A comparison of Chinese wild and cultivar soybean with European soybean collections on genetic diversity by Genome-Wide Scan

doi:10.21203/rs.3.rs-4647180/v1

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A comparison of Chinese wild and cultivar soybean with European soybean collections on genetic diversity by Genome-Wide Scan

https://doi.org/10.21203/rs.3.rs-4647180/v1

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Although soybeans (Glycine max [L.] Merr.) originated in China and have spread worldwide, artificial selection for different breeding targets and methods in various regions can alter the genetic makeup of soybeans, enabling them to adapt to different environments. China has established a soybean germplasm gene bank that stores over 30,000 soybean germplasms from all over the world, but it contains few modern European varieties. The selective sweep analysis is an effective method for evaluating genetic diversity among populations and subpopulations. To compare the genetic diversity between Chinese and European germplasms, we genotyped 797 European varieties, 804 Chinese elite cultivars and landraces, and 54 Chinese wild varieties using the ZDX1 array, respectively. An analysis of 158,315 SNPs demonstrated a higher genetic diversity in Chinese wild soybeans and cultivars. Moreover, population structure findings indicated that European varieties possess partial Chinese ancestry. The joint analysis of pi, F_ST and XP-CLR identified 140 selected regions between Chinese and European germplasms in total. Specifically, the Chinese collection had 124 regions distributed across 15 chromosomes, while the European collection had 16 regions spread over 10 chromosomes. The QTLs identified within these selected regions highlight the significant differences in breeding targets across regions, providing a scientific basis for both Chinese and European breeders to utilize these germplasm resources.

Genetic diversity

Selective sweep analysis

European soybean

Chinese soybean

Soybean (Glycine max [L.] Merr.), as an essential source of vegetable protein and oil, traces its origin to China, boasting a cultivation history exceeding 3000 years (Li et al. 2008).. The crop made its way to Korea around the 2nd century BCE from China, subsequently reaching Japan from Korea. By the 6th century CE, late-ripening soybeans from southern China were introduced to the Kyushu region of Japan via maritime routes. Soybeans were brought to the Netherlands before 1737 and to the United States from China via the United Kingdom in 1765. The earliest records of soybeans in Argentina date back to 1882, with Brazil's introduction of the crop occurring relatively later. Artificial selection across different regions for various breeding objectives has significantly influenced the genetic diversity of soybeans, allowing them to adapt to diverse environments. According to the Food and Agriculture Organization (FAO), the global inventory of soybean germplasm resources surpasses 200,000 entries, including duplicates. The Chinese National Genebank holds over 43,000 cultivated soybean germplasms and more than 10,000 annual wild soybean germplasms (Insititute of Crop Sciences 2013). China leads globally with a collection exceeding 30,000 soybean germplasms, including more than 23,000 cultivated and over 7,000 wild types (Qiu et al. 2013); meanwhile, all soybeans in the United States are of foreign origin, with the country now preserving more than 20,000 soybean germplasms. Prior to World War II, soybean cultivation and production received limited attention. Post-1945, global soybean production saw a significant expansion, spearheaded by the United States, where soybean output surpassed China's by 1954. Since the 1970s, South American countries like Brazil, Argentina, and Paraguay have vigorously developed soybean production, with Brazil's yield exceeding China's by 1974. China's soybean germplasm resources have not only played a crucial role in domestic breeding and production but also have made indelible contributions to global soybean breeding and production.

In China, soybeans rank as the fourth largest crop after corn, rice, and wheat. Between 2021 and 2022, China's total soybean production ranged from 16.4 to 20.28 million tons, with imports reaching 91.08 to 96.52 million tons, resulting in a self-sufficiency rate of merely 15–18%. The country's high dependency on soybean imports and the significant risk to its industry are notable. Against the backdrop of limited arable land and in the effort not to compete with staple crops, enhancing per unit area yield and increasing total soybean production are key strategies to alleviate import pressure. Currently, China has developed approximately 3000 varieties (Qiu & Wang 2007, 2018). The modern breeding process grapples with the challenge of a narrow genetic base, with most varieties developed in China between 1923 and 1995 in the main soybean-producing regions of Northeast and Huang-Huai-Hai using local varieties as parents, leading to a narrowing genetic basis due to the over-concentration of parental sources (Xiong et al. 2010). Although Chinese soybeans possess a vast gene pool, traditional breeding has utilized only a fraction (Wang et al. 2006). Recently, the cultivation and utilization of key parental lines in breeding have resulted in closely related breeds with uniform traits, highlighting the genetic vulnerability of these varieties without breakthroughs in yield. Employing foreign germplasm as parents presents a viable and economical solution to this issue. Germplasm collections from various regions serve as important sources of beneficial genetic variation, and the introduction of foreign varieties as parents can effectively address the problem of a narrow genetic base (Wang et al. 2017; Hegstad et al. 2019).

