Allelic Variation and Distribution of the Major Maturity Genes in Different Soybean Collections

Genome-Wide Association Studies Prioritize Genes Controlling Seed Size and Reproductive Period Length in Soybean

Hundred-seed weight (HSW) and reproductive period length (RPL) are two major agronomic traits critical for soybean production and adaptation. However, both traits are quantitatively controlled by multiple genes that have yet to be comprehensively elucidated due to the lack of major genes; thereby, the genetic basis is largely unknown. In the present study, we conducted comprehensive genome-wide association analyses (GWAS) of HSW and RPL with multiple sets of accessions that were phenotyped across different environments. The large-scale analysis led to the identification of sixty-one and seventy-four significant QTLs for HSW and RPL, respectively. An ortholog-based search analysis prioritized the most promising candidate genes for the QTLs, including nine genes (TTG2, BZR1, BRI1, ANT, KLU, EOD1/BB, GPA1, ABA2, and ABI5) for HSW QTLs and nine genes (such as AGL8, AGL9, TOC1, and COL4) and six known soybean flowering time genes (E2, E3, E4, Tof11, Tof12, and FT2b) for RPL QTLs. We also demonstrated that some QTLs were targeted during domestication to drive the artificial selection of both traits towards human-favored traits. Local adaptation likely contributes to the increased genomic diversity of the QTLs underlying RPL. The results provide additional insight into the genetic basis of HSW and RPL and prioritize a valuable resource of candidate genes that merits further investigation to reveal the complex molecular mechanism and facilitate soybean improvement.

Genome-wide association study reveals GmFulb as candidate gene for maturity time and reproductive length in soybeans (Glycine max)

The ability of soybean [Glycine max (L.) Merr.] to adapt to different latitudes is attributed to genetic variation in major E genes and quantitative trait loci (QTLs) determining flowering time (R1), maturity (R8), and reproductive length (RL). Fully revealing the genetic basis of R1, R8, and RL in soybeans is necessary to enhance genetic gains in soybean yield improvement. Here, we performed a genome-wide association analysis (GWA) with 31,689 single nucleotide polymorphisms (SNPs) to detect novel loci for R1, R8, and RL using a soybean panel of 329 accessions with the same genotype for three major E genes (e1-as/E2/E3). The studied accessions were grown in nine environments and observed for R1, R8 and RL in all environments. This study identified two stable peaks on Chr 4, simultaneously controlling R8 and RL. In addition, we identified a third peak on Chr 10 controlling R1. Association peaks overlap with previously reported QTLs for R1, R8, and RL. Considering the alternative alleles, significant SNPs caused RL to be two days shorter, R1 two days later and R8 two days earlier, respectively. We identified association peaks acting independently over R1 and R8, suggesting that trait-specific minor effect loci are also involved in controlling R1 and R8. From the 111 genes highly associated with the three peaks detected in this study, we selected six candidate genes as the most likely cause of R1, R8, and RL variation. High correspondence was observed between a modifying variant SNP at position 04:39294836 in GmFulb and an association peak on Chr 4. Further studies using map-based cloning and fine mapping are necessary to elucidate the role of the candidates we identified for soybean maturity and adaptation to different latitudes and to be effectively used in the marker-assisted breeding of cultivars with optimal yield-related traits.

Going north: adaptation of soybean to long-day environments

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Zhu X, Leiser WL, Hahn V, Würschum T. 2023. The genetic architecture of soybean photothermal adaptation to high latitudes. Journal of Experimental Botany 74,2987–3002

In plant breeding, understanding genetic variation in the photoperiodic control of flowering time of crop plants such as soybean is a prerequisite for managing adaptation to new environments. Zhu et al. (2023) analyzed a large diversity panel of >1500 early maturity soybean lines to disclose the genetic architecture behind the timing of flowering and maturity. Their findings confirm known maturity loci and reveal new candidate genes and alleles as well as environmental interactions of individual quantitative trait loci (QTLs) for flowering and maturity time. The results shed light on the complexity of the regulatory network which controls the timing of flowering in soybean. This supports the fine-tuning of plant architectures through the combination of stem termination and flowering genes towards a better adaptation of soybean to high latitudes or other stressful environments.

