Identification of novel QTL governing root architectural traits in an interspecific soybean population

Genome-Wide Association study for root system architecture traits in field soybean [Glycine max (L.) Merr.]

Roots play a crucial role in plant development, serving to absorb water and nutrients from the soil while also providing structural stability. However, the impacts of global warming can impede root growth by altering soil conditions that hinder overall plant growth. To address this challenge, there is a need to screen and identify plant genotypes with superior Root System Architecture traits (RSA), that can be used for future breeding efforts in enhancing their resilience to these environmental changes. In this project, 500 mid to late-maturity soybean accessions were grown on blue blotting papers hydroponically with six replicates and assessed seven RSA traits. Genome-Wide Association Studies (GWAS) were carried out with root phenotypic data and SNP data from the SoySNP50K iSelect SNP BeadChip, using both the TASSEL 5.0 and FarmCPU techniques. A total of 26 significant SNP-trait correlations were discovered, with 11 SNPs on chromosome 13. After SNP selection, we identified 14 candidate genes within 100-kb regions flanking the SNPs, which are related to root architecture. Notably, Glyma.17G258700, which exhibited substantial differential expression in root tips and its Arabidopsis homolog, AT4G24190 (GRP94) is involved in the regulation of meristem size and organization. Other candidate genes includes Glyma.03G023000 and Glyma.13G273500 that are also play a key role in lateral root initiation and root meristem growth, respectively. These findings significantly contribute to the discovery of key genes associated with root system architecture, facilitating the breeding of resilient cultivars adaptable to changing climates.

Genome-wide association study provides new insight into the underlying mechanism of drought tolerance during seed germination stage in soybean

Drought is one of the major environmental issues that reduce crop yield. Seed germination is a crucial stage of plant development in all crop plants, including soybean. In soybean breeding, information about genetic mechanism of drought tolerance has great importance. However, at germination stage, there is relatively little knowledge on the genetic basis of soybean drought resistance. The objective of this work was to find the quantitative trait nucleotides (QTNs) linked to drought tolerance related three traits using a genome-wide association study (GWAS), viz., germination rate (GR), root length (RL), and whole seedling length (WSL), using germplasm population of 240 soybean PIs with 34,817 SNPs genotype data having MAF > 0.05. It was observed that heritability (H2) for GR, WSL, and RL across both environments (2020, and 2019) were high in the range of 0.76-0.99, showing that genetic factors play a vital role in drought tolerance as compared to environmental factors. A number of 23 and 27 QTNs were found to be linked to three traits using MLM and mrMLM, respectively. Three significant QTNs, qGR8-1, qWSL13-1, and qRL-8, were identified using both MLM and mrMLM methods among these QTNs. QTN8, located on chromosome 8 was consistently linked to two traits (GR and RL). The area (± 100 Kb) associated with this QTN was screened for drought tolerance based on gene annotation. Fifteen candidate genes were found by this screening. Based on the expression data, four candidate genes i.e. Glyma08g156800, Glyma08g160000, Glyma08g162700, and Glyma13g249600 were found to be linked to drought tolerance regulation in soybean. Hence, the current study provides evidence to understand the genetic constitution of drought tolerance during the germination stage and identified QTNs or genes could be utilized in molecular breeding to enhance the yield under drought stress.

From phenotyping to genetic mapping: identifying water-stress adaptations in legume root traits

BACKGROUND

Climate change induces perturbation in the global water cycle, profoundly impacting water availability for agriculture and therefore global food security. Water stress encompasses both drought (i.e. water scarcity) that causes the drying of soil and subsequent plant desiccation, and flooding, which results in excess soil water and hypoxia for plant roots. Terrestrial plants have evolved diverse mechanisms to cope with soil water stress, with the root system serving as the first line of defense. The responses of roots to water stress can involve both structural and physiological changes, and their plasticity is a vital feature of these adaptations. Genetic methodologies have been extensively employed to identify numerous genetic loci linked to water stress-responsive root traits. This knowledge is immensely important for developing crops with optimal root systems that enhance yield and guarantee food security under water stress conditions.

RESULTS

This review focused on the latest insights into modifications in the root system architecture and anatomical features of legume roots in response to drought and flooding stresses. Special attention was given to recent breakthroughs in understanding the genetic underpinnings of legume root development under water stress. The review also described various root phenotyping techniques and examples of their applications in different legume species. Finally, the prevailing challenges and prospective research avenues in this dynamic field as well as the potential for using root system architecture as a breeding target are discussed.

CONCLUSIONS

This review integrated the latest knowledge of the genetic components governing the adaptability of legume roots to water stress, providing a reference for using root traits as the new crop breeding targets.

Identification of Quantitative Trait Loci Controlling Root Morphological Traits in an Interspecific Soybean Population Using 2D Imagery Data

Roots are the hidden and most important part of plants. They serve as stabilizers and channels for uptaking water and nutrients and play a crucial role in the growth and development of plants. Here, two-dimensional image data were used to identify quantitative trait loci (QTL) controlling root traits in an interspecific mapping population derived from a cross between wild soybean 'PI366121' and cultivar 'Williams 82'. A total of 2830 single-nucleotide polymorphisms were used for genotyping, constructing genetic linkage maps, and analyzing QTLs. Forty-two QTLs were identified on twelve chromosomes, twelve of which were identified as major QTLs, with a phenotypic variation range of 36.12% to 39.11% and a logarithm of odds value range of 12.01 to 17.35. Two significant QTL regions for the average diameter, root volume, and link average diameter root traits were detected on chromosomes 3 and 13, and both wild and cultivated soybeans contributed positive alleles. Six candidate genes, Glyma.03G027500 (transketolase/glycoaldehyde transferase), Glyma.03G014500 (dehydrogenases), Glyma.13G341500 (leucine-rich repeat receptor-like protein kinase), Glyma.13G341400 (AGC kinase family protein), Glyma.13G331900 (60S ribosomal protein), and Glyma.13G333100 (aquaporin transporter) showed higher expression in root tissues based on publicly available transcriptome data. These results will help breeders improve soybean genetic components and enhance soybean root morphological traits using desirable alleles from wild soybeans.

C-terminally encoded peptide-like genes are associated with the development of primary root at qRL16.1 in soybean

Root architecture traits are belowground traits that harness moisture and nutrients from the soil and are equally important to above-ground traits in crop improvement. In soybean, the root length locus qRL16.1 was previously mapped on chromosome 16. The qRL16.1 has been characterized by transcriptome analysis of roots in near-isogenic lines (NILs), gene expression analysis in a pair of lines contrasting with alleles of qRL16.1, and differential gene expression analysis in germplasm accessions contrasting with root length. Two candidate genes, Glyma.16g108500 and Glyma.16g108700, have shown relatively higher expression in longer root accessions than in shorter rooting accessions. The C-terminal domain of Glyma.16g108500 and Glyma.16g108700 is similar to the conserved domain of C-terminally encoded peptides (CEPs) that regulate root length and nutrient response in Arabidopsis. Two polymorphisms upstream of Glyma.16g108500 showed a significant association with primary root length and total root length traits in a germplasm set. Synthetic peptide assay with predicted CEP variants of Glyma.16g108500 and Glyma.16g108700 demonstrated their positive effect on primary root length. The two genes are root-specific in the early stage of soybean growth and showed differential expression only in the primary root. These genes will be useful for improving soybean to develop a deep and robust root system to withstand low moisture and nutrient regimes.