The soybean, native to China, has seen extensive research into the genetic relationships between Chinese and foreign germplasm. Studies spanning various countries, including China-USA (Lijuan et al. 1997; Li et al. 2001; Liu et al. 2017) and China-Japan (Guan et al. 2010), have laid a theoretical foundation for the introduction and utilization of foreign germplasm in Chinese breeding programs.

The genetic relationships uncovered in these studies are pivotal. For instance, research by Guan Rongxia et al. (2007) using SSR markers to analyze the genetic diversity among 32 Chinese soybean varieties and 40 foreign soybean ancestors introduced to China revealed significant findings. Across 22 SSR loci, 170 allelic variations were detected, with Chinese and introduced foreign soybeans averaging 60 and 69 allelic variations, respectively, both showing a genetic diversity index of 0.71. The study identified 48 unique allelic variations in foreign varieties, compared to 22 in Chinese soybeans, with a significant frequency difference in shared allelic variations between Chinese and foreign soybeans. Cluster analysis indicated substantial differences between Chinese breeds and their foreign ancestors. Genomic composition analysis showed that the introduction of Amsoy (USA) and Tokachi Nagaha (Japan) added 23 unique foreign allelic variations to five Chinese soybean breeds, with a retention rate of 29.13%. However, the retention of these allelic variations varies across different genetic backgrounds, suggesting that many unique allelic variations remain unutilized and could further contribute to soybean improvement in China.

Further studies by Qin Jun et al. (2006) on the pedigrees of widely cultivated varieties Suinong 14 and Hefeng 25, which contain foreign genetic material, used SSR markers for genomic analysis. Allelic variations from Tokachi Nagaha (Japanese germplasm) and Amsoy (American germplasm) passed on to Hefeng 25 and Suinong 14 were found to be associated with 100-seed weight and oil content, indicating potential functional gene clusters in certain chromosomal regions. Additionally, American and Japanese germplasms, such as Amsoy, Clark63, Mamoton, and Tokachi Nagaha, have significantly contributed genetic diversity to popular Chinese varieties like Hefeng 25, Suinong 14 (Qin et al. 2006), and Zhonghuang 13 (Zhang et al. 2020).

These findings underscore the importance of integrating global genetic resources into Chinese soybean breeding, demonstrating how foreign germplasm can enrich genetic diversity and contribute to crop improvement. The research not only facilitates the strategic use of global soybean genetic resources but also highlights the potential for discovering and utilizing unique genetic variations for future soybean enhancement.

Soybean was first introduced from China to Europe in the 18th century, and soybean harvested area and yield in Europe began to increase rapidly in the 21st century, and the gap with China is getting smaller (Fogelberg & Recknagel 2017; Karges et al. 2022). Northeast China is the main soybean producing area in China, which is also at the same latitude with the central and north Europe, thus introduce early maturity varieties from Europe can expand the genetic background, thereby improve the main cultivars in Northeast China. But several analysis were carried on between European cultivars and Chinese germplasm bank. In this study, a high-throughput genotyping approach (Sun et al. 2022a) was used to sequence the germplasm from Chinese gene bank and the introduced varieties from Europe. This study aimed to compare the genetic diversity and analyze population structure differences between Chinese and European soybean varieties, enhancing our understanding of their adaptation and evolution. Additionally, it aims to identify genomic regions that may have undergone selective sweeps in soybean breeding and explore their significance for future soybean improvement efforts in Northeast China.

