Discovering consensus genomic regions in wheat for root-related traits by QTL meta-analysis

Durum wheat (Triticum turgidum L. var. durum) root system response to drought and salt stresses and genetic characterization for root-related traits

Abiotic stresses such as drought and salt are significant threats to crop productivity. The root system adaptation and tolerance to abiotic stresses are regulated by many biochemical reactions, which create a complex and multigenic response. The present study aims to evaluate the diversity of root responses to cyclic abiotic stress in three modern durum wheat varieties and one hydric stress-tolerant landrace in a pot experiment from seedling to more advanced plant development stages. The genotypes responded to abiotic stress during the whole experiment very differently, and at the end of the experiment, nine out of the 13 traits for the landrace J. Khetifa were significantly higher than other genotypes. Moreover, single sequence repeat (SSR) genetic analysis revealed high polymorphism among the genotypes screened and interesting private alleles associated with root system architecture traits. We propose that the markers used in this study could be a resource as material for durum wheat breeding programs based on marker-assisted selection to increase the vegetal material with high drought and salt stress tolerance and to identify candidates with strong early vigor and efficient root systems. This study provides appropriate genetic materials for marker-assisted breeding programs as well as a basic study for the genetic diversity of root traits of durum wheat crops.

Genome-wide association study of drought tolerance in wheat (Triticum aestivum L.) identifies SNP markers and candidate genes

Drought stress poses a severe threat to global wheat production, necessitating an in-depth exploration of the genetic basis for drought tolerance associated traits. This study employed a 90 K SNP array to conduct a genome-wide association analysis, unravelling genetic determinants of key traits related to drought tolerance in wheat, namely plant height, root length, and root and shoot dry weight. Using the mixed linear model (MLM) method on 125 wheat accessions subjected to both well-watered and drought stress treatments, we identified 53 SNPs significantly associated with stress susceptibility (SSI) and tolerance indices (STI) for the targeted traits. Notably, chromosomes 2A and 3B stood out with ten and nine associated markers, respectively. Across 17 chromosomes, 44 unique candidate genes were pinpointed, predominantly located on the distal ends of 1A, 1B, 1D, 2A, 3A, 3B, 4A, 6A, 6B, 7A, 7B, and 7D chromosomes. These genes, implicated in diverse functions related to plant growth, development, and stress responses, offer a rich resource for future investigation. A clustering pattern emerged, notably with seven genes associated with SSI for plant height and four genes linked to both STI of plant height and shoot dry weight, converging on specific regions of chromosome arms of 2AS and 3BL. Additionally, shared genes encoding polygalacturonase, auxilin-related protein 1, peptide deformylase, and receptor-like kinase underscored the interconnectedness between plant height and shoot dry weight. In conclusion, our findings provide insights into the molecular mechanisms governing wheat drought tolerance, identifying promising genomic loci for further exploration and crop improvement strategies.

Quantitative trait loci mapping for survival of virus infection and virus levels in honey bees

Israeli acute paralysis virus (IAPV) is a highly virulent, Varroa-vectored virus that is of global concern for honey bee health. Little is known about the genetic basis of honey bees to withstand infection with IAPV or other viruses. We set up and analyzed a backcross between preselected honey bee colonies of low and high IAPV susceptibility to identify quantitative trait loci (QTL) associated with IAPV susceptibility. Experimentally inoculated adult worker bees were surveyed for survival and selectively sampled for QTL analysis based on SNPs identified by whole-genome resequencing and composite interval mapping. Additionally, natural titers of other viruses were quantified in the abdomen of these workers via qPCR and also used for QTL mapping. In addition to the full dataset, we analyzed distinct subpopulations of susceptible and non-susceptible workers separately. These subpopulations are distinguished by a single, suggestive QTL on chromosome 6, but we identified numerous other QTL for different abdominal virus titers, particularly in the subpopulation that was not susceptible to IAPV. The pronounced QTL differences between the susceptible and non-susceptible subpopulations indicate either an interaction between IAPV infection and the bees' interaction with other viruses or heterogeneity among workers of a single cohort that manifests itself as IAPV susceptibility and results in distinct subgroups that differ in their interaction with other viruses. Furthermore, our results indicate that low susceptibility of honey bees to viruses can be caused by both, virus tolerance and virus resistance. QTL were partially overlapping among different viruses, indicating a mixture of shared and specific processes that control viruses. Some functional candidate genes are located in the QTL intervals, but their genomic co-localization with numerous genes of unknown function delegates any definite characterization of the underlying molecular mechanisms to future studies.

Integration of genome-wide association study, linkage analysis, and population transcriptome analysis to reveal the TaFMO1-5B modulating seminal root growth in bread wheat

Bread wheat, one of the keystone crops for global food security, is challenged by climate change and resource shortage. The root system plays a vital role in water and nutrient absorption, making it essential for meeting the growing global demand. Here, using an association-mapping population composed of 406 accessions, we identified QTrl.Rs-5B modulating seminal root development with a genome-wide association study and validated its genetic effects with two F5 segregation populations. Transcriptome-wide association study prioritized TaFMO1-5B, a gene encoding the flavin-containing monooxygenases, as the causal gene for QTrl.Rs-5B, whose expression levels correlate negatively with the phenotyping variations among our population. The lines silenced for TaFMO1-5B consistently showed significantly larger seminal roots in different genetic backgrounds. Additionally, the agriculture traits measured in multiple environments showed that QTrl.Rs-5B also affects yield component traits and plant architecture-related traits, and its favorable haplotype modulates these traits toward that of modern cultivars, suggesting the application potential of QTrl.Rs-5B for wheat breeding. Consistently, the frequency of the favorable haplotype of QTrl.Rs-5B increased with habitat expansion and breeding improvement of bread wheat. In conclusion, our findings identified and demonstrated the effects of QTrl.Rs-5B on seminal root development and illustrated that it is a valuable genetic locus for wheat root improvement.

Meta-QTL analysis in wheat: progress, challenges and opportunities

Wheat, an important cereal crop globally, faces major challenges due to increasing global population and changing climates. The production and productivity are challenged by several biotic and abiotic stresses. There is also a pressing demand to enhance grain yield and quality/nutrition to ensure global food and nutritional security. To address these multifaceted concerns, researchers have conducted numerous meta-QTL (MQTL) studies in wheat, resulting in the identification of candidate genes that govern these complex quantitative traits. MQTL analysis has successfully unraveled the complex genetic architecture of polygenic quantitative traits in wheat. Candidate genes associated with stress adaptation have been pinpointed for abiotic and biotic traits, facilitating targeted breeding efforts to enhance stress tolerance. Furthermore, high-confidence candidate genes (CGs) and flanking markers to MQTLs will help in marker-assisted breeding programs aimed at enhancing stress tolerance, yield, quality and nutrition. Functional analysis of these CGs can enhance our understanding of intricate trait-related genetics. The discovery of orthologous MQTLs shared between wheat and other crops sheds light on common evolutionary pathways governing these traits. Breeders can leverage the most promising MQTLs and CGs associated with multiple traits to develop superior next-generation wheat cultivars with improved trait performance. This review provides a comprehensive overview of MQTL analysis in wheat, highlighting progress, challenges, validation methods and future opportunities in wheat genetics and breeding, contributing to global food security and sustainable agriculture.

Genome-wide linkage mapping of root system architecture-related traits in common wheat (Triticum aestivum L.)

Identifying loci for root system architecture (RSA) traits and developing available markers are crucial for wheat breeding. In this study, RSA-related traits, including total root length (TRL), total root area (TRA), and number of root tips (NRT), were evaluated in the Doumai/Shi4185 recombinant inbred line (RIL) population under hydroponics. In addition, both the RILs and parents were genotyped using the wheat 90K single-nucleotide polymorphism (SNP) array. In total, two quantitative trait loci (QTLs) each for TRL (QTRL.caas-4A.1 and QTRL.caas-4A.2), TRA (QTRA.caas-4A and QTRA.caas-4D), and NRT (QNRT.caas-5B and QNRT.caas-5D) were identified and each explaining 5.94%-9.47%, 6.85%-7.10%, and 5.91%-10.16% phenotypic variances, respectively. Among these, QTRL.caas-4A.1 and QTRA.caas-4A overlapped with previous reports, while QTRL.caas-4A.2, QTRA.caas-4D, QNRT.caas-5B, and QNRT.caas-5D were novel. The favorable alleles of QTRL.caas-4A.1, QTRA.caas-4A, and QTRA.caas-5B were contributed by Doumai, whereas the favorable alleles of QTRL.caas-4A.2, QTRA.caas-4D, and QTRA.caas-5D originated from Shi 4185. Additionally, two competitive allele-specific PCR (KASP) markers, Kasp_4A_RL (QTRA.caas-4A) and Kasp_5D_RT (QNRT.caas-5D), were developed and validated in 165 wheat accessions. This study provides new loci and available KASP markers, accelerating wheat breeding for higher yields.