Phenotyping and metabolome analysis reveal the role of AdoMetDC and Di19 genes in determining acquired tolerance to drought in rice

Water-saving attempts for rice cultivation often reduce yields. Maintaining productivity under drought is possible when rice genotypes are bred with improved metabolism and spikelet fertility. Although attempts have been made to introgress water mining and water use efficiency traits, combining acquired tolerance traits (ATTs), that is, specific traits induced or upregulated to better tolerate severe stress, appears equally important. In our study, we screened 90 rice germplasm accessions that represented the molecular and phenotypic variations of 851 lines of the 3 K rice panel. Utilising phenomics, we identified markers linked to ATTs through association analysis of over 0.2 million SNPs derived from whole-genome sequences. Propensity to respond to 'induction' stress varied significantly among genotypes, reflecting differences in cellular protection against oxidative stress. Among the ATTs, the hydroxyl radical and proline contents exhibited the highest variability. Furthermore, these significant variations in ATTs were strongly correlated with spikelet fertility. The 43 significant markers associated with ATTs were further validated using a different subset of contrasting genotypes. Gene expression studies and metabolomic profiling of two well-known contrasting genotypes, APO (tolerant) and IR64 (sensitive), identified two ATT genes: AdoMetDC and Di19. Our study highlights the relevance of polyamine biosynthesis in modulating ATTs in rice. Genotypes with superior ATTs and the associated markers can be effectively employed in breeding rice varieties with sustained spikelet fertility and grain yield under drought.

Genome-wide association study for biomass accumulation traits in soybean

Soybean is one of the most versatile crops for oil production, human diets, and feedstocks. The vegetative biomass of soybean is an important determinant of seed yield and is crucial for the forage usages. However, the genetic control of soybean biomass is not well explained. In this work, we used a soybean germplasm population, including 231 improved cultivars, 207 landraces, and 121 wild soybeans, to investigate the genetic basis of biomass accumulation of soybean plants at the V6 stage. We found that biomass-related traits, including NDW (nodule dry weight), RDW (root dry weight), SDW (shoot dry weight), and TDW (total dry weight), were domesticated during soybean evolution. In total, 10 loci, encompassing 47 putative candidate genes, were detected for all biomass-related traits by a genome-wide association study. Among these loci, seven domestication sweeps and six improvement sweeps were identified. Glyma.05G047900, a purple acid phosphatase, was a strong candidate gene to improve biomass for future soybean breeding. This study provided new insights into the genetic basis of biomass accumulation during soybean evolution.

Supplementary information

The online version contains supplementary material available at 10.1007/s11032-023-01380-6.

Genome-Wide Association Studies of Seven Root Traits in Soybean (Glycine max L.) Landraces

Soybean [Glycine max (L.) Merr.], an important oilseed crop, is a low-cost source of protein and oil. In Southeast Asia and Africa, soybeans are widely cultivated for use as traditional food and feed and industrial purposes. Given the ongoing changes in global climate, developing crops that are resistant to climatic extremes and produce viable yields under predicted climatic conditions will be essential in the coming decades. To develop such crops, it will be necessary to gain a thorough understanding of the genetic basis of agronomic and plant root traits. As plant roots generally lie beneath the soil surface, detailed observations and phenotyping throughout plant development present several challenges, and thus the associated traits have tended to be ignored in genomics studies. In this study, we phenotyped 357 soybean landraces at the early vegetative (V2) growth stages and used a 180 K single-nucleotide polymorphism (SNP) soybean array in a genome-wide association study (GWAS) conducted to determine the phenotypic relationships among root traits, elucidate the genetic bases, and identify significant SNPs associated with root trait-controlling genomic regions/loci. A total of 112 significant SNP loci/regions were detected for seven root traits, and we identified 55 putative candidate genes considered to be the most promising. Our findings in this study indicate that a combined approach based on SNP array and GWAS analyses can be applied to unravel the genetic basis of complex root traits in soybean, and may provide an alternative high-resolution marker strategy to traditional bi-parental mapping. In addition, the identified SNPs, candidate genes, and diverse variations in the root traits of soybean landraces will serve as a valuable basis for further application in genetic studies and the breeding of climate-resilient soybeans characterized by improved root traits.

Divergence of functions and expression patterns of soybean bZIP transcription factors

Soybean (Glycine max) is a major protein and oil crop. Soybean basic region/leucine zipper (bZIP) transcription factors are involved in many regulatory pathways, including yield, stress responses, environmental signaling, and carbon-nitrogen balance. Here, we discuss the members of the soybean bZIP family and their classification: 161 members have been identified and clustered into 13 groups. Our review of the transcriptional regulation and functions of soybean bZIP members provides important information for future study of bZIP transcription factors and genetic resources for soybean breeding.

Identification of Drought-Tolerance Genes in the Germination Stage of Soybean

Drought stress influences the vigor of plant seeds and inhibits seed germination, making it one of the primary environmental factors adversely affecting food security. The seed germination stage is critical to ensuring the growth and productivity of soybeans in soils prone to drought conditions. We here examined the genetic diversity and drought-tolerance phenotypes of 410 accessions of a germplasm diversity panel for soybean and conducted quantitative genetics analyses to identify loci associated with drought tolerance of seed germination. We uncovered significant differences among the diverse genotypes for four growth indices and five drought-tolerance indices, which revealed abundant variation among genotypes, upon drought stress, and for genotype × treatment effects. We also used 158,327 SNP markers and performed GWAS for the drought-related traits. Our data met the conditions (PCA + K) for using a mixed linear model in TASSEL, and we thus identified 26 SNPs associated with drought tolerance indices for germination stage distributed across 10 chromosomes. Nine SNP sites, including, for example, Gm20_34956219 and Gm20_36902659, were associated with two or more phenotypic indices, and there were nine SNP markers located in or adjacent to (within 500 kb) previously reported drought tolerance QTLs. These SNPs led to our identification of 41 candidate genes related to drought tolerance in the germination stage. The results of our study contribute to a deeper understanding of the genetic mechanisms underlying drought tolerance in soybeans at the germination stage, thereby providing a molecular basis for identifying useful soybean germplasm for breeding new drought-tolerant varieties.

