Genetic regulatory networks of soybean seed size, oil and protein contents

GmIRT1.1 from soybean (Glycine max L.) is involved in transporting Fe, Mn and Cd

Soybean is one of the most important crops for producing high quality oil and protein. Mineral nutrient deficiencies are frequently observed in soybeans. However, there are few studies to understand the absorption process of mineral nutrients in soybeans. Here, we investigated the functions of soybean (Glycine max L.) IRT1.1 (IRON-REGULATED TRANSPORTER 1.1) in the transportation of mineral elements. Heterologous expression of GmIRT1.1 in yeast mutants revealed that GmIRT1.1 compensated for the growth defects of Δfet3fet4 and Δsmf1 mutants under iron (Fe) and manganese (Mn) deficiency conditions, respectively, and enhanced the sensitivity of the Δycf1 mutant to cadmium (Cd) toxicity. Expression analysis revealed that GmIRT1.1 was only significantly induced by Fe deficiency and was primarily expressed in roots. Furthermore, the GmIRT1.1 overexpression lines enhanced Arabidopsis tolerance to Fe deficiency, leading to increased accumulation of Fe in the roots and shoots. Additionally, the transgenic lines increased the sensitivity to Mn and Cd toxicity. Subcellular localization analysis revealed that GmIRT1.1 was localized on the plasma membrane. Moreover, the results obtained from the soybean hairy roots system indicated that the localization of GmIRT1.1 was dependent on the regulation of Fe homeostasis in plant. Consequently, these results suggested that GmIRT1.1 was responsible for the transportation of Fe, Mn and Cd.

Natural variation in GmSW17 controls seed size in soybean

Seed size/weight plays an important role in determining crop yield, yet only few genes controlling seed size have been characterized in soybean. Here, we perform a genome-wide association study and identify a major quantitative trait locus (QTL), named GmSW17 (Seed Width 17), on chromosome 17 that determine soybean seed width/weight in natural population. GmSW17 encodes a ubiquitin-specific protease, an ortholog to UBP22, belonging to the ubiquitin-specific protease (USPs/UBPs) family. Further functional investigations reveal that GmSW17 interacts with GmSGF11 and GmENY2 to form a deubiquitinase (DUB) module, which influences H2Bub levels and negatively regulates the expression of GmDP-E2F-1, thereby inhibiting the G1-to-S transition. Population analysis demonstrates that GmSW17 undergo artificial selection during soybean domestication but has not been fixed in modern breeding. In summary, our study identifies a predominant gene related to soybean seed weight, providing potential advantages for high-yield breeding in soybean.

Identification of a Major QTL for Seed Protein Content in Cultivated Peanut (Arachis hypogaea L.) Using QTL-Seq

Peanut (Arachis hypogaea L.) is a great plant protein source for human diet since it has high protein content in the kernel. Therefore, seed protein content (SPC) is considered a major agronomic and quality trait in peanut breeding. However, few genetic loci underlying SPC have been identified in peanuts, and the underlying regulatory mechanisms remain unknown, limiting the effectiveness of breeding for high-SPC peanut varieties. In this study, a major QTL (qSPCB10.1) controlling peanut SPC was identified within a 2.3 Mb interval in chromosome B10 by QTL-seq using a recombinant inbred line population derived from parental lines with high and low SPCs, respectively. Sequence comparison, transcriptomic analysis, and annotation analysis of the qSPCB10.1 locus were performed. Six differentially expressed genes with sequence variations between two parents were identified as candidate genes underlying qSPCB10.1. Further locus interaction analysis revealed that qSPCB10.1 could not affect the seed oil accumulation unless qOCA08.1XH13 was present, a high seed oil content (SOC) allele for a major QTL underlying SOC. In summary, our study provides a basis for future investigation of the genetic basis of seed protein accumulation and facilitates marker-assisted selection for developing high-SPC peanut genotypes.