Genomic Regions Associated with Resistance to Three Rusts in CIMMYT Wheat Line "Mokue#1"

Understanding the genetic basis of rust resistance in elite CIMMYT wheat germplasm enhances breeding and deployment of durable resistance globally. "Mokue#1", released in 2023 in Pakistan as TARNAB Gandum-1, has exhibited high levels of resistance to stripe rust, leaf rust, and stem rust pathotypes present at multiple environments in Mexico and Kenya at different times. To determine the genetic basis of resistance, a F5 recombinant inbred line (RIL) mapping population consisting of 261 lines was developed and phenotyped for multiple years at field sites in Mexico and Kenya under the conditions of artificially created rust epidemics. DArTSeq genotyping was performed, and a linkage map was constructed using 7892 informative polymorphic markers. Composite interval mapping identified three significant and consistent loci contributed by Mokue: QLrYr.cim-1BL and QLrYr.cim-2AS on chromosome 1BL and 2AS, respectively associated with stripe rust and leaf rust resistance, and QLrSr.cim-2DS on chromosome 2DS for leaf rust and stem rust resistance. The QTL on 1BL was confirmed to be the Lr46/Yr29 locus, whereas the QTL on 2AS represented the Yr17/Lr37 region on the 2NS/2AS translocation. The QTL on 2DS was a unique locus conferring leaf rust resistance in Mexico and stem rust resistance in Kenya. In addition to these pleiotropic loci, four minor QTLs were also identified on chromosomes 2DL and 6BS associated with stripe rust, and 3AL and 6AS for stem rust, respectively, using the Kenya disease severity data. Significant decreases in disease severities were also demonstrated due to additive effects of QTLs when present in combinations.

Genetic dissection of root architectural plasticity and identification of candidate loci in response to drought stress in bread wheat

BACKGROUND

The frequency of droughts has dramatically increased over the last 50 years, causing yield declines in cereals, including wheat. Crop varieties with efficient root systems show great potential for plant adaptation to drought stress, however; genetic control of root systems in wheat under field conditions is not yet well understood.

RESULTS

Natural variation in root architecture plasticity (phenotypic alteration due to changing environments) was dissected under field-based control (well-irrigated) and drought (rain-out shelter) conditions by a genome-wide association study using 200 diverse wheat cultivars. Our results revealed root architecture and plasticity traits were differentially responded to drought stress. A total of 25 marker-trait associations (MTAs) underlying natural variations in root architectural plasticity were identified in response to drought stress. They were abundantly distributed on chromosomes 1 A, 1B, 2 A, 2B, 3 A, 3B, 4B, 5 A, 5D, 7 A and 7B of the wheat genome. Gene ontology annotation showed that many candidate genes associated with plasticity were involved in water-transport and water channel activity, cellular response to water deprivation, scavenging reactive oxygen species, root growth and development and hormone-activated signaling pathway-transmembrane transport, indicating their response to drought stress. Further, in silico transcript abundance analysis demonstrated that root plasticity-associated candidate genes were highly expressed in roots across different root growth stages and under drought treatments.

CONCLUSION

Our results suggest that root phenotypic plasticity is highly quantitative, and the corresponding loci are associated with drought stress that may provide novel ways to enable root trait breeding.

Comprehensive meta-analysis of QTL and gene expression studies identify candidate genes associated with Aspergillus flavus resistance in maize

Aflatoxin (AF) contamination, caused by Aspergillus flavus, compromises the food safety and marketability of commodities, such as maize, cotton, peanuts, and tree nuts. Multigenic inheritance of AF resistance impedes conventional introgression of resistance traits into high-yielding commercial maize varieties. Several AF resistance-associated quantitative trait loci (QTLs) and markers have been reported from multiple biparental mapping and genome-wide association studies (GWAS) in maize. However, QTLs with large confidence intervals (CI) explaining inconsistent phenotypic variance limit their use in marker-assisted selection. Meta-analysis of published QTLs can identify significant meta-QTLs (MQTLs) with a narrower CI for reliable identification of genes and linked markers for AF resistance. Using 276 out of 356 reported QTLs controlling resistance to A. flavus infection and AF contamination in maize, we identified 58 MQTLs on all 10 chromosomes with a 66.5% reduction in the average CI. Similarly, a meta-analysis of maize genes differentially expressed in response to (a)biotic stresses from the to-date published literature identified 591 genes putatively responding to only A. flavus infection, of which 14 were significantly differentially expressed (-1.0 ≤ Log2Fc ≥ 1.0; p ≤ 0.05). Eight MQTLs were validated by their colocalization with 14 A. flavus resistance-associated SNPs identified from GWAS in maize. A total of 15 genes were physically close between the MQTL intervals and SNPs. Assessment of 12 MQTL-linked SSR markers identified three markers that could discriminate 14 and eight cultivars with resistance and susceptible responses, respectively. A comprehensive meta-analysis of QTLs and differentially expressed genes led to the identification of genes and makers for their potential application in marker-assisted breeding of A. flavus-resistant maize varieties.

Physical Mapping of QTLs for Root Traits in a Population of Recombinant Inbred Lines of Hexaploid Wheat

Root architecture is key in determining how effective plants are at intercepting and absorbing nutrients and water. Previously, the wheat (Triticum aestivum) cultivars Spica and Maringa were shown to have contrasting root morphologies. These cultivars were crossed to generate an F_6:1 population of recombinant inbred lines (RILs) which was genotyped using a 90 K single nucleotide polymorphisms (SNP) chip. A total of 227 recombinant inbred lines (RILs) were grown in soil for 21 days in replicated trials under controlled conditions. At harvest, the plants were scored for seven root traits and two shoot traits. An average of 7.5 quantitative trait loci (QTL) were associated with each trait and, for each of these, physical locations of the flanking markers were identified using the Chinese Spring reference genome. We also compiled a list of genes from wheat and other monocotyledons that have previously been associated with root growth and morphology to determine their physical locations on the Chinese Spring reference genome. This allowed us to determine whether the QTL discovered in our study encompassed genes previously associated with root morphology in wheat or other monocotyledons. Furthermore, it allowed us to establish if the QTL were co-located with the QTL identified from previously published studies. The parental lines together with the genetic markers generated here will enable specific root traits to be introgressed into elite wheat lines. Moreover, the comprehensive list of genes associated with root development, and their physical locations, will be a useful resource for researchers investigating the genetics of root morphology in cereals.

Transcriptome Analysis of Roots from Wheat (Triticum aestivum L.) Varieties in Response to Drought Stress

Under climate change, drought is one of the most limiting factors that influences wheat (Triticum aestivum L.) production. Exploring stress-related genes is vital for wheat breeding. To identify genes related to the drought tolerance response, two common wheat cultivars, Zhengmai 366 (ZM366) and Chuanmai 42 (CM42), were selected based on their obvious difference in root length under 15% PEG-6000 treatment. The root length of the ZM366 cultivar was significantly longer than that of CM42. Stress-related genes were identified by RNA-seq in samples treated with 15% PEG-6000 for 7 days. In total, 11,083 differentially expressed genes (DEGs) and numerous single nucleotide polymorphisms (SNPs) and insertions/deletions (InDels) were identified. GO enrichment analysis revealed that the upregulated genes were mainly related to the response to water, acidic chemicals, oxygen-containing compounds, inorganic substances, and abiotic stimuli. Among the DEGs, the expression levels of 16 genes in ZM366 were higher than those in CM42 after the 15% PEG-6000 treatment based on RT-qPCR. Furthermore, EMS-induced mutants in Kronos (T. turgidum L.) of 4 representative DEGs possessed longer roots than the WT after the 15% PEG-6000 treatment. Altogether, the drought stress genes identified in this study represent useful gene resources for wheat breeding.

Genome-Wide Meta-Analysis of QTLs Associated with Root Traits and Implications for Maize Breeding

Root system architecture (RSA), also known as root morphology, is critical in plant acquisition of soil resources, plant growth, and yield formation. Many QTLs associated with RSA or root traits in maize have been identified using several bi-parental populations, particularly in response to various environmental factors. In the present study, a meta-analysis of QTLs associated with root traits was performed in maize using 917 QTLs retrieved from 43 mapping studies published from 1998 to 2020. A total of 631 QTLs were projected onto a consensus map involving 19,714 markers, which led to the prediction of 68 meta-QTLs (MQTLs). Among these 68 MQTLs, 36 MQTLs were validated with the marker-trait associations available from previous genome-wide association studies for root traits. The use of comparative genomics approaches revealed several gene models conserved among the maize, sorghum, and rice genomes. Among the conserved genomic regions, the ortho-MQTL analysis uncovered 20 maize MQTLs syntenic to 27 rice MQTLs for root traits. Functional analysis of some high-confidence MQTL regions revealed 442 gene models, which were then subjected to in silico expression analysis, yielding 235 gene models with significant expression in various tissues. Furthermore, 16 known genes viz., DXS2, PHT, RTP1, TUA4, YUC3, YUC6, RTCS1, NSA1, EIN2, NHX1, CPPS4, BIGE1, RCP1, SKUS13, YUC5, and AW330564 associated with various root traits were present within or near the MQTL regions. These results could aid in QTL cloning and pyramiding in developing new maize varieties with specific root architecture for proper plant growth and development under optimum and abiotic stress conditions.

