QTL analysis and fine mapping of a QTL for yield-related traits in wheat grown in dry and hot environments

Identification of QTLs associated with yield-related traits and superior genotype prediction using recombinant inbred line population in tobacco

Tobacco is an economically significant industrial crop and model plant for genetic research, yet little is known about its genetic architecture. Quantitative trait loci (QTL) analysis was performed for six agronomic traits on an F_7 population of 341 genotypes, parents, and F1 plants using 1974 SSR markers across two environments. 31 QTLs contributing single-locus additive effects on 13 linkage groups (LGs) and 6 QTL pairs contributing epistatic effects on 6 LGs, were detected by the QTLNetwork 2.0 which was developed for the mixed-linear-model-based composite interval mapping (MCIM). Notably, 5 QTLs and 1 epistatic QTL pair were found to have pleiotropic effects on some genetically related traits. Moreover, the Broad sense heritability of the detected QTLs ranged from 1.05% to 43.33%, while genotype-by-environment interaction heritability spanned from 27.09% to 56.25%. Based on the results of QTL mapping, the potential superior lines for all or specific environments were designed and evaluated. Five major QTLs were finely dissected based on the tobacco reference genome of K326, and 31 candidate genes were predicted. This study offered new insights into the complicated genetic architecture and QTL resources for efficient breeding design for genetic improvement of agronomic traits in tobacco.

Fine mapping of a major QTL, qKl-1BL controlling kernel length in common wheat

KEY MESSAGE

A major stable QTL, qKl-1BL, for kernel length of wheat was narrowed down to a 2.04-Mb interval on chromosome 1BL; the candidate genes were predicated and the genetic effects on yield-related traits were characterized. As a key factor influencing kernel weight, wheat kernel shape is closely related to yield formation, and in turn affects both wheat processing quality and market value. Fine mapping of the major quantitative trait loci (QTL) for kernel shape could provide genetic resources and a theoretical basis for the genetic improvement of wheat yield-related traits. In this study, a major QTL for kernel length (KL) on 1BL, named qKl-1BL, was identified from the recombinant inbred lines (RIL) in multiple environments based on the genetic map and physical map, with 4.76-21.15% of the phenotypic variation explained. To fine map qKl-1BL, the map-based cloning strategy was used. By using developed InDel markers, the near-isogenic line (NIL) pairs and eight key recombinants were identified from a segregating population containing 3621 individuals derived from residual heterozygous lines (RHLs) self-crossing. In combination with phenotype identification, qKl-1BL was finely positioned into a 2.04-Mb interval, KN1B:698.15-700.19 Mb, with eight differentially expressed genes enriched at the key period of kernel elongation. Based on transcriptome analysis and functional annotation information, two candidate genes for qKl-1BL controlling kernel elongation were identified. Additionally, genetic effect analysis showed that the superior allele of qKl-1BL from Jing411 could increase KL, thousand kernel weight (TKW), and yield per plant (YPP) significantly, as well as kernel bulk density and stability time. Taken together, this study identified a QTL interval for controlling kernel length with two possible candidate genes, which provides an important basis for qKl-1BL cloning, functional analysis, and application in molecular breeding programs.

The use of weighted multiple linear regression to estimate QTL × QTL × QTL interaction effects of winter wheat (Triticum aestivum L.) doubled-haploid lines

Knowledge of the magnitude of gene effects and their interactions, their nature, and contribution to determining quantitative traits is very important in conducting an effective breeding program. In traditional breeding, information on the parameter related to additive gene effect and additive-additive interaction (epistasis) and higher-order additive interactions would be useful. Although commonly overlooked in studies, higher-order interactions have a significant impact on phenotypic traits. Failure to account for the effect of triplet interactions in quantitative genetics can significantly underestimate additive QTL effects. Understanding the genetic architecture of quantitative traits is a major challenge in the post-genomic era, especially for quantitative trait locus (QTL) effects, QTL-QTL interactions, and QTL-QTL-QTL interactions. This paper proposes using weighted multiple linear regression to estimate the effects of triple interaction (additive-additive-additive) quantitative trait loci (QTL-QTL-QTL). The material for the study consisted of 126 doubled haploid lines of winter wheat (Mandub × Begra cross). The lines were analyzed for 18 traits, including percentage of necrosis leaf area, percentage of leaf area covered by pycnidia, heading data, and height. The number of genes (the number of effective factors) was lower than the number of QTLs for nine traits, higher for four traits and equal for five traits. The number of triples for unweighted regression ranged from 0 to 9, while for weighted regression, it ranged from 0 to 13. The total aaagu effect ranged from - 14.74 to 15.61, while aaagw ranged from - 23.39 to 21.65. The number of detected threes using weighted regression was higher for two traits and lower for four traits. Forty-nine statistically significant threes of the additive-by-additive-by-additive interaction effects were observed. The QTL most frequently occurring in threes was 4407404 (9 times). The use of weighted regression improved (in absolute value) the assessment of QTL-QTL-QTL interaction effects compared to the assessment based on unweighted regression. The coefficients of determination for the weighted regression model were higher, ranging from 0.8 to 15.5%, than for the unweighted regression. Based on the results, it can be concluded that the QTL-QTL-QTL triple interaction had a significant effect on the expression of quantitative traits. The use of weighted multiple linear regression proved to be a useful statistical tool for estimating additive-additive-additive (aaa) interaction effects. The weighted regression also provided results closer to phenotypic evaluations than estimator values obtained using unweighted regression, which is closer to the true values.