Regional Variability in Sugar and Amino Acid Content of U.S. Soybeans and the Impact of Autoclaving on Reducing Sugars and Free Lysine

Exploring the sugar and amino acid content variability and the influence of thermal processing on these in soybeans can help optimize their utilization in animal feed. This study examined 209 samples harvested in 2020 and 55 samples harvested in 2021 from across the U.S. to assess their sugar variability and amino acid variability. Harvest regions included the East Corn Belt, West Corn Belt, Mid-South, East Coast, and the Southeast of the U.S. In addition to the sugar and amino acid contents, protein, oil, and seed size were also analyzed. Samples from 2021 were evaluated for their sugar and amino acid contents before and after autoclaving the seeds at 105-110 °C for 15 min. For the samples harvested in 2020, sucrose (4.45 g 100 g-1) and stachyose (1.34 g 100 g-1) were the most prevalent sugars. For the samples harvested in 2021, L-arginine (9.82 g 100 g-1), leucine (5.29 g 100 g-1), and glutamate (4.90 g 100 g-1) were the most prevalent amino acids. Heat treatment resulted in an 8.47%, 20.88%, 11.18%, and 1.46% median loss of free lysine, sucrose, glucose, and fructose. This study's insights into the variability in sugar and amino acid content and the heat-induced changes in the nutritional composition of soybeans provide a reference for improving soybean quality assessment and optimizing its use in animal feed formulations in the U.S.

Identification and Genetic Dissection of Resistance to Red Crown Rot Disease in a Diverse Soybean Germplasm Population

Red crown rot (RCR) disease caused by Calonectria ilicicola negatively impacts soybean yield and quality. Unfortunately, the knowledge of the genetic architecture of RCR resistance in soybeans is limited. In this study, 299 diverse soybean accessions were used to explore their genetic diversity and resistance to RCR, and to mine for candidate genes via emergence rate (ER), survival rate (SR), and disease severity (DS) by a multi-locus random-SNP-effect mixed linear model of GWAS. All accessions had brown necrotic lesions on the primary root, with five genotypes identified as resistant. Nine single-nucleotide polymorphism (SNP) markers were detected to underlie RCR response (ER, SR, and DS). Two SNPs colocalized with at least two traits to form a haplotype block which possessed nine genes. Based on their annotation and the qRT-PCR, three genes, namely Glyma.08G074600, Glyma.08G074700, and Glyma.12G043600, are suggested to modulate soybean resistance to RCR. The findings from this study could serve as the foundation for breeding RCR-tolerant soybean varieties, and the candidate genes could be validated to deepen our understanding of soybean response to RCR.

Regulation of seed traits in soybean

Soybean (Glycine max) is an essential economic crop that provides vegetative oil and protein for humans, worldwide. Increasing soybean yield as well as improving seed quality is of great importance. Seed weight/size, oil and protein content are the three major traits determining seed quality, and seed weight also influences soybean yield. In recent years, the availability of soybean omics data and the development of related techniques have paved the way for better research on soybean functional genomics, providing a comprehensive understanding of gene functions. This review summarizes the regulatory genes that influence seed size/weight, oil content and protein content in soybean. We also provided a general overview of the pleiotropic effect for the genes in controlling seed traits and environmental stresses. Ultimately, it is expected that this review will be beneficial in breeding improved traits in soybean.

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.

QTLs and Candidate Genes for Seed Protein Content in Two Recombinant Inbred Line Populations of Soybean

This study aimed to discover the quantitative trait loci (QTL) associated with a high seed protein content in soybean and unravel the potential candidate genes. We developed two recombinant inbred line populations: YS and SI, by crossing Saedanbaek (high protein) with YS2035-B-91-1-B-1 (low protein) and Saedanbaek with Ilmi (low protein), respectively, and evaluated the protein content for three consecutive years. Using single-nucleotide polymorphism (SNP)-marker-based linkage maps, four QTLs were located on chromosomes 15, 18, and 20 with high logarithm of odds values (5.9-55.0), contributing 5.5-66.0% phenotypic variance. In all three experimental years, qPSD20-1 and qPSD20-2 were stable and identified in overlapping positions in the YS and SI populations, respectively. Additionally, novel QTLs were identified on chromosomes 15 and 18. Considering the allelic sequence variation between parental lines, 28 annotated genes related to soybean seed protein-including starch, lipid, and fatty acid biosynthesis-related genes-were identified within the QTL regions. These genes could potentially affect protein accumulation during seed development, as well as sucrose and oil metabolism. Overall, this study offers insights into the genetic mechanisms underlying a high soybean protein content. The identified potential candidate genes can aid marker-assisted selection for developing soybean lines with an increased protein content.