Chromosome groups 5, 6 and 7 harbor major quantitative trait loci controlling root traits in bread wheat (Triticum aestivum L.)

Identifying genomic regions for root traits in bread wheat can help breeders develop climate-resilient and high-yielding wheat varieties with desirable root traits. This study used the recombinant inbred line (RIL) population of Synthetic W7984 × Opata M85 to identify quantitative trait loci (QTL) for different root traits such as rooting depth (RD), root dry mass (RM), total root length (RL), root diameter (Rdia) and root surface areas (RSA1 for coarse roots and RSA2 for fine roots) under controlled conditions in a semi-hydroponic system. We detected 14 QTL for eight root traits on nine wheat chromosomes; we discovered three QTL each for RD and RSA1, two QTL each for RM and RSA2, and one QTL each for RL, Rdia, specific root length and nodal root number per plant. The detected QTL were concentrated on chromosome groups 5, 6 and 7. The QTL for shallow RD (Q.rd.uwa.7BL: Xbarc50) and high RM (Q.rm.uwa.6AS: Xgwm334) were validated in two independent F₂ populations of Synthetic W7984 × Chara and Opata M85 × Cascade, respectively. Genotypes containing negative alleles for Q.rd.uwa.7BL had 52% shallower RD than other Synthetic W7984 × Chara population lines. Genotypes with the positive alleles for Q.rm.uwa.6AS had 31.58% higher RM than other Opata M85 × Cascade population lines. Further, we identified 21 putative candidate genes for RD (Q.rd.uwa.7BL) and 13 for RM (Q.rm.uwa.6AS); TraesCS6A01G020400, TraesCS6A01G024400 and TraesCS6A01G021000 identified from Q.rm.uwa.6AS, and TraesCS7B01G404000, TraesCS7B01G254900 and TraesCS7B01G446200 identified from Q.rd.uwa.7BL encoded important proteins for root traits. We found germin-like protein encoding genes in both Q.rd.uwa.7BL and Q.rm.uwa.6AS regions. These genes may play an important role in RM and RD improvement. The identified QTL, especially the validated QTL and putative candidate genes are valuable genetic resources for future root trait improvement in wheat.

Phenotypic and Genotypic Diversity of Roots Response to Salt in Durum Wheat Seedlings

Soil salinity is a serious threat to food production now and in the near future. In this study, the root system of six durum wheat genotypes, including one highly salt-tolerant (J. Khetifa) used as a check genotype, was evaluated, by a high-throughput phenotyping system, under control and salt conditions at the seedling stage. Genotyping was performed using 11 SSR markers closely linked with genome regions associated with root traits. Based on phenotypic cluster analysis, genotypes were grouped differently under control and salt conditions. Under control conditions, genotypes were clustered mainly due to a root angle, while under salt stress, genotypes were grouped according to their capacity to maintain higher roots length, volume, and surface area, as J. Khetifa, Sebatel, and Azeghar. SSR analysis identified a total of 42 alleles, with an average of about three alleles per marker. Moreover, quite a high number of Private alleles in total, 18 were obtained. The UPGMA phenogram of the Nei (1972) genetic distance clusters for 11 SSR markers and all phenotypic data under control conditions discriminate genotypes almost into the same groups. The study revealed as the combination of high-throughput systems for phenotyping with SSR markers for genotyping it's a useful tool to provide important data for the selection of suitable parental lines for salt-tolerance breeding. Nevertheless, the narrow root angle, which is an important trait in drought tolerance, is not a good indicator of salt tolerance. Instated for salt tolerance is more important the amount of roots.

A 'wiring diagram' for source strength traits impacting wheat yield potential

Source traits are currently of great interest for the enhancement of yield potential; for example, much effort is being expended to find ways of modifying photosynthesis. However, photosynthesis is but one component of crop regulation, so sink activities and the coordination of diverse processes throughout the crop must be considered in an integrated, systems approach. A set of 'wiring diagrams' has been devised as a visual tool to integrate the interactions of component processes at different stages of wheat development. They enable the roles of chloroplast, leaf, and whole-canopy processes to be seen in the context of sink development and crop growth as a whole. In this review, we dissect source traits both anatomically (foliar and non-foliar) and temporally (pre- and post-anthesis), and consider the evidence for their regulation at local and whole-plant/crop levels. We consider how the formation of a canopy creates challenges (self-occlusion) and opportunities (dynamic photosynthesis) for components of photosynthesis. Lastly, we discuss the regulation of source activity by feedback regulation. The review is written in the framework of the wiring diagrams which, as integrated descriptors of traits underpinning grain yield, are designed to provide a potential workspace for breeders and other crop scientists that, along with high-throughput and precision phenotyping data, genetics, and bioinformatics, will help build future dynamic models of trait and gene interactions to achieve yield gains in wheat and other field crops.

Identification of quantitative trait loci (QTL) and meta-QTL analysis for kernel size-related traits in wheat (Triticum aestivum L.)

BACKGROUND

Kernel size-related traits, including kernel length (KL), kernel width (KW), kernel diameter ratio (KDR) and kernel thickness (KT), are critical determinants for wheat kernel weight and yield and highly governed by a type of quantitative genetic basis. Genome-wide identification of major and stable quantitative trait loci (QTLs) and functional genes are urgently required for genetic improvement in wheat kernel yield. A hexaploid wheat population consisting of 120 recombinant inbred lines was developed to identify QTLs for kernel size-related traits under different water environments. The meta-analysis and transcriptome evaluation were further integrated to identify major genomic regions and putative candidate genes.

RESULTS

The analysis of variance (ANOVA) revealed more significant genotypic effects for kernel size-related traits, indicating the moderate to high heritability of 0.61-0.89. Thirty-two QTLs for kernel size-related traits were identified, explaining 3.06%-14.2% of the phenotypic variation. Eleven stable QTLs were detected in more than three water environments. The 1103 original QTLs from the 34 previous studies and the present study were employed for the MQTL analysis and refined into 58 MQTLs. The average confidence interval of the MQTLs was 3.26-fold less than that of the original QTLs. The 1864 putative candidate genes were mined within the regions of 12 core MQTLs, where 70 candidate genes were highly expressed in spikes and kernels by comprehensive analysis of wheat transcriptome data. They were involved in various metabolic pathways, such as carbon fixation in photosynthetic organisms, carbon metabolism, mRNA surveillance pathway, RNA transport and biosynthesis of secondary metabolites.

CONCLUSIONS

Major genomic regions and putative candidate genes for kernel size-related traits in wheat have been revealed by an integrative strategy with QTL linkage mapping, meta-analysis and transcriptomic assessment. The findings provide a novel insight into understanding the genetic determinants of kernel size-related traits and will be useful for the marker-assisted selection of high yield in wheat breeding.

Genetic structure and molecular mechanism underlying the stalk lodging traits in maize (Zea mays L.)

Stalk lodging seriously affects yield and quality of crops, and it can be caused by several factors, such as environments, developmental stages, and internal chemical components of plant stalks. Breeding of stalk lodging-resistant varieties is thus an important task for maize breeders. To better understand the genetic basis underlying stalk lodging resistance, several methods such as quantitative trait locus (QTL) mapping and genome-wide association study (GWAS) have been used to mine potential gene resources. Based on different types of genetic populations and mapping methods, many significant loci associated with stalk lodging resistance have been identified so far. However, few work has been performed to compare and integrate these reported genetic loci. In this study, we first collected hundreds of QTLs and quantitative trait nucleotides (QTNs) related to stalk lodging traits in maize. Then we mapped and integrated the QTLs and QTNs in maize genome to identify overlapped hotspot regions. Based on the genomic confidence intervals harboring these overlapped hotspot regions, we predicted candidate genes related to stalk lodging traits. Meanwhile, we mapped reported genes to these hotspot regions. Finally, we constructed molecular regulatory networks underlying stalk lodging resistance in maize. Collectively, this study provides not only useful genetic loci for deeply exploring molecular mechanisms of stalk lodging resistance traits, but also potential candidate genes and targeted strategies for improving stalk lodging resistance to increase crop yields in future.

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.

