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

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.

Similar soil drying-induced stomatal closure in soybean genotypes varying in abscisic acid accumulation and stomatal sensitivity to abscisic acid

Different soybean cultivars (Williams 82 , Union , Jindou 21 , Long Huang 1 , Long Huang 2 ) were exposed to drying soil, to investigate whether endogenous abscisic acid (ABA) concentrations and leaf water relations regulated stomatal behaviour. We measured ABA concentrations in xylem and tissue of the first and second trifoliate leaves respectively; stomatal conductance (gs ) and leaf water potential (Ψleaf ) in both leaves; and water content in soil. Cultivar variation in leaf area and g s caused different rates of soil drying, but g s and Ψ leaf declined similarly with soil drying in all cultivars. Variation in leaf xylem ABA concentration better explained stomatal responses than foliar ABA concentration in some cultivars, and was highly correlated with stomatal conductance. Xylem ABA concentration in well-watered soil was highest in Union , and in drying soil was lowest in Jindou 21 and Long Huang 2 , although the latter had the highest foliar ABA concentrations. Jindou 21 accumulated lower xylem ABA concentrations than other cultivars as soil moisture or Ψ leaf decreased, but its stomatal sensitivity to xylem ABA was greater. Because cultivars varied in both ABA accumulation and stomatal sensitivity to ABA, but had similar stomatal sensitivity to Ψ leaf , leaf water relations seem more important in regulating stomatal closure of soybean.

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.

Breeding implications of nodulation performance and root structure under natural inoculation for soil fertility enhancement and sustainable cowpea production

Nitrogen deficiency is the most limiting abiotic stress factor affecting the grain yield of cowpea (Vigna unguiculata L.) in sub-Saharan Africa (SSA) countries. Breeding for high-yielding potential in association with high nitrogen fixation performance is the principal objective of cowpea breeding programs to improve both the productivity and production of this orphan crop in the region. Therefore, the present study was undertaken to determine the diversity of genotypes for nodulation capacity in two environments and to understand the root architecture and morphology of genotypes as well as grain yield and yield-related traits in 324 cowpea genotypes. The experiment was conducted in two different environments during the 2017 cropping season. The experiments were laid out in 18 × 18 simple lattice design. Grain yield exhibited highly significant and positive genotypic correlations with stem diameter, basal root length of 1st whorls, basal root branching density, taproot length and adventitious root length, demonstrating that selection of cowpea genotypes based on these traits could be effective to capitalize on grain yield under low nitrogen conditions. Days to flowering, days to maturity, stem diameter, 1st whorl angle, basal root length of 1st whorls, basal root branching density, taproot length, adventitious root diameter and adventitious root length had significant and positive genotypic correlations with days to maturity. The first ten principal components (PC) explained 65.13% of the total variation. Stem diameter, taproot width, and taproot length traits were important contributors to the variability in the first PC. The highest inter-cluster distance (D2) was recorded between clusters III and IV. However, clusters II and V recorded the minimum inter-cluster distance (78.96 units). The range of intra-cluster distance was 24.22–5,112.92 units, indicating that the high genetic distance displayed within and between clusters has to be exploited via crossing and selecting the most divergent parents for future cowpea improvement. Five clusters of cowpea genotypes were evident, and within the clusters, the genotypes had good nodulation potential with high grain yield traits, which could significantly contribute to SSA food and nutritional security. Moreover, it can contribute to resilience and improve crop production and sustainability under marginal environmental conditions.

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.

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.

Physiology and metabonomics reveal differences in drought resistance among soybean varieties

BACKGROUND

The soybean is an important food crop worldwide. Drought during the first pod stage significantly affects soybean yield, and understanding the metabolomic and physiological changes in soybeans under drought stress is crucial. This study identified the differential metabolites in initial pod stage soybean leaves under polyethylene glycol-simulated drought stress, using ultra performance liquid chromatography and tandem mass spectrometry, and the physiological indexes related to drought resistance.