QTL analyses of soybean root system architecture revealed genetic relationships with shoot-related traits

The genetic basis of soybean root system architecture (RSA) and the genetic relationship between shoot and RSA were revealed by integrating data from recombinant inbred population grafting and QTL mapping. Variations in root system architecture (RSA) affect the functions of roots and thus play vital roles in plant adaptations and agricultural productivity. The aim of this study was to unravel the genetic relationship between RSA traits and shoot-related traits in soybean. This study characterized RSA variability at seedling stage in a recombinant inbred population, derived from a cross between cultivated soybean C08 and wild soybean W05, and performed high-resolution quantitative trait locus (QTL) mapping. In total, 34 and 41 QTLs were detected for RSA-related and shoot-related traits, respectively, constituting eight QTL clusters. Significant QTL correspondence was found between shoot biomass and RSA-related traits, consistent with significant correlations between these phenotypes. RSA-related QTLs also overlapped with selection regions in the genome, suggesting the cultivar RSA could be a partial consequence of domestication. Using reciprocal grafting, we confirmed that shoot-derived signals affected root development and the effects were controlled by multiple loci. Meanwhile, RSA-related QTLs were found to co-localize with four soybean flowering-time loci. Consistent with the phenotypes of the parental lines of our RI population, diminishing the function of flowering controlling E1 family through RNA interference (RNAi) led to reduced root growth. This implies that the flowering time-related genes within the RSA-related QTLs are actually contributing to RSA. To conclude, this study identified the QTLs that determine RSA through controlling root growth indirectly via regulating shoot functions, and discovered superior alleles from wild soybean that could be used to improve the root structure in existing soybean cultivars.

An allelic variant in the ACS7 gene promotes primary root growth in watermelon

Gene mining in a C. lanatus × C. amarus population revealed one gene, ACS7, linked to primary root elongation in watermelon. Watermelon is a xerophytic crop characterized by a long primary root and robust lateral roots. Therefore, watermelon serves as an excellent model for studying root elongation and development. However, the genetic mechanism underlying the primary root elongation in watermelon remains unknown. Herein, through bulk segregant analysis we identified a genetic locus, qPRL.Chr03, controlling primary root length (PRL) using two different watermelon species (Citrullus lanatus and Citrullus amarus) that differ in their root architecture. Fine mapping revealed that xaa-Pro dipeptidase and 1-aminocyclopropane-1-carboxylate synthase 7 (ACS7) are candidate regulators of the primary root growth. Allelic variation in the delimited region among 193 watermelon accessions indicated that the long-root alleles might only exist in C. amarus. Interestingly, the discrepancy in PRL among the C. amarus accessions was clearly associated with a nonsynonymous single nucleotide polymorphism variant within the ACS7 gene. The ACS7 expression and ethylene levels in the primary root tips suggested that ethylene is a negative regulator of root elongation in watermelon, as supported by the application of 1-aminocyclopropane-1-carboxylate (ACC, the ethylene precursor) or 2-aminoethoxyvinyl glycine (AVG, an ACS inhibitor). To the best of our knowledge, these findings provide the first description of the genetic basis of root elongation in watermelon. The detected markers of the ACS7 gene will facilitate marker-assisted selection for the PRL trait to improve water and nutrient use efficacy in watermelon and beyond.

Intraspecific Variation for Leaf Physiological and Root Morphological Adaptation to Drought Stress in Alfalfa (Medicago sativa L.)

Drought stress reduces crop biomass yield and the profitability of rainfed agricultural systems. Evaluation of populations or accessions adapted to diverse geographical and agro-climatic environments sheds light on beneficial plant responses to enhance and optimize yield in resource-limited environments. This study used the morphological and physiological characteristics of leaves and roots from two different alfalfa subspecies during progressive drought stress imposed on controlled and field conditions. Two different soils (Experiments 1 and 2) imposed water stress at different stress intensities and crop stages in the controlled environment. Algorithm-based image analysis of leaves and root systems revealed key morphological and physiological traits associated with biomass yield under stress. The Medicago sativa subspecies (ssp.) sativa population, PI478573, had smaller leaves and maintained higher chlorophyll content (CC), leaf water potential, and osmotic potential under water stress. In contrast, M. sativa ssp. varia, PI502521, had larger leaves, a robust root system, and more biomass yield. In the field study, an unmanned aerial vehicle survey revealed PI502521 to have a higher normalized difference vegetation index (vegetation cover and plant health characteristics) throughout the cropping season, whereas PI478573 values were low during the hot summer and yielded low biomass in both irrigated and rainfed treatments. RhizoVision Explorer image analysis of excavated roots revealed a smaller diameter and a narrow root angle as target traits to increase alfalfa biomass yield irrespective of water availability. Root architectural traits such as network area, solidity, volume, surface area, and maximum radius exhibited significant variation at the genotype level only under limited water availability. Different drought-adaptive strategies identified across subspecies populations will benefit the plant under varying levels of water limitation and facilitate the development of alfalfa cultivars suitable across a broad range of growing conditions. The alleles from both subspecies will enable the development of drought-tolerant alfalfa with enhanced productivity under limited water availability.

Dissecting the Root Phenotypic and Genotypic Variability of the Iowa Mung Bean Diversity Panel

Mung bean [Vigna radiata (L.) Wilczek] is a drought-tolerant, short-duration crop, and a rich source of protein and other valuable minerals, vitamins, and antioxidants. The main objectives of this research were (1) to study the root traits related with the phenotypic and genetic diversity of 375 mung bean genotypes of the Iowa (IA) diversity panel and (2) to conduct genome-wide association studies of root-related traits using the Automated Root Image Analysis (ARIA) software. We collected over 9,000 digital images at three-time points (days 12, 15, and 18 after germination). A broad sense heritability for days 15 (0.22-0.73) and 18 (0.23-0.87) was higher than that for day 12 (0.24-0.51). We also reported root ideotype classification, i.e., PI425425 (India), PI425045 (Philippines), PI425551 (Korea), PI264686 (Philippines), and PI425085 (Sri Lanka) that emerged as the top five in the topsoil foraging category, while PI425594 (unknown origin), PI425599 (Thailand), PI425610 (Afghanistan), PI425485 (India), and AVMU0201 (Taiwan) were top five in the drought-tolerant and nutrient uptake "steep, cheap, and deep" ideotype. We identified promising genotypes that can help diversify the gene pool of mung bean breeding stocks and will be useful for further field testing. Using association studies, we identified markers showing significant associations with the lateral root angle (LRA) on chromosomes 2, 6, 7, and 11, length distribution (LED) on chromosome 8, and total root length-growth rate (TRL_GR), volume (VOL), and total dry weight (TDW) on chromosomes 3 and 5. We discussed genes that are potential candidates from these regions. We reported beta-galactosidase 3 associated with the LRA, which has previously been implicated in the adventitious root development via transcriptomic studies in mung bean. Results from this work on the phenotypic characterization, root-based ideotype categories, and significant molecular markers associated with important traits will be useful for the marker-assisted selection and mung bean improvement through breeding.

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.

Underground heterosis for yield improvement in melon

Heterosis, the superiority of hybrids over their parents, is a major genetic force associated with plant fitness and crop yield enhancement. We investigated root-mediated yield heterosis in melons (Cucumis melo) by characterizing a common variety grafted onto 190 hybrid rootstocks, resulting from crossing 20 diverse inbreds in a diallel-mating scheme. Hybrid rootstocks improved yield by more than 40% compared with their parents, and the best hybrid yield outperformed the reference commercial variety by 65% under both optimal and minimal irrigation treatments. To characterize the genetics of underground heterosis we conducted whole genome re-sequencing of the 20 founder lines, and showed that parental genetic distance was no predictor for the level of heterosis. Through inference of the 190 hybrid genotypes from their parental genomes, followed by genome-wide association analysis, we mapped multiple quantitative trait loci for root-mediated yield. Yield enhancement of the four best-performing hybrid rootstocks was validated in multiple experiments with four different scion varieties. Our grafting approach is complementary to the common roots genetic approach that focuses mainly on variation in root system architecture, and is a step towards discovery of candidate genes involved in root function and yield enhancement.

