Gene-allele system of shade tolerance in southern China soybean germplasm revealed by genome-wide association study using gene-allele sequence as markers.

KEY MESSAGE: Fifty-three shade tolerance genes with 281 alleles in the SCSGP were identified directly using gene-allele sequence as markers in RTM GWAS, from which optimized crosses, evolutionary motivators, and gene-allele networks were explored. Shade tolerance is a key for optimal cultivation of soybean inter/relay-cropped with corn. To explore the shade tolerance gene-allele system in the southern China soybean germplasm, we proposed using gene-allele sequence markers (GASMs) in a restricted two-stage multi-locus model genome-wide association study (GASM-RTM-GWAS). A representative sample with 394 accessions was tested for their shade tolerance index (STI), in Nanning, China. Through whole-genome re-sequencing, 47,586 GASMs were assembled. From GASM-RTM-GWAS, 53 main-effect STI genes with 281 alleles (2-13 alleles/gene) (totally 63 genes with 308 alleles, including 38 G × E genes with 191 alleles) were identified and then organized into a gene-allele matrix composed of eight submatrices corresponding to geo-seasonal subpopulations. The population featured mild STI changes (1.69 → 1.56-1.82) and mild gene-allele changes (92.5% alleles inherited, 0% alleles excluded, 7.5% alleles emerged) from the primitive (SAIII) to the derived seven subpopulations, but large transgressive recombination potentials and optimal crosses were predicted. The 63 STI genes were annotated into six biological categories (metabolic process, catalytic activity, response to stresses, transcription and translation, signal transduction and transport and unknown functions), interacted as gene networks. From the STI gene-allele system, 38 important alleles of 22 genes were nominated for further in-depth study. GASM-RTM-GWAS performed powerful and efficient in germplasm population genetic study comparing to other procedures through facilitating direct and thorough identification of its gene-allele system, from which genome-wide breeding by design could be achieved, and evolutionary motivators and gene-allele networks could be explored.

Mapping Locus RSC11K and predicting candidate gene resistant to Soybean mosaic virus strain SC11 through linkage analysis combined with genome resequencing of the parents in soybean.

Soybean mosaic virus (SMV) strain SC11 was prevalent in middle China. Its resistance was controlled by a Mendelian single dominant gene RSC11K in soybean Kefeng-1. This study aimed at mapping RSC11K and identifying its candidate gene. RSC11K locus was mapped ~217 kb interval between two SNP-linkage-disequilibrium-blocks (Gm02_BLOCK_11273955_11464884 and Gm02_BLOCK_11486875_11491354) in W82.a1.v1 genome using recombinant inbred lines population derived from Kefeng-1 (Resistant) × NN1138-2 (Susceptible), but inserted with a ~245 kb segment in W82.a2.v1 genome. In the entire 462 kb RSC11K region, 429 SNPs, 142 InDels and 34 putative genes were identified with more SNPs/InDels distributed in non-functional regions. Thereinto, ten genes contained SNP/InDel variants with high and moderate functional impacts on proteins, among which Glyma.02G119700 encoded a typical innate immune receptor-like kinase involving in virus disease process and responded to SMV inoculation, therefore was recognized as RSC11K's candidate gene. The novel RSC11K locus and candidate genes may help developing SMV resistance germplasm.

An Improved Genome-Wide Association Procedure Explores Gene-Allele Constitutions and Evolutionary Drives of Growth Period Traits in the Global Soybean Germplasm Population.

In soybeans (Glycine max (L.) Merr.), their growth periods, DSF (days of sowing-to-flowering), and DFM (days of flowering-to-maturity) are determined by their required accumulative day-length (ADL) and active temperature (AAT). A sample of 354 soybean varieties from five world eco-regions was tested in four seasons in Nanjing, China. The ADL and AAT of DSF and DFM were calculated from daily day-lengths and temperatures provided by the Nanjing Meteorological Bureau. The improved restricted two-stage multi-locus genome-wide association study using gene-allele sequences as markers (coded GASM-RTM-GWAS) was performed. (i) For DSF and its related ADLDSF and AATDSF, 130-141 genes with 384-406 alleles were explored, and for DFM and its related ADLDFM and AATDFM, 124-135 genes with 362-384 alleles were explored, in a total of six gene-allele systems. DSF shared more ADL and AAT contributions than DFM. (ii) Comparisons between the eco-region gene-allele submatrices indicated that the genetic adaptation from the origin to the geographic sub-regions was characterized by allele emergence (mutation), while genetic expansion from primary maturity group (MG)-sets to early/late MG-sets featured allele exclusion (selection) without allele emergence in addition to inheritance (migration). (iii) Optimal crosses with transgressive segregations in both directions were predicted and recommended for breeding purposes, indicating that allele recombination in soybean is an important evolutionary drive. (iv) Genes of the six traits were mostly trait-specific involved in four categories of 10 groups of biological functions. GASM-RTM-GWAS showed potential in detecting directly causal genes with their alleles, identifying differential trait evolutionary drives, predicting recombination breeding potentials, and revealing population gene networks.

Differential SW16.1 allelic effects and genetic backgrounds contributed to increased seed weight after soybean domestication.