Responses of root system architecture to water stress at multiple levels: A meta-analysis of trials under controlled conditions

Plants are exposed to increasingly severe drought events and roots play vital roles in maintaining plant survival, growth, and reproduction. A large body of literature has investigated the adaptive responses of root traits in various plants to water stress and these studies have been reviewed in certain groups of plant species at a certain scale. Nevertheless, these responses have not been synthesized at multiple levels. This paper screened over 2000 literatures for studies of typical root traits including root growth angle, root depth, root length, root diameter, root dry weight, root-to-shoot ratio, root hair length and density and integrates their drought responses at genetic and morphological scales. The genes, quantitative trait loci (QTLs) and hormones that are involved in the regulation of drought response of the root traits were summarized. We then statistically analyzed the drought responses of root traits and discussed the underlying mechanisms. Moreover, we highlighted the drought response of 1-D and 2-D root length density (RLD) distribution in the soil profile. This paper will provide a framework for an integrated understanding of root adaptive responses to water deficit at multiple scales and such insights may provide a basis for selection and breeding of drought tolerant crop lines.

A meta-quantitative trait loci analysis identified consensus genomic regions and candidate genes associated with grain yield in rice

Improving grain yield potential in rice is an important step toward addressing global food security challenges. The meta-QTL analysis offers stable and robust QTLs irrespective of the genetic background of mapping populations and phenotype environment and effectively narrows confidence intervals (CI) for candidate gene (CG) mining and marker-assisted selection improvement. To achieve these aims, a comprehensive bibliographic search for grain yield traits (spikelet fertility, number of grains per panicle, panicles number per plant, and 1000-grain weight) QTLs was conducted, and 462 QTLs were retrieved from 47 independent QTL research published between 2002 and 2022. QTL projection was performed using a reference map with a cumulative length of 2,945.67 cM, and MQTL analysis was conducted on 313 QTLs. Consequently, a total of 62 MQTLs were identified with reduced mean CI (up to 3.40 fold) compared to the mean CI of original QTLs. However, 10 of these MQTLs harbored at least six of the initial QTLs from diverse genetic backgrounds and environments and were considered the most stable and robust MQTLs. Also, MQTLs were compared with GWAS studies and resulted in the identification of 16 common significant loci modulating the evaluated traits. Gene annotation, gene ontology (GO) enrichment, and RNA-seq analyses of chromosome regions of the stable MQTLs detected 52 potential CGs including those that have been cloned in previous studies. These genes encode proteins known to be involved in regulating grain yield including cytochrome P450, zinc fingers, MADs-box, AP2/ERF domain, F-box, ubiquitin ligase domain protein, homeobox domain, DEAD-box ATP domain, and U-box domain. This study provides the framework for molecular dissection of grain yield in rice. Moreover, the MQTLs and CGs identified could be useful for fine mapping, gene cloning, and marker-assisted selection to improve rice productivity.

Genome-wide association, RNA-seq and iTRAQ analyses identify candidate genes controlling radicle length of wheat

The radicle, present in the embryo of a seed, is the first root to emerge at germination, and its rapid growth is essential for establishment and survival of the seedling. However, there are few studies on the critical mechanisms underlying radicle and then radicle length in wheat seedlings, despite its importance as a food crop throughout the world. In the present study, 196 wheat accessions from the Huanghuai Wheat Region were screened to measure radicle length under 4 hydroponic culture environments over 3 years. Different expression genes and proteins (DEGs/DEPs) between accessions with extremely long [Yunong 949 (WRL1), Zhongyu 9,302 (WRL2)] and short roots [Yunong 201 (WRS1), Beijing 841 (WRS2)] were identified in 12 sets of root tissue samples by RNA-seq and iTRAQ (Isobaric tags for relative and absolute quantification). Phenotypic results showed that the elongation zone was significantly longer in root accessions with long roots compared to the short-rooted accessions. A genome-wide association study (GWAS) identified four stable chromosomal regions significantly associated with radicle length, among which 1A, 4A, and 7A chromosomes regions explained 7.17% to12.93% of the phenotypic variation. The omics studies identified the expression patterns of 24 DEGs/DEPs changed at both the transcriptional and protein levels. These DEGs/DEPs were mainly involved in carbon fixation in photosynthetic organisms, photosynthesis and phenylpropanoid biosynthesis pathways. TraesCS1A02G104100 and TraesCS2B02G519100 were involved in the biosynthesis of tricin-lignins in cell walls and may affect the extension of cell walls in the radicle elongation zone. A combination of GWAS and RNA-seq analyses revealed 19 DEGs with expression changes in the four accessions, among which, TraesCS1A02G422700 (a cysteine-rich receptor-like protein kinase 6, CRK6) also showed upregulation in the comparison group by RNA-seq, iTRAQ, and qRT-PCR. BSMV-mediated gene silencing also showed that TaCRK6 improves root development in wheat. Our data suggest that TaCRK6 is a candidate gene regulating radicle length in wheat.

Compatibility between snails and schistosomes: insights from new genetic resources, comparative genomics, and genetic mapping

The freshwater snail Biomphalaria glabrata is an important intermediate host of the parasite Schistosoma mansoni that causes human intestinal schistosomiasis. To better understand vector snail biology and help advance innovative snail control strategies, we have developed a new snail model consisting of two homozygous B. glabrata lines (iM line and iBS90) with sharply contrasting schistosome-resistance phenotypes. We produced and compared high-quality genome sequences for iM line and iBS90 which were assembled from 255 (N50 = 22.7 Mb) and 346 (N50 = 19.4 Mb) scaffolds, respectively. Using F2 offspring bred from the two lines and the newly generated iM line genome, we constructed 18 linkage groups (representing the 18 haploid chromosomes) covering 96% of the genome and identified three new QTLs (quantitative trait loci), two involved in snail resistance/susceptibility and one relating to body pigmentation. This study provides excellent genomic resources for unveiling complex vector snail biology, reveals genomic difference between resistant and susceptible lines, and offers novel insights into genetic mechanism of the compatibility between snail and schistosome.

A consensus map for quality traits in durum wheat based on genome-wide association studies and detection of ortho-meta QTL across cereal species

The present work focused on the identification of durum wheat QTL hotspots from a collection of genome-wide association studies, for quality traits, such as grain protein content and composition, yellow color, fiber, grain microelement content (iron, magnesium, potassium, selenium, sulfur, calcium, cadmium), kernel vitreousness, semolina, and dough quality test. For the first time a total of 10 GWAS studies, comprising 395 marker-trait associations (MTA) on 57 quality traits, with more than 1,500 genotypes from 9 association panels, were used to investigate consensus QTL hotspots representative of a wide durum wheat genetic variation. MTA were found distributed on all the A and B genomes chromosomes with minimum number of MTA observed on chromosome 5B (15) and a maximum of 45 on chromosome 7A, with an average of 28 MTA per chromosome. The MTA were equally distributed on A (48%) and B (52%) genomes and allowed the identification of 94 QTL hotspots. Synteny maps for QTL were also performed in Zea mays, Brachypodium, and Oryza sativa, and candidate gene identification allowed the association of genes involved in biological processes playing a major role in the control of quality traits.

Deciphering the Genetic Basis of Root and Biomass Traits in Rapeseed (Brassica napus L.) through the Integration of GWAS and RNA-Seq under Nitrogen Stress

An excellent root system is responsible for crops with high nitrogen-use efficiency (NUE). The current study evaluated the natural variations in 13 root- and biomass-related traits under a low nitrogen (LN) treatment in a rapeseed association panel. The studied traits exhibited significant phenotypic differences with heritabilities ranging from 0.53 to 0.66, and most of the traits showed significant correlations with each other. The genome-wide association study (GWAS) found 51 significant and 30 suggestive trait–SNP associations that integrated into 14 valid quantitative trait loci (QTL) clusters and explained 5.7–21.2% phenotypic variance. In addition, RNA sequencing was performed at two time points to examine the differential expression of genes (DEGs) between high and low NUE lines. In total, 245, 540, and 399 DEGs were identified as LN stress-specific, high nitrogen (HN) condition-specific, and HNLN common DEGs, respectively. An integrated analysis of GWAS, weighted gene co-expression network, and DEGs revealed 16 genes involved in rapeseed root development under LN stress. Previous studies have reported that the homologs of seven out of sixteen potential genes control root growth and NUE. These findings revealed the genetic basis underlying nitrogen stress and provided worthwhile SNPs/genes information for the genetic improvement of NUE in rapeseed.

Genome-Wide Identification of Auxin Response Factors in Peanut (Arachis hypogaea L.) and Functional Analysis in Root Morphology

Auxin response factors (ARFs) play important roles in plant growth and development; however, research in peanut (Arachis hypogaea L.) is still lacking. Here, 63, 30, and 30 AhARF genes were identified from an allotetraploid peanut cultivar and two diploid ancestors (A. duranensis and A. ipaensis). Phylogenetic tree and gene structure analysis showed that most AhARFs were highly similar to those in the ancestors. By scanning the whole-genome for ARF-recognized cis-elements, we obtained a potential target gene pool of AhARFs, and the further cluster analysis and comparative analysis showed that numerous members were closely related to root development. Furthermore, we comprehensively analyzed the relationship between the root morphology and the expression levels of AhARFs in 11 peanut varieties. The results showed that the expression levels of AhARF14/26/45 were positively correlated with root length, root surface area, and root tip number, suggesting an important regulatory role of these genes in root architecture and potential application values in peanut breeding.

