/Sc.cib-2D.1 is linked to the Rht8 gene, their additive effects on plant type and spike type were analysed. Remarkably, the superior allele of QSl/Sc.cib-2D.1 combined with Rht8 can increase SL and TGW, and decrese SC without any apparent trade-offs in other yield-related traits. In addition, the closely linked kompetitive allele-specific PCR (KASP) markers of this locus were developed for marker-assisted selection (MAS) breeding. Four genes within the physical interval were considered as potential candidates based on expression patterns as well as orthologous gene functions. These results laid the foundation for map-based cloning of the gene(s) underlying QSl/Sc.cib-2D.1 and its potential application in wheat ideotype breeding.

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

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

A framework for improving wheat spike development and yield based on the master regulatory TOR and SnRK gene systems

The low rates of yield gain in wheat breeding programs create an ominous situation for the world. Amongst the reasons for this low rate are issues manifested in spike development that result in too few spikelets, fertile florets, and therefore grains being produced. Phases in spike development are particularly sensitive to stresses of various kinds and origins, and these are partly responsible for the deficiencies in grain production and slow rates of gain in yield. The diversity of developmental processes, stresses, and the large numbers of genes involved make it particularly difficult to prioritize approaches in breeding programs without an overarching, mechanistic framework. Such a framework, introduced here, is provided around the master regulator target of rapamycin and sucrose non-fermenting-1 (SNF1)-related protein kinase complexes and their control by trehalose-6-phosphate and other molecules. Being master regulators of the balance between growth and growth inhibition under stress, these provide genetic targets for creating breakthroughs in yield enhancement. Examples of potential targets and experimental approaches are described.

Amand P, Bai G, Baker J, Baker S, Liu S. QTL mapping of yield components and kernel traits in wheat cultivars TAM 112 and Duster

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

Genome-Wide Association Analysis for Hybrid Breeding in Wheat

Disclosure of markers that are significantly associated with plant traits can help develop new varieties with desirable properties. This study determined the genome-wide associations based on DArTseq markers for six agronomic traits assessed in eight environments for wheat. Moreover, the association study for heterosis and analysis of the effects of markers grouped by linkage disequilibrium were performed based on mean values over all experiments. All results were validated using data from post-registration trials. GWAS revealed 1273 single nucleotide polymorphisms with biologically significant effects. Most polymorphisms were predicted to be modifiers of protein translation, with only two having a more pronounced effect. Markers significantly associated with the considered set of features were clustered within chromosomes based on linkage disequilibrium in 327 LD blocks. A GWAS for heterosis revealed 1261 markers with significant effects.

Patterns of genetic variation and QTLs controlling grain traits in a collection of global wheat germplasm revealed by high-quality SNP markers

BACKGROUND

Establish a molecular breeding program involved assembling a diverse germplasm collection and generating accurate genotypes to characterize their genetic potential and associate them with agronomic traits. In this study, we acquired over eight hundred wheat accessions from international gene banks and assessed their genetic relatedness using high-quality SNP genotypes. Understanding the scope of genomic variation in this collection allows the breeders to utilize the genetic resources efficiently while improving wheat yield and quality.

RESULTS

A wheat diversity panel comprising 39 durum wheat, 60 spelt wheat, and 765 bread wheat accessions was genotyped on iSelect 90 K wheat SNP arrays. A total of 57,398 SNP markers were mapped to IWGSC RefSeq v2.1 assembly, over 30,000 polymorphic SNPs in the A, B, D genomes were used to analyze population structure and diversity, the results revealed the separation of the three species and the differentiation of CIMMYT improved breeding lines and landraces or widely grown cultivars. In addition, several chromosomal regions under selection were detected. A subset of 280 bread wheat accessions was evaluated for grain traits, including grain length, width, surface area, and color. Genome-wide association studies (GWAS) revealed that several chromosomal regions were significantly linked to known quantitative trait loci (QTL) controlling grain-related traits. One of the SNP peaks at the end of chromosome 7A was in strong linkage disequilibrium (LD) with WAPO-A1, a gene that governs yield components.

CONCLUSIONS

Here, the most updated and accurate physical positions of SNPs on 90 K genotyping array are provided for the first time. The diverse germplasm collection and associated genotypes are available for the wheat researchers to use in their molecular breeding program. We expect these resources to broaden the genetic basis of original breeding and pre-breeding materials and ultimately identify molecular markers associated with important agronomic traits which are evaluated in diverse environmental conditions.

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

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

Genome-wide association study for grain yield and component traits in bread wheat (Triticum aestivum L.)