Plant materials

To examine the genetic diversity between Chinese and European soybean germplasms, this study compiled a dataset of 1,655 accessions. Of these, 858 accessions originated from China, comprising 804 elite cultivars and landraces, referred to as Chinese cultivars, along with 54 Glycine soja specimens, denoting the wild soybean varieties native to China. Additionally, the study included 797 accessions from Europe, spanning 16 countries or regions. The entire collection of accessions was sourced from the Institute of Crop Sciences, Chinese Academy of Agricultural Sciences. This comprehensive assembly facilitates a robust comparative analysis, aiming to uncover the genetic diversity and potential unique traits present within and between these distinct soybean populations, providing valuable insights for breeding and conservation efforts (Table S1).

DNA extraction and SNP genotyping

The methods for DNA extraction and SNP genotyping followed those described by Yao et al. (2023). The ZDX1 soybean array, designed by the Institute of Crop Sciences, Chinese Academy of Agricultural Sciences and Beijing Compass Biotechnology Co., Ltd. (Beijing, China), was utilized for genotyping (Sun et al. 2022a).

Genetic diversity analysis

To comprehensively assess the genetic diversity within our soybean germplasm collection, we calculated two key genetic diversity parameters: nucleotide diversity (Pi) and the fixation index (F_ST), utilizing VCFtools (Danecek et al. 2011). These calculations were performed over genomic windows of 100 kilobases (kb) with a stepwise progression of 10kb, allowing for a detailed examination of genetic variation across the genome. The nucleotide diversity (Pi) serves as a measure of the average number of nucleotide differences per site between any two DNA sequences randomly chosen from the sample population, offering insights into the genetic variation present. The fixation index (F_ST), on the other hand, is a statistic that quantifies the degree of genetic differentiation between populations, providing a measure of population divergence due to genetic structure.

In addition to these parameters, the linkage disequilibrium (LD) within the populations was analyzed using PopLDdecay software (Zhang et al. 2019). This analysis involved calculating LD values (r²) for all pairwise combinations of Single Nucleotide Polymorphisms (SNPs) to understand the non-random association of alleles at different loci. LD decay was assessed at the threshold of r² = 0.2 to gauge the extent of linkage disequilibrium, which can offer insights into the genetic architecture and breeding history of the populations under study.

Population structure analysis

To further elucidate the genetic structure of our soybean germplasm collection, Principal Component Analysis (PCA) was performed using PLINK 1.9 software (Chang et al. 2015). PCA is a statistical technique that transforms the original, possibly correlated variables into a set of values of linearly uncorrelated variables called principal components. This method is particularly useful in revealing the underlying genetic structure of populations by identifying patterns of variation that explain the greatest difference between individuals. Phylogenetic analyses were conducted using the FastTree software (Price et al. 2010) with a maximum likelihood estimation method. This approach generated a phylogenetic tree that represents the genetic relationships among the soybean accessions, effectively highlighting the evolutionary pathways and genetic differentiation within the collection.

To complement the PCA and phylogenetic analyses, the ADMIXTURE software (Alexander et al. 2009) was employed to infer the optimal population structure within the study. ADMIXTURE utilizes a model-based clustering algorithm to assign individuals to populations based on their genotype data, estimating the proportions of individual genomes derived from each of the inferred ancestral populations. This method is invaluable for detecting admixture events and understanding the genetic lineage and composition of the soybean germplasm. Together, these analytical approaches offer a comprehensive understanding of the population structure, facilitating the identification of genetic relationships and the distribution of genetic diversity across the soybean collection, thereby informing conservation strategies and breeding programs.

Selective Sweep Analysis

In our study, we employed a multifaceted approach to identify genomic regions under selection between Chinese and European soybean germplasms. Initially, we determined the selection areas by selecting the top 10% of the F_ST values, which indicate population differentiation, and focused on the overlapping areas of the top and bottom 5% of the pi-ratio, a measure of nucleotide diversity, between the two germplasms. In these overlapping areas, the top 5% of the pi-ratio was considered the selection area in the Chinese accessions, while the bottom 5% delineated the selection area in the European accessions. This methodology allows for the nuanced differentiation of selective pressures that have acted distinctly on the genetic makeup of the Chinese and European soybean populations.