Genomic regions involved in the control of 1,000-kernel weight in wild relative-derived populations of durum wheat

Terminal drought is one of the most common and devastating climatic stress factors affecting durum wheat (Triticum durum Desf.) production worldwide. The wild relatives of this crop are deemed a vast potential source of useful alleles to adapt to this stress. A nested association mapping (NAM) panel was generated using as a recurrent parent the Moroccan variety 'Nachit' derived from Triticum dicoccoides and known for its large grain size. This was recombined to three top-performing lines derived from T. dicoccoides, T. araraticum, and Aegilops speltoides, for a total of 426 inbred progenies. This NAM was evaluated across eight environments (Syria, Lebanon, and Morocco) experiencing different degrees of terminal moisture stress over two crop seasons. Our results showed that drought stress caused on average 41% loss in yield and that 1,000-kernel weight (TKW) was the most important trait for adaptation to it. Genotyping with the 25K TraitGenetics array resulted in a consensus map of 1,678 polymorphic SNPs, spanning 1,723 cM aligned to the reference 'Svevo' genome assembly. Kinship distinguished the progenies in three clades matching the parent of origin. A total of 18 stable quantitative trait loci (QTLs) were identified as controlling various traits but independent from flowering time. The most significant genomic regions were named Q.ICD.NAM-04, Q.ICD.NAM-14, and Q.ICD.NAM-16. Allelic investigation in a second germplasm panel confirmed that carrying the positive allele at all three loci produced an average TKW advantage of 25.6% when field-tested under drought conditions. The underlying SNPs were converted to Kompetitive Allele-Specific PCR (KASP) markers and successfully validated in a third germplasm set, where they explained up to 19% of phenotypic variation for TKW under moisture stress. These findings confirm the identification of critical loci for drought adaptation derived from wild relatives that can now be readily exploited via molecular breeding.

Combined linkage analysis and association mapping identifies genomic regions associated with yield-related and drought-tolerance traits in wheat (Triticum aestivum L.)

KEY MESSAGE

Combined linkage analysis and association mapping identified genomic regions associated with yield and drought tolerance, providing information to assist breeding for high yield and drought tolerance in wheat. Wheat (Triticum aestivum L.) is one of the most widely grown food crops and provides adequate amounts of protein to support human health. Drought stress is the most important abiotic stress constraining yield during the flowering and grain development periods. Precise targeting of genomic regions underlying yield- and drought tolerance-responsive traits would assist in breeding programs. In this study, two water treatments (well-watered, WW, and rain-fed water stress, WS) were applied, and five yield-related agronomic traits (plant height, PH; spike length, SL; spikelet number per spike, SNPS; kernel number per spike, KNPS; thousand kernel weight, TKW) and drought response values (DRVs) were used to characterize the drought sensitivity of each accession. Association mapping was performed on an association panel of 304 accessions, and linkage analysis was applied to a doubled haploid (DH) population of 152 lines. Eleven co-localized genomic regions associated with yield traits and DRV were identified in both populations. Many previously cloned key genes were located in these regions. In particular, a TKW-associated region on chromosome 2D was identified using both association mapping and linkage analysis and a key candidate gene, TraesCS2D02G142500, was detected based on gene annotation and differences in expression levels. Exonic SNPs were analyzed by sequencing the full length of TraesCS2D02G142500 in the association panel, and a rare haplotype, Hap-2, which reduced TKW to a lesser extent than Hap-1 under drought stress, and the Hap-2 varieties presented drought-insensitive. Altogether, this study provides fundamental insights into molecular targets for high yield and drought tolerance in wheat.

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.

An Overview of Factors Affecting the Functional Quality of Common Wheat (Triticum aestivum L.)

Wheat (Triticum aestivum L.) is one of the most important crops worldwide, and, as a resilient cereal, it grows in various climatic zones. Due to changing climatic conditions and naturally occurring environmental fluctuations, the priority problem in the cultivation of wheat is to improve the quality of the crop. Biotic and abiotic stressors are known factors leading to the deterioration of wheat grain quality and to crop yield reduction. The current state of knowledge on wheat genetics shows significant progress in the analysis of gluten, starch, and lipid genes responsible for the synthesis of the main nutrients in the endosperm of common wheat grain. By identifying these genes through transcriptomics, proteomics, and metabolomics studies, we influence the creation of high-quality wheat. In this review, previous works were assessed to investigate the significance of genes, puroindolines, starches, lipids, and the impact of environmental factors, as well as their effects on the wheat grain quality.

Construction of a high-density genetic map and dissection of genetic architecture of six agronomic traits in tobacco (Nicotiana tabacum L.)