Genomic regions governing days to heading (DH), grain filling duration (GFD), grain number per spike (GNPS), grain weight per spike (GWPS), plant height (PH), and grain yield (GY) were investigated in a set of 280 diverse bread wheat genotypes. The genome-wide association studies (GWAS) panel was genotyped using a 35K Axiom Array and phenotyped in five environments. The GWAS analysis showed a total of 27 Bonferroni-corrected marker-trait associations (MTAs) on 15 chromosomes representing all three wheat subgenomes. The GFD showed the highest MTAs (8), followed by GWPS (7), GY (4), GNPS (3), PH (3), and DH (2). Furthermore, 20 MTAs were identified with more than 10% phenotypic variation. A total of five stable MTAs (AX-95024590, AX-94425015, AX-95210025 AX-94539354, and AX-94978133) were identified in more than one environment and associated with the expression of DH, GFD, GNPS, and GY. Similarly, two novel pleiotropic genomic regions with associated MTAs i.e. AX-94978133 (4D) and AX-94539354 (6A) harboring co-localized QTLs governing two or more traits were also identified. In silico analysis revealed that the SNPs were located on important putative candidate genes such as F-box-like domain superfamily, Lateral organ boundaries, LOB, Thioredoxin-like superfamily Glutathione S-transferase, RNA-binding domain superfamily, UDP-glycosyltransferase family, Serine/threonine-protein kinase, Expansin, Patatin, Exocyst complex component Exo70, DUF1618 domain, Protein kinase domain involved in the regulation of grain size, grain number, growth and development, grain filling duration, and abiotic stress tolerance. The identified novel MTAs will be validated to estimate their effects in different genetic backgrounds for subsequent use in marker-assisted selection (MAS).

Genetic Dissection of Three Major Quantitative Trait Loci for Spike Compactness and Length in Bread Wheat (Triticum aestivum L.)

Spike compactness (SC) and length (SL) are the components of spike morphology and are strongly related to grain yield in wheat (Triticum aestivum L.). To investigate quantitative trait loci (QTL) associated with SC and SL, a recombinant inbred lines (RIL) population derived from the cross of Bailangmai (BLM, a Tibet landrace) and Chuanyu 20 (CY20, an improved variety) was employed in six environments. Three genomic regions responsible for SC and SL traits were identified on chromosomes 2A and 2D using bulked segregant exome sequencing (BSE-Seq). By constructing genetic maps, six major QTL were repeatedly detected in more than four environments and the best linear unbiased estimation (BLUE) datasets, explaining 7.00-28.56% of the phenotypic variation and the logarithm of the odd (LOD) score varying from 2.50 to 13.22. They were co-located on three loci, designed as QSc/Sl.cib-2AS, QSc/Sl.cib-2AL, and QSc/Sl.cib-2D, respectively. Based on the flanking markers, their interactions and effects on the corresponding trait and other agronomic traits were also analyzed. Comparison analysis showed that QSc/Sl.cib-2AS and QSc/Sl.cib-2AL were possibly two novel loci for SC and SL. QSc/Sl.cib-2AS and QSc/Sl.cib-2D showed pleiotropic effects on plant height and grain morphology, while QSc/Sl.cib-2AL showed effects on spikelet number per spike (SNS) and grain width (GW). Based on the gene annotation, orthologous search, and spatiotemporal expression patterns of genes, TraesCS2A03G0410600 and TraesCS2A03G0422300 for QSc/Sl.cib-2AS, and TraesCS2D03G1129300 and TraesCS2D03G1131500 for QSc/Sl.cib-2D were considered as potential candidate genes, respectively. These results will be useful for fine mapping and developing new varieties with high yield in the future.

Genome-wide association mapping of bread wheat genotypes for sustainable food security and yield potential under limited water conditions

Determining the genetic basis of yield and water deficient tolerance in wheat is vital for wheat breeding programs. Herein, a genome-wide association study (GWAS) was performed for water deficient and yield-related attributes on wheat genotypes with high-density Illumina 90K Infinium SNP array. Major yield and drought-related attributes were phenotyped on a panel of Pakistani and foreign accessions grown in non-stressed and water deficient stressed environments during two crop cycles. Among all accessions, highly significant variations were shown in studied environments for examined characters. Water deficient conditions, reduced the wheat yield and had strong and positive correlation among relative water content and grain yield per plant. Population structure analyses based on 90,000 SNP data, classify the accessions into 4 sub-populations. Marker-trait association analyses (MTA) revealed that 134 significant SNPs were linked with yield and drought tolerance attributes. Pleotropic loci RAC875_s117925_244 and RAC875_c16333_340 located on chromosome 5A and 2A respectively, were significantly linked with relative water contents (RWC), cell membrane thermo-stability (CMT), grain per spike (GPS), spikelet per spike (SPS) and grain yield per plant (GYP). The markers Ra_c58279_684, BobWhite_c23828_341 and IAAV3414 located on chromosomes 2A, 6B and 7B respectively, showed pleotropic effects for RWC, GPS and GYP under both environments. The current experiment not only validated several MTAs reported in other studies but also discovered novel MTAs which significant under drought-stressed conditions. A total of 171 candidate genes were recognized that could be cloned and functionally characterized for the respective associated traits. For RWC and CMT, total 11 and 3 associated SNPs were mapped on coding DNA sequence (CDS) of the identified candidate genes. Isolation and characterization of the candidate genes herein mapped SNPs will be useful in discovering novel genes underpinning drought tolerance in bread wheat to fulfill the wheat demand and sustainable food security under limited water conditions.

