Dissection of the practical soybean breeding pipeline by developing ZDX1, a high-throughput functional array.

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. 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.

Genetic dynamics of earlier maturity group emergence in south-to-north extension of Northeast China soybeans.

KEY MESSAGE: This population genetic study is characterized with direct comparisons of days to flowering QTL-allele matrices between newly evolved and originally old maturity groups of soybeans to explore its evolutionary dynamics using the RTM-GWAS procedure. The Northeast China (NEC) soybeans are the major germplasm source of modern soybean production in Americas (> 80% of the world total). NEC is a relatively new soybean area in China, expanded after its nomadic status in the seventeenth century. At nine sites of four ecoregions in NEC, 361 varieties were tested for their days to flowering (DTF), a geography-sensitive trait as an indicator for maturity groups (MGs). The DTF reduced obviously along with soybeans extended to higher latitudes, ranging in 41-83 days and MG 000-III. Using the RTM-GWAS (restricted two-stage multi-locus model genome-wide association study) procedure, 81 QTLs with 342 alleles were identified, accounting for 77.85% genetic contribution (R2 = 0.01-7.74%/locus), and other 20.75% (98.60-77.85%, h2 = 98.60%) genetic variation was due to a collective of unmapped QTLs. With soybeans northward, breeding effort made the original MG I-III evolved to MG 0-00-000. In direct comparisons of QTL-allele matrices among MGs, the genetic dynamics are identified with local exotic introduction/migration (58.48%) as the first and selection against/exclusion of positive alleles causing new recombination (40.64%) as the second, while only a few allele emergence/mutation happened (0.88%, limited in MG 0, not in MG 00-000). In new MG emergence, 24 QTLs with 19 candidate genes are the major sources. A genetic potential of further DTF shortening (13-21 days) is predicted for NEC population. The QTL detection in individual ecoregions showed various ecoregion-specific QTLs-alleles/genes after co-localization treatment (removing the random environment shifting ones).

Potential of marker selection to increase prediction accuracy of genomic selection in soybean (Glycine max L.).

Genomic selection is a promising molecular breeding strategy enhancing genetic gain per unit time. The objectives of our study were to (1) explore the prediction accuracy of genomic selection for plant height and yield per plant in soybean [Glycine max (L.) Merr.], (2) discuss the relationship between prediction accuracy and numbers of markers, and (3) evaluate the effect of marker preselection based on different methods on the prediction accuracy. Our study is based on a population of 235 soybean varieties which were evaluated for plant height and yield per plant at multiple locations and genotyped by 5361 single nucleotide polymorphism markers. We applied ridge regression best linear unbiased prediction coupled with fivefold cross-validations and evaluated three strategies of marker preselection. For plant height, marker density and marker preselection procedure impacted prediction accuracy only marginally. In contrast, for grain yield, prediction accuracy based on markers selected with a haplotype block analyses-based approach increased by approximately 4 % compared with random or equidistant marker sampling. Thus, applying marker preselection based on haplotype blocks is an interesting option for a cost-efficient implementation of genomic selection for grain yield in soybean breeding.