Quantitative trait loci associated with soybean seed weight and composition under different phosphorus levels

Development of KASP markers assisted with soybean drought tolerance in the germination stage based on GWAS

Soybean [Glycine max(L.)Merr.] is a leading oil-bearing crop and cultivated globally over a vast scale. The agricultural landscape in China faces a formidable challenge with drought significantly impacting soybean production. In this study, we treated a natural population of 264 Chinese soybean accessions using 15% PEG-6000 and used GR, GE, GI, RGR, RGE, RGI and ASFV as evaluation index. Using the ASFV, we screened 17 strong drought-tolerant soybean germplasm in the germination stage. Leveraging 2,597,425 high-density SNP markers, we conducted Genome-Wide Association Studies (GWAS) and identified 92 SNPs and 9 candidate genes significantly associated with drought tolerance. Furthermore, we developed two KASP markers for S14_5147797 and S18_53902767, which closely linked to drought tolerance. This research not only enriches the pool of soybean germplasm resources but also establishes a robust foundation for the molecular breeding of drought tolerance soybean varieties.

Genome-wide association study and RNA-seq identifies GmWRI1-like transcription factor related to the seed weight in soybean

The cultivated soybean (Glycine max (L.) Merrill) is domesticated from wild soybean (Glycine soja) and has heavier seeds with a higher oil content than the wild soybean. In this study, we identified a novel candidate gene associated with SW using a genome-wide association study (GWAS). The candidate gene GmWRI14-like was detected by GWAS analysis in three consecutive years. By constructing transgenic soybeans overexpressing the GmWRI14-like gene and gmwri14-like soybean mutants, we found that overexpression of GmWRI14-like increased the SW and increased total fatty acid content. We then used RNA-seq and qRT-PCR to identify the target genes directly or indirectly regulated by GmWRI14-like. Transgenic soyabeans overexpressing GmWRI14-like showed increased accumulation of GmCYP78A50 and GmCYP78A69 than non-transgenic soybean lines. Interestingly, we also found that GmWRI14-like proteins could interact with GmCYP78A69/GmCYP78A50 using yeast two-hybrid and bimolecular fluorescence complementation. Our results not only shed light on the genetic architecture of cultivated soybean SW, but also lays a theoretical foundation for improving the SW and oil content of soybeans.

Genome-wide association mapping for yield-related traits in soybean (Glycine max) under well-watered and drought-stressed conditions

Soybean (Glycine max) productivity is significantly reduced by drought stress. Breeders are aiming to improve soybean grain yields both under well-watered (WW) and drought-stressed (DS) conditions, however, little is known about the genetic architecture of yield-related traits. Here, a panel of 188 soybean germplasm was used in a genome wide association study (GWAS) to identify single nucleotide polymorphism (SNP) markers linked to yield-related traits including pod number per plant (PN), biomass per plant (BM) and seed weight per plant (SW). The SLAF-seq genotyping was conducted on the population and three phenotype traits were examined in WW and DS conditions in four environments. Based on best linear unbiased prediction (BLUP) data and individual environmental analyses, 39 SNPs were significantly associated with three soybean traits under two conditions, which were tagged to 26 genomic regions by linkage disequilibrium (LD) analysis. Of these, six QTLs qPN-WW19.1, qPN-DS8.8, qBM-WW1, qBM-DS17.4, qSW-WW4 and qSW-DS8 were identified controlling PN, BM and SW of soybean. There were larger proportions of favorable haplotypes for locus qPN-WW19.1 and qSW-WW4 rather than qBM-WW1, qBM-DS17.4, qPN-DS8.8 and qSW-DS8 in both landraces and improved cultivars. In addition, several putative candidate genes such as Glyma.19G211300, Glyma.17G057100 and Glyma.04G124800, encoding E3 ubiquitin-protein ligase BAH1, WRKY transcription factor 11 and protein zinc induced facilitator-like 1, respectively, were predicted. We propose that the further exploration of these locus will facilitate accelerating breeding for high-yield soybean cultivars.