Genome wide association study of frost tolerance in wheat

Winter wheat growing areas in the Northern hemisphere are regularly exposed to heavy frost. Due to the negative impact on yield, the identification of genetic factors controlling frost tolerance (FroT) and development of tools for breeding is of prime importance. Here, we detected QTL associated with FroT by genome wide association studies (GWAS) using a diverse panel of 276 winter wheat genotypes that was phenotyped at five locations in Germany and Russia in three years. The panel was genotyped using the 90 K iSelect array and SNPs in FroT candidate genes. In total, 17,566 SNPs were used for GWAS resulting in the identification of 53 markers significantly associated (LOD ≥ 4) to FroT, corresponding to 23 QTL regions located on 11 chromosomes (1A, 1B, 2A, 2B, 2D, 3A, 3D, 4A, 5A, 5B and 7D). The strongest QTL effect confirmed the importance of chromosome 5A for FroT. In addition, to our best knowledge, eight FroT QTLs were discovered for the first time in this study comprising one QTL on chromosomes 3A, 3D, 4A, 7D and two on chromosomes 1B and 2D. Identification of novel FroT candidate genes will help to better understand the FroT mechanism in wheat and to develop more effective combating strategies.

Identification and characterization of QTL for spike morphological traits, plant height and heading date derived from the D genome of natural and resynthetic allohexaploid wheat

QHd.cau-7D.1 for heading date was delimited into the physical interval of approximately 17.38 Mb harboring three CONSTANS-like zinc finger genes. Spike morphological traits, plant height and heading date play important roles in yield improvement of wheat. To reveal the genetic factors that controlling spike morphological traits, plant height and heading date on the D genome, we conducted analysis of quantitative traits locus (QTL) using 198 F_7:8 recombinant inbred lines (RILs) derived from a cross between the common wheat TAA10 and resynthesized allohexaploid wheat XX329 with similar AABB genomes. A total of 23 environmentally stable QTL on the D sub-genome for spike length (SL), fertile spikelet number per spike (FSN), sterile spikelet number per spike (SSN), total spikelet number per spike (TSN), spike compactness (SC), plant height (PHT) and heading date (HD) were detected, among which eight appeared to be novel QTL. Furthermore, QHd.cau-7D.1 and QPht.cau-7D.2 shared identical confidence interval and were delimited into the physical interval of approximately 17.38 Mb with 145 annotated genes, including three CONSTANS-like zinc finger genes (TraesCS7D02G209000, TraesCS7D02G213000 and TraesCS7D02G220300). This study will help elucidate the molecular mechanism of the seven traits (SL, FSN, SSN, TSN, SC, PHT and HD) and provide a potentially valuable resource for genetic improvement.

Comprehensive evaluation of mapping complex traits in wheat using genome-wide association studies

Genome-wide association studies (GWAS) are effectively applied to detect the marker trait associations (MTAs) using whole genome-wide variants for complex quantitative traits in different crop species. GWAS has been applied in wheat for different quality, biotic and abiotic stresses, and agronomic and yield-related traits. Predictions for marker-trait associations are controlled with the development of better statistical models taking population structure and familial relatedness into account. In this review, we have provided a detailed overview of the importance of association mapping, population design, high-throughput genotyping and phenotyping platforms, advancements in statistical models and multiple threshold comparisons, and recent GWA studies conducted in wheat. The information about MTAs utilized for gene characterization and adopted in breeding programs is also provided. In the literature that we surveyed, as many as 86,122 wheat lines have been studied under various GWA studies reporting 46,940 loci. However, further utilization of these is largely limited. The future breakthroughs in area of genomic selection, multi-omics-based approaches, machine, and deep learning models in wheat breeding after exploring the complex genetic structure with the GWAS are also discussed. This is a most comprehensive study of a large number of reports on wheat GWAS and gives a comparison and timeline of technological developments in this area. This will be useful to new researchers or groups who wish to invest in GWAS.

Goyal A, Chaudhury A. Molecular and Transcriptional Regulation of Seed Development in Cereals: Present Status and Future Prospects

Cereals are a rich source of vitamins, minerals, carbohydrates, fats, oils and protein, making them the world’s most important source of nutrition. The influence of rising global population, as well as the emergence and spread of disease, has the major impact on cereal production. To meet the demand, there is a pressing need to increase cereal production. Optimal seed development is a key agronomical trait that contributes to crop yield. The seed development and maturation is a complex process that includes not only embryo and endosperm development, but also accompanied by huge physiological, biochemical, metabolic, molecular and transcriptional changes. This chapter discusses the growth of cereal seed and highlights the novel biological insights, with a focus on transgenic and new molecular breeding, as well as biotechnological intervention strategies that have improved crop yield in two major cereal crops, primarily wheat and rice, over the last 21 years (2000–2021).

Identification of genetic loci associated with major agronomic traits of wheat (Triticum aestivum L.) based on genome-wide association analysis

BACKGROUND

Bread wheat (Triticum aestivum L.) is one of the most widely consumed cereal crops, but its complex genome makes it difficult to investigate the genetic effect on important agronomic traits. Genome-wide association (GWA) analysis is a useful method to identify genetic loci controlling complex phenotypic traits. With the RNA-sequencing based gene expression analysis, putative candidate genes governing important agronomic trait can be suggested and also molecular markers can be developed.

