Combined Linkage Mapping and BSA to Identify QTL and Candidate Genes for Plant Height and the Number of Nodes on the Main Stem in Soybean

Construction of Genetic Map and QTL Mapping for Seed Size and Quality Traits in Soybean (Glycine max L.)

Soybean (Glycine max L.) is the main source of vegetable protein and edible oil for humans, with an average content of about 40% crude protein and 20% crude fat. Soybean yield and quality traits are mostly quantitative traits controlled by multiple genes. The quantitative trait loci (QTL) mapping for yield and quality traits, as well as for the identification of mining-related candidate genes, is of great significance for the molecular breeding and understanding the genetic mechanism. In this study, 186 individual plants of the F2 generation derived from crosses between Changjiangchun 2 and Yushuxian 2 were selected as the mapping population to construct a molecular genetic linkage map. A genetic map containing 445 SSR markers with an average distance of 5.3 cM and a total length of 2375.6 cM was obtained. Based on constructed genetic map, 11 traits including hundred-seed weight (HSW), seed length (SL), seed width (SW), seed length-to-width ratio (SLW), oil content (OIL), protein content (PRO), oleic acid (OA), linoleic acid (LA), linolenic acid (LNA), palmitic acid (PA), stearic acid (SA) of yield and quality were detected by the multiple- d size traits and 113 QTLs related to quality were detected by the multiple QTL model (MQM) mapping method across generations F2, F2:3, F2:4, and F2:5. A total of 71 QTLs related to seed size traits and 113 QTLs related to quality traits were obtained in four generations. With those QTLs, 19 clusters for seed size traits and 20 QTL clusters for quality traits were summarized. Two promising clusters, one related to seed size traits and the other to quality traits, have been identified. The cluster associated with seed size traits spans from position 27876712 to 29009783 on Chromosome 16, while the cluster linked to quality traits spans from position 12575403 to 13875138 on Chromosome 6. Within these intervals, a reference genome of William82 was used for gene searching. A total of 36 candidate genes that may be involved in the regulation of soybean seed size and quality were screened by gene functional annotation and GO enrichment analysis. The results will lay the theoretical and technical foundation for molecularly assisted breeding in soybean.

QTL Mapping of Soybean (Glycine max) Vine Growth Habit Trait

The vine growth habit (VGH) is a notable property of wild soybean plants that also holds a high degree of importance in domestication as it can preclude using these wild cultivars for breeding and improving domesticated soybeans. Here, a bulked segregant analysis (BSA) approach was employed to study the genetic etiology of the VGH in soybean plants by integrating linkage mapping and population sequencing approaches. To develop a recombinant inbred line (RIL) population, the cultivated Zhongdou41 (ZD41) soybean cultivar was bred with ZYD02787, a wild soybean accession. The VGH status of each line in the resultant population was assessed, ultimately leading to the identification of six and nine QTLs from the BSA sequencing of the F4 population and F6-F8 population sequence mapping, respectively. One QTL shared across these analyzed generations was detected on chromosome 19. Three other QTLs detected by BSA-seq were validated and localized to the 90.93 kb, 2.9 Mb, and 602.08 kb regions of chromosomes 6 and 13, harboring 14, 53, and 4 genes, respectively. Three consistent VGH-related QTLs located on chromosomes 2 and 19 were detected in a minimum of three environments, while an additional six loci on chromosomes 2, 10, 13, and 18 were detected in at least two environments via ICIM mapping. Of all the detected loci, five had been reported previously whereas seven represent novel QTLs. Together, these data offer new insights into the genetic basis of the VGH in soybean plants, providing a rational basis to inform the use of wild accessions in future breeding efforts.

The genetic basis of shoot architecture in soybean

Shoot architecture refers to the three-dimensional body plan of the above ground organs of the plant. The patterning of this body plan results from the tight genetic control of the size and maintenance of meristems, the initiation of axillary growth, and the timing of developmental phase transition. Variation in shoot architecture can result in dramatic differences in plant productivity and/or grain yield due to their effects on light interception, photosynthetic efficiency, response to agronomic inputs, and environmental adaptation. The fine-tuning of shoot architecture has consequently been of great interest to plant breeders, driving the need for deeper understanding of the genes and molecular mechanisms governing these traits. In soybean, the world's most important oil and protein crop, major components of shoot architecture include stem growth habit, plant height, branch angle, branch number, leaf petiole angle, and the size and shape of leaves. Key genes underlying some of these traits have been identified to integrate hormonal, developmental, and environmental signals modulating the growth and orientation of shoot organs. Here we summarize the current knowledge and recent advances in the understanding of the genetic control of these important architectural traits in soybean.