Tobacco (Nicotiana tabacum L.) is an economic crop and a model organism for studies on plant biology and genetics. A population of 271 recombinant inbred lines (RIL) derived from K326 and Y3, two elite flue-cured tobacco parents, has been constructed to investigate the genetic basis of agronomic traits in tobacco. Six agronomic traits including natural plant height (nPH), natural leaf number (nLN), stem girth (SG), inter-node length (IL), length of the largest leaf (LL) and width of the largest leaf (LW) were measured in seven environments, spanning the period between 2018 and 2021. We firstly developed an integrated SNP-indel-SSR linkage map with 43,301 SNPs, 2,086 indels and 937 SSRs, which contained 7,107 bin markers mapped on 24 LGs and covered 3334.88 cM with an average genetic distance of 0.469cM. Based on this high-density genetic map, a total of 70 novel QTLs were detected for six agronomic traits by a full QTL model using the software QTLNetwork, of which 32 QTLs showed significant additive effects, 18 QTLs showed significant additive-by-environment interaction effects, 17 pairs showed significant additive-by-additive epistatic effects and 13 pairs showed significant epistasis-by-environment interaction effects. In addition to additive effect as a major contributor to genetic variation, both epistasis effects and genotype-by-environment interaction effects played an important role in explaining phenotypic variation for each trait. In particular, qnLN6-1 was detected with considerably large main effect and high heritability ( h a 2 =34.80%). Finally, four genes including Nt16g00284.1, Nt16g00767.1, Nt16g00853.1, Nt16g00877.1 were predicted as pleiotropic candidate genes for five traits.

QTL and Candidate Genes: Techniques and Advancement in Abiotic Stress Resistance Breeding of Major Cereals

At least 75% of the world's grain production comes from the three most important cereal crops: rice (Oryza sativa), wheat (Triticum aestivum), and maize (Zea mays). However, abiotic stressors such as heavy metal toxicity, salinity, low temperatures, and drought are all significant hazards to the growth and development of these grains. Quantitative trait locus (QTL) discovery and mapping have enhanced agricultural production and output by enabling plant breeders to better comprehend abiotic stress tolerance processes in cereals. Molecular markers and stable QTL are important for molecular breeding and candidate gene discovery, which may be utilized in transgenic or molecular introgression. Researchers can now study synteny between rice, maize, and wheat to gain a better understanding of the relationships between the QTL or genes that are important for a particular stress adaptation and phenotypic improvement in these cereals from analyzing reports on QTL and candidate genes. An overview of constitutive QTL, adaptive QTL, and significant stable multi-environment and multi-trait QTL is provided in this article as a solid framework for use and knowledge in genetic enhancement. Several QTL, such as DRO1 and Saltol, and other significant success cases are discussed in this review. We have highlighted techniques and advancements for abiotic stress tolerance breeding programs in cereals, the challenges encountered in introgressing beneficial QTL using traditional breeding techniques such as mutation breeding and marker-assisted selection (MAS), and the in roads made by new breeding methods such as genome-wide association studies (GWASs), the clustered regularly interspaced short palindromic repeat (CRISPR)/Cas9 system, and meta-QTL (MQTL) analysis. A combination of these conventional and modern breeding approaches can be used to apply the QTL and candidate gene information in genetic improvement of cereals against abiotic stresses.

Nested association mapping-based GWAS for grain yield and related traits in wheat grown under diverse Australian environments

Utilising a nested association mapping (NAM) population-based GWAS, 98 stable marker-trait associations with 127 alleles unique to the exotic parents were detected for grain yield and related traits in wheat. Grain yield, thousand-grain weight, screenings and hectolitre weight are important wheat yield traits. An understanding of their genetic basis is crucial for improving grain yield in breeding programmes. Nested association mapping (NAM) populations are useful resources for the dissection of the genetic basis of complex traits such as grain yield and related traits in wheat. Coupled with phenotypic data collected from multiple environments, NAM populations have the power to detect quantitative trait loci and their multiple alleles, providing germplasm that can be incorporated into breeding programmes. In this study, we evaluated a large-scale wheat NAM population with two recurrent parents in unbalanced trials in nine diverse Australian field environments over three years. By applying a single-stage factor analytical linear mixed model (FALMM) to the NAM multi-environment trials (MET) data and conducting a genome-wide association study (GWAS), we detected 98 stable marker-trait associations (MTAs) with their multiple alleles. 74 MTAs had 127 alleles that were derived from the exotic parents and were absent in either of the two recurrent parents. The exotic alleles had favourable effects on 46 MTAs of the 74 MTAs, for grain yield, thousand-grain weight, screenings and hectolitre weight. Two NAM RILs with consistently high yield in multiple environments were also identified, highlighting the potential of the NAM population in supporting plant breeding through provision of germplasm that can be readily incorporated into breeding programmes. The identified beneficial exotic alleles introgressed into the NAM population provide potential target alleles for the genetic improvement of wheat and further studies aimed at pinpointing the underlying genes.

Identification of quantitative trait loci of agronomic traits in bread wheat using a Pamyati Azieva × Paragon mapping population harvested in three regions of Kazakhstan

Background

Although genome-wide association studies (GWAS) are an increasingly informative tool in the mining of new quantitative trait loci (QTLs), a classical biparental mapping approach is still a powerful, widely used method to search the unique genetic factors associated with important agronomic traits in bread wheat.

Methods

In this study, a newly constructed mapping population of Pamyati Azieva (Russian Federation) × Paragon (UK), consisting of 94 recombinant inbred lines (RILs), was tested in three different regions of Kazakhstan with the purpose of QTL identification for key agronomic traits. The RILs were tested in 11 environments of two northern breeding stations (Petropavlovsk, North Kazakhstan region, and Shortandy, Aqmola region) and one southeastern station (Almalybak, Almaty region). The following eight agronomic traits were studied: heading days, seed maturation days, plant height, spike length, number of productive spikes, number of kernels per spike, thousand kernel weight, and yield per square meter. The 94 RILs of the PAxP cross were genotyped using Illumina's iSelect 20K single nucleotide polymorphism (SNP) array and resulted in the identification of 4595 polymorphic SNP markers.