Building upon this foundation, we further utilized the Cross Population Composite Likelihood Ratio (XP-CLR) (Chen et al. 2010) method to pinpoint areas within the genome exhibiting signs of selective sweeps by contrasting genetic variances across the populations. The analysis was conducted using windows of 100,000 base pairs (100K) with a step size of 10,000 base pairs (10K). This specific setup was chosen to achieve an optimal balance between detecting selective sweeps with precision and maintaining computational efficiency. Through the application of the XP-CLR algorithm, our study systematically scanned the genome, calculating XP-CLR scores to identify regions where significantly elevated scores indicate the occurrence of recent positive selection. This thorough approach enabled a comprehensive examination of genomic regions subjected to evolutionary selection pressures, offering insights into the adaptive histories of the populations under investigation. Together, these strategies form a comprehensive framework for detecting and analyzing selection in soybean germplasms, reflecting the complex dynamics of evolution and adaptation. SoyBase (https://www.soybase.org) was utilized to conduct searches for Quantitative Trait Loci (QTLs) in selected regions.

Genetic diversity and linkage disequilibrium analysis

Based on an analysis of 158,315 SNPs, it was discovered that 16.36%, 14.73%, and 19.82% of the loci exhibited a minor allele frequency (MAF) of 0 in Chinese wild soybeans, Chinese cultivars, and European soybeans, respectively (Table 1). Conversely, a MAF of greater than or equal to 0.05 was observed in 74.81%, 63.93%, and 57.03% of the loci in Chinese wild soybeans, Chinese cultivars, and European soybeans, respectively. The polymorphic information content (PIC) values for Chinese wild soybeans, Chinese cultivars, and European soybeans were determined to be 0.2782, 0.2221, and 0.2078, respectively, indicating a higher genetic diversity in wild soybeans from China compared to both Chinese and European cultivated soybeans.

Table 1

Distribution of Minor Allele Frequencies (MAF) in SNPs from Different Soybean Sources
Source	MAF
Source	0	> 0.05
CN_cultivate	23313	101205
EU_cultivate	31383	90284
CN_wild	25895	118438

In addition, the analysis of linkage disequilibrium (LD) revealed notable differences among the populations. The average r² value for 797 European varieties was 0.3859, with the r² value declining to half its maximum value at a distance of 99 kb. For the 54 Chinese wild soybeans, the average r² value was notably lower at 0.1428, with the r² value halving at just 14 kb. Similarly, for the 804 Chinese cultivars, the average r² value was 0.2372, with a halving distance of 84 kb (Fig. 1). These findings suggest a greater degree of homozygosity in European varieties compared to both wild and cultivated soybeans in China, providing insight into the genetic structure and evolutionary dynamics of these soybean populations.

Population structure analysis

The population structure of the soybean germplasm was meticulously analyzed through Admixture and Principal Component Analysis (PCA). At a specified value of K = 10, the distinctive population structures of the Chinese and European germplasms emerged with clarity (Fig. 2C). Among the Chinese accessions, it was observed that landraces harbored a richer genetic diversity in comparison to the cultivated varieties, which exhibited a relatively uniform population structure.

Further insights were gleaned from Principal Component Analysis, which highlighted that the first two principal components effectively differentiated wild soybeans in China from others, placing Chinese cultivars in closer genetic proximity to these wild counterparts (Fig. 2A). Nevertheless, a noteworthy overlap between Chinese and European cultivated soybeans was observed, hinting at the possibility that the genetic discrepancies among the overlapping entities might be relatively minor.

Moreover, the construction of an evolutionary tree using the neighbor-joining method underscored a distinct separation between Chinese wild soybeans and Chinese cultivar soybeans (Fig. 2B). This clear delineation not only highlights the genetic diversity within the Chinese soybean germplasm but also emphasizes the complexities involved in soybean evolution and classification. However, the nuanced genetic variances among certain Chinese and European varieties posed challenges in their distinct classification through the evolutionary tree, indicating the complex nature of soybean genetic diversity and evolution. This complexity suggests a rich tapestry of genetic variation that spans across geographical boundaries, reflecting the adaptive responses of soybeans to diverse environments and selective pressures.