Identifications of QTLs and Candidate Genes Associated with Pseudomonas syringae Responses in Cultivated Soybean (Glycine max) and Wild Soybean (Glycine soja)

Soybeans (Glycine max) are a key food crop, serving as a valuable source of both oil and plant-derived protein. Pseudomonas syringae pv. glycinea (Psg) is among the most aggressive and prevalent pathogens affecting soybean production, causing a form of bacterial spot disease that impacts soybean leaves and thereby reduces crop yields. In this study, 310 natural soybean varieties were screened for Psg resistance and susceptibility. The identified susceptible and resistant varieties were then used for linkage mapping, BSA-seq, and whole genome sequencing (WGS) analyses aimed at identifying key QTLs associated with Psg responses. Candidate Psg-related genes were further confirmed through WGS and qPCR analyses. Candidate gene haplotype analyses were used to explore the associations between haplotypes and soybean Psg resistance. In addition, landrace and wild soybean plants were found to exhibit a higher degree of Psg resistance as compared to cultivated soybean varieties. In total, 10 QTLs were identified using chromosome segment substitution lines derived from Suinong14 (cultivated soybean) and ZYD00006 (wild soybean). Glyma.10g230200 was found to be induced in response to Psg, with the Glyma.10g230200 haplotype corresponding to soybean disease resistance. The QTLs identified herein can be leveraged to guide the marker-assisted breeding of soybean cultivars that exhibit partial resistance to Psg. Moreover, further functional and molecular studies of Glyma.10g230200 have the potential to offer insight into the mechanistic basis for soybean Psg resistance.

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.

GmARP is Related to the Type III Effector NopAA to Promote Nodulation in Soybean (Glycine max)

Type III effectors secreted by rhizobia regulate nodulation in the host plant and are important modulators of symbiosis between rhizobia and soybean (Glycine max), although the underlying mechanisms are poorly understood. Here, we studied the type III effector NopAA in Sinorhizobium fredii HH103, confirming its secretion into the extracellular environment under the action of genistein. The enzyme activity of NopAA was investigated in vitro, using xyloglucan and β-glucan as substrates. NopAA functions were investigated by the generation of a NopAA mutant and the effects of NopAA deficiency on symbiosis were analyzed. Soybean genes associated with NopAA were identified in a recombinant inbred line (RIL) population and their functions were verified. NopAA was confirmed to be a type III effector with glycosyl hydrolase activity, and its mutant did not promote nodulation. Quantitative trait locus (QTL) analysis identified 10 QTLs with one, Glyma.19g074200 (GmARP), found to be associated with NopAA and to positively regulate the establishment of symbiosis. All these results support the hypothesis that type III effectors interact with host proteins to regulate the establishment of symbiosis and suggest the possibility of manipulating the symbiotic soybean–rhizobia interaction to promote efficient nitrogen fixation.

Identification of Genomic Regions Associated with Vine Growth and Plant Height of Soybean

Vining growth (VG) and high plant height (PH) are the physiological traits of wild soybean that preclude their utilization for domesticated soybean breeding and improvement. To identify VG- and PH-related quantitative trait loci (QTLs) in different genetic resources, two populations of recombinant inbred lines (RILs) were developed by crossing a cultivated soybean, Zhonghuang39 (ZH39), with two wild soybean accessions, NY27-38 and NY36-87. Each line from the two crosses was evaluated for VG and PH. Three QTLs for VG and three for PH, detected in the ZH39 × NY27-38 population of the RILs, co-located on chromosomes 2, 17 and 19. The VG- and PH-related QTL in the ZH39 × NY36-87 population co-located on chromosome 19. A common QTL shared by the two populations was located on chromosome 19, suggesting that this major QTL was consistently selected for in different genetic backgrounds. The results suggest that different loci are involved in the domestication or adaptations of soybean of various genetic backgrounds. The molecular markers presented here would benefit the fine mapping and cloning of candidate genes underlying the VG and PH co-localized regions and thus facilitate the utilization of wild resources in breeding by avoiding undesirable traits.