Results

The application of the QTL Cartographer statistical package allowed the identification of 53 stable QTLs for the studied traits. A survey of published studies related to common wheat QTL identification suggested that 28 of those 53 QTLs were presumably novel genetic factors. The SNP markers for the identified QTLs of the analyzed agronomic traits of common wheat can be efficiently applied in ongoing breeding activities in the wheat breeding community using a marker-assisted selection approach.

Genetic identification of the pleiotropic gene Tasg-D1/2 affecting wheat grain shape by regulating brassinolide metabolism

Improving yield potential is a major goal of wheat breeding that depends on identifying key genetic loci. In this study, two residual heterozygous line RHL351- and RHL78-derived populations were employed for genetic linkage map construction and QTL detection. Two genetic populations indicated a robust grain-size QTL between Marker6 and Marker10. It covered a 95.54-99.38 Mb physical interval and was named Qpleio.nwafu.3D, containing the candidate gene Tasg (TraesCS3D02G137200). Intriguingly, RNA-seq analysis and sequencing revealed two different allelic variants in Tasg, named Tasg-D1 (G>A) and Tasg-D2 (C>G), respectively. Although the relationship between Tasg-D1 and grain size had been demonstrated previously, here we provided the first genetic evidence that C/G allelic variation in Tasg-D2 was associated with grain shape and size through a newly developed dCAPS marker. In addition, transcriptome comparison indicated that Tasg-D1/2 might primarily contribute to significant expression differences in brassinolide (BR) metabolism-related genes rather than those related to BR responses in developing grains and spikes. Our study provided new evidence and a breeder-friendly dCAPS marker for improving grain size through the selection of Tasg, as well as a basis to understand Tasg function in the future.

A multi-environment framework to evaluate the adaptation of wheat (Triticum aestivum) to heat stress

Assessing adaptation to abiotic stresses such as high temperature conditions across multiple environments presents opportunities for breeders to target selection for broad adaptation and specific adaptation. Adaptation of wheat to heat stress is an important component of adaptation in variable climates such as the cereal producing areas of Australia. However, in variable climates stress conditions may not be present in every season or are present to varying degrees, at different times during the season. Such conditions complicate plant breeders' ability to select for adaptation to abiotic stress. This study presents a framework for the assessment of the genetic basis of adaptation to heat stress conditions with improved relevance to breeders' selection objectives. The framework was applied here with the evaluation of 1225 doubled haploid lines from five populations across six environments (three environments selected for contrasting temperature stress conditions during anthesis and grain fill periods, over two consecutive seasons), using regionally best practice planting times to evaluate the role of heat stress conditions in genotype adaptation. Temperature co-variates were determined for each genotype, in each environment, for the anthesis and grain fill periods. Genome-wide QTL analysis identified performance QTL for stable effects across all environments, and QTL that illustrated responsiveness to heat stress conditions across the sampled environments. A total of 199 QTL were identified, including 60 performance QTL, and 139 responsiveness QTL. Of the identified QTL, 99 occurred independent of the 21 anthesis date QTL identified. Assessing adaptation to heat stress conditions as the combination of performance and responsiveness offers breeders opportunities to select for grain yield stability across a range of environments, as well as genotypes with higher relative yield in stress conditions.

Identification and Validation of a Chromosome 4D Quantitative Trait Locus Hotspot Conferring Heat Tolerance in Common Wheat (Triticum aestivum L.)

Understanding of the genetic mechanism of heat tolerance (HT) can accelerate and improve wheat breeding in dealing with a warming climate. This study identified and validated quantitative trait loci (QTL) responsible for HT in common wheat. The International Triticeae Mapping Initiative (ITMI) population, recombinant inbreed lines (RILs) derived from a cross between Synthetic W7984 and Opata M85, was phenotyped for shoot length, root length, whole plant length under heat stress and corresponding damage indices (DIs) to compare HT performances of individuals. Wide variations among the RILs were shown for all the traits. A total of 13 QTL including 9 major QTL and 4 minor QTL were identified, distributed on 6 wheat chromosomes. The six major QTL with the highest R² were associated with different traits under heat stress. They were all from Opata M85 background and located within a 2.2 cm interval on chromosome 4D, making up a QTL hotspot conferring HT in common wheat. The QTL hotspot was validated by genotyping-phenotyping association analysis using single-nucleotide-polymorphism (SNP) assays. The QTL, especially the 4D QTL hotspot identified and validated in this study, are valuable for the further fine mapping and identification of key genes and exploring genetic mechanism of HT in wheat.

Impacts, Tolerance, Adaptation, and Mitigation of Heat Stress on Wheat under Changing Climates

Heat stress (HS) is one of the major abiotic stresses affecting the production and quality of wheat. Rising temperatures are particularly threatening to wheat production. A detailed overview of morpho-physio-biochemical responses of wheat to HS is critical to identify various tolerance mechanisms and their use in identifying strategies to safeguard wheat production under changing climates. The development of thermotolerant wheat cultivars using conventional or molecular breeding and transgenic approaches is promising. Over the last decade, different omics approaches have revolutionized the way plant breeders and biotechnologists investigate underlying stress tolerance mechanisms and cellular homeostasis. Therefore, developing genomics, transcriptomics, proteomics, and metabolomics data sets and a deeper understanding of HS tolerance mechanisms of different wheat cultivars are needed. The most reliable method to improve plant resilience to HS must include agronomic management strategies, such as the adoption of climate-smart cultivation practices and use of osmoprotectants and cultured soil microbes. However, looking at the complex nature of HS, the adoption of a holistic approach integrating outcomes of breeding, physiological, agronomical, and biotechnological options is required. Our review aims to provide insights concerning morpho-physiological and molecular impacts, tolerance mechanisms, and adaptation strategies of HS in wheat. This review will help scientific communities in the identification, development, and promotion of thermotolerant wheat cultivars and management strategies to minimize negative impacts of HS.