Meta-QTL analysis and candidate genes identification for various abiotic stresses in maize (Zea mays L.) and their implications in breeding programs

Global climate change leads to the concurrence of a number of abiotic stresses including moisture stress (drought, waterlogging), temperature stress (heat, cold), and salinity stress, which are the major factors affecting maize production. To develop abiotic stress tolerance in maize, many quantitative trait loci (QTL) have been identified, but very few of them have been utilized successfully in breeding programs. In this context, the meta-QTL analysis of the reported QTL will enable the identification of stable/real QTL which will pave a reliable way to introgress these QTL into elite cultivars through marker-assisted selection. In this study, a total of 542 QTL were summarized from 33 published studies for tolerance to different abiotic stresses in maize to conduct meta-QTL analysis using BiomercatorV4.2.3. Among those, only 244 major QTL with more than 10% phenotypic variance were preferably utilised to carry out meta-QTL analysis. In total, 32 meta-QTL possessing 1907 candidate genes were detected for different abiotic stresses over diverse genetic and environmental backgrounds. The MQTL2.1, 5.1, 5.2, 5.6, 7.1, 9.1, and 9.2 control different stress-related traits for combined abiotic stress tolerance. The candidate genes for important transcription factor families such as ERF, MYB, bZIP, bHLH, NAC, LRR, ZF, MAPK, HSP, peroxidase, and WRKY have been detected for different stress tolerances. The identified meta-QTL are valuable for future climate-resilient maize breeding programs and functional validation of candidate genes studies, which will help to deepen our understanding of the complexity of these abiotic stresses.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-022-01294-9.

Genetic Analysis of Platform-Phenotyped Root System Architecture of Bread and Durum Wheat in Relation to Agronomic Traits

Roots are essential for water and nutrient uptake but are rarely the direct target of breeding efforts. To characterize the genetic variability of wheat root architecture, the root and shoot traits of 200 durum and 715 bread wheat varieties were measured at a young stage on a high-throughput phenotyping platform. Heritability of platform traits ranged from 0.40 for root biomass in durum wheat to 0.82 for the number of tillers. Field phenotyping data for yield components and SNP genotyping were already available for all the genotypes. Taking differences in earliness into account, several significant correlations between root traits and field agronomic performances were found, suggesting that plants investing more resources in roots in some stressed environments favored water and nutrient uptake, with improved wheat yield. We identified 100 quantitative trait locus (QTLs) of root traits in the bread wheat panels and 34 in the durum wheat panel. Most colocalized with QTLs of traits measured in field conditions, including yield components and earliness for bread wheat, but only in a few environments. Stress and climatic indicators explained the differential effect of some platform QTLs on yield, which was positive, null, or negative depending on the environmental conditions. Modern breeding has led to deeper rooting but fewer seminal roots in bread wheat. The number of tillers has been increased in bread wheat, but decreased in durum wheat, and while the root-shoot ratio for bread wheat has remained stable, for durum wheat it has been increased. Breeding for root traits or designing ideotypes might help to maintain current yield while adapting to specific drought scenarios.

Genome-Wide Association Study on Root System Architecture and Identification of Candidate Genes in Wheat (Triticum aestivum L.)

The root tissues play important roles in water and nutrient acquisition, environmental adaptation, and plant development. In this study, a diversity panel of 388 wheat accessions was collected to investigate nine root system architecture (RSA) traits at the three-leaf stage under two growing environments: outdoor pot culture (OPC) and indoor pot culture (IPC). Phenotypic analysis revealed that root development was faster under OPC than that under IPC and a significant correlation was observed between the nine RSA traits. The 660K single-nucleotide polymorphism (SNP) chip was used for a genome-wide association study (GWAS). Significant SNPs with a threshold of −log10 (p-value) ≥ 4 were considered. Thus, 36 quantitative trait loci (QTLs), including 13 QTL clusters that were associated with more than one trait, were detected, and 31 QTLs were first identified. The QTL clusters on chromosomes 3D and 5B were associated with four and five RSA traits, respectively. Two candidate genes, TraesCS2A01G516200 and TraesCS7B01G036900, were found to be associated with more than one RSA trait using haplotype analysis, and preferentially expressed in the root tissues. These favourable alleles for RSA traits identified in this study may be useful to optimise the root system in wheat.

Meta-analysis and validation of genomic loci governing seedling and reproductive stage salinity tolerance in rice

Identification of concurrent genomic regions contributing tolerance to salinity at the seedling and reproductive stages were done using 45 quantitative trait loci (QTL) mapping studies reporting 915 individual QTLs. The QTL-data were used to perform a meta-analysis to predict, validate and analyze the Meta-QTLs governing component traits contributing to salinity tolerance. We predicted a total of 65 and 49 Meta-QTLs distributed across the genome governing seedling and reproductive stage salinity tolerance, respectively. Salinity stress (EC ~10.0 dSm^-1 ) was evaluated in a set of 32 genotypes grown hydroponically, from these eight extreme (highly tolerant and highly susceptible) genotypes were selected for validation of significant Meta-QTLs. Another set of eight previously known and reported (highly tolerant and highly susceptible) genotypes were evaluated under saline micro plot conditions (EC ~8.0 dSm^-1 ) and used for validation of significant Meta-QTLs for reproductive stage salinity tolerance. The microsatellite marker "RM5635" linked to MSQTL4.2 (~295.43 kb) was able to clearly differentiate contrasting genotypes for seedling stage salinity tolerance, whereas at the reproductive stage, none of the markers were able to validate the predicted Meta-QTL for salinity tolerance. Earlier reported, gene expression studies were used for candidate gene analysis of validated MSQTL4.2, which indicated the down regulation of Os04g0423100, a gene encoding Mono-oxygenase-FAD binding domain containing protein. The traits associated with this Meta-QTL were root and shoot sodium and potassium concentration and leaf chlorophyll content. The identified and validated genomic region assumes a great significant role in seedling stage salinity tolerance in rice, and it can be used for marker-assisted backcross breeding programs.

Major Genomic Regions for Wheat Grain Weight as Revealed by QTL Linkage Mapping and Meta-Analysis

Grain weight is a key determinant for grain yield potential in wheat, which is highly governed by a type of quantitative genetic basis. The identification of major quantitative trait locus (QTL) and functional genes are urgently required for molecular improvements in wheat grain yield. In this study, major genomic regions and putative candidate genes for thousand grain weight (TGW) were revealed by integrative approaches with QTL linkage mapping, meta-analysis and transcriptome evaluation. Forty-five TGW QTLs were detected using a set of recombinant inbred lines, explaining 1.76-12.87% of the phenotypic variation. Of these, ten stable QTLs were identified across more than four environments. Meta-QTL (MQTL) analysis were performed on 394 initial TGW QTLs available from previous studies and the present study, where 274 loci were finally refined into 67 MQTLs. The average confidence interval of these MQTLs was 3.73-fold less than that of initial QTLs. A total of 134 putative candidate genes were mined within MQTL regions by combined analysis of transcriptomic and omics data. Some key putative candidate genes similar to those reported early for grain development and grain weight formation were further discussed. This finding will provide a better understanding of the genetic determinants of TGW and will be useful for marker-assisted selection of high yield in wheat breeding.

A comprehensive meta-QTL analysis for yield-related traits of durum wheat (Triticum turgidum L. var. durum) grown under different water regimes

Abiotic stress strongly affects yield-related traits in durum wheat, in particular drought is one of the main environmental factors that have effect on grain yield and plant architecture. In order to obtain new genotypes well adapted to stress conditions, the highest number of desirable traits needs to be combined in the same genotype. In this context, hundreds of quantitative trait loci (QTL) have been identified for yield-related traits in different genetic backgrounds and environments. Meta-QTL (MQTL) analysis is a useful approach to combine data sets and for creating consensus positions for the QTL detected in independent studies for the reliability of their location and effects. MQTL analysis is a useful method to dissect the genetic architecture of complex traits, which provide an extensive allelic coverage, a higher mapping resolution and allow the identification of putative molecular markers useful for marker-assisted selection (MAS). In the present study, a complete and comprehensive MQTL analysis was carried out to identify genomic regions associated with grain-yield related traits in durum wheat under different water regimes. A total of 724 QTL on all 14 chromosomes (genomes A and B) were collected for the 19 yield-related traits selected, of which 468 were reported under rainfed conditions, and 256 under irrigated conditions. Out of the 590 QTL projected on the consensus map, 421 were grouped into 76 MQTL associated with yield components under both irrigated and rainfed conditions, 12 genomic regions containing stable MQTL on all chromosomes except 1A, 4A, 5A, and 6B. Candidate genes associated to MQTL were identified and an in-silico expression analysis was carried out for 15 genes selected among those that were differentially expressed under drought. These results can be used to increase durum wheat grain yields under different water regimes and to obtain new genotypes adapted to climate change.