RESULTS

Physiologically, drought resistance also generates enzyme and antioxidant activity; levels of superoxide dismutase, peroxidase, and catalase first increased and subsequently decreased, while those of soluble sugar, soluble protein, malondialdehyde, and proline content increased in both varieties. The contents of CAT, proline and soluble sugar in Heinong 44 (HN44) were higher than those in Heinong 65 (HN65), and the contents of MDA were lower than those in HN65. In metabolomics, the OPLS-DA model was used to screen different metabolites. KEGG analysis showed that the two varieties resisted drought through different ways. Amino acid metabolism and lipid metabolism play a key role in drought resistance of the two varieties, respectively. TCA cycle was one of the core pathways of drought resistance in two varieties. Changes in the content of L-Asparagine and citric acid may be one of the reasons for the difference in drought resistance between the two varieties.

CONCLUSIONS

We think that the reasons of drought resistance among soybean varieties are as follows: the main metabolic pathways are different under drought stress; the contents of metabolites in these metabolic pathways are different; some physiological indexes are different, such as MDA, CAT, proline content and so on. Our study enhances the understanding of the metabolomic soybean drought stress response and provides a reference for soybean drought resistance 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.

A Large Root Phenome Dataset Wide-Opened the Potential for Underground Breeding in Soybean

The root is the most critical plant organ for water and nutrient acquisition. Although the root is vital for water and nutrient uptake, the diverse root characters of soybean still need to be identified owing to the difficulty of root sampling. In this study, we used 150 wild and 50 cultivated soybean varieties to collect root image samples. We analyzed root morphological traits using acquired-image. Except for the main total length (MTL), the root morphological traits for most cultivated and wild plants were significantly different. According to correlation analysis, the wild and cultivated plants showed a significant correlation among total root length (TRL), projected area (PA), forks, total lateral length (TLL), link average diameter, and MTL. In particular, TRL was highly correlated with PA in both cultivated (0.92) and wild (0.82) plants compared with between MTL (0.43 for cultivated and 0.27 for wild) and TLL (0.82 for cultivated and 0.52 for wild). According to principal component analysis results, both plants could be separated; however, there was some overlap of the traits among the wild and cultivated individuals from some regions. Nevertheless, variation among the cultivated plants was higher than that found in the wild plants. Furthermore, three groups, including MTL, TLL, and the remaining traits, could explain all the variances.

Ascophyllum nodosum Extract (SealicitTM) Boosts Soybean Yield Through Reduction of Pod Shattering-Related Seed Loss and Enhanced Seed Production

Soybean is one of the most valuable commercial crops because of its high protein, carbohydrate, and oil content. The land area cultivated with soybean in subtropical regions, such as Brazil, is continuously expanding, in some instances at the expense of carbon storing natural habitats. Strategies to decrease yield/seed losses and increase production efficiency are urgently required to meet global demand for soybean in a sustainable manner. Here, we evaluated the effectiveness of an Ascophyllum nodosum extract (ANE), Sealicit^TM, in increasing yields of different soybean varieties, in two geographical regions (Canada and Brazil). In addition, we investigated the potential of Sealicit^TM to reduce pod shattering at the trials in Brazil. Three different concentrations of Sealicit^TM were applied to pod shatter-susceptible (SS) UFUS 6901 and shatter-resistant (SR) UFUS 7415 varieties to assess their impact on pod firmness. SS variety demonstrated a significant decrease in pod shattering, which coincided with deregulation of GmPDH1.1 and GmSHAT1-5 expression, genes that determine pod dehiscence, and higher seed weight per pod. Sealicit^TM application to the SR variety did not significantly alter its inherent pod shatter resistance, but provided higher increases in seed yield at harvest. This yield increase maybe associated with to other yield components stimulated by the biostimulant. This work demonstrates that Sealicit^TM, which has previously been shown to improve pod firmness in Arabidopsis and selected commercial oilseed rape varieties through IND gene down-regulation, also has the potential to improve pod resistance and seed productivity in soybean, a member of the legume family sharing a similar strategy for seed dispersal.

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.