Although seed weight has increased following domestication from wild soybean (Glycine soja) to cultivated soybean (Glycine max), the genetic basis underlying this change is unclear. Using mapping populations derived from chromosome segment substitution lines of wild soybean, we identified SW16.1 as the causative gene underlying a major quantitative trait locus controlling seed weight. SW16.1 encodes a nucleus-localized LIM domain-containing protein. Importantly, the GsSW16.1 allele from wild soybean accession N24852 had a negative effect on seed weight, whereas the GmSW16.1 allele from cultivar NN1138-2 had a positive effect. Gene expression network analysis, reverse-transcription quantitative polymerase chain reaction, and promoter-luciferase reporter transient expression assays suggested that SW16.1 regulates the transcription of MT4, a positive regulator of seed weight. The natural variations in SW16.1 and other known seed weight genes were analyzed in soybean germplasm. The SW16.1 polymorphism was associated with seed weight in 247 soybean accessions, showing much higher frequency of positive-effect alleles in cultivated soybean than in wild soybean. Interestingly, gene allele matrix analysis of the known seed weight genes revealed that G. max has lost 38.5% of the G. soja alleles and that most of the lost alleles had negative effects on seed weight. Our results suggest that eliminating negative alleles from G. soja led to a higher frequency of positive alleles and changed genetic backgrounds in G. max, which contributed to larger seeds in cultivated soybean after domestication from wild soybean. Our findings provide new insights regarding soybean domestication and should assist current soybean breeding programs.

Transgressive Potential Prediction and Optimal Cross Design of Seed Protein Content in the Northeast China Soybean Population Based on Full Exploration of the QTL-Allele System.

Northeast China is a major soybean production region in China. A representative sample of the Northeast China soybean germplasm population (NECSGP) composed of 361 accessions was evaluated for their seed protein content (SPC) in Tieling, Northeast China. This SPC varied greatly, with a mean SPC of 40.77%, ranging from 36.60 to 46.07%, but it was lower than that of the Chinese soybean landrace population (43.10%, ranging from 37.51 to 50.46%). The SPC increased slightly from 40.32-40.97% in the old maturity groups (MG, MGIII + II + I) to 40.93-41.58% in the new MGs (MG0 + 00 + 000). The restricted two-stage multi-locus genome-wide association study (RTM-GWAS) with 15,501 SNP linkage-disequilibrium block (SNPLDB) markers identified 73 SPC quantitative trait loci (QTLs) with 273 alleles, explaining 71.70% of the phenotypic variation, wherein 28 QTLs were new ones. The evolutionary changes of QTL-allele structures from old MGs to new MGs were analyzed, and 97.79% of the alleles in new MGs were inherited from the old MGs and 2.21% were new. The small amount of new positive allele emergence and possible recombination between alleles might explain the slight SPC increase in the new MGs. The prediction of recombination potentials in the SPC of all the possible crosses indicated that the mean of SPC overall crosses was 43.29% (+2.52%) and the maximum was 50.00% (+9.23%) in the SPC, and the maximum transgressive potential was 3.93%, suggesting that SPC breeding potentials do exist in the NECSGP. A total of 120 candidate genes were annotated and functionally classified into 13 categories, indicating that SPC is a complex trait conferred by a gene network.

Identification of the QTL-allele System Underlying Two High-Throughput Physiological Traits in the Chinese Soybean Germplasm Population.

The QTL-allele system underlying two spectral reflectance physiological traits, NDVI (normalized difference vegetation index) and CHL (chlorophyll index), related to plant growth and yield was studied in the Chinese soybean germplasm population (CSGP), which consisted of 341 wild accessions (WA), farmer landraces (LR), and released cultivars (RC). Samples were evaluated in the Photosynthetic System II imaging platform at Nanjing Agricultural University. The NDVI and CHL data were obtained from hyperspectral reflectance images in a randomized incomplete block design experiment with two replicates. The NDVI and CHL ranged from 0.05-0.18 and 1.20-4.78, had averages of 0.11 and 3.57, and had heritabilities of 78.3% and 69.2%, respectively; the values of NDVI and CHL were both significantly higher in LR and RC than in WA. Using the RTM-GWAS (restricted two-stage multi-locus genome-wide association study) method, 38 and 32 QTLs with 89 and 82 alleles and 2-4 and 2-6 alleles per locus were identified for NDVI and CHL, respectively, which explained 48.36% and 51.35% of the phenotypic variation for NDVI and CHL, respectively. The QTL-allele matrices were established and separated into WA, LR, and RC submatrices. From WA to LR + RC, 4 alleles and 2 new loci emerged, and 1 allele was excluded for NDVI, whereas 6 alleles emerged, and no alleles were excluded, in LR + RC for CHL. Recombination was the major motivation of evolutionary differences. For NDVI and CHL, 39 and 32 candidate genes were annotated and assigned to GO groups, respectively, indicating a complex gene network. The NDVI and CHL were upstream traits that were relatively conservative in their genetic changes compared with those of downstream agronomic traits. High-throughput phenotyping integrated with RTM-GWAS provides an efficient procedure for studying the population genetics of traits.