RESULTS

We observed major quantitative agronomic traits of wheat; the winter survival rate (WSR), days to heading (DTH), days to maturity (DTM), stem length (SL), spike length (SPL), awn length (AL), liter weight (LW), thousand kernel weight (TKW), and the number of seeds per spike (SPS), of 287 wheat accessions from diverse country origins. A significant correlation was observed between the observed traits, and the wheat genotypes were divided into three subpopulations according to the population structure analysis. The best linear unbiased prediction (BLUP) values of the genotypic effect for each trait under different environments were predicted, and these were used for GWA analysis based on a mixed linear model (MLM). A total of 254 highly significant marker-trait associations (MTAs) were identified, and 28 candidate genes closely located to the significant markers were predicted by searching the wheat reference genome and RNAseq data. Further, it was shown that the phenotypic traits were significantly affected by the accumulation of favorable or unfavorable alleles.

CONCLUSIONS

From this study, newly identified MTA and putative agronomically useful genes will help to study molecular mechanism of each phenotypic trait. Further, the agronomically favorable alleles found in this study can be used to develop wheats with superior agronomic traits.

Mapping QTL for spike fertility and related traits in two doubled haploid wheat (Triticum aestivum L.) populations

BACKGROUND

In breeding programs, the selection of cultivars with the highest yield potential consisted in the selection of the yield per se, which resulted in cultivars with higher grains per spike (GN) and occasionally increased grain weight (GW) (main numerical components of the yield). In this study, quantitative trait loci (QTL) for GW, GN and spike fertility traits related to GN determination were mapped using two doubled haploid (DH) populations (Baguette Premium 11 × BioINTA 2002 and Baguette 19 × BioINTA 2002).

RESULTS

In total 305 QTL were identified for 14 traits, out of which 12 QTL were identified in more than three environments and explained more than 10% of the phenotypic variation in at least one environment. Eight hotspot regions were detected on chromosomes 1A, 2B, 3A, 5A, 5B, 7A and 7B in which at least two major and stable QTL sheared confidence intervals. QTL on two of these regions (R5A.1 and R5A.2) have previously been described, but the other six regions are novel.

CONCLUSIONS

Based on the pleiotropic analysis within a robust physiological model we conclude that two hotspot genomic regions (R5A.1 and R5A.2) together with the QGW.perg-6B are of high relevance to be used in marker assisted selection in order to improve the spike yield potential. All the QTL identified for the spike related traits are the first step to search for their candidate genes, which will allow their better manipulation in the future.

Transcriptome profiling of developing leaf and shoot apices to reveal the molecular mechanism and co-expression genes responsible for the wheat heading date

Background

Wheat is one of the most widely planted crops worldwide. The heading date is important for wheat environmental adaptability, as it not only controls flowering time but also determines the yield component in terms of grain number per spike.

Results

In this research, homozygous genotypes with early and late heading dates derived from backcrossed progeny were selected to conduct RNA-Seq analysis at the double ridge stage (W2.0) and androgynous primordium differentiation stage (W3.5) of the leaf and apical meristem, respectively. In total, 18,352 differentially expressed genes (DEGs) were identified, many of which are strongly associated with wheat heading date genes. Gene Ontology (GO) enrichment analysis revealed that carbohydrate metabolism, trehalose metabolic process, photosynthesis, and light reaction are closely related to the flowering time regulation pathway. Based on MapMan metabolic analysis, the DEGs are mainly involved in the light reaction, hormone signaling, lipid metabolism, secondary metabolism, and nucleotide synthesis. In addition, 1,225 DEGs were annotated to 45 transcription factor gene families, including LFY, SBP, and MADS-box transcription factors closely related to flowering time. Weighted gene co-expression network analysis (WGCNA) showed that 16, 336, 446, and 124 DEGs have biological connections with Vrn1-5 A, Vrn3-7B, Ppd-1D, and WSOC1, respectively. Furthermore, TraesCS2D02G181400 encodes a MADS-MIKC transcription factor and is co-expressed with Vrn1-5 A, which indicates that this gene may be related to flowering time.

Conclusions

RNA-Seq analysis provided transcriptome data for the wheat heading date at key flower development stages of double ridge (W2.0) and androgynous primordium differentiation (W3.5). Based on the DEGs identified, co-expression networks of key flowering time genes in Vrn1-5 A, Vrn3-7B, WSOC1, and Ppd-1D were established. Moreover, we discovered a potential candidate flowering time gene, TraesCS2D02G181400. Taken together, these results serve as a foundation for further study on the regulatory mechanism of the wheat heading date.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07797-7.

The physiology and genetics behind fruiting efficiency: a promising spike trait to improve wheat yield potential

Fruiting efficiency (FE, grains per g of spike dry weight at anthesis) was proposed as a promising spike trait to improve wheat yield potential, based on its functional relationship with grain number determination and the evidence of trait variability in elite germplasm. During the last few years, we have witnessed great advances in the understanding of the physiological and genetic basis of this trait. The present review summarizes the recent heritability estimations and the genetic gains obtained when fruiting efficiency was measured at maturity (FEm, grains per g of chaff) and used as selection criterion. In addition, we propose spike ideotypes for contrasting fruiting efficiencies based on the fertile floret efficiency (FFE, fertile florets per g of spike dry weight at anthesis) and grain set (grains per fertile floret), together with other spike fertility-related traits. We also review novel genes and quantitative trait loci available for using marker-assisted selection for fruiting efficiency and other spike fertility traits. The possible trade-off between FE and grain weight and the genes reported to alter this relation are also considered. Finally, we discuss the benefits and future steps towards the use of fruiting efficiency as a selection criterion in breeding programs.