Genetic Diversity and Population Structure of European Soybean Germplasm Revealed by Single Nucleotide Polymorphism

Soybean is the most grown high-protein crop in the world. Despite the rapid increase of acreage and production volume, European soybean production accounts for only 34% of its consumption in Europe. This study aims to support the optimal exploitation of genetic resources by European breeding programs by investigating the genetic diversity and the genetic structure of 207 European cultivars or American introductions registered in Europe, which were genotyped by the SoySNP50K array. The expected heterozygosity (H_e) was 0.34 for the entire collection and ranged among countries from 0.24 for Swiss cultivars to 0.32 for American cultivars (partly reflecting differences in sample size between countries). Cluster analysis grouped all genotypes into two main clusters with eight subgroups that corresponded to the country of origin of cultivars and their maturity group. Pairwise F_st values between countries of origin showed the highest differentiation of Swiss cultivars from the rest of the European gene pool, while the lowest mean differentiation was found between American introductions and all other European countries. On the other hand, F_st values between maturity groups were much lower compared to those observed between countries. In analysis of molecular variance, the total genetic variation was partitioned either by country of origin or by maturity group, explaining 9.1% and 3.5% of the total genetic variance, respectively. On the whole, our results suggest that the European soybean gene pool still has sufficient diversity due to the different historical breeding practices in western and eastern countries and the relatively short period of breeding in Europe.

Crop breeding for a changing climate in the Pannonian region: towards integration of modern phenotyping tools

The Pannonian Plain, as the most productive region of Southeast Europe, has a long tradition of agronomic production as well as agronomic research and plant breeding. Many research institutions from the agri-food sector of this region have a significant impact on agriculture. Their well-developed and fruitful breeding programmes resulted in productive crop varieties highly adapted to the specific regional environmental conditions. Rapid climatic changes that occurred during the last decades led to even more investigations of complex interactions between plants and their environments and the creation of climate-smart and resilient crops. Plant phenotyping is an essential part of botanical, biological, agronomic, physiological, biochemical, genetic, and other omics approaches. Phenotyping tools and applied methods differ among these disciplines, but all of them are used to evaluate and measure complex traits related to growth, yield, quality, and adaptation to different environmental stresses (biotic and abiotic). During almost a century-long period of plant breeding in the Pannonian region, plant phenotyping methods have changed, from simple measurements in the field to modern plant phenotyping and high-throughput non-invasive and digital technologies. In this review, we present a short historical background and the most recent developments in the field of plant phenotyping, as well as the results accomplished so far in Croatia, Hungary, and Serbia. Current status and perspectives for further simultaneous regional development and modernization of plant phenotyping are also discussed.

Artificial Neural Network for Discrimination and Classification of Tropical Soybean Genotypes of Different Relative Maturity Groups

Soybean has a recognized narrow genetic base that often makes it difficult to visualize available genetic and phenotypic variability and identify superior genotypes during the selection process. However, the phenotypic expression of soybean plants is highly affected by photoperiod and the cultivation of a given variety is performed in the latitude range that presents ideal conditions for its development based on its relative maturity group (RMG) for the optimization of the phenotypic expression of its genotype. Based on the above, this study aimed to evaluate the efficiency of artificial neural networks (ANNs) as a tool for the correct discrimination and classification of tropical soybean genotypes according to their relative maturity group during the population selection process with the aim of optimizing the phenotypic performance of these selected genotypes. For this purpose, three biparental populations were synthesized, one with a wide genetic variability for the RMG character obtained from the hybridization between genitors of maturity groups RMG 5 (Sub-tropical 23° LS) × RMG 9.4 (Tropical 0° LS) and two populations with a narrow variability obtained between genitors RMG 7.3 (Tropical 20° LS) × RMG 9.4 and RMG 5.3 × RMG 6.7, respectively. Criteria for comparing the developed ANN architecture with Fisher's linear and Anderson's quadratic parametric discriminant methodologies were applied to the data for the discrimination and classification of the genotypes. ANN showed an apparent error rate of less than 8.16% as well as a low influence of environmental factors, correctly classifying the genotypes in the populations even in cases of reduced genetic variability such as in the RMG 5 × RMG 6 population. In contrast, the discriminant functions were inefficient in correctly classifying the genotypes in the populations with genealogical similarity (RMG 5 × RMG 6) and wide genetic variability, with an error rate of more than 50%. Based on the results of this study, ANN can be used for the discrimination of genotypes in the initial generations of selection in breeding programs for the development of high performance cultivars for wide and reduced photoperiod amplitudes, even with fewer selection environments, more efficiently, and with fewer time and resources applied. As a result of similarity between the parents, ANN can correctly classify genotypes from populations with a narrow genetic base, in addition to pure lines and genotypes with a high degree of inbreeding.

