Identification and Mapping of Stable QTLs for Seed Oil and Protein Content in Soybean [Glycine max (L.) Merr.]

Identification of QTLs for symbiotic nitrogen fixation and related traits in a soybean recombinant inbred line population

KEY MESSAGE

The genetic architecture of symbiotic N fixation and related traits was investigated in the field. QTLs were identified for percent N derived from the atmosphere, shoot [N] and C to N ratio. Soybean [Glycine max (L.) Merr.] is cultivated worldwide and is the most abundant source of plant-based protein. Symbiotic N2 fixation (SNF) in legumes such as soybean is of great importance; however, yields may still be limited by N in both high yielding and stressful environments. To better understand the genetic architecture of SNF and facilitate the development of high yielding cultivars and sustainable soybean production in stressful environments, a recombinant inbred line population consisting of 190 lines, developed from a cross between PI 442012A and PI 404199, was evaluated for N derived from the atmosphere (Ndfa), N concentration ([N]), and C to N ratio (C/N) in three environments. Significant genotype, environment and genotype × environment effects were observed for all three traits. A linkage map was constructed containing 3309 single nucleotide polymorphism (SNP) markers. QTL analysis was performed for additive effects of QTLs, QTL × environment interactions, and QTL × QTL interactions. Ten unique additive QTLs were identified across all traits and environments. Of these, two QTLs were detected for Ndfa and eight for C/N. Of the eight QTLs for C/N, four were also detected for [N]. Using QTL × environment analysis, six QTLs were detected, of which five were also identified in the additive QTL analysis. The QTL × QTL analysis identified four unique epistatic interactions. The results of this study may be used for genomic selection and introgression of favorable alleles for increased SNF, [N], and C/N via marker-assisted selection.

Natural variation of GmFATA1B regulates seed oil content and composition in soybean

Soybean (Glycine max) produces seeds that are rich in unsaturated fatty acids and is an important oilseed crop worldwide. Seed oil content and composition largely determine the economic value of soybean. Due to natural genetic variation, seed oil content varies substantially across soybean cultivars. Although much progress has been made in elucidating the genetic trajectory underlying fatty acid metabolism and oil biosynthesis in plants, the causal genes for many quantitative trait loci (QTLs) regulating seed oil content in soybean remain to be revealed. In this study, we identified GmFATA1B as the gene underlying a QTL that regulates seed oil content and composition, as well as seed size in soybean. Nine extra amino acids in the conserved region of GmFATA1B impair its function as a fatty acyl-acyl carrier protein thioesterase, thereby affecting seed oil content and composition. Heterogeneously overexpressing the functional GmFATA1B allele in Arabidopsis thaliana increased both the total oil content and the oleic acid and linoleic acid contents of seeds. Our findings uncover a previously unknown locus underlying variation in seed oil content in soybean and lay the foundation for improving seed oil content and composition in soybean.

Fatty acid composition and genome-wide associations of a chickpea (Cicer arietinum L.) diversity panel for biofortification efforts

Chickpea is a nutritionally dense pulse crop with high levels of protein, carbohydrates, micronutrients and low levels of fats. Chickpea fatty acids are associated with a reduced risk of obesity, blood cholesterol, and cardiovascular diseases in humans. We measured four primary chickpea fatty acids; palmitic acid (PA), linoleic acid (LA), alpha-linolenic acid (ALA), and oleic acid (OA), which are crucial for human health and plant stress responses in a chickpea diversity panel with 256 accessions (Kabuli and desi types). A wide concentration range was found for PA (450.7-912.6 mg/100 g), LA (1605.7-3459.9 mg/100 g), ALA (416.4-864.5 mg/100 g), and OA (1035.5-1907.2 mg/100 g). The percent recommended daily allowances also varied for PA (3.3-6.8%), LA (21.4-46.1%), ALA (34.7-72%), and OA (4.3-7.9%). Weak correlations were found among fatty acids. Genome-wide association studies (GWAS) were conducted using genotyping-by-sequencing data. Five significant single nucleotide polymorphisms (SNPs) were identified for PA. Admixture population structure analysis revealed seven subpopulations based on ancestral diversity in this panel. This is the first reported study to characterize fatty acid profiles across a chickpea diversity panel and perform GWAS to detect associations between genetic markers and concentrations of selected fatty acids. These findings demonstrate biofortification of chickpea fatty acids is possible using conventional and genomic breeding techniques, to develop superior cultivars with better fatty acid profiles for improved human health and plant stress responses.

