Loci and candidate genes controlling root traits in wheat seedlings-a wheat root GWAS

Genome-wide association analysis reveal candidate genes and haplotypes related to root weight in cucumber (Cucumis sativus L.)

Background

The plant root system is critical for the absorption of water and nutrients, and have a direct influence on growth and yield. In cucumber, a globally consumed crop, the molecular mechanism of root development remains unclear, and this has implications for developing stress tolerant varieties. This study sought to determine the genetic patterns and related genes of cucumber root weight. A core cucumber germplasms population was used to do the GWAS analysis in three environments.

Results

Here, we investigated four root-weight related traits including root fresh weight (RFW), root dry weight (RDW), ratio of root dry weight to root fresh weight (RDFW) and the comprehensive evaluation index, D-value of root weight (DRW) deduced based on the above three traits for the core germplasm of the cucumber global repository. According to the D-value, we identified 21 and 16 accessions with light and heavy-root, respectively. We also found that the East Asian ecotype accessions had significantly heavier root than other three ecotypes. The genome-wide association study (GWAS) for these four traits reveals that 4 of 10 significant loci (gDRW3.1, gDRW3.2, gDRW4.1 and gDRW5.1) were repeatedly detected for at least two traits. Further haplotype and expression analysis for protein-coding genes positioned within these 4 loci between light and heavy-root accessions predicted five candidate genes (i.e., Csa3G132020 and Csa3G132520 both encoding F-box protein PP2-B1 for gDRW3.1, Csa3G629240 encoding a B-cell receptor-associated protein for gDRW3.2, Csa4G499330 encodes a GTP binding protein for gDRW4.1, and Csa5G286040 encodes a proteinase inhibitor for gDRW5.1).

Conclusions

We conducted a systematic analysis of the root genetic basis and characteristics of cucumber core germplasms population. We detected four novel loci, which regulate the root weight in cucumber. Our study provides valuable candidate genes and haplotypes for the improvement of root system in cucumber breeding.

Regulation of root growth and elongation in wheat

Currently, the control of rhizosphere selection on farms has been applied to achieve enhancements in phenotype, extending from improvements in single root characteristics to the dynamic nature of entire crop systems. Several specific signals, regulatory elements, and mechanisms that regulate the initiation, morphogenesis, and growth of new lateral or adventitious root species have been identified, but much more work remains. Today, phenotyping technology drives the development of root traits. Available models for simulation can support all phenotyping decisions (root trait improvement). The detection and use of markers for quantitative trait loci (QTLs) are effective for enhancing selection efficiency and increasing reproductive genetic gains. Furthermore, QTLs may help wheat breeders select the appropriate roots for efficient nutrient acquisition. Single-nucleotide polymorphisms (SNPs) or alignment of sequences can only be helpful when they are associated with phenotypic variation for root development and elongation. Here, we focus on major root development processes and detail important new insights recently generated regarding the wheat genome. The first part of this review paper discusses the root morphology, apical meristem, transcriptional control, auxin distribution, phenotyping of the root system, and simulation models. In the second part, the molecular genetics of the wheat root system, SNPs, TFs, and QTLs related to root development as well as genome editing (GE) techniques for the improvement of root traits in wheat are discussed. Finally, we address the effect of omics strategies on root biomass production and summarize existing knowledge of the main molecular mechanisms involved in wheat root development and elongation.

Root system architecture change in response to waterlogging stress in a 448 global collection of rapeseeds (Brassica napus L.)

MAIN CONCLUSIONS

A novel image-based screening method for precisely identifying genotypic variations in rapeseed RSA under waterlogging stress was developed. Five key root traits were confirmed as good indicators of waterlogging and might be employed in breeding, particularly when using the MFVW approach. Waterlogging is a vital environmental factor that has detrimental effects on the growth and development of rapeseed (Brassica napus L.). Plant roots suffer from hypoxia under waterlogging, which ultimately confers yield penalty. Therefore, it is crucially important to understand the genetic variation of root system architecture (RSA) in response to waterlogging stress to guide the selection of new tolerant cultivars with favorable roots. This research was conducted to investigate RSA traits using image-based screening techniques to better understand how RSA changes over time during waterlogging at the seedling stage. First, we performed a t-test by comparing the relative root trait value between four tolerant and four sensitive accessions. The most important root characteristics associated with waterlogging tolerance at 12 h are total root length (TRL), total root surface area (TRSA), total root volume (TRV), total number of tips (TNT), and total number of forks (TNF). The root structures of 448 rapeseed accessions with or without waterlogging showed notable genetic diversity, and all traits were generally restrained under waterlogging conditions, except for the total root average diameter. Additionally, according to the evaluation and integration analysis of 448 accessions, we identified that five traits, TRL, TRSA, TRV, TNT, and TNF, were the most reliable traits for screening waterlogging-tolerant accessions. Using analysis of the membership function value (MFVW) and D-value of the five selected traits, 25 extremely waterlogging-tolerant materials were screened out. Waterlogging significantly reduced RSA, inhibiting root growth compared to the control. Additionally, waterlogging increased lipid peroxidation, accompanied by a decrease in the activities of superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT). This study effectively improves our understanding of the response of RSA to waterlogging. The image-based screening method developed in this study provides a new scientific guidance for quickly examining the basic RSA changes and precisely predicting waterlogging-tolerant rapeseed germplasms, thus expanding the genetic diversity of waterlogging-tolerant rapeseed germplasm available for breeding.

Genetic Signature Controlling Root System Architecture in Diverse Spring Wheat Germplasm

Roots are the main sensing organ, initiating multiple signaling pathways in response to abiotic factors, including nutrients, drought, and salt stress. A focus on improving the root system architecture is a key strategy to mitigate these stresses in wheat crop. In the present study, a diversity panel comprising indigenous landraces and historical cultivars from Pakistan was characterized for the root system architecture (RSA) and important loci were identified using a genome-wide association study (GWAS). RSA of the diversity panel was characterized 30 days after sowing in brunch tubes, and root images were taken. A high-throughput root imaging analysis using Rhizovision software was performed by setting the scale to extract the eight RSA traits and four plant biomass-related traits. GWAS identified 323 association signals for 12 root and biomass traits present on all wheat chromosomes, while the most important and reliable genetic loci (based on pleotropic loci and candidate genes) were identified on chromosomes 2A, 2B, 5A, 5D, 6A, 7B, and 7D for RSA. SNP annotation and transcriptome profiling identified nine candidate genes regulating the RSA and plant biomass traits, including ROOTLESS WITH UNDETECTABLE MERISTEM1, MYB TRANSCRIPTION FACTOR4, BRASSINOSTEROID INSENSITIVE1, SLENDER RICE1, AUXIN-RESPONSIVE FACTOR25, SCARECROW, NARROW LEAF2, PIN-FORMED1 AND PHOSPHATE TRANSCRIPTION FACTOR1. This study provided pre-breeding information for deep-rooting genotypes and associated markers that will accelerate the incorporation of such traits in breeding.