Comprehensive RNA-seq analysis revealed molecular pathways and genes associated with drought tolerance in wild soybean (Glycine soja Sieb. and Zucc.)

Drought stress at the germination stage is an important environmental stress limiting crop yield. Hence, our study investigated comparative root transcriptome profiles of four contrasting soybean genotypes viz., drought-tolerant (PI342618B/DTP and A214/DTL) and drought-sensitive (NN86-4/DSP and A195/DSL) under drought stress using RNA-Seq approach. A total of 4850 and 6272 differentially expressed genes (DEGs) were identified in tolerant (DTP and DTL) and sensitive (DSP and DSL) genotypes, respectively. Principle component analysis (PCA) and correlation analysis revealed higher correlation between DTP and DTL. Both gene ontology (GO) and MapMan analyses showed that the drought response was enriched in DEGs associated with water and auxin transport, cell wall/membrane, antioxidant activity, catalytic activity, secondary metabolism, signaling and transcription factor (TF) activities. Out of 981 DEGs screened from above terms, only 547 showed consistent opposite expression between contrasting genotypes. Twenty-eight DEGs of 547 were located on Chr.08 rich in QTLs and "Hotspot regions" associated with drought stress, and eight of them showed non-synonymous single nucleotide polymorphism. Hence, 10 genes (including above eight genes plus two hub genes) were predicated as possible candidates regulating drought tolerance, which needs further functional validation. Overall, the transcriptome profiling provided in-depth understanding about the genetic mechanism and candidate genes underlying drought tolerance in soybean.

Mapping and validation of a major QTL for primary root length of soybean seedlings grown in hydroponic conditions

BACKGROUND

The root system provides nutrient absorption and is closely related to abiotic stress tolerance, but it is difficult to study the roots under field conditions. This study was conducted to identify quantitative trait loci (QTL) associated with primary root length (PRL) during soybean seedling growth in hydroponic conditions. A total of 103 F7 recombinant inbred lines (RILs) derived from a cross between K099 (short primary root) and Fendou 16 (long primary root) were used to identify QTL for PRL in soybean. The RIL population was genotyped with 223 simple sequence repeats markers covering 20 chromosomes. Phenotyping for primary root length was performed for 3-weeks plants grown in hydoponic conditions. The identified QTL was validated in near isogenic lines and in a separate RIL population.

RESULTS

QTL analysis using inclusive composite interval mapping method identified a major QTL on Gm16 between SSR markers Sat_165 and Satt621, explaining 30.25 % of the total phenotypic variation. The identified QTL, qRL16.1, was further confirmed in a segregating population derived from a residual heterozygous line (RHLs-98). To validate qRL16.1 in a different genetic background, QTL analysis was performed in another F6 RIL population derived from a cross between Union (medium primary root) and Fendou 16, in which a major QTL was detected again in the same genomic region as qRL16.1, explaining 14 % of the total phenotypic variation for PRL. In addition, the effect of qRL16.1 was confirmed using two pair of near-isogenic lines (NILs). PRL was significantly higher in NILs possessing the qRL16.1 allele from Fendou 16 compared to allele from K099.

CONCLUSIONS

The qRL16.1 is a novel QTL for primary root length in soybean which provides important information on the genetic control of root development. Identification of this major QTL will facilitate positional cloning and DNA marker-assisted selection for root traits in soybean.

Genome-Wide Association Study of Root and Shoot Related Traits in Spring Soybean (Glycine max L.) at Seedling Stages Using SLAF-Seq

Root systems can display variable genetic architectures leading to nutrient foraging or improving abiotic stress tolerance. Breeding for new soybean varieties with efficient root systems has tremendous potential in enhancing resource use efficiency and plant adaptation for challenging climates. In this study, root related traits were analyzed in a panel of 260 spring soybean with genome-wide association study (GWAS). Genotyping was done with specific locus amplified fragment sequencing (SLAF-seq), and five GWAS models (GLM, MLM, CMLM, FaST-LMM, and EMMAX) were used for analysis. A total of 179,960 highly consistent SNP markers distributed over the entire genome with an inter-marker distance of 2.36 kb was used for GWAS analysis. Overall, 27 significant SNPs with a phenotypic contribution ranging from 20 to 72% and distributed on chromosomes 2, 6, 8, 9, 13, 16 and 18 were identified and two of them were found to be associated with multiple root-related traits. Based on the linkage disequilibrium (LD) distance of 9.5 kb for the different chromosomes, 11 root and shoot regulating genes were detected based on LD region of a maximum 55-bp and phenotypic contribution greater than 22%. Expression analysis revealed an association between expression levels of those genes and the degree of root branching number. The current study provides new insights into the genetic architecture of soybean roots, and the underlying SNPs/genes could be critical for future breeding of high-efficient root system in soybean.

Harnessing High-throughput Phenotyping and Genotyping for Enhanced Drought Tolerance in Crop Plants

Development of drought-tolerant cultivars is one of the challenging tasks for the plant breeders due to its complex inheritance and polygenic regulation. Evaluating genetic material for drought tolerance is a complex process due to its spatiotemporal interactions with environmental factors. The conventional breeding approaches are costly, lengthy, and inefficient to achieve the expected gain in drought tolerance. In this regard, genomics-assisted breeding (GAB) offers promise to develop cultivars with improved drought tolerance in a more efficient, quicker, and cost-effective manner. The success of GAB depends upon the precision in marker-trait association and estimation of genomic estimated breeding values (GEBVs), which mostly depends on coverage and precision of genotyping and phenotyping. A wide gap between the discovery and practical use of quantitative trait loci (QTL) for crop improvement has been observed for many important agronomical traits. Such a limitation could be due to the low accuracy in QTL detection, mainly resulting from low marker density and manually collected phenotypes of complex agronomic traits. Increasing marker density using the high-throughput genotyping (HTG), and accurate and precise phenotyping using high-throughput digital phenotyping (HTP) platforms can improve the precision and power of QTL detection. Therefore, both HTG and HTP can enhance the practical utility of GAB along with a faster characterization of germplasm and breeding material. In the present review, we discussed how the recent innovations in HTG and HTP would assist in the breeding of improved drought-tolerant varieties. We have also discussed strategies, tools, and analytical advances made on the HTG and HTP along with their pros and cons.