Collectively, these three analytical approaches converge on a common inference: the genetic disparities between select segments of Chinese and European soybean germplasms are potentially minimal, underscoring a subtle complexity within the genetic landscape of soybean populations.

Selective Sweep Analysis

We utilized a 100 kb window and 10 kb step to identify selected blocks in Chinese and European accessions using F_ST and pi values, resulting in 1579 blocks for Chinese germplasm and 311 blocks for European germplasm. We integrated the overlapping blocks to obtain a total of 109 and 32 selected regions for Chinese and European accessions, respectively. Additionally, XP-CLR identified 1591 selected regions, and by integrating the results of both methods, we screened 124 regions in China and 16 regions in Europe (Fig. 3).

The selected regions in Chinese germplasm were distributed across all chromosomes except for 1, 5, 7, 10, and 13, spanning the remaining 15 chromosomes, with an average length of 1.31 Mb.These regions contained 41 QTLs related to various traits such as flowering and maturity, S, Zn or Cu content of plants, amino acid content of seeds, oil or oleic acid content of seeds, protein content of seeds, grain number per plant, Sclerotinia sclerotiorum resistance, seed coat color, and water use efficiency. Similarly, the selected regions in European germplasm were distributed on chromosomes 6, 7, 10, 12, 14, 18, and 19, with an average length of 1.76 Mb. These regions contained 7 QTLs related to flowering and palmitic acid content in grains (Table 2, S2).

Table 2

QTLs name and location in the select regions in Chinese varieties and European varieties
Chinese varieties			European varieties
QTL name	Chromosome	Position	QTL name	Chromosome	Position
Seeds per plant 2-g4	2	15923907	First flower 6-g2	7	2434258
Plant height 2-g3	2	15923907	Seed weight 4-g7	7	2434258
Seed oleic 4-g3	6	8208575	First flower 3-g5	7	2434258
Seed linoleic 4-g2	6	8208575	Seed palmitic 2-g3.1	7	2438596
Reproductive period 4-g7	6	10283306	Seed long-chain fatty acid 1-g23.1	7	2438596
Seed protein 9-g3	6	10211244	Seed palmitic 2-g3.2	7	2439023
Seed Met 1-g1	6	10277748	Seed long-chain fatty acid 1-g23.2	7	2439023
Reproductive period 2-g7	6	10283306
Seed coat color 4-g3	8	20702756
Seed Gly 2-g4	9	42738613
Seed Thr 2-g4	9	42738613
Seed Val 2-g4	9	42738613
Seed Leu 2-g4	9	42738613
Shoot Mg 1-g10	12	32521921
Shoot S 1-g21	12	32521921
Shoot Cu 1-g10	12	32374613
Shoot Zn 1-g21	12	32347348
Shoot Cu 1-g9	12	32347348
Shoot Zn 1-g22.1	12	32374613
Shoot Zn 1-g22.2	12	32403359
Sclero 3-g5	12	32434240
Seed protein 5-g1	14	24367698
Reproductive stage length 4-g4	14	31326567
First flower 4-g57	15	1265085
Seed oil 10-g5	15	3913001
Seed oil 4-g11	15	3936757
Seed protein 3-g13	15	3936757
Seed protein 3-g14	15	3937899
Seed oil 4-g12	15	3937899
Seed oil 4-g13	15	3985288
Seed protein 3-g15	15	3985288
Seed Trp 1-g19	15	4006986
First flower 4-g62	15	45731853
Shoot S 1-g24	15	45851553
First flower 4-g74	19	5182596
Seed Trp 1-g23	19	5251007
WUE 2-g52	20	3196500
First flower 4-g84	20	3867301
R8 full maturity 3-g8	20	3903416
First flower 3-g11	20	3903416
Seed protein 7-g30	20	4036946

Comparative Analysis of Soybean Genetic Diversity Across Geographies

In comparison to cultivated varieties, wild soybeans exhibit a higher degree of genetic diversity (Zhao et al. 2018; Li et al. 2020). Our study also revealed that the genetic diversity of wild soybeans in China surpassed that of both cultivated soybeans in China and Europe. As the original center of soybeans, China boasts abundant soybean resources, and previous research has shown that Chinese local varieties typically possess greater genetic diversity and more rapid LD decay rates (Dong et al. 2004; Li et al. 2020). In contrast, the breeding foundation for soybeans in Europe is relatively weaker due to the shorter history of soybean cultivation and smaller cultivation area (Haupt & Schmid 2020). Tavaud-Pirra et al. (2009) were the first to examine 32 European soybean populations from 1950–2000 and found that the genetic diversity of European soybean germplasm was significantly lower than that of North American and Asian soybean germplasm.