MOTHER-OF-FT-AND-TFL1 regulates the seed oil and protein content in soybean

Soybean is a major crop that produces valuable seed oil and protein for global consumption. Seed oil and protein are regulated by complex quantitative trait loci (QTLs) and have undergone intensive selections during the domestication of soybean. It is essential to identify the major genetic components and understand their mechanism behind seed oil and protein in soybean. We report that MOTHER-OF-FT-AND-TFL1 (GmMFT) is the gene of a classical QTL that has been reported to regulate seed oil and protein content in many studies. Mutation of MFT decreased seeds oil content and weight in both Arabidopsis and soybean, whereas increased expression of GmMFT enhanced seeds oil content and weight. Haplotype analysis showed that GmMFT has undergone selection, which resulted in the extended haplotype homozygosity in the cultivated soybean and the enriching of the oil-favorable allele in modern soybean cultivars. This work unraveled the GmMFT-mediated mechanism regulating seed oil and protein content and seed weight, and revealed a previously unknown function of MFT that provides new insights into targeted soybean improvement and breeding.

Identification and Mapping of QTLs for Sulfur-Containing Amino Acids in Soybean (Glycine max L.)

Soybean is a major source of high-quality protein for humans and animals. The content of sulfur-containing amino acids (SAA) in soybean is insufficient, which has become the main factor limiting soybean nutrition. In this study, we used the high-density genetic maps derived from Guizao 1 and Brazil 13 to evaluate the quantitative trait loci of cysteine (Cys), methionine (Met), SAA, glycinin (7S), β-conglycinin (11S), ratio of glycinin to β-conglycinin (RGC), and protein content (PC). In genetic map linkage analysis, the major and stable 44 QTLs were detected, which shared nine bin intervals. Among them, the bin interval (bin157-bin160) on chromosome 5 was detected in multiple environments as a stable QTL, which was linked to 11S, 7S, RGC, and SSA. Based on the analysis of bioinformatics and RNA-sequencing data, 16 differentially expressed genes (DEGs) within these QTLs were selected as candidate genes. These results will help to elucidate the genetic mechanism of soybean SAA-related traits and provide the basis for the gene mining of sulfur-containing amino acids.

Genome-Wide Association Studies of Salt Tolerance at the Seed Germination Stage and Yield-Related Traits in Brassica napus L

Salt stress severely affects crop growth and development and reduces the yield of Brassica napus. Exploring natural genetic variations for high salt tolerance in B. napus seedlings is an effective approach to improve productivity under salt stress. Using 10,658 high-quality single nucleotide polymorphic (SNP) markers developed by specific-locus amplified fragment sequencing (SLAF-seq) technology, genome-wide association studies (GWAS) were performed to investigate the genetic basis of salt tolerance and yield-related traits of B. napus. The results revealed that 77 and 497 SNPs were significantly associated with salt tolerance and yield-related traits, of which 40 and 58 SNPs were located in previously reported QTLs/SNPs, respectively. We identified nineteen candidate genes orthologous with Arabidopsis genes known to be associated with salt tolerance and seven potential candidates controlling both salt tolerance and yield. Our study provides a novel genetic resource for the breeding of high-yield cultivars resistant to salt stress.