Identification of Candidate Genes for Root Traits Using Genotype-Phenotype Association Analysis of Near-Isogenic Lines in Hexaploid Wheat (Triticum aestivum L.)

Global wheat (Triticum aestivum L.) production is constrained by different biotic and abiotic stresses, which are increasing with climate change. An improved root system is essential for adaptability and sustainable wheat production. In this study, 10 pairs of near-isogenic lines (NILs)-targeting four genomic regions (GRs) on chromosome arms 4BS, 4BL, 4AS, and 7AL of hexaploid wheat-were used to phenotype root traits in a semi-hydroponic system. Seven of the 10 NIL pairs significantly differed between their isolines for 11 root traits. The NIL pairs targeting qDSI.4B.1 GR varied the most, followed by the NIL pair targeting qDT.4A.1 and QHtscc.ksu-7A GRs. For pairs 5-7 targeting qDT.4A.1 GR, pair 6 significantly differed in the most root traits. Of the 4 NIL pairs targeting qDSI.4B.1 GR, pairs 2 and 4 significantly differed in 3 and 4 root traits, respectively. Pairs 9 and 10 targeting QHtscc.ksu-7A GR significantly differed in 1 and 4 root traits, respectively. Using the wheat 90K Illumina iSelect array, we identified 15 putative candidate genes associated with different root traits in the contrasting isolines, in which two UDP-glycosyltransferase (UGT)-encoding genes, TraesCS4A02G185300 and TraesCS4A02G442700, and a leucine-rich repeat receptor-like protein kinase (LRR-RLK)-encoding gene, TraesCS4A02G330900, also showed important functions for root trait control in other crops. This study characterized, for the first time, that these GRs control root traits in wheat, and identified candidate genes, although the candidate genes will need further confirmation and validation for marker-assisted wheat breeding.

Genetic Mapping by Integration of 55K SNP Array and KASP Markers Reveals Candidate Genes for Important Agronomic Traits in Hexaploid Wheat

Agronomic traits such as heading date (HD), plant height (PH), thousand grain weight (TGW), and spike length (SL) are important factors affecting wheat yield. In this study, we constructed a high-density genetic linkage map using the Wheat55K SNP Array to map quantitative trait loci (QTLs) for these traits in 207 recombinant inbred lines (RILs). A total of 37 QTLs were identified, including 9 QTLs for HD, 7 QTLs for PH, 12 QTLs for TGW, and 9 QTLs for SL, which explained 3.0-48.8% of the phenotypic variation. Kompetitive Allele Specific PCR (KASP) markers were developed based on sequencing data and used for validation of the stably detected QTLs on chromosomes 3A, 4B and 6A using 400 RILs. A QTL cluster on chromosome 4B for PH and TGW was delimited to a 0.8 Mb physical interval explaining 12.2-22.8% of the phenotypic variation. Gene annotations and analyses of SNP effects suggested that a gene encoding protein Photosynthesis Affected Mutant 68, which is essential for photosystem II assembly, is a candidate gene affecting PH and TGW. In addition, the QTL for HD on chromosome 3A was narrowed down to a 2.5 Mb interval, and a gene encoding an R3H domain-containing protein was speculated to be the causal gene influencing HD. The linked KASP markers developed in this study will be useful for marker-assisted selection in wheat breeding, and the candidate genes provide new insight into genetic study for those traits in wheat.

Linkage mapping identifies a non-synonymous mutation in FLOWERING LOCUS T (FT-B1) increasing spikelet number per spike

Total spikelet number per spike (TSN) is a major component of spike architecture in wheat (Triticumaestivum L.). A major and consistent quantitative trait locus (QTL) was discovered for TSN in a doubled haploid spring wheat population grown in the field over 4 years. The QTL on chromosome 7B explained up to 20.5% of phenotypic variance. In its physical interval (7B: 6.37–21.67 Mb), the gene FLOWERINGLOCUST (FT-B1) emerged as candidate for the observed effect. In one of the parental lines, FT-B1 carried a non-synonymous substitution on position 19 of the coding sequence. This mutation modifying an aspartic acid (D) into a histidine (H) occurred in a highly conserved position. The mutation was observed with a frequency of ca. 68% in a set of 135 hexaploid wheat varieties and landraces, while it was not found in other plant species. FT-B1 only showed a minor effect on heading and flowering time (FT) which were dominated by a major QTL on chromosome 5A caused by segregation of the vernalization gene VRN-A1. Individuals carrying the FT-B1 allele with amino acid histidine had, on average, a higher number of spikelets (15.1) than individuals with the aspartic acid allele (14.3) independent of their VRN-A1 allele. We show that the effect of TSN is not mainly related to flowering time; however, the duration of pre-anthesis phases may play a major role.