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.

Dissecting the genetic architecture of root-related traits in a grafted wild Vitis berlandieri population for grapevine rootstock breeding

In woody perennial plants, quantitative genetics and association studies remain scarce for root-related traits, due to the time required to obtain mature plants and the complexity of phenotyping. In grapevine, a grafted cultivated plant, most of the rootstocks used are hybrids between American Vitis species (V. rupestris, V. riparia, and V. berlandieri). In this study, we used a wild population of an American Vitis species (V. berlandieri) to analyze the genetic architecture of the root-related traits of rootstocks in a grafted context. We studied a population consisting of 211 genotypes, with one to five replicates each (n = 846 individuals), plus four commercial rootstocks as control genotypes (110R, 5BB, Börner, and SO4). After two independent years of experimentation, the best linear unbiased estimates method revealed root-related traits with a moderate-to-high heritability (0.36-0.82) and coefficient of genetic variation (0.15-0.45). A genome-wide association study was performed with the BLINK model, leading to the detection of 11 QTL associated with four root-related traits (one QTL was associated with the total number of roots, four were associated with the number of small roots (< 1 mm in diameter), two were associated with the number of medium-sized roots (1 mm < diameter < 2 mm), and four were associated with mean diameter) accounting for up to 25.1% of the variance. Three genotypes were found to have better root-related trait performances than the commercial rootstocks and therefore constitute possible new candidates for use in grapevine rootstock breeding programs.

Symbiotic Variations among Wheat Genotypes and Detection of Quantitative Trait Loci for Molecular Interaction with Auxin-Producing Azospirillum PGPR

Crop varieties differ in their ability to interact with Plant Growth-Promoting Rhizobacteria (PGPR), but the genetic basis for these differences is unknown. This issue was addressed with the PGPR Azospirillum baldaniorum Sp245, using 187 wheat accessions. We screened the accessions based on the seedling colonization by the PGPR and the expression of the phenylpyruvate decarboxylase gene ppdC (for synthesis of the auxin indole-3-acetic acid), using gusA fusions. Then, the effects of the PGPR on the selected accessions stimulating Sp245 (or not) were compared in soil under stress. Finally, a genome-wide association approach was implemented to identify the quantitative trait loci (QTL) associated with PGPR interaction. Overall, the ancient genotypes were more effective than the modern genotypes for Azospirillum root colonization and ppdC expression. In non-sterile soil, A. baldaniorum Sp245 improved wheat performance for three of the four PGPR-stimulating genotypes and none of the four non-PGPR-stimulating genotypes. The genome-wide association did not identify any region for root colonization but revealed 22 regions spread on 11 wheat chromosomes for ppdC expression and/or ppdC induction rate. This is the first QTL study focusing on molecular interaction with PGPR bacteria. The molecular markers identified provide the possibility to improve the capacity of modern wheat genotypes to interact with Sp245, as well as, potentially, other Azospirillum strains.

Genetic analysis of protein content and oil content in soybean by genome-wide association study

Soybean seed protein content (PC) and oil content (OC) have important economic value. Detecting the loci/gene related to PC and OC is important for the marker-assisted selection (MAS) breeding of soybean. To detect the stable and new loci for PC and OC, a total of 320 soybean accessions collected from the major soybean-growing countries were used to conduct a genome-wide association study (GWAS) by resequencing. The PC ranged from 37.8% to 46.5% with an average of 41.1% and the OC ranged from 16.7% to 22.6% with an average of 21.0%. In total, 23 and 29 loci were identified, explaining 3.4%-15.4% and 5.1%-16.3% of the phenotypic variations for PC and OC, respectively. Of these, eight and five loci for PC and OC, respectively, overlapped previously reported loci and the other 15 and 24 loci were newly identified. In addition, nine candidate genes were identified, which are known to be involved in protein and oil biosynthesis/metabolism, including lipid transport and metabolism, signal transduction, and plant development pathway. These results uncover the genetic basis of soybean protein and oil biosynthesis and could be used to accelerate the progress in enhancing soybean PC and OC.

Identifying genomic regions determining shoot and root traits related to nitrogen uptake efficiency in a multiparent advanced generation intercross (MAGIC) winter wheat population in a high-throughput phenotyping facility

In the context of a continuously increasing human population that needs to be fed, with environmental protection in mind, nitrogen use efficiency (NUE) improvement is becoming very important. To understand the natural variation of traits linked to nitrogen uptake efficiency (UPE), one component of NUE, the multiparent advanced generation intercross (MAGIC) winter wheat population WM-800 was phenotyped under two contrasting nitrogen (N) levels in a high-throughput phenotyping facility for six weeks. Three biomass-related, three root-related, and two reflectance-related traits were measured weekly under each treatment. Subsequently, the population was genetically analysed using a total of 13,060 polymorphic haplotypes and singular SNPs for a genome-wide association study (GWAS). In total, we detected 543 quantitative trait loci (QTL) across all time points and traits, which were pooled into 42 stable QTL (sQTL; present in at least three of the six weeks). Besides Rht-B1 and Rht-D1, candidate genes playing a role in gibberellic acid-regulated growth and nitrate transporter genes from the NPF gene family, like NRT 1.1, were linked to sQTL. Two novel sQTL on chromosomes 5 A and 6D showed pleiotropic effects on several traits. The high number of N-specific sQTL indicates that selection for UPE is useful specifically under N-limited conditions.

Multi-omics assisted breeding for biotic stress resistance in soybean

Biotic stress is a critical factor limiting soybean growth and development. Soybean responses to biotic stresses such as insects, nematodes, fungal, bacterial, and viral pathogens are governed by complex regulatory and defense mechanisms. Next-generation sequencing has availed research techniques and strategies in genomics and post-genomics. This review summarizes the available information on marker resources, quantitative trait loci, and marker-trait associations involved in regulating biotic stress responses in soybean. We discuss the differential expression of related genes and proteins reported in different transcriptomics and proteomics studies and the role of signaling pathways and metabolites reported in metabolomic studies. Recent advances in omics technologies offer opportunities to reshape and improve biotic stress resistance in soybean by altering gene regulation and/or other regulatory networks. We suggest using 'integrated omics' to precisely understand how soybean responds to different biotic stresses. We also discuss the potential challenges of integrating multi-omics for the functional analysis of genes and their regulatory networks and the development of biotic stress-resistant cultivars. This review will help direct soybean breeding programs to develop resistance against different biotic stresses.