GWAS Case Studies in Wheat

With the advancements in next-generation sequencing technologies, leading to millions of single nucleotide polymorphisms in all crop species including wheat, genome-wide association study (GWAS) has become a leading approach for trait dissection. In wheat, GWAS has been conducted for a plethora of traits and more and more studies are being conducted and reported in journals. While application of GWAS has become a routine in wheat using the standardized approaches, there has been a great leap forward using newer models and combination of GWAS with other sets of data. This chapter has reviewed all these latest advancements in GWAS in wheat by citing the most important studies and their outputs. Specially, we have focused on studies that conducted meta-GWAS, multilocus GWAS, haplotype-based GWAS, Environmental- and Eigen-GWAS, and/or GWAS combined with gene regulatory network and pathway analyses or epistatic interactions analyses; all these have taken the association mapping approach to new heights in wheat.

Meta-QTLs, ortho-MQTLs, and candidate genes for thermotolerance in wheat (Triticum aestivum L.)

Meta-QTL analysis for thermotolerance in wheat was conducted to identify robust meta-QTLs (MQTLs). In this study, 441 QTLs related to 31 heat-responsive traits were projected on the consensus map with 50,310 markers. This exercise resulted in the identification of 85 MQTLs with confidence interval (CI) ranging from 0.11 to 34.9 cM with an average of 5.6 cM. This amounted to a 2.96-fold reduction relative to the mean CI (16.5 cM) of the QTLs used. Seventy-seven (77) of these MQTLs were also compared and verified with the results of recent genome-wide association studies (GWAS). The 85 MQTLs included seven MQTLs that are particularly useful for breeding purposes (we called them breeders' MQTLs). Seven ortho-MQTLs between wheat and rice genomes were also identified using synteny and collinearity. The MQTLs were used for the identification of 1,704 candidate genes (CGs). In silico expression analysis of these CGs permitted identification of 182 differentially expressed genes (DEGs), which included 36 high confidence CGs with known functions previously reported to be important for thermotolerance. These high confidence CGs encoded proteins belonging to the following families: protein kinase, WD40 repeat, glycosyltransferase, ribosomal protein, SNARE associated Golgi protein, GDSL lipase/esterase, SANT/Myb domain, K homology domain, etc. Thus, the present study resulted in the identification of MQTLs (including breeders' MQTLs), ortho-MQTLs, and underlying CGs, which could prove useful not only for molecular breeding for the development of thermotolerant wheat cultivars but also for future studies focused on understanding the molecular basis of thermotolerance.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-021-01264-7.

Physical mapping of QTL associated with agronomic and end-use quality traits in spring wheat under conventional and organic management systems

Using phenotypic data of four biparental spring wheat populations evaluated at multiple environments under two management systems, we discovered 152 QTL and 22 QTL hotspots, of which two QTL accounted for up to 37% and 58% of the phenotypic variance, consistently detected in all environments, and fell within genomic regions harboring known genes. Identification of the physical positions of quantitative trait loci (QTL) would be highly useful for developing functional markers and comparing QTL results across multiple independent studies. The objectives of the present study were to map and characterize QTL associated with nine agronomic and end-use quality traits (tillering ability, plant height, lodging, grain yield, grain protein content, thousand kernel weight, test weight, sedimentation volume, and falling number) in hard red spring wheat recombinant inbred lines (RILs) using the International Wheat Genome Sequencing Consortium (IWGSC) RefSeq v2.0 physical map. We evaluated a total of 698 RILs from four populations derived from crosses involving seven parents at 3-8 conventionally (high N) and organically (low N) managed field environments. Using the phenotypic data combined across all environments per management, and the physical map between 1058 and 6526 markers per population, we identified 152 QTL associated with the nine traits, of which 29 had moderate and 2 with major effects. Forty-nine of the 152 QTL mapped across 22 QTL hotspot regions with each region coincident to 2-6 traits. Some of the QTL hotspots were physically located close to known genes. QSv.dms-1A and QPht.dms-4B.1 individually explained up to 37% and 58% of the variation in sedimentation volume and plant height, respectively, and had very large LOD scores that varied from 19.0 to 35.7 and from 16.7 to 55.9, respectively. We consistently detected both QTL in the combined and all individual environments, laying solid ground for further characterization and possibly for cloning.

Association mapping of drought tolerance and agronomic traits in rice (Oryza sativa L.) landraces

BACKGROUND

Asian cultivars were predominantly represented in global rice panel selected for sequencing and to identify novel alleles for drought tolerance. Diverse genetic resources adapted to Indian subcontinent were not represented much in spite harboring useful alleles that could improve agronomic traits, stress resilience and productivity. These rice accessions are valuable genetic resource in developing rice varieties suited to different rice ecosystem that experiences varying drought stress level, and at different crop stages. A core collection of rice germplasm adapted to Southwestern Indian peninsular genotyped using SSR markers and characterized by contrasting water regimes to associate genomic regions for physiological, root traits and yield related traits. Genotyping-By-Sequencing of selected accessions within the diverse panel revealed haplotype variation in genic content within genomic regions mapped for physiological, morphological and root traits.

RESULTS

Diverse rice panel (99 accessions) were evaluated in field and measurements on plant physiological, root traits and yield related traits were made over five different seasons experiencing varying drought stress intensity at different crop stages. Traits like chlorophyll stability index, leaf rolling, days to 50% flowering, chlorophyll content, root volume and root biomass were identified as best predictors of grain yield under stress. Association mapping revealed genetic variation among accessions and revealed 14 genomic targets associated with different physiological, root and plant production traits. Certain accessions were found to have beneficial allele to improve traits, plant height, root length and spikelet fertility, that contribute to the grain yield under stress. Genomic characterization of eleven accessions revealed haplotype variation within key genomic targets on chromosomes 1, 4, 6 and 11 for potential use as molecular markers to combine drought avoidance and tolerance traits. Genes mined within the genomic QTL intervals identified were prioritized based on tissue specific expression level in publicly available rice transcriptome data.

CONCLUSION

The genetic and genomic resources identified will enable combining traits with agronomic value to optimize yield under stress and hasten trait introgression into elite cultivars. Alleles associated with plant height, specific leaf area, root length from PTB8 and spikelet fertility and grain weight from PTB26 can be harnessed in future rice breeding program.

Comparative Genomic Analysis of Quantitative Trait Loci Associated With Micronutrient Contents, Grain Quality, and Agronomic Traits in Wheat (Triticum aestivum L.)

Comparative genomics and meta-quantitative trait loci (MQTLs) analysis are important tools for the identification of reliable and stable QTLs and functional genes controlling quantitative traits. We conducted a meta-analysis to identify the most stable QTLs for grain yield (GY), grain quality traits, and micronutrient contents in wheat. A total of 735 QTLs retrieved from 27 independent mapping populations reported in the last 13 years were used for the meta-analysis. The results showed that 449 QTLs were successfully projected onto the genetic consensus map which condensed to 100 MQTLs distributed on wheat chromosomes. This consolidation of MQTLs resulted in a three-fold reduction in the confidence interval (CI) compared with the CI for the initial QTLs. Projection of QTLs revealed that the majority of QTLs and MQTLs were in the non-telomeric regions of chromosomes. The majority of micronutrient MQTLs were located on the A and D genomes. The QTLs of thousand kernel weight (TKW) were frequently associated with QTLs for GY and grain protein content (GPC) with co-localization occurring at 55 and 63%, respectively. The co- localization of QTLs for GY and grain Fe was found to be 52% and for QTLs of grain Fe and Zn, it was found to be 66%. The genomic collinearity within Poaceae allowed us to identify 16 orthologous MQTLs (OrMQTLs) in wheat, rice, and maize. Annotation of promising candidate genes (CGs) located in the genomic intervals of the stable MQTLs indicated that several CGs (e.g., TraesCS2A02G141400, TraesCS3B02G040900, TraesCS4D02G323700, TraesCS3B02G077100, and TraesCS4D02G290900) had effects on micronutrients contents, yield, and yield-related traits. The mapping refinements leading to the identification of these CGs provide an opportunity to understand the genetic mechanisms driving quantitative variation for these traits and apply this information for crop improvement programs.

Functional phenomics and genetics of the root economics space in winter wheat using high-throughput phenotyping of respiration and architecture

The root economics space is a useful framework for plant ecology but is rarely considered for crop ecophysiology. In order to understand root trait integration in winter wheat, we combined functional phenomics with trait economic theory, utilizing genetic variation, high-throughput phenotyping, and multivariate analyses. We phenotyped a diversity panel of 276 genotypes for root respiration and architectural traits using a novel high-throughput method for CO2 flux and the open-source software RhizoVision Explorer to analyze scanned images. We uncovered substantial variation in specific root respiration (SRR) and specific root length (SRL), which were primary indicators of root metabolic and structural costs. Multiple linear regression analysis indicated that lateral root tips had the greatest SRR, and the residuals from this model were used as a new trait. Specific root respiration was negatively correlated with plant mass. Network analysis, using a Gaussian graphical model, identified root weight, SRL, diameter, and SRR as hub traits. Univariate and multivariate genetic analyses identified genetic regions associated with SRR, SRL, and root branching frequency, and proposed gene candidates. Combining functional phenomics and root economics is a promising approach to improving our understanding of crop ecophysiology. We identified root traits and genomic regions that could be harnessed to breed more efficient crops for sustainable agroecosystems.