Genome-wide association study of yield and related traits in common wheat under salt-stress conditions

BACKGROUND

Soil salinization is a major threat to wheat production. It is essential to understand the genetic basis of salt tolerance for breeding and selecting new salt-tolerant cultivars that have the potential to increase wheat yield.

RESULT

In this study, a panel of 191 wheat accessions was subjected to genome wide association study (GWAS) to identify SNP markers linked with adult-stage characters. The population was genotyped by Wheat660K SNP array and eight phenotype traits were investigated under low and high salinity environments for three consecutive years. A total of 389 SNPs representing 11 QTLs were significantly associated with plant height, spike number, spike length, grain number, thousand kernels weight, yield and biological mass under different salt treatments, with the phenotypic explanation rate (R²) ranging from 9.14 to 50.45%. Of these, repetitive and pleiotropic loci on chromosomes 4A, 5A, 5B and 7A were significantly linked to yield and yield related traits such as thousand kernels weight, spike number, spike length, grain number and so on under low salinity conditions. Spike length-related loci were mainly located on chromosomes 1B, 3B, 5B and 7A under different salt treatments. Two loci on chromosome 4D and 5A were related with plant height in low and high salinity environment, respectively. Three salt-tolerant related loci were confirmed to be important in two bi-parental populations. Distribution of favorable haplotypes indicated that superior haplotypes of pleiotropic loci on group-5 chromosomes were strongly selected and had potential for increasing wheat salt tolerance. A total of 14 KASP markers were developed for nine loci associating with yield and related traits to improve the selection efficiency of wheat salt-tolerance breeding.

CONCLUSION

Utilizing a Wheat660K SNPs chip, QTLs for yield and its related traits were detected under salt treatment in a natural wheat population. Important salt-tolerant related loci were validated in RIL and DH populations. This study provided reliable molecular markers that could be crucial for marker-assisted selection in wheat salt tolerance breeding programs.

GWAS revealed effect of genotype × environment interactions for grain yield of Nebraska winter wheat

Background

Improving grain yield in cereals especially in wheat is a main objective for plant breeders. One of the main constrains for improving this trait is the G × E interaction (GEI) which affects the performance of wheat genotypes in different environments. Selecting high yielding genotypes that can be used for a target set of environments is needed. Phenotypic selection can be misleading due to the environmental conditions. Incorporating information from phenotypic and genomic analyses can be useful in selecting the higher yielding genotypes for a group of environments.

Results

A set of 270 F_3:6 wheat genotypes in the Nebraska winter wheat breeding program was tested for grain yield in nine environments. High genetic variation for grain yield was found among the genotypes. G × E interaction was also highly significant. The highest yielding genotype differed in each environment. The correlation for grain yield among the nine environments was low (0 to 0.43). Genome-wide association study revealed 70 marker traits association (MTAs) associated with increased grain yield. The analysis of linkage disequilibrium revealed 16 genomic regions with a highly significant linkage disequilibrium (LD). The candidate parents’ genotypes for improving grain yield in a group of environments were selected based on three criteria; number of alleles associated with increased grain yield in each selected genotype, genetic distance among the selected genotypes, and number of different alleles between each two selected parents.

Conclusion

Although G × E interaction was present, the advances in DNA technology provided very useful tools and analyzes. Such features helped to genetically select the highest yielding genotypes that can be used to cross grain production in a group of environments.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-020-07308-0.

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.

Insights into the Genetic Architecture of Bran Friability and Water Retention Capacity, Two Important Traits for Whole Grain End-Use Quality in Winter Wheat

Bran friability (particle size distribution after milling) and water retention capacity (WRC) impact wheat bran functionality in whole grain milling and baking applications. The goal of this study was to identify genomic regions and underlying genes that may be responsible for these traits. The Hard Winter Wheat Association Mapping Panel, which comprised 299 lines from breeding programs in the Great Plains region of the US, was used in a genome-wide association study. Bran friability ranged from 34.5% to 65.9% (median, 51.1%) and WRC ranged from 159% to 458% (median, 331%). Two single-nucleotide polymorphisms (SNPs) on chromosome 5D were significantly associated with bran friability, accounting for 11-12% of the phenotypic variation. One of these SNPs was located within the Puroindoline-b gene, which is known for influencing endosperm texture. Two SNPs on chromosome 4A were tentatively associated with WRC, accounting for 4.6% and 4.4% of phenotypic variation. The favorable alleles at the SNP sites were present in only 15% (friability) and 34% (WRC) of lines, indicating a need to develop new germplasm for these whole-grain end-use quality traits. Validation of these findings in independent populations will be useful for breeding winter wheat cultivars with improved functionality for whole grain food applications.