Genetic control and allele variation among soybean maturity groups 000 through IX

Soybean [Glycinemax (L.) Merr.] maturity determines the growing region of a given soybean variety and is a primary factor in yield and other agronomic traits. The objectives of this research were to identify the quantitative trait loci (QTL) associated with maturity groups (MGs) and determine the genetic control of soybean maturity in each MG. Using data from 16,879 soybean accessions, genome-wide association (GWA) analyses were conducted for each paired MG and across MGs 000 through IX. Genome-wide association analyses were also performed using 184 genotypes (MGs V-IX) with days to flowering (DTF) and maturity (DTM) collected in the field. A total of 58 QTL were identified to be significantly associated with MGs in individual GWAs, which included 12 reported maturity loci and two stem termination genes. Genome-wide associations across MGs 000-IX detected a total of 103 QTL and confirmed 54 QTL identified in the individual GWAs. Of significant loci identified, qMG-5.2 had effects on the highest number (9) of MGs, followed by E2, E3, Dt2, qMG-15.5, E1, qMG-13.1, qMG-7.1, and qMG-16.1, which affected five to seven MGs. A high number of genetic loci (8-25) that affected MGs 0-V were observed. Stem termination genes Dt1 and Dt2 mainly had significant allele variation in MGs II-V. Genome-wide associations for DTF, DTM, and reproductive period (RP) in the diversity panel confirmed 15 QTL, of which seven were observed in MGs V-IX. The results generated can help soybean breeders manipulate the maturity loci for genetic improvement of soybean yield.

Genome-wide association study and genomic selection for yield and related traits in soybean

Soybean [Glycine max (L.) Merr.] is a crop of great interest worldwide. Exploring molecular approaches to increase yield genetic gain has been one of the main challenges for soybean breeders and geneticists. Agronomic traits such as maturity, plant height, and seed weight have been found to contribute to yield. In this study, a total of 250 soybean accessions were genotyped with 10,259 high-quality SNPs postulated from genotyping by sequencing (GBS) and evaluated for grain yield, maturity, plant height, and seed weight over three years. A genome-wide association study (GWAS) was performed using a Bayesian Information and Linkage Disequilibrium Iteratively Nested Keyway (BLINK) model. Genomic selection (GS) was evaluated using a ridge regression best linear unbiased predictor (rrBLUP) model. The results revealed that 20, 31, 37, and 23 SNPs were significantly associated with maturity, plant height, seed weight, and yield, respectively; Many SNPs were mapped to previously described maturity and plant height loci (E2, E4, and Dt1) and a new plant height locus was mapped to chromosome 20. Candidate genes were found in the vicinity of the two SNPs with the highest significant levels associated with yield, maturity, plant height, seed weight, respectively. A 11.5-Mb region of chromosome 10 was associated with both yield and seed weight. Overall, the accuracy of GS was dependent on the trait, year, and population structure, and high accuracy indicates that these agronomic traits can be selected in molecular breeding through GS. The SNP markers identified in this study can be used to improve yield and agronomic traits through the marker-assisted selection and GS in breeding programs.

The Synchronized Efforts to Decipher the Molecular Basis for Soybean Maturity Loci E1, E2, and E3 That Regulate Flowering and Maturity

The general concept of photoperiodism, i.e., the photoperiodic induction of flowering, was established by Garner and Allard (1920). The genetic factor controlling flowering time, maturity, or photoperiodic responses was observed in soybean soon after the discovery of the photoperiodism. E1, E2, and E3 were named in 1971 and, thereafter, genetically characterized. At the centennial celebration of the discovery of photoperiodism in soybean, we recount our endeavors to successfully decipher the molecular bases for the major maturity loci E1, E2, and E3 in soybean. Through systematic efforts, we successfully cloned the E3 gene in 2009, the E2 gene in 2011, and the E1 gene in 2012. Recently, successful identification of several circadian-related genes such as PRR3a, LUX, and J has enriched the known major E1-FTs pathway. Further research progresses on the identification of new flowering and maturity-related genes as well as coordinated regulation between flowering genes will enable us to understand profoundly flowering gene network and determinants of latitudinal adaptation in soybean.