Genome-wide association study to identify genomic loci associated with early vigor in bread wheat under simulated water deficit complemented with quantitative trait loci meta-analysis

A genome-wide association study (GWAS) was used to identify associated loci with early vigor under simulated water deficit and grain yield under field drought in a diverse collection of Iranian bread wheat landraces. In addition, a meta-quantitative trait loci (MQTL) analysis was used to further expand our approach by retrieving already published quantitative trait loci (QTL) from recombinant inbred lines, double haploids, back-crosses, and F2 mapping populations. In the current study, around 16%, 14%, and 16% of SNPs were in significant linkage disequilibrium (LD) in the A, B, and D genomes, respectively, and varied between 5.44% (4A) and 21.85% (6A). Three main subgroups were identified among the landraces with different degrees of admixture, and population structure was further explored through principal component analysis. Our GWAS identified 54 marker-trait associations (MTAs) that were located across the wheat genome but with the highest number found in the B sub-genome. The gene ontology (GO) analysis of MTAs revealed that around 75% were located within or closed to protein-coding genes. In the MQTL analysis, 23 MQTLs, from a total of 215 QTLs, were identified and successfully projected onto the reference map. MQT-YLD4, MQT-YLD9, MQT-YLD13, MQT-YLD17, MQT-YLD18, MQT-YLD19, and MQTL-RL1 contributed to the highest number of projected QTLs and were therefore regarded as the most reliable and stable QTLs under water deficit conditions. These MQTLs greatly facilitate the identification of putative candidate genes underlying at each MQTL interval due to the reduced confidence of intervals associated with MQTLs. These findings provide important information on the genetic basis of early vigor traits and grain yield under water deficit conditions and set the foundation for future investigations into adaptation to water deficit in bread wheat.

Unraveling Genomic Regions Controlling Root Traits as a Function of Nitrogen Availability in the MAGIC Wheat Population WM-800

An ever-growing world population demands to be fed in the future and environmental protection and climate change need to be taken into account. An important factor here is nitrogen uptake efficiency (NUpE), which is influenced by the root system (the interface between plant and soil). To understand the natural variation of root system architecture (RSA) as a function of nitrogen (N) availability, a subset of the multiparent advanced generation intercross (MAGIC) winter wheat population WM-800 was phenotyped under two contrasting N treatments in a high-throughput phenotyping system at the seedling stage. Fourteen root and shoot traits were measured. Subsequently, these traits were genetically analyzed using 13,060 polymorphic haplotypes and SNPs in a genome-wide association study (GWAS). In total, 64 quantitative trait loci (QTL) were detected; 60 of them were N treatment specific. Candidate genes for the detected QTL included NRT1.1 and genes involved in stress signaling under N-, whereas candidate genes under N+ were more associated with general growth, such as mei2 and TaWOX11b. This finding may indicate (i) a disparity of the genetic control of root development under low and high N supply and, furthermore, (ii) the need for an N specific selection of genes and genotypes in breeding new wheat cultivars with improved NUpE.

Integrating advancements in root phenotyping and genome-wide association studies to open the root genetics gateway

Plant adaptation to challenging environmental conditions around the world has made root growth and development an important research area for plant breeders and scientists. Targeted manipulation of root system architecture (RSA) to increase water and nutrient use efficiency can minimize the adverse effects of climate change on crop production. However, phenotyping of RSA is a major bottleneck since the roots are hidden in the soil. Recently the development of 2- and 3D root imaging techniques combined with the genome-wide association studies (GWASs) have opened up new research tools to identify the genetic basis of RSA. These approaches provide a comprehensive understanding of the RSA, by accelerating the identification and characterization of genes involved in root growth and development. This review summarizes the latest developments in phenotyping techniques and GWAS for RSA, which are used to map important genes regulating various aspects of RSA under varying environmental conditions. Furthermore, we discussed about the state-of-the-art image analysis tools integrated with various phenotyping platforms for investigating and quantifying root traits with the highest phenotypic plasticity in both artificial and natural environments which were used for large scale association mapping studies, leading to the identification of RSA phenotypes and their underlying genetics with the greatest potential for RSA improvement. In addition, challenges in root phenotyping and GWAS are also highlighted, along with future research directions employing machine learning and pan-genomics approaches.

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.

Genotypic variation and covariation in wheat seedling seminal root architecture and grain yield under field conditions

Greater embryo size in a large and carefully phenotyped mapping population was genetically associated with a greater number of longer seminal roots to increase grain yield in droughted field environments. Breeding modification of root architecture is challenging in field environments owing to genetic and phenotypic complexity, and poor repeatability with root sampling. Seeds from a large mapping population varying in embryo size were harvested from a common glasshouse and standardised to a common size before assessing in rolled germination paper at 12 and 20 °C for seedling growth. Differences in genotype means were large and heritabilities high (h² = 0.55-0.93) indicating strong and repeatable genotypic differences for most root traits. Seminal roots 1 to 3 were produced on all seedlings, whereas growth of seminal roots 4, 5 and 6 was associated with differences in embryo size. Increases in seminal root number from 4 to 6 per plant were strongly, genetically correlated with increases in total seminal length (r_g = 0.84, < 0.01). Multivariate analysis confirmed initiation and growth of seminal roots 1, 2 and 3, and of roots 4, 5 and 6 behaved as genetically independent (r_Pg = 0.15 ns) cohorts. Tails representing extremes in seedling root length and number were associated with significant differences in grain yield of up to 35% in droughted field environments but were not different in irrigated environments. Increases in grain yield were linked to greater lengths of seminal roots 4, 5 and 6 and were largely independent of plant height or development. This is the first report on the genetic relationship of seedling root architecture and embryo size, and potential in selection of seminal root size for accessing deep-soil moisture in droughted environments.

Genetic analysis of morphological traits in spring wheat from the Northeast of China by a genome-wide association study

Identification of the gene for agronomic traits is important for the wheat marker-assisted selection (MAS) breeding. To identify the new and stable loci for agronomic traits, including flag leaf length (FLL), flag leaf width (FLW), uppermost internode length (UIL), and plant morphology (PM, including prostrate, semi-prostrate, and erect). A total of 251 spring wheat accessions collected from the Northeast of China were used to conduct genome-wide association study (GWAS) by 55K SNP arrays. A total of 30 loci for morphological traits were detected, and each explained 4.8–17.9% of the phenotypic variations. Of these, 13 loci have been reported by previous studies, and the other 17 are novel. We have identified seven genes involved in the signal transduction, cell-cycle progression, and plant development pathway as candidate genes. This study provides new insights into the genetic basis of morphological traits. The associated SNPs and accessions with more of favorable alleles identified in this study could be used to promote the wheat breeding progresses.

Genome-wide association mapping for component traits of drought and heat tolerance in wheat

Identification of marker trait association is a prerequisite for marker-assisted breeding. To find markers linked with traits under heat and drought stress in bread wheat (Triticum aestivum L.), we performed a genome-wide association study (GWAS). GWAS mapping panel used in this study consists of advanced breeding lines from the IARI stress breeding programme produced by pairwise and complex crosses. Phenotyping was done at multi locations namely New Delhi, Karnal, Indore, Jharkhand and Pune with augmented-RCBD design under different moisture and heat stress regimes, namely timely sown irrigated (IR), timely sown restricted irrigated (RI) and late sown (LS) conditions. Yield and its component traits, viz., Days to Heading (DH), Days to Maturity (DM), Normalized Difference Vegetation Index (NDVI), Chlorophyll Content (SPAD), Canopy temperature (CT), Plant Height (PH), Thousand grain weight (TGW), Grain weight per spike (GWPS), Plot Yield (PLTY) and Biomass (BMS) were phenotyped. Analysis of variance and descriptive statistics revealed significant differences among the studied traits. Genotyping was done using the 35k SNP Wheat Breeder's Genotyping Array. Population structure and diversity analysis using filtered 10,546 markers revealed two subpopulations with sufficient diversity. A large whole genome LD block size of 7.15 MB was obtained at half LD decay value. Genome-wide association search identified 57 unique markers associated with various traits across the locations. Twenty-three markers were identified to be stable, among them nine pleiotropic markers were also identified. In silico search of the identified markers against the IWGSC ref genome revealed the presence of a majority of the SNPs at or near the gene coding region. These SNPs can be used for marker-assisted transfer of genes/QTLs after validation to develop climate-resilient cultivars.