Previous analysis of smaller-scale Chinese and European soybean populations often revealed clearer population structures (Saleem et al. 2021; Yao et al. 2023). However, our study found significant gene flow between Chinese and European soybean germplasms (Fig. 2B, C), making it challenging to separate them using conventional population structure analysis. Liu et al. (2020) provided a thorough overview of the global spread of soybeans originating from China. However, their study was constrained by the limited variety of European soybean germplasm available, leading them to use soybean varieties from southern Sweden as a proxy for European germplasm. Despite these limitations, they asserted that the European soybean lineage can be traced back to Northeast China and North America, with the North American soybean germplasm itself having roots in Northeast China (Gizlice et al. 1994). In contrast, our research utilized a broader spectrum of European germplasm, comprising 797 soybean varieties preserved by the Chinese National Soybean GeneBank (CNSGB). This extensive collection facilitated a more comprehensive comparison between the soybean germplasms of Northeast China and Europe. Our findings indicate that certain European soybean germplasms exhibit minimal genetic differences when compared to the Northeast Chinese soybean germplasm, thereby providing molecular evidence supporting the Northeast Chinese ancestry of some European soybeans. This insight enhances our understanding of the genetic continuity and diversity resulting from decades of breeding work, underscoring the close genetic ties between European and Northeast Chinese soybeans.

Selective Sweeps in CN and EU collections

During the domestication of soybean, some genes associated with certain traits were selected and fixed, resulting in a significant reduction in genetic diversity in the affected regions (Goettel et al. 2022; Qin et al. 2023). Selective sweep analysis can be used to locate these selected regions, and in combination with previously identified loci, can help infer differences in selection pressures between populations or aid in the discovery of new genes (Wen et al. 2015; Kim et al. 2021). In this study, we used F_ST, pi, and XP-CLR to perform selective sweep analysis on Chinese Northeast and European soybean populations, which minimized the occurrence of false positives and facilitated the mapping and genetic analysis of the identified regions.

Building on the foundation laid by genome-wide association studies and QTL mapping, our investigation delves into the genetic underpinnings of soybean adaptation to diverse climatic conditions. Several QTLs related to flowering and maturity were identified through a selective sweep, echoing the discoveries in Saleem's study (Saleem et al. 2021). Specifically, our research unveiled a region with pronounced selection signals in the vicinity of loci E4, in addition to a robust selection region in the E1 loci. This observation aligns with the introduction of early-maturing European soybeans into our study, highlighting the genetic influence of breeding efforts aimed at adapting to different climatic conditions. Furthermore, we identified a strong selection signal adjacent to PRR genes, notable for their functional significance in the PRR3/7 subclade, particularly in response to long-day conditions (Lu et al. 2020). These findings underscore the profound impact of domestication and breeding practices on the genetic variation observed within soybean populations across China and Europe, as they have been tailored to thrive under the distinct latitudinal challenges presented by their respective environments.

Seed protein content is one of the most important breeding objectives for soybeans (Singer et al. 2023). In our study, we identified six protein-related QTLs that have undergone selection in Chinese germplasm, yet none were identified within European germplasm. Despite this, preliminary findings indicate that European varieties generally possess higher protein content. This discrepancy leads us to suspect that there are additional protein-related QTLs and genes in European soybeans that remain undiscovered. This possibility highlights the need for further genetic exploration to fully understand and utilize the genetic potential of European soybean varieties for protein content enhancement. In addition, seven QTLs related to seed amino acid content were identified in Chinese germplasm, indicating that Chinese Northeast soybeans may have undergone specific selection for some amino acid content.