Genome-wide and SNP network analyses reveal genetic control of spikelet sterility and yield-related traits in wheat

Revealing the genetic factors underlying yield and agronomic traits in wheat are an imperative need for covering the global food demand. Yield boosting requires a deep understanding of the genetic basis of grain yield-related traits (e.g., spikelet fertility and sterility). Here, we have detected much natural variation among ancient hexaploid wheat accessions in twenty-two agronomic traits collected over eight years of field experiments. A genome-wide association study (GWAS) using 15 K single nucleotide polymorphisms (SNPs) was applied to detect the genetic basis of studied traits. Subsequently, the GWAS output was reinforced via other statistical and bioinformatics analyses to detect putative candidate genes. Applying the genome-wide SNP-phenotype network defined the most decisive SNPs underlying the traits. Six pivotal SNPs, co-located physically within the genes encoding enzymes, hormone response, metal ion transport, and response to oxidative stress have been identified. Of these, metal ion transport and Gibberellin 2-oxidases (GA2oxs) genes showed strong involvement in controlling the spikelet sterility, which had not been reported previously in wheat. SNP-gene haplotype analysis confirmed that these SNPs influence spikelet sterility, especially the SNP co-located on the exon of the GA2ox gene. Interestingly, these genes were highly expressed in the grain and spike, demonstrating their pivotal role in controlling the trait. The integrative analysis strategy applied in this study, including GWAS, SNP-phenotype network, SNP-gene haplotype, expression analysis, and genome-wide prediction (GP), empower the identification of functional SNPs and causal genes. GP outputs obtained in this study are encouraging for the implementation of the traits to accelerate yield improvement by making an early prediction of complex yield-related traits in wheat. Our findings demonstrate the usefulness of the ancient wheat material as a valuable resource for yield-boosting. This is the first comprehensive genome-wide analysis for spikelet sterility in wheat, and the results provide insights into yield improvement.

Haplotype block analysis of an Argentinean hexaploid wheat collection and GWAS for yield components and adaptation

BACKGROUND

Increasing wheat (Triticum aestivum L.) production is required to feed a growing human population. In order to accomplish this task a deeper understanding of the genetic structure of cultivated wheats and the detection of genomic regions significantly associated with the regulation of important agronomic traits are necessary steps. To better understand the genetic basis and relationships of adaptation and yield related traits, we used a collection of 102 Argentinean hexaploid wheat cultivars genotyped with the 35k SNPs array, grown from two to six years in three different locations. Based on SNPs data and gene-related molecular markers, we performed a haplotype block characterization of the germplasm and a genome-wide association study (GWAS).

RESULTS

The genetic structure of the collection revealed four subpopulations, reflecting the origin of the germplasm used by the main breeding programs in Argentina. The haplotype block characterization showed 1268 blocks of different sizes spread along the genome, including highly conserved regions like the 1BS chromosome arm where the 1BL/1RS wheat/rye translocation is located. Based on GWAS we identified ninety-seven chromosome regions associated with heading date, plant height, thousand grain weight, grain number per spike and fruiting efficiency at harvest (FEh). In particular FEh stands out as a promising trait to raise yield potential in Argentinean wheats; we detected fifteen haplotypes/markers associated with increased FEh values, eleven of which showed significant effects in all three evaluated locations. In the case of adaptation, the Ppd-D1 gene is consolidated as the main determinant of the life cycle of Argentinean wheat cultivars.

CONCLUSION

This work reveals the genetic structure of the Argentinean hexaploid wheat germplasm using a wide set of molecular markers anchored to the Ref Seq v1.0. Additionally GWAS detects chromosomal regions (haplotypes) associated with important yield and adaptation components that will allow improvement of these traits through marker-assisted selection.

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

Totally, 48 loci responsible for six spike-related traits were identified in wheat, and a major locus QGl-4A for grain length was mapped and validated for marker-assisted selection in breeding. Wheat yield is determined by the number of spikes, number of grains per spike (GN), and one-thousand kernel weight (TKW), among which GN and TKW are greatly related to the spike development and thus the spike-related traits, including spike length (SL), number of spikelet per spike (SN), grain length (GL) and grain width (GW). To identify the key loci governing the spike-related traits (SL, SN, GN, TKW, GL and GW), we conducted the quantitative trait loci (QTL) analysis combined with wheat 660K SNP chip and Kompetitive allele-specific PCR (KASP) assay, using the F₂ and F_2:3 populations derived from Luohan6 (LH6) with big spike and grain and Zhengmai366 with small spike and grain, and identified a total of 48 QTLs on 18 chromosomes. Moreover, a major stable QTL for GL on chromosome 4A, designated as QGl-4A, was mapped into a 0.37 cM interval between KASP markers Xib4A-10 and Xib4A-12, corresponding to 20 Mb physical region in the Chinese Spring genome. This QTL explained 17.30% and 5.12% of the phenotypic variation for GL in the F₂ and F_2:3 populations. Further association analysis of flanking markers Xib4A-10 and Xib4A-12 in 192 wheat varieties showed that these two markers could be used for marker-assisted selection in breeding. These results provide valuable information for map-based cloning of the target genes involved in the regulation of spike-related traits in common wheat.