Understandings and future challenges in soybean functional genomics and molecular breeding

Soybean (Glycine max) is a major source of plant protein and oil. Soybean breeding has benefited from advances in functional genomics. In particular, the release of soybean reference genomes has advanced our understanding of soybean adaptation to soil nutrient deficiencies, the molecular mechanism of symbiotic nitrogen (N) fixation, biotic and abiotic stress tolerance, and the roles of flowering time in regional adaptation, plant architecture, and seed yield and quality. Nevertheless, many challenges remain for soybean functional genomics and molecular breeding, mainly related to improving grain yield through high-density planting, maize-soybean intercropping, taking advantage of wild resources, utilization of heterosis, genomic prediction and selection breeding, and precise breeding through genome editing. This review summarizes the current progress in soybean functional genomics and directs future challenges for molecular breeding of soybean.

Prospects of genetics and breeding for low-phosphate tolerance: an integrated approach from soil to cell

Improving phosphorus (P) crop nutrition has emerged as a key factor toward achieving a more resilient and sustainable agriculture. P is an essential nutrient for plant development and reproduction, and phosphate (Pi)-based fertilizers represent one of the pillars that sustain food production systems. To meet the global food demand, the challenge for modern agriculture is to increase food production and improve food quality in a sustainable way by significantly optimizing Pi fertilizer use efficiency. The development of genetically improved crops with higher Pi uptake and Pi-use efficiency and higher adaptability to environments with low-Pi availability will play a crucial role toward this end. In this review, we summarize the current understanding of Pi nutrition and the regulation of Pi-starvation responses in plants, and provide new perspectives on how to harness the ample repertoire of genetic mechanisms behind these adaptive responses for crop improvement. We discuss on the potential of implementing more integrative, versatile, and effective strategies by incorporating systems biology approaches and tools such as genome editing and synthetic biology. These strategies will be invaluable for producing high-yielding crops that require reduced Pi fertilizer inputs and to develop a more sustainable global agriculture.

Sequencing the USDA core soybean collection reveals gene loss during domestication and breeding

The gene content of plants varies between individuals of the same species due to gene presence/absence variation, and selection can alter the frequency of specific genes in a population. Selection during domestication and breeding will modify the genomic landscape, though the nature of these modifications is only understood for specific genes or on a more general level (e.g., by a loss of genetic diversity). Here we have assembled and analyzed a soybean (Glycine spp.) pangenome representing more than 1,000 soybean accessions derived from the USDA Soybean Germplasm Collection, including both wild and cultivated lineages, to assess genomewide changes in gene and allele frequency during domestication and breeding. We identified 3,765 genes that are absent from the Lee reference genome assembly and assessed the presence/absence of all genes across this population. In addition to a loss of genetic diversity, we found a significant reduction in the average number of protein-coding genes per individual during domestication and subsequent breeding, though with some genes and allelic variants increasing in frequency associated with selection for agronomic traits. This analysis provides a genomic perspective of domestication and breeding in this important oilseed crop.

Flax and Sorghum: Multi-Element Contents and Nutritional Values within 210 Varieties and Potential Selection for Future Climates to Sustain Food Security

The Dietary Guidelines for Americans recommends giving priority to nutrient-dense foods while decreasing energy-dense foods. Although both flax (Linum usitatissimum) and sorghum (Sorghum bicolor) are rich in various essential minerals, their ionomes have yet to be investigated. Furthermore, previous studies have shown that elevated CO₂ levels could reduce key nutrients in crops. In this study, we analyzed 102 flax and 108 sorghum varieties to investigate their ionomic variations (N, P, K, Ca, Mg, S, B, Zn, Mn, Fe, Cu, and Mo), elemental level interactions, and nutritional value. The results showed substantial genetic variations and elemental correlations in flax and sorghum. While a serving size of 28 g of flax delivers 37% daily value (DV) of Cu, 31% of Mn, 28% of Mg, and 19% of Zn, sorghum delivers 24% of Mn, 16% of Cu, 11% of Mg, and 10% of Zn of the recommended daily value (DV). We identified a set of promising flax and sorghum varieties with superior seed mineral composition that could complement breeding programs for improving the nutritional quality of flax and sorghum. Overall, we demonstrate additional minerals data and their corresponding health and food security benefits within flax and sorghum that could be considered by consumers and breeding programs to facilitate improving seed nutritional content and to help mitigate human malnutrition as well as the effects of rising CO₂ stress.