The Impacts of Domestication and Agricultural Practices on Legume Nutrient Acquisition Through Symbiosis With Rhizobia and Arbuscular Mycorrhizal Fungi

Legumes are unique among plants as they can obtain nitrogen through symbiosis with nitrogen-fixing rhizobia that form root nodules in the host plants. Therefore they are valuable crops for sustainable agriculture. Increasing nitrogen fixation efficiency is not only important for achieving better plant growth and yield, but it is also crucial for reducing the use of nitrogen fertilizer. Arbuscular mycorrhizal fungi (AMF) are another group of important beneficial microorganisms that form symbiotic relationships with legumes. AMF can promote host plant growth by providing mineral nutrients and improving the soil ecosystem. The trilateral legume-rhizobia-AMF symbiotic relationships also enhance plant development and tolerance against biotic and abiotic stresses. It is known that domestication and agricultural activities have led to the reduced genetic diversity of cultivated germplasms and higher sensitivity to nutrient deficiencies in crop plants, but how domestication has impacted the capability of legumes to establish beneficial associations with rhizospheric microbes (including rhizobia and fungi) is not well-studied. In this review, we will discuss the impacts of domestication and agricultural practices on the interactions between legumes and soil microbes, focusing on the effects on AMF and rhizobial symbioses and hence nutrient acquisition by host legumes. In addition, we will summarize the genes involved in legume-microbe interactions and studies that have contributed to a better understanding of legume symbiotic associations using metabolic modeling.

Mapping Quantitative Trait Loci for Soybean Seedling Shoot and Root Architecture Traits in an Inter-Specific Genetic Population

Wild soybean species (Glycine soja Siebold & Zucc.) comprise a unique resource to widen the genetic base of cultivated soybean [Glycine max (L.) Merr.] for various agronomic traits. An inter-specific mapping population derived from a cross of cultivar Williams 82 and PI 483460B, a wild soybean accession, was utilized for genetic characterization of root architecture traits. The objectives of this study were to identify and characterize quantitative trait loci (QTL) for seedling shoot and root architecture traits, as well as to determine additive/epistatic interaction effects of identified QTLs. A total of 16,469 single nucleotide polymorphisms (SNPs) developed for the Illumina beadchip genotyping platform were used to construct a high resolution genetic linkage map. Among the 11 putative QTLs identified, two significant QTLs on chromosome 7 were determined to be associated with total root length (RL) and root surface area (RSA) with favorable alleles from the wild soybean parent. These seedling root traits, RL (BARC_020495_04641 ~ BARC_023101_03769) and RSA (SNP02285 ~ SNP18129_Magellan), could be potential targets for introgression into cultivated soybean background to improve both tap and lateral roots. The RL QTL region harbors four candidate genes with higher expression in root tissues: Phosphofructokinase (Glyma.07g126400), Snf7 protein (Glyma.07g127300), unknown functional gene (Glyma.07g127900), and Leucine Rich-Repeat protein (Glyma.07g127100). The novel alleles inherited from the wild soybean accession could be used as molecular markers to improve root system architecture and productivity in elite soybean lines.

Soybean Root System Architecture Trait Study through Genotypic, Phenotypic, and Shape-Based Clusters

We report a root system architecture (RSA) traits examination of a larger scale soybean accession set to study trait genetic diversity. Suffering from the limitation of scale, scope, and susceptibility to measurement variation, RSA traits are tedious to phenotype. Combining 35,448 SNPs with an imaging phenotyping platform, 292 accessions (replications = 14) were studied for RSA traits to decipher the genetic diversity. Based on literature search for root shape and morphology parameters, we used an ideotype-based approach to develop informative root (iRoot) categories using root traits. The RSA traits displayed genetic variability for root shape, length, number, mass, and angle. Soybean accessions clustered into eight genotype- and phenotype-based clusters and displayed similarity. Genotype-based clusters correlated with geographical origins. SNP profiles indicated that much of US origin genotypes lack genetic diversity for RSA traits, while diverse accession could infuse useful genetic variation for these traits. Shape-based clusters were created by integrating convolution neural net and Fourier transformation methods, enabling trait cataloging for breeding and research applications. The combination of genetic and phenotypic analyses in conjunction with machine learning and mathematical models provides opportunities for targeted root trait breeding efforts to maximize the beneficial genetic diversity for future genetic gains.

Genome-Wide Association Study of Topsoil Root System Architecture in Field-Grown Soybean [Glycine max (L.) Merr.]

Water and nutrient acquisition is a critical function of plant root systems. Root system architecture (RSA) traits are often complex and controlled by many genes. This is the first genome-wide association study reporting genetic loci for RSA traits for field-grown soybean (Glycine max). A collection of 289 soybean genotypes was grown in three environments, root crowns were excavated, and 12 RSA traits assessed. The first two components of a principal component analysis of these 12 traits were used as additional aggregate traits for a total of 14 traits. Marker-trait association for RSA traits were identified using 31,807 single-nucleotide polymorphisms (SNPs) by a genome-wide association analysis. In total, 283 (non-unique) SNPs were significantly associated with one or more of the 14 root traits. Of these, 246 were unique SNPs and 215 SNPs were associated with a single root trait, while 26, four, and one SNPs were associated with two, three, and four root traits, respectively. The 246 SNPs marked 67 loci associated with at least one of the 14 root traits. Seventeen loci on 13 chromosomes were identified by SNPs associated with more than one root trait. Several genes with annotation related to processes that could affect root architecture were identified near these 67 loci. Additional follow-up studies will be needed to confirm the markers and candidate genes identified for RSA traits and to examine the importance of the different root characteristics for soybean productivity under a range of soil and environmental conditions.

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.

Current Perspectives on Introgression Breeding in Food Legumes

Food legumes are important for defeating malnutrition and sustaining agri-food systems globally. Breeding efforts in legume crops have been largely confined to the exploitation of genetic variation available within the primary genepool, resulting in narrow genetic base. Introgression as a breeding scheme has been remarkably successful for an array of inheritance and molecular studies in food legumes. Crop wild relatives (CWRs), landraces, and exotic germplasm offer great potential for introgression of novel variation not only to widen the genetic base of the elite genepool for continuous incremental gains over breeding cycles but also to discover the cryptic genetic variation hitherto unexpressed. CWRs also harbor positive quantitative trait loci (QTLs) for improving agronomic traits. However, for transferring polygenic traits, "specialized population concept" has been advocated for transferring QTLs from CWR into elite backgrounds. Recently, introgression breeding has been successful in developing improved cultivars in chickpea (Cicer arietinum), pigeonpea (Cajanus cajan), peanut (Arachis hypogaea), lentil (Lens culinaris), mungbean (Vigna radiata), urdbean (Vigna mungo), and common bean (Phaseolus vulgaris). Successful examples indicated that the usable genetic variation could be exploited by unleashing new gene recombination and hidden variability even in late filial generations. In mungbean alone, distant hybridization has been deployed to develop seven improved commercial cultivars, whereas in urdbean, three such cultivars have been reported. Similarly, in chickpea, three superior cultivars have been developed from crosses between C. arietinum and Cicer reticulatum. Pigeonpea has benefited the most where different cytoplasmic male sterility genes have been transferred from CWRs, whereas a number of disease-resistant germplasm have also been developed in Phaseolus. As vertical gene transfer has resulted in most of the useful gene introgressions of practical importance in food legumes, the horizontal gene transfer through transgenic technology, somatic hybridization, and, more recently, intragenesis also offer promise. The gains through introgression breeding are significant and underline the need of bringing it in the purview of mainstream breeding while deploying tools and techniques to increase the recombination rate in wide crosses and reduce the linkage drag. The resurgence of interest in introgression breeding needs to be capitalized for development of commercial food legume cultivars.