The Northeast region of China is renowned as a major hub for high-oil soybean production. Breeding efforts in this area have been focused on enhancing the oil composition of soybeans towards healthier profiles, a trend also reflected in recent European varieties. Our research has identified several oil-related Quantitative Trait Loci (QTLs) in this region, emphasizing its importance in soybean oil production (Song et al. 2023).

Soybean oil typically comprises 21.5% oleic acid, a beneficial unsaturated fatty acid, and 12.2% palmitic acid, a saturated fatty acid which, while stabilizing the oil, can be detrimental to health if consumed excessively (Abdelghany et al. 2020; Julibert et al. 2019). Given the health implications, increasing the proportion of unsaturated fatty acids is a significant breeding target to enhance the nutritional value of soybean oil (Thelen & Ohlrogge 2002). In line with these objectives, our study identified two QTLs related to seed oleic acid content in Chinese germplasm. Furthermore, we discovered an additional QTL in newly introduced European germplasm, indicating potential genetic avenues for improving oil quality in both regions. This cross-regional genetic investigation could further enhance the quality of soybeans by informing targeted breeding strategies.

We also identified some QTL related to nutrient use efficiency and accumulation. The regulation mechanism of nutrient accumulation in soybean tissues is very complex and may vary depending on the soil and environmental conditions in different regions, leading to different selection directions (Ray et al. 2015; Dhanapal et al. 2018).

ZDX1 soybean SNP array

The ZDX1 soybean SNP array was developed using the largest scale of soybean core germplasm to date, encompassing 2214 soybean accessions from China and worldwide. This revolutionary array is capable of accurately identifying soybean germplasm from both China and abroad. When compared to other soybean array like SoySNP50K, 180 K AXIOM®, and NJAU 355 K SoySNP, the ZDX1 array boasts 80% unique SNPs, providing greater coverage of the soybean genome (Sun et al. 2022b). Moreover, its functional sites can efficiently and precisely identify crucial agronomic traits.

Soybean cyst nematode is a widespread issue that continues to affect soybean production regions across the world, and it is rapidly expanding to other areas (Tylka & Marett 2017). In this study, using the ZDX1 array to examine functional loci, we discovered 24 European varieties with resistance to soybean cyst nematode (Table S3). However, we also observed that the genetic diversity and quantity of resistance to soybean cyst nematode may be inadequate in European germplasm. This inadequacy may hinder the future expansion of soybean cultivation in Europe.

This study aimed to explore the genetic differences between soybeans from Northeast China and Europe. Our findings revealed that European soybean varieties exhibit relatively lower genetic diversity compared to the Chinese collections, which include elite cultivars, landraces, and wild accessions. This observation suggests a narrower genetic base within European varieties. Additionally, population structure analysis suggested that these European varieties likely originated from China, underscoring a historical connection in soybean cultivation between the regions. Through a combined analysis using F_ST, pi, and XP-CLR, we identified distinct breeding targets between the Northeast Chinese and European varieties. This comparison provides insights into the developmental trajectory and adaptation strategies of soybean breeding in different geographical contexts.

Author Contribution

Lijuan Qiu and Zhangxiong Liu conceived and designed the experiments, analyzed the data, prepared figures and/or tables, and wrote or reviewed the draft manuscript. Jiangyuan Xu, Xindong Yao, and Yuqing Lu conceived and designed the experiments, performed the experiments, analyzed the data, prepared figures and/or tables, and wrote or reviewed the draft manuscript. Rittler Leopold analyzed the data and prepared figures and/or tables. Yongzhe Gu, Ming Yuan, Yong Zhang, Rujian Sun, Yongguo Xue, Yeli Liu, Dezhi Han, Jinxing Wang, and Huawei Gao performed the experiments, analyzed the data, and wrote or reviewed the draft manuscript. All authors read and approved the final manuscript.

Acknowledgement

†Jiangyuan Xu, Xindong Yao and Yuqing Lu contributed equally to this work.

Data Availability

The datasets analyzed during the current study are not publicly available but are available from the corresponding author on reasonable request.

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A comparison of Chinese wild and cultivar soybean with European soybean collections on genetic diversity by Genome-Wide Scan

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