Functional phenomics and genetics of the root economics space in winter wheat using high-throughput phenotyping of respiration and architecture

The root economics space is a useful framework for plant ecology but is rarely considered for crop ecophysiology. In order to understand root trait integration in winter wheat, we combined functional phenomics with trait economic theory, utilizing genetic variation, high-throughput phenotyping, and multivariate analyses. We phenotyped a diversity panel of 276 genotypes for root respiration and architectural traits using a novel high-throughput method for CO₂ flux and the open-source software RhizoVision Explorer to analyze scanned images. We uncovered substantial variation in specific root respiration (SRR) and specific root length (SRL), which were primary indicators of root metabolic and structural costs. Multiple linear regression analysis indicated that lateral root tips had the greatest SRR, and the residuals from this model were used as a new trait. Specific root respiration was negatively correlated with plant mass. Network analysis, using a Gaussian graphical model, identified root weight, SRL, diameter, and SRR as hub traits. Univariate and multivariate genetic analyses identified genetic regions associated with SRR, SRL, and root branching frequency, and proposed gene candidates. Combining functional phenomics and root economics is a promising approach to improving our understanding of crop ecophysiology. We identified root traits and genomic regions that could be harnessed to breed more efficient crops for sustainable agroecosystems.

Meta-QTLs, ortho-MQTLs and candidate genes for nitrogen use efficiency and root system architecture in bread wheat (Triticum aestivum L.)

In wheat, meta-QTLs (MQTLs), ortho-MQTLs, and candidate genes (CGs) were identified for nitrogen use efficiency and root system architecture. For this purpose, 1788 QTLs were available from 24 studies published during 2006-2020. Of these, 1098 QTLs were projected onto the consensus map resulting in 118 MQTLs. The average confidence interval (CI) of MQTLs was reduced up to 8.56 folds in comparison to the average CI of QTLs. Of the 118 MQTLs, 112 were anchored to the physical map of the wheat reference genome. The physical interval of MQTLs ranged from 0.02 to 666.18 Mb with a mean of 94.36 Mb. Eighty-eight of these 112 MQTLs were verified by marker-trait associations (MTAs) identified in published genome-wide association studies (GWAS); the MQTLs that were verified using GWAS also included 9 most robust MQTLs, which are particularly useful for breeders; we call them 'Breeder's QTLs'. Some selected wheat MQTLs were further utilized for the identification of ortho-MQTLs for wheat and maize; 9 such ortho-MQTLs were available. As many as 1991 candidate genes (CGs) were also detected, which included 930 CGs with an expression level of > 2 transcripts per million in relevant organs/tissues. Among the CGs, 97 CGs with functions previously reported as important for the traits under study were selected. Based on homology analysis and expression patterns, 49 orthologues of 35 rice genes were also identified in MQTL regions. The results of the present study may prove useful for the improvement of selection strategy for yield potential, stability, and performance under N-limiting conditions.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s12298-021-01085-0.

Large-scale integration of meta-QTL and genome-wide association study discovers the genomic regions and candidate genes for yield and yield-related traits in bread wheat

Based on the large-scale integration of meta-QTL and Genome-Wide  Association Study, 76 high-confidence MQTL regions and 237 candidate genes that affected wheat yield and yield-related traits were discovered. Improving yield and yield-related traits are key goals in wheat breeding program. The integration of accumulated wheat genetic resources provides an opportunity to uncover important genomic regions and candidate genes that affect wheat yield. Here, a comprehensive meta-QTL analysis was conducted on 2230 QTL of yield-related traits obtained from 119 QTL studies. These QTL were refined into 145 meta-QTL (MQTL), and 89 MQTL were verified by GWAS with different natural populations. The average confidence interval (CI) of these MQTL was 2.92 times less than that of the initial QTL. Furthermore, 76 core MQTL regions with a physical distance less than 25 Mb were detected. Based on the homology analysis and expression patterns, 237 candidate genes in the MQTL involved in photoperiod response, grain development, multiple plant growth regulator pathways, carbon and nitrogen metabolism and spike and flower organ development were determined. A novel candidate gene TaKAO-4A was confirmed to be significantly associated with grain size, and a CAPS marker was developed based on its dominant haplotype. In summary, this study clarified a method based on the integration of meta-QTL, GWAS and homology comparison to reveal the genomic regions and candidate genes that affect important yield-related traits in wheat. This work will help to lay a foundation for the identification, transfer and aggregation of these important QTL or candidate genes in wheat high-yield breeding.

WheatQTLdb: a QTL database for wheat

During the last three decades, QTL analysis in wheat has been conducted for a variety of individual traits, so that thousands of QTL along with the linked markers, their genetic positions and contribution to phenotypic variation (PV) for concerned traits are now known. However, no exhaustive database for wheat QTL is currently available at a single platform. Therefore, the present database was prepared which is an exhaustive information resource for wheat QTL data from the published literature till May, 2020. QTL data from both interval mapping and genome-wide association studies (GWAS) have been included for the following classes of traits: (i) morphological traits, (ii) N and P use efficiency, (iii) traits for biofortification (Fe, K, Se, and Zn contents), (iv) tolerance to abiotic stresses including drought, water logging, heat stress, pre-harvest sprouting and salinity, (v) resistance to biotic stresses including those due to bacterial, fungal, nematode and insects, (vi) quality traits, and (vii) a variety of physiological traits, (viii) developmental traits, and (ix) yield and its related traits. For the preparation of the database, literature was searched for data on QTL/marker-trait associations (MTAs), curated and then assembled in the form of WheatQTLdb. The available information on metaQTL, epistatic QTL and candidate genes, wherever available, is also included in the database. Information on QTL in this WheatQTLdb includes QTL names, traits, associated markers, parental genotypes, crosses/mapping populations, association mapping panels and other useful information. To our knowledge, WheatQTLdb prepared by us is the largest collection of QTL (11,552), epistatic QTL (107) and metaQTL (330) data for hexaploid wheat to be used by geneticists and plant breeders for further studies involving fine mapping, cloning, and marker-assisted selection (MAS) during wheat breeding.

Meta-analysis of QTLs associated with popping traits in maize (Zea mays L.)

The rising demand for popcorn necessitates improving the popping quality with higher yield of popcorn cultivars. Towards this direction several Quantitative Traits Loci (QTLs) for popping traits have been identified. However, identification of accurate and consistent QTLs across different genetic backgrounds and environments is necessary to effectively utilize the identified QTLs in marker-assisted breeding. In the current study, 99 QTLs related to popping traits reported in 8 different studies were assembled and projected on the reference map "Genetic 2005" using BioMercator v4.2 to identify metaQTLs with consistent QTLs. Total ten metaQTLs were identified on chromosome 1 (7 metaQTLs) and 6 (3 metaQTLs) with physical distance ranging between 0.43 and 12.75 Mb, respectively. Four identified metaQTLs, viz., mQTL1_1, mQTL1_5, mQTL1_7 and mQTL6_2 harboured 5-8 QTL clusters with moderately high R2 value. The clustered QTLs were from two or more experiments. Based on the expression pattern in endosperm and pericarp tissues, a total of 229 genes were selected. Nineteen of these genes are involved in carbohydrate metabolism. Of the 19 genes specifically involved in carbohydrate metabolism, 11 of them were in these regions, implying the importance of these clustered QTLs. MetaQTL1_1 at bin location 1.01 coincided with the reported QTLs related to various agronomic traits like stalk diameter, tassel length, leaf area and plant height. The identified metaQTLs can be further explored for fine mapping and candidate gene identification, which can be validated by loss or gain of function. Identified metaQTLs can be used for introgression of popping traits towards enhancing the popping ability.

Recognizing the hidden half in wheat: root system attributes associated with drought tolerance

Improving drought tolerance in wheat is crucial for maintaining productivity and food security. Roots are responsible for the uptake of water from soil, and a number of root traits are associated with drought tolerance. Studies have revealed many quantitative trait loci and genes controlling root development in plants. However, the genetic dissection of root traits in response to drought in wheat is still unclear. Here, we review crop root traits associated with drought, key genes governing root development in plants, and quantitative trait loci and genes regulating root system architecture under water-limited conditions in wheat. Deep roots, optimal root length density and xylem diameter, and increased root surface area are traits contributing to drought tolerance. In view of the diverse environments in which wheat is grown, the balance among root and shoot traits, as well as individual and population performance, are discussed. The known functions of key genes provide information for the genetic dissection of root development of wheat in a wide range of conditions, and will be beneficial for molecular marker development, marker-assisted selection, and genetic improvement in breeding for drought tolerance.