Dissecting the Genetics of Early Vigour to Design Drought-Adapted Wheat

Due to the climate change and an increased frequency of drought, it is of enormous importance to identify and to develop traits that result in adaptation and in improvement of crop yield stability in drought-prone regions with low rainfall. Early vigour, defined as the rapid development of leaf area in early developmental stages, is reported to contribute to stronger plant vitality, which, in turn, can enhance resilience to erratic drought periods. Furthermore, early vigour improves weed competitiveness and nutrient uptake. Here, two sets of a multi-reference nested association mapping (MR-NAM) population of bread wheat (Triticum aestivum ssp. aestivum L.) were used to investigate early vigour in a rain-fed field environment for 3 years, and additionally assessed under controlled conditions in a greenhouse experiment. The normalised difference vegetation index (NDVI) calculated from red/infrared light reflectance was used to quantify early vigour in the field, revealing a correlation (p < 0.05; r = 0.39) between the spectral measurement and the length of the second leaf. Under controlled environmental conditions, the measured projected leaf area, using a green-pixel counter, was also correlated to the leaf area of the second leaf (p < 0.05; r = 0.38), as well as to the recorded biomass (p < 0.01; r = 0.71). Subsequently, genetic determination of early vigour was tested by conducting a genome-wide association study (GWAS) for the proxy traits, revealing 42 markers associated with vegetation index and two markers associated with projected leaf area. There are several quantitative trait loci that are collocated with loci for plant developmental traits including plant height on chromosome 2D (log₁₀ (P) = 3.19; PVE = 0.035), coleoptile length on chromosome 1B (-log₁₀ (P) = 3.24; PVE = 0.112), as well as stay-green and vernalisation on chromosome 5A (-log₁₀ (P) = 3.14; PVE = 0.115).

Genetic dissection of quantitative trait loci for grain size and weight by high-resolution genetic mapping in bread wheat (Triticum aestivum L.)

Six major QTLs for wheat grain size and weight were identified on chromosomes 4A, 4B, 5A and 6A across multiple environments, and were validated in different genetic backgrounds. Grain size and weight are crucial components of wheat yield. Dissection of their genetic control is thus essential for the improvement of yield potential in wheat breeding. We used a doubled haploid (DH) population to detect quantitative trait loci (QTLs) for grain width (GW), grain length (GL), and thousand grain weight (TGW) in five environments. Six major QTLs, QGw.cib-4B.2, QGl.cib-4A, QGl.cib-5A.1, QGl.cib-6A, QTgw.cib-4B, and QTgw.cib-5A, were consistently identified in at least three individual environments and in best linear unbiased prediction (BLUP) datasets, and explained 5.65-34.06% of phenotypic variation. QGw.cib-4B.2, QTgw.cib-4B, QGl.cib-5A.1 and QGl.cib-6A had no effect on grain number per spike (GNS). In addition to QGl.cib-4A, the other major QTLs were further validated by using Kompetitive Allele Specific PCR (KASP) markers in different genetic backgrounds. Moreover, significant interactions between the three major GL QTLs and two major TGW QTLs were observed. Comparison analysis showed that QGl.cib-5A.1 and QGl.cib-6A are likely new loci. Notably, QGw.cib-4B.2 and QTgw.cib-4B were co-located on chromosome 4B and improved TGW by increasing only GW, unlike nearby or overlapped loci reported previously. Three genes associated with grain development within the QGw.cib-4B.2/QTgw.cib-4B interval were identified by searches on sequence similarity, spatial expression patterns, and orthologs. The major QTLs and KASP markers reported here will be useful for elucidating the genetic architecture of grain size and weight and for developing new wheat cultivars with high and stable yield.

Genome-wide association study of yield components in spring wheat collection harvested under two water regimes in Northern Kazakhstan

Background

Bread wheat is the most important cereal in Kazakhstan, where it is grown on over 12 million hectares. One of the major constraints affecting wheat grain yield is drought due to the limited water supply. Hence, the development of drought-resistant cultivars is critical for ensuring food security in this country. Therefore, identifying quantitative trait loci (QTLs) associated with drought tolerance as an essential step in modern breeding activities, which rely on a marker-assisted selection approach.

Methods

A collection of 179 spring wheat accessions was tested under irrigated and rainfed conditions in Northern Kazakhstan over three years (2018, 2019, and 2020), during which data was collected on nine traits: heading date (HD), seed maturity date (SMD), plant height (PH), peduncle length (PL), number of productive spikes (NPS), spike length (SL), number of kernels per spike (NKS), thousand kernel weight (TKW), and kernels yield per m² (YM2). The collection was genotyped using a 20,000 (20K) Illumina iSelect SNP array, and 8,662 polymorphic SNP markers were selected for a genome-wide association study (GWAS) to identify QTLs for targeted agronomic traits.