A Genome-Wide Genetic Diversity Scan Reveals Multiple Signatures of Selection in a European Soybean Collection Compared to Chinese Collections of Wild and Cultivated Soybean Accessions

Targeted and untargeted selections including domestication and breeding efforts can reduce genetic diversity in breeding germplasm and create selective sweeps in crop genomes. The genomic regions at which selective sweeps are detected can reveal important information about signatures of selection. We have analyzed the genetic diversity within a soybean germplasm collection relevant for breeding in Europe (the EUCLEG collection), and have identified selective sweeps through a genome-wide scan comparing that collection to Chinese soybean collections. This work involved genotyping of 480 EUCLEG soybean accessions, including 210 improved varieties, 216 breeding lines and 54 landraces using the 355K SoySNP microarray. SNP calling of 477 EUCLEG accessions together with 328 Chinese soybean accessions identified 224,993 high-quality SNP markers. Population structure analysis revealed a clear differentiation between the EUCLEG collection and the Chinese materials. Further, the EUCLEG collection was sub-structured into five subgroups that were differentiated by geographical origin. No clear association between subgroups and maturity group was detected. The genetic diversity was lower in the EUCLEG collection compared to the Chinese collections. Selective sweep analysis revealed 23 selective sweep regions distributed over 12 chromosomes. Co-localization of these selective sweep regions with previously reported QTLs and genes revealed that various signatures of selection in the EUCLEG collection may be related to domestication and improvement traits including seed protein and oil content, phenology, nitrogen fixation, yield components, diseases resistance and quality. No signatures of selection related to stem determinacy were detected. In addition, absence of signatures of selection for a substantial number of QTLs related to yield, protein content, oil content and phenological traits suggests the presence of substantial genetic diversity in the EUCLEG collection. Taken together, the results obtained demonstrate that the available genetic diversity in the EUCLEG collection can be further exploited for research and breeding purposes. However, incorporation of exotic material can be considered to broaden its genetic base.

Productivity of soybean varieties under different irrigation regimes

Abstract. World soybean acreage increases by 3 million hectares annually with average yield of 2.7 t/ha. Significant growth of soybean production in Russia is constrained by increased climate aridization and a declining yield of up to 1.5 t/ha. An important factor in intensification of soybean production is to expand its crops under irrigation. Introduction of adapted and high-yielding varieties of regional selection, followed by improvement of crop water supply, increases yields up to 34 t/ha. Soybean varieties selected by Russian Research Institute of Irrigated Agriculture and admitted to production in the Lower Volga region: VNIIOZ 86 (since 2002), VNIIOZ 31 (since 2011), Volgogradka 2 (since 2020) were studied. The experiments were conducted at Russian Research Institute of Irrigated Agriculture in 2013-2015. The experiment included two factors: factor A - varieties, factor B - irrigation regime (70-80-70 % of FMC, 80-80-70 % of FMC and control - 80-80-80 % of FMC). Plots of the 1st (600 m2) and 2nd (200 m2) order were sown in 4-fold replication by a wide-row method (0.7 m) in mid-May with a planned yield of 2.53.5 t/ha (N90P90K60 a. i./ha). Soybean varieties differed in peculiarities of crop structure formation. Differentiated irrigation regime resulted in more cost-efficient water consumption followed by yield increase compared to the control. The highest yields were formed by Volgogradka 2 variety (2.873.23 t/ha) and VNIIOZ 31 (2.823.19 t/ha), which was significantly higher than in VNIIOZ 86 variety (2.172.51 t/ha). The variable irrigation regime led to yield increase in all soybean varieties, especially in Volgogradka 2 - by 0.310.36 t/ha (10.812.5 %) as compared to the control. It was due to grain increase to 30.936.2 % in the total biomass compared to the control values - 26.627.5 %. The highest amount of post-harvest plant residues (stems, leaves and roots) remained after harvesting Volgogradka 2 (6.397.63 t/ha) and VNIIOZ 31(6.737.9 t/ha), which improved soil fertility well, and the smallest amount was after VNIIOZ 86 variety (4.415.66 t/ha). Differentiated irrigation regime led to decrease in vegetative mass in soil - 4.417.42 t/ha compared to the control (5.667.9 t/ha). Thus, Volgogradka 2 and VNIIOZ 31 can be recommended for irrigated agriculture in the Lower Volga region, as they provide high yields under differentiated (relatively cost-efficient) irrigation regime and improve soil fertility due to large biomass remained in soil after harvesting.