Harnessing translational research in wheat for climate resilience

Despite being the world's most widely grown crop, research investments in wheat (Triticum aestivum and Triticum durum) fall behind those in other staple crops. Current yield gains will not meet 2050 needs, and climate stresses compound this challenge. However, there is good evidence that heat and drought resilience can be boosted through translating promising ideas into novel breeding technologies using powerful new tools in genetics and remote sensing, for example. Such technologies can also be applied to identify climate resilience traits from among the vast and largely untapped reserve of wheat genetic resources in collections worldwide. This review describes multi-pronged research opportunities at the focus of the Heat and Drought Wheat Improvement Consortium (coordinated by CIMMYT), which together create a pipeline to boost heat and drought resilience, specifically: improving crop design targets using big data approaches; developing phenomic tools for field-based screening and research; applying genomic technologies to elucidate the bases of climate resilience traits; and applying these outputs in developing next-generation breeding methods. The global impact of these outputs will be validated through the International Wheat Improvement Network, a global germplasm development and testing system that contributes key productivity traits to approximately half of the global wheat-growing area.

Genetic Dissection of Seedling Root System Architectural Traits in a Diverse Panel of Hexaploid Wheat through Multi-Locus Genome-Wide Association Mapping for Improving Drought Tolerance

Cultivars with efficient root systems play a major role in enhancing resource use efficiency, particularly water absorption, and thus in drought tolerance. In this study, a diverse wheat association panel of 136 wheat accessions including mini core subset was genotyped using Axiom 35k Breeders' Array to identify genomic regions associated with seedling stage root architecture and shoot traits using multi-locus genome-wide association studies (ML-GWAS). The association panel revealed a wide variation of 1.5- to 50-fold and were grouped into six clusters based on 15 traits. Six different ML-GWAS models revealed 456 significant quantitative trait nucleotides (QTNs) for various traits with phenotypic variance in the range of 0.12-38.60%. Of these, 87 QTNs were repeatedly detected by two or more models and were considered reliable genomic regions for the respective traits. Among these QTNs, eleven were associated with average diameter and nine each for second order lateral root number (SOLRN), root volume (RV) and root length density (RLD). A total of eleven genomic regions were pleiotropic and each controlled two or three traits. Some important candidate genes such as Formin homology 1, Ubiquitin-like domain superfamily and ATP-dependent 6-phosphofructokinase were identified from the associated genomic regions. The genomic regions/genes identified in this study could potentially be targeted for improving root traits and drought tolerance in wheat.

A transposon in the vacuolar sorting receptor gene TaVSR1-B promoter region is associated with wheat root depth at booting stage

Root depth, as an important component of root architecture, plays a significant role in growth, grain yield determination and abiotic stress tolerance in crop plants, but its genetic basis remains poorly elucidated. In this study, a panel composed of 323 wheat (Triticum aestivum L.) accessions was assessed for variation in root depth and genotyped with the Wheat 660K SNP Array. GWAS (genome-wide association study) detected significant association between a 125 bp miniature inverted-repeat transposable element (MITE) in the promoter of the TaVSR1-B gene with root depth at the booting stage. We showed that the MITE repressed TaVSR1-B expression by DNA methylation and H3K27 tri-methylation. The roles of TaVSR1-B in root growth were verified by altered expression of the gene in transgenic wheat, rice and a tavsr1 TILLING mutant. Increased TaVSR1-B expression made the root elongation zone shorter and the differentiation zone longer, leading to deeper root. This work provides novel insight into the genetic basis of variation in root depth and a promising target for genetic improvement of root architecture in wheat.

Meta-QTL analysis and identification of candidate genes for quality, abiotic and biotic stress in durum wheat

The genetic improvement of durum wheat and enhancement of plant performance often depend on the identification of stable quantitative trait loci (QTL) and closely linked molecular markers. This is essential for better understanding the genetic basis of important agronomic traits and identifying an effective method for improving selection efficiency in breeding programmes. Meta-QTL analysis is a useful approach for dissecting the genetic basis of complex traits, providing broader allelic coverage and higher mapping resolution for the identification of putative molecular markers to be used in marker-assisted selection. In the present study, extensive QTL meta-analysis was conducted on 45 traits of durum wheat, including quality and biotic and abiotic stress-related traits. A total of 368 QTL distributed on all 14 chromosomes of genomes A and B were projected: 171 corresponded to quality-related traits, 127 to abiotic stress and 71 to biotic stress, of which 318 were grouped in 85 meta-QTL (MQTL), 24 remained as single QTL and 26 were not assigned to any MQTL. The number of MQTL per chromosome ranged from 4 in chromosomes 1A and 6A to 9 in chromosome 7B; chromosomes 3A and 7A showed the highest number of individual QTL (4), and chromosome 7B the highest number of undefined QTL (4). The recently published genome sequence of durum wheat was used to search for candidate genes within the MQTL peaks. This work will facilitate cloning and pyramiding of QTL to develop new cultivars with specific quantitative traits and speed up breeding programs.

Wheat root systems as a breeding target for climate resilience

In the coming decades, larger genetic gains in yield will be necessary to meet projected demand, and this must be achieved despite the destabilizing impacts of climate change on crop production. The root systems of crops capture the water and nutrients needed to support crop growth, and improved root systems tailored to the challenges of specific agricultural environments could improve climate resiliency. Each component of root initiation, growth and development is controlled genetically and responds to the environment, which translates to a complex quantitative system to navigate for the breeder, but also a world of opportunity given the right tools. In this review, we argue that it is important to know more about the 'hidden half' of crop plants and hypothesize that crop improvement could be further enhanced using approaches that directly target selection for root system architecture. To explore these issues, we focus predominantly on bread wheat (Triticum aestivum L.), a staple crop that plays a major role in underpinning global food security. We review the tools available for root phenotyping under controlled and field conditions and the use of these platforms alongside modern genetics and genomics resources to dissect the genetic architecture controlling the wheat root system. To contextualize these advances for applied wheat breeding, we explore questions surrounding which root system architectures should be selected for, which agricultural environments and genetic trait configurations of breeding populations are these best suited to, and how might direct selection for these root ideotypes be implemented in practice.

Deciphering the genetic basis of wheat seminal root anatomy uncovers ancestral axial conductance alleles

Root axial conductance, which describes the ability of water to move through the xylem, contributes to the rate of water uptake from the soil throughout the whole plant lifecycle. Under the rainfed wheat agro-system, grain-filling is typically occurring during declining water availability (i.e., terminal drought). Therefore, preserving soil water moisture during grain filling could serve as a key adaptive trait. We hypothesized that lower wheat root axial conductance can promote higher yields under terminal drought. A segregating population derived from a cross between durum wheat and its direct progenitor wild emmer wheat was used to underpin the genetic basis of seminal root architectural and functional traits. We detected 75 QTL associated with seminal roots morphological, anatomical and physiological traits, with several hotspots harbouring co-localized QTL. We further validated the axial conductance and central metaxylem QTL using wild introgression lines. Field-based characterization of genotypes with contrasting axial conductance suggested the contribution of low axial conductance as a mechanism for water conservation during grain filling and consequent increase in grain size and yield. Our findings underscore the potential of harnessing wild alleles to reshape the wheat root system architecture and associated hydraulic properties for greater adaptability under changing climate.

Physical Mapping of QTL in Four Spring Wheat Populations under Conventional and Organic Management Systems. I. Earliness

In previous studies, we reported quantitative trait loci (QTL) associated with the heading, flowering, and maturity time in four hard red spring wheat recombinant inbred line (RIL) populations but the results are scattered in population-specific genetic maps, which is challenging to exploit efficiently in breeding. Here, we mapped and characterized QTL associated with these three earliness traits using the International Wheat Genome Sequencing Consortium (IWGSC) RefSeq v2.0 physical map. Our data consisted of (i) 6526 single nucleotide polymorphisms (SNPs) and two traits evaluated at five conventionally managed environments in the 'Cutler' × 'AC Barrie' population; (ii) 3158 SNPs and two traits evaluated across three organic and seven conventional managements in the 'Attila' × 'CDC Go' population; (iii) 5731 SilicoDArT and SNP markers and the three traits evaluated at four conventional and organic management systems in the 'Peace' × 'Carberry' population; and (iv) 1058 SNPs and two traits evaluated across two conventionally and organically managed environments in the 'Peace' × 'CDC Stanley' population. Using composite interval mapping, the phenotypic data across all environments, and the IWGSC RefSeq v2.0 physical maps, we identified a total of 44 QTL associated with days to heading (11), flowering (10), and maturity (23). Fifteen of the 44 QTL were common to both conventional and organic management systems, and the remaining QTL were specific to either the conventional (21) or organic (8) management systems. Some QTL harbor known genes, including the Vrn-A1, Vrn-B1, Rht-A1, and Rht-B1 that regulate photoperiodism, flowering time, and plant height in wheat, which lays a solid basis for cloning and further characterization.