Results

Out of the total of 237 discovered QTLs, 50 were identified as being stable QTLs for irrigated and rainfed conditions in the Akmola region, Northern Kazakhstan; the identified QTLs were associated with all the studied traits except PH. The results indicate that nine QTLs for HD and 11 QTLs for SMD are presumably novel genetic factors identified in the irrigated and rainfed conditions of Northern Kazakhstan. The identified SNP markers of the QTLs for targeted traits in rainfed conditions can be applied to develop new competitive spring wheat cultivars in arid zones using a marker-assisted selection approach.

Integrated NIRS and QTL assays reveal minor mannose and galactose as contrast lignocellulose factors for biomass enzymatic saccharification in rice

BACKGROUND

Identifying lignocellulose recalcitrant factors and exploring their genetic properties are essential for enhanced biomass enzymatic saccharification in bioenergy crops. Despite genetic modification of major wall polymers has been implemented for reduced recalcitrance in engineered crops, it could most cause a penalty of plant growth and biomass yield. Alternatively, it is increasingly considered to improve minor wall components, but an applicable approach is required for efficient assay of large population of biomass samples. Hence, this study collected total of 100 rice straw samples and characterized all minor wall monosaccharides and biomass enzymatic saccharification by integrating NIRS modeling and QTL profiling.

RESULTS

By performing classic chemical analyses and establishing optimal NIRS equations, this study examined four minor wall monosaccharides and major wall polymers (acid-soluble lignin/ASL, acid-insoluble lignin/AIL, three lignin monomers, crystalline cellulose), which led to largely varied hexoses yields achieved from enzymatic hydrolyses after two alkali pretreatments were conducted with large population of rice straws. Correlation analyses indicated that mannose and galactose can play a contrast role for biomass enzymatic saccharification at P < 0.0 l level (n = 100). Meanwhile, we found that the QTLs controlling mannose, galactose, lignin-related traits, and biomass saccharification were co-located. By combining NIRS assay with QTLs maps, this study further interpreted that the mannose-rich hemicellulose may assist AIL disassociation for enhanced biomass enzymatic saccharification, whereas the galactose-rich polysaccharides should be effectively extracted with ASL from the alkali pretreatment for condensed AIL association with cellulose microfibrils.

CONCLUSIONS

By integrating NIRS assay with QTL profiling for large population of rice straw samples, this study has identified that the mannose content of wall polysaccharides could positively affect biomass enzymatic saccharification, while the galactose had a significantly negative impact. It has also sorted out that two minor monosaccharides could distinctively associate with lignin deposition for wall network construction. Hence, this study demonstrates an applicable approach for fast assessments of minor lignocellulose recalcitrant factors and biomass enzymatic saccharification in rice, providing a potential strategy for bioenergy crop breeding and biomass processing.

Genome-Wide Association Mapping for Yield and Related Traits Under Drought Stressed and Non-stressed Environments in Wheat

Understanding the genetics of drought tolerance in hard red spring wheat (HRSW) in northern USA is a prerequisite for developing drought-tolerant cultivars for this region. An association mapping (AM) study for drought tolerance in spring wheat in northern USA was undertaken using 361 wheat genotypes and Infinium 90K single-nucleotide polymorphism (SNP) assay. The genotypes were evaluated in nine different locations of North Dakota (ND) for plant height (PH), days to heading (DH), yield (YLD), test weight (TW), and thousand kernel weight (TKW) under rain-fed conditions. Rainfall data and soil type of the locations were used to assess drought conditions. A mixed linear model (MLM), which accounts for population structure and kinship (PC+K), was used for marker–trait association. A total of 69 consistent QTL involved with drought tolerance-related traits were identified, with p ≤ 0.001. Chromosomes 1A, 3A, 3B, 4B, 4D, 5B, 6A, and 6B were identified to harbor major QTL for drought tolerance. Six potential novel QTL were identified on chromosomes 3D, 4A, 5B, 7A, and 7B. The novel QTL were identified for DH, PH, and TKW. The findings of this study can be used in marker-assisted selection (MAS) for drought-tolerance breeding in spring wheat.

Dissection of Genetic Basis Underpinning Kernel Weight-Related Traits in Common Wheat

Genetic dissection kernel weight-related traits is of great significance for improving wheat yield potential. As one of the three major yield components of wheat, thousand kernel weight (TKW) was mainly affected by grain length (GL) and grain width (GW). To uncover the key loci for these traits, we carried out a quantitative trait loci (QTL) analysis of an F₆ recombinant inbred lines (RILs) population derived from a cross of Henong 5290 (small grain) and 06Dn23 (big grain) with a 50 K single nucleotide polymorphism (SNP) array. A total of 17 stable and big effect QTL, including 5 for TKW, 8 for GL and 4 for GW, were detected on the chromosomes 1B, 2A, 2B, 2D, 4B, 5A, 6A and 6D, respectively. Among these, there were two co-located loci for three traits that were mapped on the chromosome 4BS and 6AL. The QTL on 6AL was the most stable locus and explained 15.4–24.8%, 4.1–8.8% and 15.7–24.4% of TKW, GW and GL variance, respectively. In addition, two more major QTL of GL were located on chromosome arm 2BL and 2DL, accounting for 9.7–17.8% and 13.6–19.8% of phenotypic variance, respectively. In this study, we found one novel co-located QTL associated with GL and TKW in 2DL, QGl.haaf-2DL.2/QTkw.haaf-2DL.2, which could explain 13.6–19.8% and 9.8–10.7% phenotypic variance, respectively. Genetic regions and linked markers of these stable QTL will help to further refine mapping of the corresponding loci and marker-assisted selection (MAS) breeding for wheat grain yield potential improvement.