Multi-omics revolution to promote plant breeding efficiency

Crop production is the primary goal of agricultural activities, which is always taken into consideration. However, global agricultural systems are coming under increasing pressure from the rising food demand of the rapidly growing world population and changing climate. To address these issues, improving high-yield and climate-resilient related-traits in crop breeding is an effective strategy. In recent years, advances in omics techniques, including genomics, transcriptomics, proteomics, and metabolomics, paved the way for accelerating plant/crop breeding to cope with the changing climate and enhance food production. Optimized omics and phenotypic plasticity platform integration, exploited by evolving machine learning algorithms will aid in the development of biological interpretations for complex crop traits. The precise and progressive assembly of desire alleles using precise genome editing approaches and enhanced breeding strategies would enable future crops to excel in combating the changing climates. Furthermore, plant breeding and genetic engineering ensures an exclusive approach to developing nutrient sufficient and climate-resilient crops, the productivity of which can sustainably and adequately meet the world's food, nutrition, and energy needs. This review provides an overview of how the integration of omics approaches could be exploited to select crop varieties with desired traits.

Identifying Soybean Pod Borer (Leguminivora glycinivorella) Resistance QTLs and the Mechanism of Induced Defense Using Linkage Mapping and RNA-Seq Analysis

The soybean pod borer (Leguminivora glycinivorella) (SPB) is a major cause of soybean (Glycine max L.) yield losses in northeast Asia, thus it is desirable to elucidate the resistance mechanisms involved in soybean response to the SPB. However, few studies have mapped SPB-resistant quantitative trait loci (QTLs) and deciphered the response mechanism in soybean. Here, we selected two soybean varieties, JY93 (SPB-resistant) and K6 (SPB-sensitive), to construct F₂ and F_2:3 populations for QTL mapping and collected pod shells before and after SPB larvae chewed on the two parents to perform RNA-Seq, which can identify stable QTLs and explore the response mechanism of soybean to the SPB. The results show that four QTLs underlying SPB damage to seeds were detected on chromosomes 4, 9, 13, and 15. Among them, qESP-9-1 was scanned in all environments, hence it can be considered a stable QTL. All QTLs explained 0.79 to 6.09% of the phenotypic variation. Meanwhile, 2298 and 3509 DEGs were identified for JY93 and K6, respectively, after the SPB attack, and most of these genes were upregulated. Gene Ontology enrichment results indicated that the SPB-induced and differently expressed genes in both parents are involved in biological processes such as wound response, signal transduction, immune response, and phytohormone pathways. Interestingly, secondary metabolic processes such as flavonoid synthesis were only significantly enriched in the upregulated genes of JY93 after SPB chewing compared with K6. Finally, we identified 18 candidate genes related to soybean pod borer resistance through the integration of QTL mapping and RNA-Seq analysis. Seven of these genes had similar expression patterns to the mapping parents in four additional soybean germplasm after feeding by the SPB. These results provide additional knowledge of the early response and induced defense mechanisms against the SPB in soybean, which could help in breeding SPB-resistant soybean accessions.

Linkage analysis and residual heterozygotes derived near isogenic lines reveals a novel protein quantitative trait loci from a Glycine soja accession

