Guizhen Kan

The Acid Phosphatase-Encoding Gene GmACP1 Contributes to Soybean Tolerance to Low-Phosphorus Stress

Phosphorus (P) is essential for all living cells and organisms, and low-P stress is a major factor constraining plant growth and yield worldwide. In plants, P efficiency is a complex quantitative trait involving multiple genes, and the mechanisms underlying P efficiency are largely unknown. Combining linkage analysis, genome-wide and candidate-gene association analyses, and plant transformation, we identified a soybean gene related to P efficiency, determined its favorable haplotypes and developed valuable functional markers. First, six major genomic regions associated with P efficiency were detected by performing genome-wide associations (GWAs) in various environments. A highly significant region located on chromosome 8, qPE8, was identified by both GWAs and linkage mapping and explained 41% of the phenotypic variation. Then, a regional mapping study was performed with 40 surrounding markers in 192 diverse soybean accessions. A strongly associated haplotype (P = 10−7) consisting of the markers Sat_233 and BARC-039899-07603 was identified, and qPE8 was located in a region of approximately 250 kb, which contained a candidate gene GmACP1 that encoded an acid phosphatase. GmACP1 overexpression in soybean hairy roots increased P efficiency by 11–20% relative to the control. A candidate-gene association analysis indicated that six natural GmACP1 polymorphisms explained 33% of the phenotypic variation. The favorable alleles and haplotypes of GmACP1 associated with increased transcript expression correlated with higher enzyme activity. The discovery of the optimal haplotype of GmACP1 will now enable the accurate selection of soybeans with higher P efficiencies and improve our understanding of the molecular mechanisms underlying P efficiency in plants.

Association mapping of soybean seed germination under salt stress

Soil salinity is a serious threat to agriculture sustainability worldwide. Seed germination is a critical phase that ensures the successful establishment and productivity of soybeans in saline soils. However, little information is available regarding soybean salt tolerance at the germination stage. The objective of this study was to identify the genetic mechanisms of soybean seed germination under salt stress. One natural population consisting of 191 soybean landraces was used in this study. Soybean seeds produced in four environments were used to evaluate the salt tolerance at their germination stage. Using 1142 single-nucleotide polymorphisms (SNPs), the molecular markers associated with salt tolerance were detected by genome-wide association analysis. Eight SNP-trait associations and 13 suggestive SNP-trait associations were identified using a mixed linear model and the TASSEL 4.0 software. Eight SNPs or suggestive SNPs were co-associated with two salt tolerance indices, namely (1) the ratio of the germination index under salt conditions to the germination index under no-salt conditions (ST-GI) and (2) the ratio of the germination rate under salt conditions to the germination rate under no-salt conditions (ST-GR). One SNP (BARC-021347-04042) was significantly associated with these two traits (ST-GI and ST-GR). In addition, nine possible candidate genes were located in or near the genetic region where the above markers were mapped. Of these, five genes, Glyma08g12400.1, Glyma08g09730.1, Glyma18g47140.1, Glyma09g00460.1, and Glyma09g00490.3, were verified in response to salt stress at the germination stage. The SNPs detected could facilitate a better understanding of the genetic basis of soybean salt tolerance at the germination stage, and the marker BARC-021347-04042 could contribute to future breeding for soybean salt tolerance by marker-assisted selection.

Association mapping of yield-related traits and SSR markers in wild soybean (Glycine soja Sieb. and Zucc.)

Wild soybean, the progenitor of cultivated soybean, is an important gene pool for ongoing soybean breeding efforts. To identify yield-enhancing quantitative trait locus (QTL) or gene from wild soybean, 113 wild soybeans accessions were phenotyped for five yield-related traits and genotyped with 85 simple sequence repeat (SSR) markers to conduct association mapping. A total of 892 alleles were detected for the 85 SSR markers, with an average 10.49 alleles; the corresponding PIC values ranged from 0.07 to 0.92, with an average 0.73. The genetic diversity of each SSR marker ranged from 0.07 to 0.93, with an average 0.75. A total of 18 SSR markers were identified for the five traits. Two SSR markers, sct_010 and satt316, which are associated with the yield per plant were stably expressed over two years at two experimental locations. Our results suggested that association mapping can be an effective approach for identifying QTL from wild soybean.

Quantitative Trait Loci (QTL) Mapping for Glycinin and β-Conglycinin Contents in Soybean (Glycine max L. Merr.).