Detection of grain yield QTLs in the durum population Lahn/Cham1 tested in contrasting environments

Durum wheat (Triticum turgidum L. var durum) is tetraploid wheat (AABB); it is the main source of semolina and other pasta products. Grain yield in wheat is quantitatively inherited and influenced by the environment. The genetic map construction constitutes the essential step in identifying quantitative trait loci (QTLs) linked to complex traits, such as grain yield. The study aimed to construct a genetic linkage map of two parents that are widely grown durum cultivars (Lahn and Cham1) in the Mediterranean basin, which is characterized by varying climate changes. The genetic linkage map of Lahn/Cham1 population consisted of 112 recombinant inbred lines (RILs) and was used to determine QTLs linked to the grain yield in 11 contrasting environments (favorable, cold, dry, and hot). Simple sequence repeat (SSR) molecular markers were used to construct an anchor map, which was later enriched with single nucleotide polymorphisms (SNPs). The map was constructed with 247 SSRs and enriched with 1425 SNPs. The map covered 6122.22 cM. One hundred and twenty-six QTLs were detected on different chromosomes. Chromosomes 2A and 4B harbored the most significant grain yield QTLs. Furthermore, by comparison with several wheat mapping populations, all the A and B chromosomes of Lahn/Cham1 QTLs contributed to grain yield. The results showed that the detected QTLs can be used as a potential candidate for marker-assisted selection in durum breeding programs.

QTL mapping of agronomic traits in wheat using the UK Avalon × Cadenza reference mapping population grown in Kazakhstan

Background

The success of wheat production is largely dependent on local breeding projects that focus on the development of high-yielding cultivars with the use of novel molecular tools. One strategy for improving wheat productivity involves the deployment of diverse germplasms with a high potential yield. An important factor for achieving success involves the dissection of quantitative trait loci (QTLs) for complex agronomic traits, such as grain yield components, in targeted environments for wheat growth.

Methods

In this study, we tested the United Kingdom (UK) spring set of the doubled haploid (DH) reference population derived from the cross between two British cultivars, Avalon (winter wheat) and Cadenza (spring wheat), in the Northern, Central, and Southern regions (Karabalyk, Karaganda, Kyzylorda) of Kazakhstan over three years (2013–2015). The DH population has previously been genotyped by UK scientists using 3647 polymorphic DNA markers. The list of tested traits includes the heading time, seed maturation time, plant height, spike length, productive tillering, number of kernels per spike, number of kernels per meter, thousand kernel weight, and yield per square meter. Windows QTL Cartographer was applied for QTL mapping using the composite interval mapping method.

Results

In total, 83 out of 232 QTLs were identified as stable QTLs from at least two environments. A literature survey suggests that 40 QTLs had previously been reported elsewhere, indicating that this study identified 43 QTLs that are presumably novel marker-trait associations (MTA) for these environments. Hence, the phenotyping of the DH population in new environments led to the discovery of novel MTAs. The identified SNP markers associated with agronomic traits in the DH population could be successfully used in local Kazakh breeding projects for the improvement of wheat productivity.

Genome-Wide Association Studies Detect Multiple QTLs for Productivity in Mesoamerican Diversity Panel of Common Bean Under Drought Stress

Drought stress is an important abiotic factor limiting common bean yield, with great impact on the production worldwide. Understanding the genetic basis regulating beans' yield and seed weight (SW) is a fundamental prerequisite for the development of superior cultivars. The main objectives of this work were to conduct genome-wide marker discovery by genotyping a Mesoamerican panel of common bean germplasm, containing cultivated and landrace accessions of broad origin, followed by the identification of genomic regions associated with productivity under two water regimes using different genome-wide association study (GWAS) approaches. A total of 11,870 markers were genotyped for the 339 genotypes, of which 3,213 were SilicoDArT and 8,657 SNPs derived from DArT and CaptureSeq. The estimated linkage disequilibrium extension, corrected for structure and relatedness (r ² _sv ), was 98.63 and 124.18 kb for landraces and breeding lines, respectively. Germplasm was structured into landraces and lines/cultivars. We carried out GWASs for 100-SW and yield in field environments with and without water stress for 3 consecutive years, using single-, segment-, and gene-based models. Higher number of associations at high stringency was identified for the SW trait under irrigation, totaling ∼185 QTLs for both single- and segment-based, whereas gene-based GWASs showed ∼220 genomic regions containing ∼650 genes. For SW under drought, 18 QTLs were identified for single- and segment-based and 35 genes by gene-based GWASs. For yield, under irrigation, 25 associations were identified, whereas under drought the total was 10 using both approaches. In addition to the consistent associations detected across experiments, these GWAS approaches provided important complementary QTL information (∼221 QTLs; 650 genes; r ² from 0.01% to 32%). Several QTLs were mined within or near candidate genes playing significant role in productivity, providing better understanding of the genetic mechanisms underlying these traits and making available molecular tools to be used in marker-assisted breeding. The findings also allowed the identification of genetic material (germplasm) with better yield performance under drought, promising to a common bean breeding program. Finally, the availability of this highly diverse Mesoamerican panel is of great scientific value for the analysis of any relevant traits in common bean.