Genome Wide Association Study and Genomic Selection of Amino Acid Concentrations in Soybean Seeds

Soybean is a major source of protein for human consumption and animal feed. Releasing new cultivars with high nutritional value is one of the major goals in soybean breeding. To achieve this goal, genome-wide association studies of seed amino acid contents were conducted based on 249 soybean accessions from China, US, Japan, and South Korea. The accessions were evaluated for 15 amino acids and genotyped by sequencing. Significant genetic variation was observed for amino acids among the accessions. Among the 231 single nucleotide polymorphisms (SNPs) significantly associated with variations in amino acid contents, fifteen SNPs localized near 14 candidate genes involving in amino acid metabolism. The amino acids were classified into two groups with five in one group and seven amino acids in the other. Correlation coefficients among the amino acids within each group were high and positive, but the correlation coefficients of amino acids between the two groups were negative. Twenty-five SNP markers associated with multiple amino acids can be used to simultaneously improve multi-amino acid concentration in soybean. Genomic selection analysis of amino acid concentration showed that selection efficiency of amino acids based on the markers significantly associated with all 15 amino acids was higher than that based on random markers or markers only associated with individual amino acid. The identified markers could facilitate selection of soybean varieties with improved seed quality.

TaAPO-A1, an ortholog of rice ABERRANT PANICLE ORGANIZATION 1, is associated with total spikelet number per spike in elite European hexaploid winter wheat (Triticum aestivum L.) varieties

We dissected the genetic basis of total spikelet number (TSN) along with other traits, viz. spike length (SL) and flowering time (FT) in a panel of 518 elite European winter wheat varieties. Genome-wide association studies (GWAS) based on 39,908 SNP markers revealed highly significant quantitative trait loci (QTL) for TSN on chromosomes 2D, 7A, and 7B, for SL on 5A, and FT on 2D, with 2D-QTL being the functional marker for the gene Ppd-D1. The physical region of the 7A-QTL for TSN revealed the presence of a wheat ortholog (TaAPO-A1) to APO1–a rice gene that positively controls the spikelet number on the panicles. Interspecific analyses of the TaAPO-A1 orthologs showed that it is a highly conserved gene important for floral development and present in a wide range of terrestrial plants. Intraspecific studies of the TaAPO-A1 across wheat genotypes revealed a polymorphism in the conserved F-box domain, defining two haplotypes. A KASP marker developed on the polymorphic site showed a highly significant association of TaAPO-A1 with TSN, explaining 23.2% of the total genotypic variance. Also, the TaAPO-A1 alleles showed weak but significant differences for SL and grain yield. Our results demonstrate the importance of wheat sequence resources to identify candidate genes for important traits based on genetic analyses.

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.

Genome-wide association study identifies variation of glucosidase being linked to natural variation of the maximal quantum yield of photosystem II

The maximum quantum yield of photosystem II (as reflected by variable to maximum chlorophyll a fluorescence, F_v /F_m ) is regarded as one of the most important photosynthetic parameters. The genetic basis underlying natural variation in F_v /F_m , which shows low level of variations in plants under non-stress conditions, is not easy to be exploited using the conventional gene cloning approaches. Thus, in order to answer this question, we have followed another strategy: we used genome-wide association study (GWAS) and transgenic analysis in a rice mini-core collection. We report here that four single-nucleotide polymorphisms, located in the promoter region of β-glucosidase 5 (BGlu-5), are associated with observed variation in F_v /F_m . Indeed, our transgenic analysis showed a good correlation between BGlu-5 and F_v /F_m . Thus, our work demonstrates the feasibility of using GWAS to study natural variation in F_v /F_m , suggesting that cis-element polymorphism, affecting the BGlu-5 expression level, may, indirectly, contribute to F_v /F_m variation in rice through the gibberellin signaling pathway. Further research is needed to understand the mechanism of our novel observation.

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

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

Dissection of Pleiotropic QTL Regions Controlling Wheat Spike Characteristics Under Different Nitrogen Treatments Using Traditional and Conditional QTL Mapping

Optimal spike characteristics are critical in improving the sink capacity and yield potential of wheat even in harsh environments. However, the genetic basis of their response to nitrogen deficiency is still unclear. In this study, quantitative trait loci (QTL) for six spike-related traits, including heading date (HD), spike length (SL), spikelet number (SN), spike compactness (SC), fertile spikelet number (FSN), and sterile spikelet number (SSN), were detected under two different nitrogen (N) supplies, based on a high-density genetic linkage map constructed by PCR markers, DArTs, and Affymetrix Wheat 660 K SNP chips. A total of 157 traditional QTLand 54 conditional loci were detected by inclusive composite interval mapping, among which three completely low N-stress induced QTL for SN and FSN (qSn-1A.1, qFsn-1B, and qFsn-7D) were found to maintain the desired spikelet fertility and kernel numbers even under N deficiency through pyramiding elite alleles. Twenty-eight stable QTL showing significant differencet in QTL detection model were found and seven genomic regions (R2D, R4A, R4B, R5A, R7A, R7B, and R7D) clustered by these stable QTL were highlighted. Among them, the effect of R4B on controlling spike characteristics might be contributed from Rht-B1. R7A harboring three major stable QTL (qSn-7A.2, qSc-7A, and qFsn-7A.3) might be one of the valuable candidate regions for further genetic improvement. In addition, the R7A was found to show syntenic with R7B, indicating the possibly exsting homoeologous candidate genes in both regions. The SNP markers involved with the above highlighted regions will eventually facilitate positional cloning or marker-assisted selection for the optimal spike characteristics under various N input conditions.