Genetic mapping high protein content QTL from soybean 'Nanxiadou 25' and candidate gene analysis

BACKGROUND

Soybean is a globally important legume crop that provides a primary source of high-quality vegetable protein and oil. Seed protein content (SPC) is a valuable quality trait controlled by multiple genes in soybean.

RESULTS

In this study, we performed quantitative trait loci (QTL) mapping, QTL-seq, and RNA sequencing (RNA-seq) to reveal the genes controlling protein content in the soybean by using the high protein content variety Nanxiadou 25. A total of 50 QTL for SPC distributed on 14 chromosomes except chromosomes 4, 12, 14, 17, 18, and 19 were identified by QTL mapping using 178 recombinant inbred lines (RILs). Among these QTL, the major QTL qSPC_20-1 and qSPC_20-2 on chromosome 20 were repeatedly detected across six tested environments, corresponding to the location of the major QTL detected using whole-genome sequencing-based QTL-seq. 329 candidate DEGs were obtained within the QTL region of qSPC_20-1 and qSPC_20-2 via gene expression profile analysis. Nine of which were associated with SPC, potentially representing candidate genes. Clone sequencing results showed that different single nucleotide polymorphisms (SNPs) and indels between high and low protein genotypes in Glyma.20G088000 and Glyma.16G066600 may be the cause of changes in this trait.

CONCLUSIONS

These results provide the basis for research on candidate genes and marker-assisted selection (MAS) in soybean breeding for seed protein content.

What Traits Should Be Measured for Biomass in Kenaf?

Kenaf (Hibiscus cannabinus L.) is widely used as an important industrial crop. It has the potential to act as a sustainable energy provider in the future, and contains beneficial compounds for medical and therapeutic use. However, there are no clear breeding strategies to increase its biomass or leaf volume. Thus, to attain an increase in these parameters, we examined potential key traits such as stem diameter, plant height, and number of nodes to determine the relationship among them. We hypothesized that it would be easier to reduce the amount of time and labor required for breeding if correlations among these parameters are identified. In this study, we found a strong positive correlation between height and number of nodes (Spearman’s Rho = 0.67, p < 0.001) and number of nodes and stem diameter (Spearman’s Rho = 0.65, p < 0.001), but a relatively low correlation (Spearman’s Rho = 0.34, p < 0.01) between height and stem diameter in the later stages of kenaf growth. We suggest that an efficient breeding strategy could be devised according to the breeding purpose, considering the correlations between various individual traits of kenaf.

Update of Genetic Linkage Map and QTL Analysis for Growth Traits in Eucommia ulmoides Oliver

Eucommia ulmoides (Tu-chung) is an economically and ecologically important tree species which has attracted worldwide attention due to its application in pharmacology, landscaping, wind sheltering and sand fixation. Molecular marker technologies can elucidate the genetic mechanism and substantially improve the breeding efficiency of E. ulmoides. The current research updated the original linkage map, and quantitative trait loci (QTL) analysis was performed on tree growth traits measured over 10 consecutive years in an E. ulmoides F1 population (“Xiaoye” × “Qinzhong No.1”). In total, 452 polymorphic markers were scored from 365 simple sequence repeat (SSR) primers, with an average of 1.24 polymorphic markers per primer combination. The integrated map was 1913.29 cM (centimorgan) long, covering 94.10% of the estimated genome and with an average marker density of 2.20 cM. A total of 869 markers were mapped into 19 major independent linkage groups. Growth-related traits measured over 10 consecutive years showed a significant correlation, and 89 hypothetical QTLs were forecasted and divided into 27 distinct loci. Three traits for tree height, ground diameter and crown diameter detected 25 QTLs (13 loci), 32 QTLs (17 loci) and 15 QTLs (10 loci), respectively. Based on BLASTX search results in the NCBI database, six candidate genes were obtained. It is important to explore the growth-related genetic mechanism and lay the foundation for the genetic improvement of E. ulmoides at the molecular level.