Progress in soybean functional genomics over the past decade

Soybean is one of the most important oilseed and fodder crops. Benefiting from the efforts of soybean breeders and the development of breeding technology, large number of germplasm has been generated over the last 100 years. Nevertheless, soybean breeding needs to be accelerated to meet the needs of a growing world population, to promote sustainable agriculture and to address future environmental changes. The acceleration is highly reliant on the discoveries in gene functional studies. The release of the reference soybean genome in 2010 has significantly facilitated the advance in soybean functional genomics. Here, we review the research progress in soybean omics (genomics, transcriptomics, epigenomics and proteomics), germplasm development (germplasm resources and databases), gene discovery (genes that are responsible for important soybean traits including yield, flowering and maturity, seed quality, stress resistance, nodulation and domestication) and transformation technology during the past decade. At the end, we also briefly discuss current challenges and future directions.

Identification of Candidate Genes and Genomic Selection for Seed Protein in Soybean Breeding Pipeline

Soybean is a primary meal protein for human consumption, poultry, and livestock feed. In this study, quantitative trait locus (QTL) controlling protein content was explored via genome-wide association studies (GWAS) and linkage mapping approaches based on 284 soybean accessions and 180 recombinant inbred lines (RILs), respectively, which were evaluated for protein content for 4 years. A total of 22 single nucleotide polymorphisms (SNPs) associated with protein content were detected using mixed linear model (MLM) and general linear model (GLM) methods in Tassel and 5 QTLs using Bayesian interval mapping (IM), single-trait multiple interval mapping (SMIM), single-trait composite interval mapping maximum likelihood estimation (SMLE), and single marker regression (SMR) models in Q-Gene and IciMapping. Major QTLs were detected on chromosomes 6 and 20 in both populations. The new QTL genomic region on chromosome 6 (Chr6_18844283-19315351) included 7 candidate genes and the Hap.X ^AA at the Chr6_19172961 position was associated with high protein content. Genomic selection (GS) of protein content was performed using Bayesian Lasso (BL) and ridge regression best linear unbiased prediction (rrBULP) based on all the SNPs and the SNPs significantly associated with protein content resulted from GWAS. The results showed that BL and rrBLUP performed similarly; GS accuracy was dependent on the SNP set and training population size. GS efficiency was higher for the SNPs derived from GWAS than random SNPs and reached a plateau when the number of markers was >2,000. The SNP markers identified in this study and other information were essential in establishing an efficient marker-assisted selection (MAS) and GS pipelines for improving soybean protein content.

Characterization of pea seed nutritional value within a diverse population of Pisum sativum

Micronutrient malnutrition is a global concern that affects more than two billion people worldwide. Pea (Pisum sativum) is a nutritious pulse crop with potential to assist in tackling hidden hunger. Here we report seed ionomic data of 96 diverse pea accessions collected via inductively coupled plasma mass spectrometry (ICP-MS). We found a 100 g serving of peas provides the following average percent daily value for U.S. recommendations: 8% Ca, 39% Mg, 73% Cu, 37% Fe, 63% Mn, 45% Zn, 28% K, and 43% P. Correlations were observed between the majority of minerals tested suggesting strong interrelationships between mineral concentration levels. Hierarchical clustering identified fifteen accessions with high-ranking mineral concentrations. Thirty accessions could be compared to earlier inductively coupled optical emission spectrometry (ICP-OES) data, which revealed significant differences particularly for elements at extreme low or high levels of accumulation. These results improve our understanding of the range of variation in mineral content found in peas and provide additional mineral data resources for germplasm selection.

Proteome characterization of two contrasting soybean genotypes in response to different phosphorus treatments

Phosphorus (P) is an essential element for the growth and development of plants. Soybean (Glycine max) is an important food crop that is grown worldwide. Soybean yield is significantly affected by P deficiency in the soil. To investigate the molecular factors that determine the response and tolerance at low-P in soybean, we conducted a comparative proteomics study of a genotype with low-P tolerance (Liaodou 13, L13) and a genotype with low-P sensitivity (Tiefeng 3, T3) in a paper culture experiment with three P treatments, i.e. P-free (0 mmol·L-1), low-P (0.05 mmol·L-1) and normal-P (0.5 mmol·L-1). A total of 4126 proteins were identified in roots of the two genotypes. Increased numbers of differentially expressed proteins (DEPs) were obtained from low-P to P-free conditions compared to the normal-P treatment. All DEPs obtained in L13 (660) were upregulated in response to P deficiency, while most DEPs detected in T3 (133) were downregulated under P deficiency. Important metabolic pathways such as oxidative phosphorylation, glutathione metabolism and carbon metabolism were suppressed in T3, which could have affected the survival of the plants in P-limited soil. In contrast, L13 increased the metabolic activity in the 2-oxocarboxylic acid metabolism, carbon metabolism, glycolysis, biosynthesis of amino acids, pentose phosphatase, oxidative phosphorylation, other types of O-glycan biosynthesis and riboflavin metabolic pathways in order to maintain normal plant growth under P deficiency. Three key proteins I1KW20 (prohibitins), I1K3U8 (alpha-amylase inhibitors) and C6SZ93 (alpha-amylase inhibitors) were suggested as potential biomarkers for screening soybean genotypes with low-P tolerance. Overall, this study provides new insights into the response and tolerance to P deficiency in soybean.