Modern soybean [Glycine max (L.) Merr] cultivars have low overall genetic variation due to repeated bottleneck events that arose during domestication and from selection strategies typical of many soybean breeding programs. In both public and private soybean breeding programs, the introgression of wild soybean (Glycine soja Siebold and Zucc.) alleles is a viable option to increase genetic diversity and identify new sources for traits of value. The objectives of our study were to examine the genetic architecture responsible for seed protein and oil using a recombinant inbred line (RIL) population derived from hybridizing a G. max line ('Osage') with a G. soja accession (PI 593983). Linkage mapping identified a total of seven significant quantitative trait loci on chromosomes 14 and 20 for seed protein and on chromosome 8 for seed oil with LOD scores ranging from 5.3 to 31.7 for seed protein content and from 9.8 to 25.9 for seed oil content. We analyzed 3,015 single F4:9 soybean plants to develop two residual heterozygotes derived near isogenic lines (RHD-NIL) populations by targeting nine SNP markers from genotype-by-sequencing, which corresponded to two novel quantitative trait loci (QTL) derived from G. soja: one for a novel seed oil QTL on chromosome 8 and another for a novel protein QTL on chromosome 14. Single marker analysis and linkage analysis using 50 RHD-NILs validated the chromosome 14 protein QTL, and whole genome sequencing of RHD-NILs allowed us to reduce the QTL interval from ∼16.5 to ∼4.6 Mbp. We identified two genomic regions based on recombination events which had significant increases of 0.65 and 0.72% in seed protein content without a significant decrease in seed oil content. A new Kompetitive allele-specific polymerase chain reaction (KASP) assay, which will be useful for introgression of this trait into modern elite G. max cultivars, was developed in one region. Within the significantly associated genomic regions, a total of eight genes are considered as candidate genes, based on the presence of gene annotations associated with the protein or amino acid metabolism/movement. Our results provide better insights into utilizing wild soybean as a source of genetic diversity for soybean cultivar improvement utilizing native traits.

Protein Biofortification in Lentils (Lens culinaris Medik.) Toward Human Health

Lentil (Lens culinaris Medik.) is a nutritionally dense crop with significant quantities of protein, low-digestible carbohydrates, minerals, and vitamins. The amino acid composition of lentil protein can impact human health by maintaining amino acid balance for physiological functions and preventing protein-energy malnutrition and non-communicable diseases (NCDs). Thus, enhancing lentil protein quality through genetic biofortification, i.e., conventional plant breeding and molecular technologies, is vital for the nutritional improvement of lentil crops across the globe. This review highlights variation in protein concentration and quality across Lens species, genetic mechanisms controlling amino acid synthesis in plants, functions of amino acids, and the effect of antinutrients on the absorption of amino acids into the human body. Successful breeding strategies in lentils and other pulses are reviewed to demonstrate robust breeding approaches for protein biofortification. Future lentil breeding approaches will include rapid germplasm selection, phenotypic evaluation, genome-wide association studies, genetic engineering, and genome editing to select sequences that improve protein concentration and quality.

Novel QTL and Meta-QTL Mapping for Major Quality Traits in Soybean

Isoflavone, protein, and oil are the most important quality traits in soybean. Since these phenotypes are typically quantitative traits, quantitative trait locus (QTL) mapping has been an efficient way to clarify their complex and unclear genetic background. However, the low-density genetic map and the absence of QTL integration limited the accurate and efficient QTL mapping in previous researches. This paper adopted a recombinant inbred lines (RIL) population derived from 'Zhongdou27'and 'Hefeng25' and a high-density linkage map based on whole-genome resequencing to map novel QTL and used meta-analysis methods to integrate the stable and consentaneous QTL. The candidate genes were obtained from gene functional annotation and expression analysis based on the public database. A total of 41 QTL with a high logarithm of odd (LOD) scores were identified through composite interval mapping (CIM), including 38 novel QTL and 2 Stable QTL. A total of 660 candidate genes were predicted according to the results of the gene annotation and public transcriptome data. A total of 212 meta-QTL containing 122 stable and consentaneous QTL were mapped based on 1,034 QTL collected from previous studies. For the first time, 70 meta-QTL associated with isoflavones were mapped in this study. Meanwhile, 69 and 73 meta-QTL, respectively, related to oil and protein were obtained as well. The results promote the understanding of the biosynthesis and regulation of isoflavones, protein, and oil at molecular levels, and facilitate the construction of molecular modular for great quality traits in soybean.