The Modification of Circadian Clock Components in Soybean During Domestication and Improvement

Agricultural production is greatly dependent on daylength, which is determined by latitude. Living organisms align their physiology to daylength through the circadian clock, which is made up of input sensors, core and peripheral clock components, and output. The light/dark cycle is the major input signal, moderated by temperature fluctuations and metabolic changes. The core clock in plants functions mainly through a number of transcription feedback loops. It is known that the circadian clock is not essential for survival. However, alterations in the clock components can lead to substantial changes in physiology. Thus, these clock components have become the de facto targets of artificial selection for crop improvement during domestication. Soybean was domesticated around 5,000 years ago. Although the circadian clock itself is not of particular interest to soybean breeders, specific alleles of the circadian clock components that affect agronomic traits, such as plant architecture, sensitivity to light/dark cycle, flowering time, maturation time, and yield, are. Consequently, compared to their wild relatives, cultivated soybeans have been bred to be more adaptive and productive at different latitudes and habitats for acreage expansion, even though the selection processes were made without any prior knowledge of the circadian clock. Now with the advances in comparative genomics, known modifications in the circadian clock component genes in cultivated soybean have been found, supporting the hypothesis that modifications of the clock are important for crop improvement. In this review, we will summarize the known modifications in soybean circadian clock components as a result of domestication and improvement. In addition to the well-studied effects on developmental timing, we will also discuss the potential of circadian clock modifications for improving other aspects of soybean productivity.

Exploring the genetic base of the soybean germplasm from Africa, America and Asia as well as mining of beneficial allele for flowering and seed weight

Genetic diversity is the foundation for any breeding program. The present study analyzed the genetic base of 163 soybean genotypes from three continents viz. Africa, America and Asia using 68 trait-linked simple sequence repeats (SSR) markers. The average number of alleles among the germplasm from the three continents followed the trend as Asia (9) > America (8) > Africa (7). Similar trends were observed for gene diversity (0.76 > 0.74 > 0.71) and polymorphism information content (PIC) (0.73 > 0.71 > 0.68). These findings revealed that soybean germplasm from Asia has wider genetic base followed by America, and least in Africa. The 163 genotypes were grouped into 4 clusters by phylogenetic analysis, whereas model-based population structure analysis also divided them into 4 subpopulations comprising 80.61% pure lines and 19.39% admixtures. The genotypes from Africa were easily distinguished from those of other two continents using phylogenetic analysis, indicating important role of geographyical differentiation for this genetic variability. Our results indicated that soybean germplasm has moved from Asia to America, and from America to Africa. Analysis of molecular variance (AMOVA) showed 8.41% variation among the four subpopulations, whereas 63.12% and 28.47% variation existed among and within individuals in the four subpopulations, respectively. Based on the association mapping, a total of 21 SSR markers showed significant association with days to flowering (DoF) and 100-seed weight (HSW). Two markers Satt365 and Satt581 on chromosome 6 and 10, respectively, showed pleiotropic effect or linkage on both traits. Genotype A50 (Gakuran Daizu/PI 506679) from Japan has 8 out of the 13 beneficial alleles for increased HSW. The diverse genotypes, polymorphic SSR markers and desirable alleles identified for DoF and HSW will be used in future breeding programs to improve reproductive, yield and quality traits.

Impacts of genomic research on soybean improvement in East Asia

It has been commonly accepted that soybean domestication originated in East Asia. Although East Asia has the historical merit in soybean production, the USA has become the top soybean producer in the world since 1950s. Following that, Brazil and Argentina have been the major soybean producers since 1970s and 1990s, respectively. China has once been the exporter of soybean to Japan before 1990s, yet she became a net soybean importer as Japan and the Republic of Korea do. Furthermore, the soybean yield per unit area in East Asia has stagnated during the past decade. To improve soybean production and enhance food security in these East Asian countries, much investment has been made, especially in the breeding of better performing soybean germplasms. As a result, China, Japan, and the Republic of Korea have become three important centers for soybean genomic research. With new technologies, the rate and precision of the identification of important genomic loci associated with desired traits from germplasm collections or mutants have increased significantly. Genome editing on soybean is also becoming more established. The year 2019 marked a new era for crop genome editing in the commercialization of the first genome-edited plant product, which is a high-oleic-acid soybean oil. In this review, we have summarized the latest developments in soybean breeding technologies and the remarkable progress in soybean breeding-related research in China, Japan, and the Republic of Korea.