Identification of a unique allele in the quantitative trait locus for crown root number in japonica rice from Japan using genome-wide association studies

To explore the genetic resources that could be utilized to help improve root system architecture phenotypes in rice (Oryza sativa), we have conducted genome-wide association studies to investigate maximum root length and crown root number in 135 10-day-old Japanese rice accessions grown hydroponically. We identified a quantitative trait locus for crown root number at approximately 32.7 Mbp on chromosome 4 and designated it qNCR1 (quantitative trait locus for Number of Crown Root 1). A linkage disequilibrium map around qNCR1 suggested that three candidate genes are involved in crown root number: a cullin (LOC_Os04g55030), a gibberellin 20 oxidase 8 (LOC_Os04g55070), and a cyclic nucleotide-gated ion channel (LOC_Os04g55080). The combination of haplotypes for each gene was designated as a haploblock, and haploblocks 1, 2, and 3 were defined. Compared to haploblock 1, the accessions with haploblocks 2 and 3 had fewer crown roots; approximately 5% and 10% reductions in 10-day-old plants and 15% and 25% reductions in 42-day-old plants, respectively. A Japanese leading variety Koshihikari and its progenies harbored haploblock 3. Their crown root number could potentially be improved using haploblocks 1 and 2.

Wheat Proteomics for Abiotic Stress Tolerance and Root System Architecture: Current Status and Future Prospects

Wheat is an important staple cereal for global food security. However, climate change is hampering wheat production due to abiotic stresses, such as heat, salinity, and drought. Besides shoot architectural traits, improving root system architecture (RSA) traits have the potential to improve yields under normal and stressed environments. RSA growth and development and other stress responses involve the expression of proteins encoded by the trait controlling gene/genes. Hence, mining the key proteins associated with abiotic stress responses and RSA is important for improving sustainable yields in wheat. Proteomic studies in wheat started in the early 21st century using the two-dimensional (2-DE) gel technique and have extensively improved over time with advancements in mass spectrometry. The availability of the wheat reference genome has allowed the exploration of proteomics to identify differentially expressed or abundant proteins (DEPs or DAPs) for abiotic stress tolerance and RSA improvement. Proteomics contributed significantly to identifying key proteins imparting abiotic stress tolerance, primarily related to photosynthesis, protein synthesis, carbon metabolism, redox homeostasis, defense response, energy metabolism and signal transduction. However, the use of proteomics to improve RSA traits in wheat is in its infancy. Proteins related to cell wall biogenesis, carbohydrate metabolism, brassinosteroid biosynthesis, and transportation are involved in the growth and development of several RSA traits. This review covers advances in quantification techniques of proteomics, progress in identifying DEPs and/or DAPs for heat, salinity, and drought stresses, and RSA traits, and the limitations and future directions for harnessing proteomics in wheat improvement.

High-LD SNP markers exhibiting pleiotropic effects on salt tolerance at germination and seedlings stages in spring wheat

Salt tolerance at germination and seedling growth stages was investigated. GWAS revealed nine genomic regions with pleiotropic effects on salt tolerance. Salt tolerant genotypes were identified for future breeding program. With 20% of the irrigated land worldwide affected by it, salinity is a serious threat to plant development and crop production. While wheat is the most stable food source worldwide, it has been classified as moderately tolerant to salinity. In several crop plants; such as barley, maize and rice, it has been shown that salinity tolerance at seed germination and seedling establishment is under polygenic control. As yield was the ultimate goal of breeders and geneticists, less attention has been paid to understanding the genetic architecture of salt tolerance at early stages. Thus, the genetic control of salt tolerance at these stages is poorly understood relative to the late stages. In the current study, 176 genotypes of spring wheat were tested for salinity tolerance at seed germination and seedling establishment. Genome-Wide Association Study (GWAS) has been used to identify the genomic regions/genes conferring salt tolerance at seed germination and seedling establishment. Salinity stress negatively impacted all germination and seedling development parameters. A set of 137 SNPs showed significant association with the traits of interest. Across the whole genome, 33 regions showed high linkage disequilibrium (LD). These high LD regions harbored 15 SNPs with pleiotropic effect (i.e. SNPs that control more than one trait). Nine genes belonging to different functional groups were found to be associated with the pleiotropic SNPs. Noteworthy, chromosome 2B harbored the gene TraesCS2B02G135900 that acts as a potassium transporter. Remarkably, one SNP marker, reported in an early study, associated with salt tolerance was validated in this study. Our findings represent potential targets of genetic manipulation to understand and improve salinity tolerance in wheat.

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.

Prospectus of Genomic Selection and Phenomics in Cereal, Legume and Oilseed Breeding Programs

The last decade witnessed an unprecedented increase in the adoption of genomic selection (GS) and phenomics tools in plant breeding programs, especially in major cereal crops. GS has demonstrated the potential for selecting superior genotypes with high precision and accelerating the breeding cycle. Phenomics is a rapidly advancing domain to alleviate phenotyping bottlenecks and explores new large-scale phenotyping and data acquisition methods. In this review, we discuss the lesson learned from GS and phenomics in six self-pollinated crops, primarily focusing on rice, wheat, soybean, common bean, chickpea, and groundnut, and their implementation schemes are discussed after assessing their impact in the breeding programs. Here, the status of the adoption of genomics and phenomics is provided for those crops, with a complete GS overview. GS’s progress until 2020 is discussed in detail, and relevant information and links to the source codes are provided for implementing this technology into plant breeding programs, with most of the examples from wheat breeding programs. Detailed information about various phenotyping tools is provided to strengthen the field of phenomics for a plant breeder in the coming years. Finally, we highlight the benefits of merging genomic selection, phenomics, and machine and deep learning that have resulted in extraordinary results during recent years in wheat, rice, and soybean. Hence, there is a potential for adopting these technologies into crops like the common bean, chickpea, and groundnut. The adoption of phenomics and GS into different breeding programs will accelerate genetic gain that would create an impact on food security, realizing the need to feed an ever-growing population.