Temporal genetic patterns of root growth in Brassica napus L. revealed by a low-cost, high-efficiency hydroponic system

Application of a low-cost and high-efficiency hydroponic system in a rapeseed population verified two types of genetic factors ("persistent" and "stage-specific") that control root development. The root system is a vital plant component for nutrient and water acquisition and is targeted to enhance plant productivity. Genetic dissection of the root system generally focuses on a single stage, but roots grow continuously during plant development. To reveal the temporal genetic patterns of root development, we measured nine root-related traits in a rapeseed recombinant inbred line population at six continuous stages during vegetative growth, using a modified hydroponic system with low-cost and high-efficiency features that could synchronize plant growth under controlled conditions. Phenotypic correlation and growth dynamic analysis suggested the existence of two types of genetic factors ("persistent" and "stage-specific") that control root development. Dynamic (unconditional and conditional) quantitative trait loci (QTL) mapping detected 28 stage-specific and 23 persistent QTLs related to root growth. Among them, 13 early stage-specific, 19 persistent and 8 later stage-specific QTLs were detected at 7 DAS (days after sowing), 16 DAS and 5 EL (expanding leaf stage), respectively, providing efficient and adaptable stages for QTL identification. The effective prediction of biomass accumulation using root morphological traits (up to 96.6% or 92.64% at a specific stage or the final stage, respectively) verified that root growth allocation with maximum root uptake area facilitated biomass accumulation. Furthermore, marker-assistant selection, which combined the "persistent" and "stage-specific" QTLs, proved their effectiveness for root improvement with an excellent uptake area. Our results highlight the potential of high-throughput and precise phenotyping to assess the dynamic genetics of root growth and provide new insights into ideotype root system-based biomass breeding.

Genome-wide association mapping for seed protein and oil contents using a large panel of soybean accessions

Soybean is globally cultivated primarily for its protein and oil. The protein and oil contents of the seeds are quantitatively inherited traits determined by the interaction of numerous genes. In order to gain a better understanding of the molecular foundation of soybean protein and oil content for the marker-assisted selection (MAS) of high quality traits, a population of 185 soybean germplasms was evaluated to identify the quantitative trait loci (QTLs) associated with the seed protein and oil contents. Using specific length amplified fragment sequencing (SLAF-seq) technology, a total of 12,072 single nucleotide polymorphisms (SNPs) with a minor allele frequency (MAF) ≥ 0.05 were detected across the 20 chromosomes (Chr), with a marker density of 78.7 kbp. A total of 31 SNPs located on 12 of the 20 soybean chromosomes were correlated with seed protein and oil content. Of the 31 SNPs that were associated with the two target traits, 31 beneficial alleles were identified. Two SNP markers, namely rs15774585 and rs15783346 on Chr 07, were determined to be related to seed oil content both in 2015 and 2016. Three SNP markers, rs53140888 on Chr 01, rs19485676 on Chr 13, and rs24787338 on Chr 20 were correlated with seed protein content both in 2015 and 2016. These beneficial alleles may potentially contribute towards the MAS of favorable soybean protein and oil characteristics.

Understanding genetic control of root system architecture in soybean: Insights into the genetic basis of lateral root number

Developing crops with better root systems is a promising strategy to ensure productivity in both optimum and stress environments. Root system architectural traits in 397 soybean accessions were characterized and a high-density single nucleotide polymorphisms (SNPs)-based genome-wide association study was performed to identify the underlying genes associated with root structure. SNPs associated with root architectural traits specific to landraces and elite germplasm pools were detected. Four loci were detected in landraces for lateral root number (LRN) and distribution of root thickness in diameter Class I with a major locus on chromosome 16. This major loci was detected in the coding region of unknown protein, and subsequent analyses demonstrated that root traits are affected with mutated haplotypes of the gene. In elite germplasm pool, 3 significant SNPs in alanine-glyoxalate aminotransferase, Leucine-Rich Repeat receptor/No apical meristem, and unknown functional genes were found to govern multiple traits including root surface area and volume. However, no major loci were detected for LRN in elite germplasm. Nucleotide diversity analysis found evidence of selective sweeps around the landraces LRN gene. Soybean accessions with minor and mutated allelic variants of LRN gene were found to perform better in both water-limited and optimal field conditions.

An Automated Image Analysis Pipeline Enables Genetic Studies of Shoot and Root Morphology in Carrot (Daucus carota L.)

Carrot is a globally important crop, yet efficient and accurate methods for quantifying its most important agronomic traits are lacking. To address this problem, we developed an automated image analysis platform that extracts components of size and shape for carrot shoots and roots, which are necessary to advance carrot breeding and genetics. This method reliably measured variation in shoot size and shape, petiole number, petiole length, and petiole width as evidenced by high correlations with hundreds of manual measurements. Similarly, root length and biomass were accurately measured from the images. This platform also quantified shoot and root shapes in terms of principal components, which do not have traditional, manually measurable equivalents. We applied the pipeline in a study of a six-parent diallel population and an F2 mapping population consisting of 316 individuals. We found high levels of repeatability within a growing environment, with low to moderate repeatability across environments. We also observed co-localization of quantitative trait loci for shoot and root characteristics on chromosomes 1, 2, and 7, suggesting these traits are controlled by genetic linkage and/or pleiotropy. By increasing the number of individuals and phenotypes that can be reliably quantified, the development of a rapid, automated image analysis pipeline to measure carrot shoot and root morphology will expand the scope and scale of breeding and genetic studies.

Genetic diversity of root system architecture in response to drought stress in grain legumes

Climate change has increased the occurrence of extreme weather patterns globally, causing significant reductions in crop production, and hence threatening food security. In order to meet the food demand of the growing world population, a faster rate of genetic gains leading to productivity enhancement for major crops is required. Grain legumes are an essential commodity in optimal human diets and animal feed because of their unique nutritional composition. Currently, limited water is a major constraint in grain legume production. Root system architecture (RSA) is an important developmental and agronomic trait, which plays vital roles in plant adaptation and productivity under water-limited environments. A deep and proliferative root system helps extract sufficient water and nutrients under these stress conditions. The integrated genetics and genomics approach to dissect molecular processes from genome to phenome is key to achieve increased water capture and use efficiency through developing better root systems. Success in crop improvement under drought depends on discovery and utilization of genetic variations existing in the germplasm. In this review, we summarize current progress in the genetic diversity in major legume crops, quantitative trait loci (QTLs) associated with RSA, and the importance and applications of recent discoveries associated with the beneficial root traits towards better RSA for enhanced drought tolerance and yield.