Major genomic regions responsible for wheat yield and its components as revealed by meta-QTL and genotype-phenotype association analyses

MAIN CONCLUSION

Meta-QTL (MQTL) analysis was done for yield-related traits in wheat. Candidate genes were identified within the refined MQTL and further validated by genotype-phenotype association analysis. Extensive studies have been undertaken on quantitative trait locus/loci (QTL) for wheat yield and its component traits. This study conducted a meta-analysis of 381 QTL related to wheat yield under various environments, including irrigated, drought- and/or heat-stressed conditions. Markers flanking meta-QTL (MQTL) were mapped on the wheat reference genome for their physical positions. Putative candidate genes were examined for MQTL with a physical interval of less than 20 Mbp. A total of 86 MQTL were identified as responsible for yield, of which 34 were for irrigated environments, 39 for drought-stressed environments, 36 for heat-stressed environments, and 23 for both drought- and heat-stressed environments. The high-confidence genes within the physical positions of the MQTL flanking markers were screened in the reference genome RefSeq V1.0, which identified 210 putative candidate genes. The phenotypic data for 14 contrasting genotypes with either high or low yield performance-according to the Australian National Variety Trials-were associated with their genotypic data obtained through ddRAD sequencing, which validated 18 genes or gene clusters associated with MQTL that had important roles for wheat yield. The detected and refined MQTL and candidate genes will be useful for marker-assisted selection of high yield in wheat breeding.

Molecular Mapping and Genomics of Grain Yield in Durum Wheat: A Review

Durum wheat is the most relevant cereal for the whole of Mediterranean agriculture, due to its intrinsic adaptation to dryland and semi-arid environments and to its strong historical cultivation tradition. It is not only relevant for the primary production sector, but also for the food industry chains associated with it. In Mediterranean environments, wheat is mostly grown under rainfed conditions and the crop is frequently exposed to environmental stresses, with high temperatures and water scarcity especially during the grain filling period. For these reasons, and due to recurrent disease epidemics, Mediterranean wheat productivity often remains under potential levels. Many studies, using both linkage analysis (LA) and a genome-wide association study (GWAS), have identified the genomic regions controlling the grain yield and the associated markers that can be used for marker-assisted selection (MAS) programs. Here, we have summarized all the current studies identifying quantitative trait loci (QTLs) and/or candidate genes involved in the main traits linked to grain yield: kernel weight, number of kernels per spike and number of spikes per unit area.

High-Resolution Genome-wide Association Study Identifies Genomic Regions and Candidate Genes for Important Agronomic Traits in Wheat

Wheat (Triticum aestivum) is a major staple food crop worldwide. Genetic dissection of important agronomic traits is essential for continuous improvement of wheat yield to meet the demand of the world's growing population. We conducted a large-scale genome-wide association study (GWAS) using a panel of 768 wheat cultivars that were genotyped with 327 609 single-nucleotide polymorphisms generated by genotyping-by-sequencing and detected 395 quantitative trait loci (QTLs) for 12 traits under 7 environments. Among them, 273 QTLs were delimited to ≤1.0-Mb intervals and 7 of them are either known genes (Rht-D, Vrn-B1, and Vrn-D1) that have been cloned or known QTLs (TaGA2ox8, APO1, TaSus1-7B, and Rht12) that were previously mapped. Eight putative candidate genes were identified for three QTLs that enhance spike seed setting and grain size using gene expression data and were validated in three bi-parental populations. Protein sequence analysis identified 33 putative wheat orthologs that have high identity with rice genes in QTLs affecting similar traits. Large r² values for additive effects observed among the QTLs for most traits indicated that the phenotypes of these identified QTLs were highly predictable. Results from this study demonstrated that significantly increasing GWAS population size and marker density greatly improves detection and identification of candidate genes underlying a QTL, solidifying the foundation for large-scale QTL fine mapping, candidate gene validation, and developing functional markers for genomics-based breeding in wheat.

Recent Progress in Germplasm Evaluation and Gene Mapping to Enable Breeding of Drought-Tolerant Wheat

There is a need to increase wheat productivity to meet the food demands of the ever-growing human population. However, accelerated development of high yielding varieties is hindered by drought, which is worsening due to climate change. In this context, germplasm diversity is central to the development of drought-tolerant wheat. Extensive collections of these genetic resources are conserved in national and international genebanks. In addition to phenotypic assessments, the use of advanced molecular techniques (e.g., genotype by sequencing) to identify quantitative trait loci (QTLs) for drought tolerance related traits is useful for genome- and marker-assisted selection based approaches. Therefore, to assist wheat breeders at a critical time, we searched the recent peer-reviewed literature (2011-current), first, to identify wheat germplasm observed to be useful genetic sources for drought tolerance, and second, to report QTLs associated with drought tolerance. Though many breeders limit the parents used in breeding programs to a familiar core collection, the results of this review show that larger germplasm collections have been sources of useful genes for drought tolerance in wheat. The review also demonstrates that QTLs for drought tolerance in wheat are associated with diverse physio-morphological traits, at different growth stages. Here, we also briefly discuss the potential of genome engineering/editing to improve drought tolerance in wheat. The use of CRISPR-Cas9 and other gene-editing technologies can be used to fine-tune the expression of genes controlling drought adaptive traits, while high throughput phenotyping (HTP) techniques can potentially accelerate the selection process. These efforts are empowered by wheat researcher consortia.

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.