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

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

Advanced high-throughput plant phenotyping techniques for genome-wide association studies: A review

Linking phenotypes and genotypes to identify genetic architectures that regulate important traits is crucial for plant breeding and the development of plant genomics. In recent years, genome-wide association studies (GWASs) have been applied extensively to interpret relationships between genes and traits. Successful GWAS application requires comprehensive genomic and phenotypic data from large populations. Although multiple high-throughput DNA sequencing approaches are available for the generation of genomics data, the capacity to generate high-quality phenotypic data is lagging far behind. Traditional methods for plant phenotyping mostly rely on manual measurements, which are laborious, inaccurate, and time-consuming, greatly impairing the acquisition of phenotypic data from large populations. In contrast, high-throughput phenotyping has unique advantages, facilitating rapid, non-destructive, and high-throughput detection, and, in turn, addressing the shortcomings of traditional methods. Aim of Review: This review summarizes the current status with regard to the integration of high-throughput phenotyping and GWAS in plants, in addition to discussing the inherent challenges and future prospects. Key Scientific Concepts of Review: High-throughput phenotyping, which facilitates non-contact and dynamic measurements, has the potential to offer high-quality trait data for GWAS and, in turn, to enhance the unraveling of genetic structures of complex plant traits. In conclusion, high-throughput phenotyping integration with GWAS could facilitate the revealing of coding information in plant genomes.

The Genetic Architecture of Grain Yield in Spring Wheat Based on Genome-Wide Association Study

Uncovering the genetic architecture for grain yield (GY)–related traits is important for wheat breeding. To detect stable loci for GY-related traits, a genome-wide association study (GWAS) was conducted in a diverse panel, which included 251 elite spring wheat accessions mainly from the Northeast of China. In total, 52,503 single nucleotide polymorphisms (SNPs) from the wheat 55 K SNP arrays were used. Thirty-eight loci for GY-related traits were detected and each explained 6.5–16.7% of the phenotypic variations among which 12 are at similar locations with the known genes or quantitative trait loci and 26 are likely to be new. Furthermore, six genes possibly involved in cell division, signal transduction, and plant development are candidate genes for GY-related traits. This study provides new insights into the genetic architecture of GY and the significantly associated SNPs and accessions with a larger number of favorable alleles could be used to further enhance GY in breeding.

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.

Genome-wide association study and transcriptome analysis reveal key genes affecting root growth dynamics in rapeseed

BACKGROUND

In terms of global demand, rapeseed is the third-largest oilseed crop after soybeans and palm, which produces vegetable oil for human consumption and biofuel for industrial production. Roots are vital organs for plant to absorb water and attain mineral nutrients, thus they are of great importance to plant productivity. However, the genetic mechanisms regulating root development in rapeseed remain unclear. In the present study, seven root-related traits and shoot biomass traits in 280 Brassica napus accessions at five continuous vegetative stages were measured to establish the genetic basis of root growth in rapeseed.

RESULTS

The persistent and stage-specific genetic mechanisms were revealed by root dynamic analysis. Sixteen persistent and 32 stage-specific quantitative trait loci (QTL) clusters were identified through genome-wide association study (GWAS). Root samples with contrasting (slow and fast) growth rates throughout the investigated stages and those with obvious stage-specific changes in growth rates were subjected to transcriptome analysis. A total of 367 differentially expressed genes (DEGs) with persistent differential expressions throughout root development were identified, and these DEGs were significantly enriched in GO terms, such as energy metabolism and response to biotic or abiotic stress. Totally, 485 stage-specific DEGs with different expressions at specific stage were identified, and these DEGs were enriched in GO terms, such as nitrogen metabolism. Four candidate genes were identified as key persistent genetic factors and eight as stage-specific ones by integrating GWAS, weighted gene co-expression network analysis (WGCNA), and differential expression analysis. These candidate genes were speculated to regulate root system development, and they were less than 100 kb away from peak SNPs of QTL clusters. The homologs of three genes (BnaA03g52990D, BnaA06g37280D, and BnaA09g07580D) out of 12 candidate genes have been reported to regulate root development in previous studies.

CONCLUSIONS

Sixteen QTL clusters and four candidate genes controlling persistently root development, and 32 QTL clusters and eight candidate genes stage-specifically regulating root growth in rapeseed were detected in this study. Our results provide new insights into the temporal genetic mechanisms of root growth by identifying key candidate QTL/genes in rapeseed.

Genome-Wide Association Study on Root Traits Under Different Growing Environments in Wheat ( Triticum aestivum L.)

Plant roots are critical for water and nutrient acquisition, environmental adaptation, and yield formation. Herein, 196 wheat accessions from the Huang-Huai Wheat Region of China were collected to investigate six root traits at seedling stage under three growing environments [indoor hydroponic culture (IHC), outdoor hydroponic culture (OHC), and outdoor pot culture (OPC)] and the root dry weight (RDW) under OPC at four growth stages and four yield traits in four environments. Additionally, a genome-wide association study was performed with a Wheat 660K SNP Array. The results showed that the root traits varied most under OPC, followed by those under both OHC and IHC, and root elongation under hydroponic culture was faster than that under pot culture. Root traits under OHC might help predict those under OPC. Moreover, root traits were significantly negatively correlated with grain yield (GY) and grains per spike (GPS), positively correlated with thousand-kernel weight (TKW), and weakly correlated with number of spikes per area (SPA). Twelve stable chromosomal regions associated with the root traits were detected on chromosomes 1D, 2A, 4A, 4B, 5B, 6D, and unmapped markers. Among them, a stable chromosomal interval from 737.85 to 742.00 Mb on chromosome 4A, which regulated total root length (TRL), was identified under three growing environments. Linkage disequilibrium (LD) blocks were used to identify 27 genes related to root development. Three genes TraesCS4A02G484200, TraesCS4A02G484800, TraesCS4A02G493800, and TraesCS4A02G493900, are involved in cell elongation and differentiation and expressed at high levels in root tissues. Another vital co-localization interval on chromosome 5B (397.72–410.88 Mb) was associated with not only RDW under OHC and OPC but also TKW.

A novel motif in the 5'-UTR of an orphan gene 'Big Root Biomass' modulates root biomass in sesame

Developing crops with improved root system is crucial in current global warming scenario. Underexploited crops are valuable reservoirs of unique genes that can be harnessed for the improvement of major crops. In this study, we performed genome-wide association studies on seven root traits in sesame (Sesamum indicum L.) and uncovered 409 significant signals, 19 quantitative trait loci containing 32 candidate genes. A peak SNP significantly associated with root number and root dry weight traits was located in the promoter of the gene named 'Big Root Biomass' (BRB), which was subsequently validated in a bi-parental population. BRB has no functional annotation and is restricted to the Lamiales order. We detected the presence of a novel motif 'AACACACAC' located in the 5'-UTR of BRB in single and duplicated copy in accessions with high and small root biomass, respectively. A strong expression level of BRB was negatively correlated with high root biomass, and this was attributed to the gene SiMYB181 which represses the activity of BRB by binding specifically to the single motif but not to the duplicated one. Curiously, the allele that enhanced BRB expression has been intensively selected by modern breeding. Overexpression of BRB in Arabidopsis modulates auxin pathway leading to reduced root biomass, improved yield parameters under normal growth conditions and increased drought stress sensitivity. Overall, BRB represents a solid gene model for improving the performance of sesame and other crops.