Quantitative trait loci analysis of root traits under phosphorus deficiency at the seedling stage in wheat

Deficiency of available phosphorus (P) in soil limits wheat production and creates a need to develop P-deficiency-tolerant cultivars. Plant roots, important organs for absorbing nutrients and synthesizing growth regulators, are good candidates for P-efficiency screening. In this study, we evaluated five root traits under hydroponic culture conditions either with (AP) or without (NP) applied P in a recombinant inbred line population (H461/CM107) of Triticum aestivum L. at the seedling stage. Four significant quantitative trait loci (QTL) were detected, on chromosomes 1D, 2D, 3D, and 7D in NP-treated plants, explaining up to 13.0%, 11.0%, 14.4%, and 12.8% of the phenotypic variance, respectively. Among these QTL, Qrt.sicau-3D and Qrt.sicau-7D showed pleiotropic and additive effects. All QTL were found to be novel. The diversity array technology markers flanking the QTL were converted to simple sequence repeat markers that can be deployed in future genetic studies of P deficiency. These QTL lead to an increase in root biomass and respond to P-deficiency stress; these characteristics are crucial to improve root traits for breeding or further investigation of the gene(s) involved in P-deficiency tolerance.

Root xylem plasticity to improve water use and yield in water-stressed soybean

We tested the hypothesis that increasing the number of metaxylem vessels would enhance the efficiency of water uptake in soybean (Glycine max) and decrease the yield gap in water-limited environments. A panel of 41 soybean accessions was evaluated in greenhouse, rainout shelter, and rain-fed field environments. The metaxylem number influenced the internal capture of CO2 and improved stomatal conductance, enhancing water uptake/use in soybeans exposed to stress during the reproductive stage. We determined that other root anatomical features, such as cortex cell area and the percentage of stele that comprised cortical cells, also affected seed yield under similar growth parameters. Seed yield was also impacted by pod retention rates under drought stress (24-80 pods/plant). We surmise that effective biomass allocation, that is, the transport of available photosynthates to floral structures at late reproductive growth stages (R6-R7), enables yield protection under drought stress. A mesocosm study of contrasting lines for yield under drought stress and root anatomical features revealed that increases in metaxylem number as an adaptation to drought in the high-yielding lines improved root hydraulic conductivity, which reduced the metabolic cost of exploring water in deeper soil strata and enhanced water transport. This allowed the maintenance of shoot physiological processes under water-limited conditions.

Genetic diversity and genomic strategies for improving drought and waterlogging tolerance in soybeans

Drought and its interaction with high temperature are the major abiotic stress factors affecting soybean yield and production stability. Ongoing climate changes are anticipated to intensify drought events, which will further impact crop production and food security. However, excessive water also limits soybean production. The success of soybean breeding programmes for crop improvement is dependent on the extent of genetic variation present in the germplasm base. Screening for natural genetic variation in drought- and flooding tolerance-related traits, including root system architecture, water and nitrogen-fixation efficiency, and yield performance indices, has helped to identify the best resources for genetic studies in soybean. Genomic resources, including whole-genome sequences of diverse germplasms, millions of single-nucleotide polymorphisms, and high-throughput marker genotyping platforms, have expedited gene and marker discovery for translational genomics in soybean. This review highlights the current knowledge of the genetic diversity and quantitative trait loci associated with root system architecture, canopy wilting, nitrogen-fixation ability, and flooding tolerance that contributes to the understanding of drought- and flooding-tolerance mechanisms in soybean. Next-generation mapping approaches and high-throughput phenotyping will facilitate a better understanding of phenotype-genotype associations and help to formulate genomic-assisted breeding strategies, including genomic selection, in soybean for tolerance to drought and flooding stress.

Potential Uses of Wild Germplasms of Grain Legumes for Crop Improvement

Challenged by population increase, climatic change, and soil deterioration, crop improvement is always a priority in securing food supplies. Although the production of grain legumes is in general lower than that of cereals, the nutritional value of grain legumes make them important components of food security. Nevertheless, limited by severe genetic bottlenecks during domestication and human selection, grain legumes, like other crops, have suffered from a loss of genetic diversity which is essential for providing genetic materials for crop improvement programs. Illustrated by whole-genome-sequencing, wild relatives of crops adapted to various environments were shown to maintain high genetic diversity. In this review, we focused on nine important grain legumes (soybean, peanut, pea, chickpea, common bean, lentil, cowpea, lupin, and pigeonpea) to discuss the potential uses of their wild relatives as genetic resources for crop breeding and improvement, and summarized the various genetic/genomic approaches adopted for these purposes.

Characterization of Genetic Basis on Synergistic Interactions between Root Architecture and Biological Nitrogen Fixation in Soybean

Soybean [Glycine max (L.) Merr] is an important legume crop and its yield largely depends on root architecture (RA) and biological nitrogen fixation (BNF). However, the relationship between RA and BNF, and its genetics behind remain unclear. Here, two soybean genotypes contrasting in RA and their 175 F_9:11 recombinant inbred lines (RILs) were evaluated in field. The shallow-root parent, JD12, had better nodulation and higher yield than the deep-root parent, NF58. Strong correlations between shoot dry weight (SDW) and RA or BNF traits existed in the RILs, and the shallow-root group had more and heavier nodules, as well as higher SDW. After inoculating with rhizobia, roots became shallower and bigger, showing strong synergistic interactions between RA and BNF. In total, 70 QTLs were identified for the 21 tested traits. Among them, qBNF-RA-C2, qBNF-RA-O, and qBNF-RA-B1, were newly identified QTLs for BNF and/or RA traits in soybean, which co-located with the QTLs for SDW detected presently, and with the QTLs for yield identified previously. The results together suggest that there are synergistic interactions between RA and BNF, and the QTLs identified here could be used for breeding new soybean varieties with higher yields through optimization of RA traits and BNF capacity.

QTLomics in Soybean: A Way Forward for Translational Genomics and Breeding

Food legumes play an important role in attaining both food and nutritional security along with sustainable agricultural production for the well-being of humans globally. The various traits of economic importance in legume crops are complex and quantitative in nature, which are governed by quantitative trait loci (QTLs). Mapping of quantitative traits is a tedious and costly process, however, a large number of QTLs has been mapped in soybean for various traits albeit their utilization in breeding programmes is poorly reported. For their effective use in breeding programme it is imperative to narrow down the confidence interval of QTLs, to identify the underlying genes, and most importantly allelic characterization of these genes for identifying superior variants. In the field of functional genomics, especially in the identification and characterization of gene responsible for quantitative traits, soybean is far ahead from other legume crops. The availability of genic information about quantitative traits is more significant because it is easy and effective to identify homologs than identifying shared syntenic regions in other crop species. In soybean, genes underlying QTLs have been identified and functionally characterized for phosphorous efficiency, flowering and maturity, pod dehiscence, hard-seededness, α-Tocopherol content, soybean cyst nematode, sudden death syndrome, and salt tolerance. Candidate genes have also been identified for many other quantitative traits for which functional validation is required. Using the sequence information of identified genes from soybean, comparative genomic analysis of homologs in other legume crops could discover novel structural variants and useful alleles for functional marker development. The functional markers may be very useful for molecular breeding in soybean and harnessing benefit of translational research from soybean to other leguminous crops. Thus, soybean crop can act as a model crop for translational genomics and breeding of quantitative traits in legume crops. In this review, we summarize current status of identification and characterization of genes underlying QTLs for various quantitative traits in soybean and their significance in translational genomics and breeding of other legume crops.