Identification and Validation of Major QTLs, Epistatic Interactions, and Candidate Genes for Soybean Seed Shape and Weight Using Two Related RIL Populations

Understanding the genetic mechanism underlying seed size, shape, and weight is essential for enhancing soybean cultivars. High-density genetic maps of two recombinant inbred line (RIL) populations, LM6 and ZM6, were evaluated across multiple environments to identify and validate M-QTLs as well as identify candidate genes behind major and stable quantitative trait loci (QTLs). A total of 239 and 43 M-QTLs were mapped by composite interval mapping (CIM) and mixed-model-based composite interval mapping (MCIM) approaches, from which 180 and 18, respectively, are novel QTLs. Twenty-two QTLs including four novel major QTLs were validated in the two RIL populations across multiple environments. Moreover, 18 QTLs showed significant AE effects, and 40 pairwise of the identified QTLs exhibited digenic epistatic effects. Thirty-four QTLs associated with seed flatness index (FI) were identified and reported here for the first time. Seven QTL clusters comprising several QTLs for seed size, shape, and weight on genomic regions of chromosomes 3, 4, 5, 7, 9, 17, and 19 were identified. Gene annotations, gene ontology (GO) enrichment, and RNA-seq analyses of the genomic regions of those seven QTL clusters identified 47 candidate genes for seed-related traits. These genes are highly expressed in seed-related tissues and nodules, which might be deemed as potential candidate genes regulating the seed size, weight, and shape traits in soybean. This study provides detailed information on the genetic basis of the studied traits and candidate genes that could be efficiently implemented by soybean breeders for fine mapping and gene cloning, and for marker-assisted selection (MAS) targeted at improving these traits individually or concurrently.

MicroRNA-mediated regulation of agronomically important seed traits: a treasure trove with shades of grey!

Seed development is an intricate process with multiple levels of regulation. MicroRNAs (miRNAs) have emerged as one of the crucial components of molecular networks underlying agronomically important seed traits in diverse plant species. In fact, loss of function of the genes regulating miRNA biogenesis also exhibits defects in seed development. A total of 21 different miRNAs have experimentally been shown to regulate seed size, nutritional content, vigor, and shattering, and have been reviewed here. The mechanism details of the associated regulatory cascades mediated through transcriptional regulators, phytohormones, basic metabolic machinery, and secondary siRNAs are elaborated. Co-localization of miRNAs and their target regions with seed-related QTLs provides new avenues for engineering these traits using conventional breeding programs or biotechnological interventions. While global analysis of miRNAs using small RNA sequencing studies are expanding the repertoire of candidate miRNAs, recent revelations on their inheritance, transport, and mechanism of action would be instrumental in designing better strategies for optimizing agronomically relevant seed traits.

Two homologous LHY pairs negatively control soybean drought tolerance by repressing the abscisic acid responses

The circadian clock plays essential roles in diverse plant biological processes, such as flowering, phytohormone biosynthesis and abiotic stress responses. The manner in which circadian clock genes regulate drought stress responses in model plants has been well established, but comparatively little is known in crop species, such as soybean, a major global crop. This paper reports that the core clock components GmLHYs, the orthologues of CCA1/LHY in Arabidopsis, negatively control drought tolerance in soybean. The expressions of four GmLHYs were all induced by drought, and the quadruple mutants of GmLHYs demonstrated significantly improved drought tolerance. Transcriptome profiling suggested that the abscisic acid (ABA) signaling pathway is regulated by GmLHYs to respond to drought tolerance. Genetic dissections showed that two homologous pairs of LHY1a and LHY1b redundantly control the drought response. Functional characterization of LHY1a and LHY1b in Arabidopsis and soybean further supported the notion that GmLHYs can maintain cellular homeostasis through the ABA signaling pathway under drought stress. This study improves our understanding of the underlying molecular mechanisms on soybean drought tolerance. Furthermore, the two homologues of LHY1a and LHY1b provide alternative targets for genome editing to rapidly generate mutant alleles in elite soybean cultivars to enhance their drought tolerance.