Omics-Facilitated Crop Improvement for Climate Resilience and Superior Nutritive Value

Novel crop improvement approaches, including those that facilitate for the exploitation of crop wild relatives and underutilized species harboring the much-needed natural allelic variation are indispensable if we are to develop climate-smart crops with enhanced abiotic and biotic stress tolerance, higher nutritive value, and superior traits of agronomic importance. Top among these approaches are the "omics" technologies, including genomics, transcriptomics, proteomics, metabolomics, phenomics, and their integration, whose deployment has been vital in revealing several key genes, proteins and metabolic pathways underlying numerous traits of agronomic importance, and aiding marker-assisted breeding in major crop species. Here, citing several relevant examples, we appraise our understanding on the recent developments in omics technologies and how they are driving our quest to breed climate resilient crops. Large-scale genome resequencing, pan-genomes and genome-wide association studies are aiding the identification and analysis of species-level genome variations, whilst RNA-sequencing driven transcriptomics has provided unprecedented opportunities for conducting crop abiotic and biotic stress response studies. Meanwhile, single cell transcriptomics is slowly becoming an indispensable tool for decoding cell-specific stress responses, although several technical and experimental design challenges still need to be resolved. Additionally, the refinement of the conventional techniques and advent of modern, high-resolution proteomics technologies necessitated a gradual shift from the general descriptive studies of plant protein abundances to large scale analysis of protein-metabolite interactions. Especially, metabolomics is currently receiving special attention, owing to the role metabolites play as metabolic intermediates and close links to the phenotypic expression. Further, high throughput phenomics applications are driving the targeting of new research domains such as root system architecture analysis, and exploration of plant root-associated microbes for improved crop health and climate resilience. Overall, coupling these multi-omics technologies to modern plant breeding and genetic engineering methods ensures an all-encompassing approach to developing nutritionally-rich and climate-smart crops whose productivity can sustainably and sufficiently meet the current and future food, nutrition and energy demands.

Chickpea (Cicer arietinum L.) as a Source of Essential Fatty Acids - A Biofortification Approach

Chickpea is a highly nutritious pulse crop with low digestible carbohydrates (40-60%), protein (15-22%), essential fats (4-8%), and a range of minerals and vitamins. The fatty acid composition of the seed adds value because fats govern the texture, shelf-life, flavor, aroma, and nutritional composition of chickpea-based food products. Therefore, the biofortification of essential fatty acids has become a nutritional breeding target for chickpea crop improvement programs worldwide. This paper examines global chickpea production, focusing on plant lipids, their functions, and their benefits to human health. In addition, this paper also reviews the chemical analysis of essential fatty acids and possible breeding targets to enrich essential fatty acids in chickpea (Cicer arietinum) biofortification. Biofortification of chickpea for essential fatty acids within safe levels will improve human health and support food processing to retain the quality and flavor of chickpea-based food products. Essential fatty acid biofortification is possible by phenotyping diverse chickpea germplasm over suitable locations and years and identifying the candidate genes responsible for quantitative trait loci mapping using genome-wide association mapping.

Metabolite Contents and Antioxidant Activities of Soybean (Glycine max (L.) Merrill) Seeds of Different Seed Coat Colors

Seed coat color is one of the main agronomical traits that determine the chemical quality of soybean seeds and has been used as a parameter during cultivar development. In this study, seeds of yellow (n = 10), greenish-yellow (n = 5), and light-yellow (n = 4) soybean accessions were evaluated for their contents of total protein, total oil, total phenolic (TPC), and five prominent fatty acids including palmitic acid (PA), stearic acid (SA), oleic acid (OA), linoleic acid (LA), and linolenic acid (LLA), relative to a control cultivar, and the effect of seed coat color on each was investigated. Antioxidant activity was also evaluated using 1,1-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging activity, Trolox equivalent antioxidant capacity (TEAC), and ferric reducing antioxidant power (FRAP). The results showed significant variations of metabolite contents and antioxidant activities between the soybeans. The average TPC, DPPH-radical scavenging activity, and FRAP were each in the order of greenish-yellow > yellow > light-yellow soybeans. In contrast, light-yellow soybeans contained a high level of OA and low levels of SA, LA, and LLA, each except LA differing significantly from yellow and greenish-yellow soybeans (p < 0.05). Our findings suggest that greenish-yellow and light-yellow soybeans could be good sources of antioxidants and high-quality soybean oil, respectively.