Genome-Wide Association Mapping of Seedling Biomass and Root Traits Under Different Water Conditions in Wheat

Drought is a major threat to global wheat production. In this study, an association panel containing 200 Chinese wheat germplasms was used for genome-wide association studies (GWASs) of genetic loci associated with eight root and seedling biomass traits under normal water and osmotic stress conditions. The following traits were investigated in wheat seedlings at the four-leaf stage: root length (RL), root number (RN), root fresh weight (RFW), root dry weight (RDW), shoot fresh weight (SFW), shoot dry weight (SDW), total fresh weight (TFW), and total dry weight (TDW). A total of 323 and 286 SNPs were detected under two water environments, respectively. Some of these SNPs were near known loci for root traits. Eleven SNPs on chromosomes 1B, 2B, 4B, and 2D had pleiotropic effects on multiple traits under different water conditions. Further analysis indicated that several genes located inside the 4 Mb LD block on each side of these 11 SNPs were known to be associated with plant growth and development and thus may be candidate genes for these loci. Results from this study increased our understanding of the genetic architecture of root and seedling biomass traits under different water conditions and will facilitate the development of varieties with better drought tolerance.

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

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

Genome-Wide Association Study on Seminal and Nodal Roots of Wheat Under Different Growth Environments

The root of wheat consists of seminal and nodal roots. Comparatively speaking, fewer studies have been carried out on the nodal root system because of its disappearance at the early seedling stage under indoor environments. In this study, 196 accessions from the Huanghuai Wheat Region (HWR) were used to identify the characteristics of seminal and nodal root traits under different growth environments, including indoor hydroponic culture (IHC), outdoor hydroponic culture (OHC), and outdoor pot culture (OPC), for three growing seasons. The results indicated that the variation range of root traits in pot environment was larger than that in hydroponic environment, and canonical coefficients were the greatest between OHC and OPC (0.86) than those in other two groups, namely, IHC vs. OPC (0.48) and IHC vs. OHC (0.46). Most root traits were negatively correlated with spikes per area (SPA), grains per spike (GPS), and grain yield (GY), while all the seminal root traits were positively correlated with thousand-kernel weight (TKW). Genome-wide association study (GWAS) was carried out on root traits by using a wheat 660K SNP array. A total of 35 quantitative trait loci (QTLs)/chromosomal segments associated with root traits were identified under OPC and OHC. In detail, 11 and 24 QTLs were significantly associated with seminal root and nodal root traits, respectively. Moreover, 13 QTLs for number of nodal roots per plant (NRP) containing 14 stable SNPs, were distributed on chromosomes 1B, 2B, 3A, 4B, 5D, 6D, 7A, 7B, and Un. Based on LD and bioinformatics analysis, these QTLs may contain 17 genes closely related to NRP. Among them, TraesCS2B02G552500 and TraesCS7A02G428300 were highly expressed in root tissues. Moreover, the frequencies of favorable alleles of these 14 SNPs were confirmed to be less than 70% in the natural population, suggesting that the utilization of these superior genes in wheat root is still improving.

Phenotypic and genetic variation in phosphorus-deficiency-tolerance traits in Chinese wheat landraces

BACKGROUND

Phosphorus deficiency is a major limiting factors for affecting crop production globally. To understand the genetic variation of phosphorus-deficiency-tolerance, a total of 15 seedling traits were evaluated among 707 Chinese wheat landraces under application of phosphorus (AP) and non-application of phosphorus (NP). A total of 18,594 single-nucleotide polymorphisms and 38,678 diversity arrays technology sequencing markers were used to detect marker-trait associations under AP and NP.

RESULTS

Top ten genotypes with extremely tolerance and bottommost ten genotypes with extremely sensitivity were selected from 707 Chinese wheat landraces for future breeding and genetic analysis. A total of 55 significant markers (81 marker-trait associations) for 13 traits by both CMLM and SUPER method. These were distributed on chromosomes 1A, 1B, 2A, 2B, 2D, 3A, 4B, 5A, 5B, 6A, 6B, 6D, 7A and 7B. Considering the linkage disequilibrium decay distance, 25 and 12 quantitative trait loci (QTL) were detected under AP and NP, respectively (9 QTL were specific to NP).

CONCLUSIONS

The extremely tolerant landraces could be used for breeding phosphorus-deficiency-tolerant cultivars. The QTL could be useful in wheat breeding through marker-assisted selection. Our findings provide new insight into the genetic analysis of P-deficiency-tolerance, and will be helpful for breeding P-deficiency-tolerant cultivars.

Identification of a novel genomic region associated with resistance to Fusarium crown rot in wheat

Genome-wide association study (GWAS) on 358 Chinese wheat germplasms and validation in a biparental population identified a novel significant genomic region on 5DL for FCR resistance. Fusarium crown rot (FCR) is a chronic and severe disease in many dryland wheat-producing areas worldwide. In the last few years, the incidence and severity of FCR progressively increased in China, and the disease has currently become a new threat to local wheat crops. Here, we report a genome-wide association study (GWAS) on a set of 358 Chinese germplasms with the wheat 55 K SNP array. A total of 104 SNPs on chromosomes 1BS, 1DS, 2AL, 5AL, 5DS, 5DL, 6BS and 7BL were significantly associated with seedling resistance to FCR in the association panel. Of these SNPs, a novel 13.78 Mb region targeted by five SNPs on chromosome arm 5DL was continually detected in all three trials. The effects of this region on FCR resistance was confirmed in biparental population. qRT-PCR showed that within this 5DL region, several genes encoding TIR-NBS-LRR proteins and proteins related to mycotoxins deoxynivalenol (DON) detoxification increased rapidly in the disease-resistant variety 04 Zhong 36 than the susceptible variety Xinmai 26 after inoculation. Our study provides new insights into gene discovery and creation of new cultivars with desirable alleles for improving FCR resistance in wheat.

Mining for Candidate Genes Controlling Secondary Growth of the Carrot Storage Root

Background: Diverse groups of carrot cultivars have been developed to meet consumer demands and industry needs. Varietal groups of the cultivated carrot are defined based on the shape of roots. However, little is known about the genetic basis of root shape determination. Methods: Here, we used 307 carrot plants from 103 open-pollinated cultivars for a genome wide association study to identify genomic regions associated with the storage root morphology. Results: A 180 kb-long region on carrot chromosome 1 explained 10% of the total observed phenotypic variance in the shoulder diameter. Within that region, DcDCAF1 and DcBTAF1 genes were proposed as candidates controlling secondary growth of the carrot storage root. Their expression profiles differed between the cultivated and the wild carrots, likely indicating that their elevated expression was required for the development of edible roots. They also showed higher expression at the secondary root growth stage in cultivars producing thick roots, as compared to those developing thin roots. Conclusions: We provided evidence for a likely involvement of DcDCAF1 and/or DcBTAF1 in the development of the carrot storage root and developed a genotyping assay facilitating the identification of variants in the region on carrot chromosome 1 associated with secondary growth of the carrot root.