Improvement in nitrogen fixation capacity could be part of the domestication process in soybean

Biological nitrogen fixation (BNF) in soybeans is a complex process involving the interplay between the plant host and the symbiotic rhizobia. As nitrogen supply has a crucial role in growth and development, higher nitrogen fixation capacity would be important to achieve bigger plants and larger seeds, which were important selection criteria during plant domestication by humans. To test this hypothesis, we monitored the nitrogen fixation-related performance in 31 cultivated and 17 wild soybeans after inoculation with the slow-growing Bradyrhizobium diazoefficiens sp. nov. USDA110 and the fast-growing Sinorhizobium (Ensifer) fredii CCBAU45436. Our results showed that, in general, cultivated soybeans gave better performance in BNF. Electron microscopic studies indicated that there was an exceptionally high accumulation of poly-β-hydroxybutyrate bodies in bacteroids in the nodules of all wild soybeans tested, suggesting that the C/N balance in wild soybeans may not be optimized for nitrogen fixation. Furthermore, we identified new quantitative trait loci (QTLs) for total ureides and total nodule fresh weight by employing a recombinant inbred population composed of descendants from a cross between a cultivated and a wild parent. Using nucleotide diversity (θπ), divergence index (Fst) and distribution of fixed single-nucleotide polymorphisms as parameters, we found that some regions in the total ureides QTL on chromosome 17 and the total nodule fresh weight QTL on chromosome 12 exhibited very low diversity among cultivated soybeans, suggesting that these were traits specially selected during the domestication and breeding process.

Evaluation of high yielding soybean germplasm under water limitation

Limited information is available for soybean root traits and their plasticity under drought stress. To date, no studies have focused on examining diverse soybean germplasm for regulation of shoot and root response under water limited conditions across varying soil types. In this study, 17 genetically diverse soybean germplasm lines were selected to study root response to water limited conditions in clay (trial 1) and sandy soil (trial 2) in two target environments. Physiological data on shoot traits was measured at multiple crop stages ranging from early vegetative to pod filling. The phenotypic root traits, and biomass accumulation data are collected at pod filling stage. In trial 1, the number of lateral roots and forks were positively correlated with plot yield under water limitation and in trial 2, lateral root thickness was positively correlated with the hill plot yield. Plant Introduction (PI) 578477A and 088444 were found to have higher later root number and forks in clay soil with higher yield under water limitation. In sandy soil, PI458020 was found to have a thicker lateral root system and higher yield under water limitation. The genotypes identified in this study could be used to enhance drought tolerance of elite soybean cultivars through improved root traits specific to target environments.

Genomic-assisted haplotype analysis and the development of high-throughput SNP markers for salinity tolerance in soybean

Soil salinity is a limiting factor of crop yield. The soybean is sensitive to soil salinity, and a dominant gene, Glyma03g32900 is primarily responsible for salt-tolerance. The identification of high throughput and robust markers as well as the deployment of salt-tolerant cultivars are effective approaches to minimize yield loss under saline conditions. We utilized high quality (15x) whole-genome resequencing (WGRS) on 106 diverse soybean lines and identified three major structural variants and allelic variation in the promoter and genic regions of the GmCHX1 gene. The discovery of single nucleotide polymorphisms (SNPs) associated with structural variants facilitated the design of six KASPar assays. Additionally, haplotype analysis and pedigree tracking of 93 U.S. ancestral lines were performed using publically available WGRS datasets. Identified SNP markers were validated, and a strong correlation was observed between the genotype and salt treatment phenotype (leaf scorch, chlorophyll content and Na(+) accumulation) using a panel of 104 soybean lines and, an interspecific bi-parental population (F8) from PI483463 x Hutcheson. These markers precisely identified salt-tolerant/sensitive genotypes (>91%), and different structural-variants (>98%). These SNP assays, supported by accurate phenotyping, haplotype analyses and pedigree tracking information, will accelerate marker-assisted selection programs to enhance the development of salt-tolerant soybean cultivars.

Identification of Quantitative Trait Loci Controlling Root and Shoot Traits Associated with Drought Tolerance in a Lentil (Lens culinaris Medik.) Recombinant Inbred Line Population

Drought is one of the major abiotic stresses limiting lentil productivity in rainfed production systems. Specific rooting patterns can be associated with drought avoidance mechanisms that can be used in lentil breeding programs. In all, 252 co-dominant and dominant markers were used for Quantitative Trait Loci (QTL) analysis on 132 lentil recombinant inbred lines based on greenhouse experiments for root and shoot traits during two seasons under progressive drought-stressed conditions. Eighteen QTLs controlling a total of 14 root and shoot traits were identified. A QTL-hotspot genomic region related to a number of root and shoot characteristics associated with drought tolerance such as dry root biomass, root surface area, lateral root number, dry shoot biomass and shoot length was identified. Interestingly, a QTL (QRSratioIX-2.30) related to root-shoot ratio, an important trait for drought avoidance, explaining the highest phenotypic variance of 27.6 and 28.9% for the two consecutive seasons, respectively, was detected. This QTL was closed to the co-dominant SNP marker TP6337 and also flanked by the two SNP TP518 and TP1280. An important QTL (QLRNIII-98.64) related to lateral root number was found close to TP3371 and flanked by TP5093 and TP6072 SNP markers. Also, a QTL (QSRLIV-61.63) associated with specific root length was identified close to TP1873 and flanked by F7XEM6b SRAP marker and TP1035 SNP marker. These two QTLs were detected in both seasons. Our results could be used for marker-assisted selection in lentil breeding programs targeting root and shoot characteristics conferring drought avoidance as an efficient alternative to slow and labor-intensive conventional breeding methods.

Genetic architecture of cyst nematode resistance revealed by genome-wide association study in soybean

BACKGROUND

Bi-parental mapping populations have been commonly utilized to identify and characterize quantitative trait loci (QTL) controlling resistance to soybean cyst nematode (SCN, Heterodera glycines Ichinohe). Although this approach successfully mapped a large number of SCN resistance QTL, it captures only limited allelic diversity that exists in parental lines, and it also has limitations for genomic resolution. In this study, a genome-wide association study (GWAS) was performed using a diverse set of 553 soybean plant introductions (PIs) belonging to maturity groups from III to V to detect QTL/genes associated with SCN resistance to HG Type 0.

RESULTS

Over 45,000 single nucleotide polymorphism (SNP) markers generated by the SoySNP50K iSelect BeadChip (http// www.soybase.org ) were utilized for analysis. GWAS identified 14 loci distributed over different chromosomes comprising 60 SNPs significantly associated with SCN resistance. Results also confirmed six QTL that were previously mapped using bi-parental populations, including the rhg1 and Rhg4 loci. GWAS identified eight novel QTL, including QTL on chromosome 10, which we have previously mapped by using a bi-parental population. In addition to the known loci for four simple traits, such as seed coat color, flower color, pubescence color, and stem growth habit, two traits, like lodging and pod shattering, having moderately complex inheritance have been confirmed with great precision by GWAS.

CONCLUSIONS

The study showed that GWAS can be employed as an effective strategy for identifying complex traits in soybean and for narrowing GWAS-defined genomic regions, which facilitates positional cloning of the causal gene(s).