Pedigree-based genetic dissection of quantitative loci for seed quality and yield characters in improved soybean

As soybean plays an indispensable role in the supply of vegetable oil and protein, balancing the relationship between seed quality and yield traits according to human demand has become an important breeding goal for soybean improvement. Here, 256 intraspecific recombinant inbred lines (RILs), derived from a cross between Qi Huang No.34 (QH34) and Ji Dou No.17 (JD17), were used for quantitative trait loci (QTLs) mapping with remarkable four chemical and physical properties with a purpose for exploring the distribution of excellent alleles in germplasm resources in China. A total of 25 QTLs were detected, of which 10 QTLs inherited the alleles from the parent QH34. Pedigree research on favorable alleles on these QTLs showed the process of excellent alleles pyramided into QH34. Meta-analysis of the 25 QTLs by comparing with existed QTLs in previous study identified 17 novel QTLs. QTLs with pleiotropic effects have been detected. Furthermore, three representative elite recombinant inbred lines in different locations that have great potential in soybean breeding were selected, and finally, four seed weight-related candidate genes were identified. The discovery of these QTLs provides a new guidance for combining the diversity and rarity of germplasm resources, which can effectively increase population genetic diversity and broaden genetic basis of varieties.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-021-01211-6.

Identification of QTNs Controlling 100-Seed Weight in Soybean Using Multilocus Genome-Wide Association Studies

Hundred-seed weight (HSW) is an important measure of yield and a useful indicator to monitor the inheritance of quantitative traits affected by genotype and environmental conditions. To identify quantitative trait nucleotides (QTNs) and mine genes useful for breeding high-yielding and high-quality soybean (Glycine max) cultivars, we conducted a multilocus genome-wide association study (GWAS) on HSW of soybean based on phenotypic data from 20 different environments and genotypic data for 109,676 single-nucleotide polymorphisms (SNPs) in 144 four-way recombinant inbred lines. Using five multilocus GWAS methods, we identified 118 QTNs controlling HSW. Among these, 31 common QTNs were detected by various methods or across multiple environments. Pathway analysis identified three potential candidate genes associated with HSW in soybean. We used allele information to study the common QTNs in 20 large-seed and 20 small-seed lines and identified a higher percentage of superior alleles in the large-seed lines than in small-seed lines. These observations will contribute to construct the gene networks controlling HSW in soybean, which can improve the genetic understanding of HSW, and provide assistance for molecular breeding of soybean large-seed varieties.

Protein, weight, and oil prediction by single-seed near-infrared spectroscopy for selection of seed quality and yield traits in pea (Pisum sativum)

BACKGROUND

Pea (Pisum sativum) is a prevalent cool-season crop that produces seeds valued for their high protein content. Modern cultivars have incorporated several traits that improved harvested yield. However, progress toward improving seed quality has received less emphasis, in part due to the lack of tools for easily and rapidly measuring seed traits. In this study we evaluated the accuracy of single-seed near-infrared spectroscopy (NIRS) for measuring pea-seed weight, protein, and oil content. A total of 96 diverse pea accessions were analyzed using both single-seed NIRS and wet chemistry methods. To demonstrate field relevance, the single-seed NIRS protein prediction model was used to determine the impact of seed treatments and foliar fungicides on the protein content of harvested dry peas in a field trial.

RESULTS

External validation of partial least squares (PLS) regression models showed high prediction accuracy for protein and weight (R2 = 0.94 for both) and less accuracy for oil (R2 = 0.74). Single-seed weight was weakly correlated with protein and oil content in contrast with previous reports. In the field study, the single-seed NIRS predicted protein values were within 10 mg g-1 of an independent analytical reference measurement and were sufficiently precise to detect small treatment effects.

CONCLUSION

The high accuracy of protein and weight estimation show that single-seed NIRS could be used in the dual selection of high-protein, high-weight peas early in the breeding cycle, allowing for faster genetic advancement toward improved pea nutritional quality. © 2020 Society of Chemical Industry.