Exploiting natural variation in root system architecture via genome-wide association studies

Root growth and development has become an important research topic for breeders and researchers based on a growing need to adapt plants to changing and more demanding environmental conditions worldwide. Over the last few years, genome-wide association studies (GWASs) became an important tool to identify the link between traits in the field and their genetic background. Here we give an overview of the current literature concerning GWASs performed on root system architecture (RSA) in plants. We summarize which root traits and approaches have been used for GWAS, mentioning their respective success rate towards a successful gene discovery. Furthermore, we zoom in on the current technical hurdles in root phenotyping and GWAS, and discuss future possibilities in this field of research.

Variation in Root and Shoot Growth in Response to Reduced Nitrogen

Recently, root traits have been suggested to play an important role in developing greater nitrogen uptake and grain yield. However, relatively few breeding programs utilize these root traits. Over a series of experiments at different growth stages with destructive plant biomass measurements, we analyzed above-ground and below-ground traits in seven geographically diverse lines of wheat. Root and shoot biomass allocation in 14-day-old seedlings were analyzed using paper roll-supported hydroponic culture in two Hoagland solutions containing 0.5 (low) and 4 (high) mM of nitrogen (N). For biomass analysis of plants at maturity, plants were grown in 7.5 L pots filled with soil mix under two nitrogen treatments. Traits were measured as plants reached maturity. High correlations were observed among duration of vegetative growth, tiller number, shoot dry matter, and root dry matter. Functionality of large roots in nitrogen uptake was dependent on the availability of N. Under high N, lines with larger roots had a greater yield response to the increase in N input. Under low N, yields were independent of root size and dry matter, meaning that there was not a negative tradeoff to the allocation of more resources to roots, though small rooted lines were more competitive with regards to grain yield and grain N concentration in the low-N treatment. In the high-N treatment, the large-rooted lines were correlated to an increase in grain N concentration (r = 0.54) and grain yield (r = 0.43). In low N, the correlation between root dry matter to yield (r = 0.20) and grain N concentration (r = -0.38) decreased. A 15-fold change was observed between lines for root dry matter; however, only a ~5-fold change was observed in shoot dry matter. Additionally, root dry matter measured at the seedling stage did not correlate to the corresponding trait at maturity. As such, in a third assay, below-ground and above-ground traits were measured at key growth stages including the four-leaf stage, stem elongation, heading, post-anthesis, and maturity. We found that root growth appears to be stagnant from stem elongation to maturity.

Ancient wheat varieties have a higher ability to interact with plant growth-promoting rhizobacteria

Plant interactions with plant growth-promoting rhizobacteria (PGPR) are highly dependent on plant genotype. Modern plant breeding has largely sought to improve crop performance but with little focus on the optimization of plant × PGPR interactions. The interactions of the model PGPR strain Pseudomonas kilonensis F113 were therefore compared in 199 ancient and modern wheat genotypes. A reporter system, in which F113 colonization and expression of 2,4-diacetylphloroglucinol biosynthetic genes (phl) were measured on roots was used to quantify F113 × wheat interactions under gnotobiotic conditions. Thereafter, eight wheat accessions that differed in their ability to interact with F113 were inoculated with F113 and grown in greenhouse in the absence or presence of stress. F113 colonization was linked to improved stress tolerance. Moreover, F113 colonization and phl expression were higher overall on ancient genotypes than modern genotypes. F113 colonization improved wheat performance in the four genotypes that showed the highest level of phl expression compared with the four genotypes in which phl expression was lowest. Taken together, these data suggest that recent wheat breeding strategies have had a negative impact on the ability of the plants to interact with PGPR.

Comprehensive Genome-Wide Association Analysis Reveals the Genetic Basis of Root System Architecture in Soybean

Increasing the understanding genetic basis of the variability in root system architecture (RSA) is essential to improve resource-use efficiency in agriculture systems and to develop climate-resilient crop cultivars. Roots being underground, their direct observation and detailed characterization are challenging. Here, were characterized twelve RSA-related traits in a panel of 137 early maturing soybean lines (Canadian soybean core collection) using rhizoboxes and two-dimensional imaging. Significant phenotypic variation (P < 0.001) was observed among these lines for different RSA-related traits. This panel was genotyped with 2.18 million genome-wide single-nucleotide polymorphisms (SNPs) using a combination of genotyping-by-sequencing and whole-genome sequencing. A total of 10 quantitative trait locus (QTL) regions were detected for root total length and primary root diameter through a comprehensive genome-wide association study. These QTL regions explained from 15 to 25% of the phenotypic variation and contained two putative candidate genes with homology to genes previously reported to play a role in RSA in other species. These genes can serve to accelerate future efforts aimed to dissect genetic architecture of RSA and breed more resilient varieties.

Genome-wide association study of drought tolerance and biomass allocation in wheat

Genome wide association studies (GWAS) are important in discerning the genetic architecture of complex traits such as biomass allocation for improving drought tolerance and carbon sequestration potential of wheat. The objectives of this study were to deduce the population structure and marker-trait association for biomass traits in wheat under drought-stressed and non-stressed conditions. A 100-wheat (Triticum aestivum L.) genotype panel was phenotyped for days to heading (DTH), days to maturity (DTM), shoot biomass (SB), root biomass (RB), root to shoot ratio (RS) and grain yield (GY). The panel was sequenced using 15,600 single nucleotide polymorphism (SNPs) markers and subjected to genetic analysis using the compressed mixed linear model (CMLM) at false discovery rate (FDR < 0.05). Population structure analysis revealed six sub-clusters with high membership ancestry coefficient of ≤0.65 to their assigned sub-clusters. A total of 75 significant marker-trait associations (MTAs) were identified with a linkage disequilibrium threshold of 0.38 at 5cM. Thirty-seven of the MTAs were detected under drought-stressed condition and 48% were on the B genome, where most quantitative trait loci (QTLs) for RB, SB and GY were previously identified. There were seven pleiotropic markers for RB and SB that may facilitate simultaneous selection. Thirty-seven putative candidate genes were mined by gene annotation on the IWGSC RefSeq 1.1. The significant MTAs observed in this study will be useful in devising strategies for marker-assisted breeding for simultaneous improvement of drought tolerance and to enhance C sequestration capacity of wheat.

