Key message We developed the ZDX1 high-throughput functional soybean array for high accuracy evaluation and selection of both parents and progeny, which can greatly accelerate soybean breeding. Abstract Microarray technology facilitates rapid, accurate, and economical genotyping. Here, using resequencing data from 2214 representative soybean accessions, we developed the high-throughput functional array ZDX1, containing 158,959 SNPs, covering 90.92% of soybean genes and sites related to important traits. By application of the array, a total of 817 accessions were genotyped, including three subpopulations of candidate parental lines, parental lines and their progeny from practical breeding. The fixed SNPs were identified in progeny, indicating artificial selection during the breeding process. By identifying functional sites of target traits, novel soybean cyst nematode-resistant progeny and maturity-related novel sources were identified by allele combinations, demonstrating that functional sites provide an efficient method for the rapid screening of desirable traits or gene sources. Notably, we found that the breeding index (BI) was a good indicator for progeny selection. Superior progeny were derived from the combination of distantly related parents, with at least one parent having a higher BI. Furthermore, new combinations based on good performance were proposed for further breeding after excluding redundant and closely related parents. Genomic best linear unbiased prediction (GBLUP) analysis was the best analysis method and achieved the highest accuracy in predicting four traits when comparing SNPs in genic regions rather than whole genomic or intergenic SNPs. The prediction accuracy was improved by 32.1% by using progeny to expand the training population. Collectively, a versatile assay demonstrated that the functional ZDX1 array provided efficient information for the design and optimization of a breeding pipeline for accelerated soybean breeding.

Soybean (Glycine max [L.] Merr.) is a legume crop important for global food security due to supplying high-quality vegetable protein and oil. China is the origin and rich center of soybean genetic diversity represented by numerous landraces and other genetic resources. During the nineteenth and twentieth centuries, world-wide dissemination of plant introductions laid the foundation of modern soybean production. Due to selection for regional adaptation, present-day elite soybean cultivars do have a comparatively narrow genetic base. However, as genetic variation is the major component of future breeding progress, diversity of early maturity Chinese and European elite soybeans was comparatively analyzed using a high-throughput functional SNP array and an SSR marker set. Results revealed a clear differentiation between Chinese and European elite cultivars, and the level of genetic diversity was similar between the two populations. Both in Chinese and European cultivars, unique SSR alleles were found which indicates that selection for specific adaptation can preserve genetic variation. The European population was markedly structured by maturity groups which was less clear in the Chinese population. Structure analysis indicated that European cultivars are based on two major ancestral lines, whereas Chinese elite soybean cultivars trace back to more ancestral lines pointing to the rich natural soybean diversity of China. The results confirm that long-term selection under divergent environmental and agronomic conditions can produce specific diversity which could potentially be utilized for future enhancing both Chinese and European soybean breeding.

Understanding the genetic basis of leaf sucrose content can provide a novel way in improving soybean yields. To identify the related QTLs, 190 materials of chromosome fragment substitution lines (CSSLs) were used in this study. The CSSLs were developed from the cross between the cultivated soybean Suinong 14 (SN14) and wild soybean ZYD00006. Only one QTL with a high logarithm of odds (LOD) score was detected in 2021 and 2022 among 3780 bin markers (combined by 580,524 SNPs) distributed in 20 chromosomes. Nine candidate genes were screened and Glyma.14G029100 was considered as the hub gene. A promoter difference and CDS mutant was found among the parents and the reference genome, which lead to the relative transcriptional level difference.. Our results lay the groundwork for further research into its genetic mechanism.

Soybean (Glycine max [L.] Merr.) is a legume crop important for global food security due to supplying high-quality vegetable protein and oil. China is the origin and rich center of soybean genetic diversity represented by numerous landraces and other genetic resources. During the 19th and 20th centuries, world-wide dissemination of plant introductions laid the foundation of modern soybean production. Due to selection for regional adaptation, present-day elite soybean cultivars do have a comparatively narrow genetic base. However, as genetic variation is the major component of future breeding progress, diversity of early maturity Chinese and European elite soybeans was comparatively analyzed using a high-throughput functional SNP array and an SSR marker set. Results revealed a clear differentiation between Chinese and European elite cultivars, and the level of genetic diversity was similar between the two populations. Both in Chinese and European cultivars, unique SSR alleles were found which indicates that selection for specific adaptation can preserve genetic variation. The European population was markedly structured by maturity groups which was less clear in the Chinese population. Structure analysis indicated that European cultivars are based on two major ancestral lines, whereas Chinese elite soybean cultivars trace back to more ancestral lines pointing to the rich natural soybean diversity of China. The results confirm that long-term selection under divergent environmental and agronomic conditions can produce specific diversity which could potentially be utilized for future enhancing both Chinese and European soybean breeding.