Root diversity in sesame (Sesamum indicum L.): insights into the morphological, anatomical and gene expression profiles

Sesame harbors a large diversity in root morphological and anatomical traits and a high root biomass improves the plant aboveground biomass as well as the seed yield. Sesame provides one of the most nutritious and healthy vegetable oils, sparking an increasing demand of its seeds. However, with the low yield and productivity of sesame, there is still a huge gap between the seed demand and supply. Improving the root system has a high potential to increase crop productivity, but information on the diversity of the sesame root systems is still lacking. In this study, 40 diverse sesame varieties were grown in soil and hydroponics systems and the diversity of the root system was investigated. The results showed that sesame holds a large root morphological and anatomical diversity, which can be harnessed in breeding programmes. Based on the clustering of the genotypes in hydroponics and soil culture systems, we found that similar genotypes were commonly clustered either in the small-root or in the big-root group, indicating that the hydroponics system can be employed for a large-scale root phenotyping. Our results further revealed that the root biomass positively contributes to increased seed yield in sesame, based on multi-environmental trials. By comparing the root transcriptome of two contrasting genotypes, 2897 differentially expressed genes were detected and they were enriched in phenylpropanoid biosynthesis, starch and sucrose metabolism, stilbenoid, diarylheptanoid and gingerol biosynthesis, flavonoid biosynthesis, suggesting that these pathways are crucial for sesame root growth and development. Overall, this study sheds light on the diversity of sesame root system and offers the basis for improving root traits and increasing sesame seed yield.

Quantitative trait loci for seeding root traits and the relationships between root and agronomic traits in common wheat

A completely developed and vigorous root system can provide a stable platform for aboveground plant organs. To identify loci controlling root traits that could be used in wheat (Triticum aestivum L.) breeding, 199 recombinant inbred lines were used to measure and analyze eight root traits. A total of 18 quantitative trait loci (QTL) located on chromosomes 1A, 2A, 2B, 2D, 4B, 4D, 6A, 7A, and 7B were identified. The phenotypic variation explained by these 18 QTL ranged from 3.27% to 11.75%, and the logarithm of odds scores ranged from 2.50 to 6.58. A comparison of physical intervals indicated several new QTL for root traits were identified. In addition, significant correlations between root and agronomic traits were detected and discussed. The results presented in this study, along with those of previous reports, suggest that chromosomes 2 and 7 likely play important roles in the growth and development of wheat roots.

Genetic Dissection of the Seminal Root System Architecture in Mediterranean Durum Wheat Landraces by Genome-Wide Association Study

Roots are crucial for adaptation to drought stress. However, phenotyping root systems is a difficult and time-consuming task due to the special feature of the traits in the process of being analyzed. Correlations between root system architecture (RSA) at the early stages of development and in adult plants have been reported. In this study, the seminal RSA was analysed on a collection of 160 durum wheat landraces from 21 Mediterranean countries and 18 modern cultivars. The landraces showed large variability in RSA, and differences in root traits were found between previously identified genetic subpopulations. Landraces from the eastern Mediterranean region, which is the driest and warmest within the Mediterranean Basin, showed the largest seminal root size in terms of root length, surface, and volume and the widest root angle, whereas landraces from eastern Balkan countries showed the lowest values. Correlations were found between RSA and yield-related traits in a very dry environment. The identification of molecular markers linked to the traits of interest detected 233 marker-trait associations for 10 RSA traits and grouped them in 82 genome regions named marker-train association quantitative trait loci (MTA-QTLs). Our results support the use of ancient local germplasm to widen the genetic background for root traits in breeding programs.

Drought Stress Tolerance in Wheat and Barley: Advances in Physiology, Breeding and Genetics Research

Climate change is a major threat to most of the agricultural crops grown in tropical and sub-tropical areas globally. Drought stress is one of the consequences of climate change that has a negative impact on crop growth and yield. In the past, many simulation models were proposed to predict climate change and drought occurrences, and it is extremely important to improve essential crops to meet the challenges of drought stress which limits crop productivity and production. Wheat and barley are among the most common and widely used crops due to their economic and social values. Many parts of the world depend on these two crops for food and feed, and both crops are vulnerable to drought stress. Improving drought stress tolerance is a very challenging task for wheat and barley researchers and more research is needed to better understand this stress. The progress made in understanding drought tolerance is due to advances in three main research areas: physiology, breeding, and genetic research. The physiology research focused on the physiological and biochemical metabolic pathways that plants use when exposed to drought stress. New wheat and barley genotypes having a high degree of drought tolerance are produced through breeding by making crosses from promising drought-tolerant genotypes and selecting among their progeny. Also, identifying genes contributing to drought tolerance is very important. Previous studies showed that drought tolerance is a polygenic trait and genetic constitution will help to dissect the gene network(s) controlling drought tolerance. This review explores the recent advances in these three research areas to improve drought tolerance in wheat and barley.

Drought Stress Tolerance in Wheat and Barley: Advances in Physiology, Breeding and Genetics Research

Climate change is a major threat to most of the agricultural crops grown in tropical and sub-tropical areas globally. Drought stress is one of the consequences of climate change that has a negative impact on crop growth and yield. In the past, many simulation models were proposed to predict climate change and drought occurrences, and it is extremely important to improve essential crops to meet the challenges of drought stress which limits crop productivity and production. Wheat and barley are among the most common and widely used crops due to their economic and social values. Many parts of the world depend on these two crops for food and feed, and both crops are vulnerable to drought stress. Improving drought stress tolerance is a very challenging task for wheat and barley researchers and more research is needed to better understand this stress. The progress made in understanding drought tolerance is due to advances in three main research areas: physiology, breeding, and genetic research. The physiology research focused on the physiological and biochemical metabolic pathways that plants use when exposed to drought stress. New wheat and barley genotypes having a high degree of drought tolerance are produced through breeding by making crosses from promising drought-tolerant genotypes and selecting among their progeny. Also, identifying genes contributing to drought tolerance is very important. Previous studies showed that drought tolerance is a polygenic trait and genetic constitution will help to dissect the gene network(s) controlling drought tolerance. This review explores the recent advances in these three research areas to improve drought tolerance in wheat and barley.

Genome-Wide Association Study Reveals Novel Genomic Regions Associated With High Grain Protein Content in Wheat Lines Derived From Wild Emmer Wheat

Grain protein content (GPC) and yield are of two important traits in wheat, but their negative correlation has hampered their simultaneous improvement in conventional breeding. Wild emmer wheat (Triticum turgidum ssp. dicoccoides) is an important genetic resource for wheat quality improvement. In this study, we report a genome-wide association study (GWAS) using 13116 DArT-seq markers to characterize GPC in 161 wheat lines derived from wild emmer. Using a general linear model, we identified 141 markers that were significantly associated with GPC, and grouped into 48 QTL regions. Using both general linear model and mixed linear model, we identified four significant markers that were grouped into two novel QTL regions on chromosomes 2BS (QGpc.cd1-2B.1) and 7BL (QGpc.cd1-7B.2). The two QTLs have no negative effects on thousand kernel weight (TKW) and should be useful for simultaneous improvement of GPC and TKW in wheat breeding. Searches of public databases revealed 61 putative candidate/flanking genes related to GPC. The putative proteins of interest were grouped in four main categories: enzymes, kinase proteins, metal transport-related proteins, and disease resistance proteins. The linked markers and associated candidate genes provide essential information for cloning genes related to high GPC and performing marker-assisted breeding in wheat.