Compared to β-conglycinin, glycinin contains 3-4 times the methionine and cysteine (sulfur-containing amino acids), accounting for approximately 40 and 30%, respectively, of the total storage protein in soybean. Increasing the soybean storage protein content while improving the ratio of glycinin to β-conglycinin is of great significance for soybean breeding and soy food products. The objective of this study is to analyze the genetic mechanism regulating the glycinin and β-conglycinin contents of soybean by using a recombinant inbred line (RIL) population derived from a cross between Kefeng No. 1 and Nannong 1138-2. Two hundred and twenty-one markers were used to map quantitative trait loci (QTLs) for glycinin (11S) and β-conglycinin (7S) contents, the ratio of glycinin to β-conglycinin (RGC), and the sum of glycinin and β-conglycinin (SGC). A total of 35 QTLs, 3 pairs of epistatic QTLs, and 5 major regions encompassing multiple QTLs were detected. Genes encoding the subunits of β-conglycinin were localized to marker intervals sat_418-satt650 and sat_196-sat_303, which are linked to RGC and SGC; marker sat_318, associated with 11S, 7S, and SGC, was located near Glyma10g04280 (Gy4), which encodes a subunit of glycinin. These results, which take epistatic interactions into account, will improve our understanding of the genetic basis of 11S and 7S contents and will lay a foundation for marker-assisted selection (MAS) breeding of soybean and improving the quality of soybean products.

Identification of novel loci for salt stress at the seed germination stage in soybean.

Salt tolerance in soybean [Glycine max (L.) Merr.] at the seed germination stage is a critical determinant of stable stand establishment in saline soil. This study examined one population of 184 recombinant inbred lines (RILs, F7:11) derived from a cross between Kefeng1 and Nannong1138-2 and one natural population consisting of 196 soybean landraces. A total of 11 quantitative trait loci (QTLs) and 22 simple sequence repeat (SSR) loci associated with three salt tolerance indices were detected by linkage and association mapping. The SSR marker Sat_162 was found to be closely linked to the co-localized QTLs at a site 792,811 bp from the gene Glyma08g12400.1, which was verified in response to salt stress at the germination stage. Five SSR markers, Satt201, BE475343, CSSR306, Satt664 and Satt567, were co-associated with two of the salt tolerance indices, and two SSR markers, Satt156 and Satt636, were co-associated with all three salt tolerance indices. Furthermore, elite alleles and their carrier materials were identified by analyzing alleles at the loci associated with these salt tolerance indices. These results may be beneficial for the future breeding of soybean salt tolerance at the germination stage using marker-assisted selection and molecular pyramiding breeding.

Association analysis for detecting significant single nucleotide polymorphisms for phosphorus-deficiency tolerance at the seedling stage in soybean [Glycine max (L) Merr].

Tolerance to low-phosphorus soil is a desirable trait in soybean cultivars. Previous quantitative trait locus (QTL) studies for phosphorus-deficiency tolerance were mainly derived from bi-parental segregating populations and few reports from natural population. The objective of this study was to detect QTLs that regulate phosphorus-deficiency tolerance in soybean using association mapping approach. Phosphorus-deficiency tolerance was evaluated according to five traits (plant shoot height, shoot dry weight, phosphorus concentration, phosphorus acquisition efficiency and use efficiency) comprising a conditional phenotype at the seedling stage. Association mapping of the conditional phenotype detected 19 SNPs including 13 SNPs that were significantly associated with the five traits across two years. A novel cluster of SNPs, including three SNPs that consistently showed significant effects over two years, that associated with more than one trait was detected on chromosome 3. All favorable alleles, which were determined based on the mean of conditional phenotypic values of each trait over the two years, could be pyramided into one cultivar through parental cross combination. The best three cross combinations were predicted with the aim of simultaneously improving phosphorus acquisition efficiency and use efficiency. These results will provide a thorough understanding of the genetic basis of phosphorus deficiency tolerance in soybean.

Genetic diversity analysis using simple sequence repeat markers in soybean

To evaluate the genetic diversity (GD) of wild and cultivated soybeans and determine the genetic relationships between them, in this study, 127 wild soybean accessions and 219 cultivated soybean accessions were genotyped using 74 simple sequence repeat (SSR) markers. The results of the study revealed that the GD of the wild soybeans exceeded that of the cultivated soybeans. In all, 924 alleles were detected in the 346 soybean accessions using 74 SSRs, with an average of 12.49 alleles per locus. In the 219 cultivated soybean accessions, 687 alleles were detected, with an average of 9.28 alleles per locus; in the 127 wild soybean accessions, 835 alleles were detected, with an average of 11.28 alleles per locus. We identified 237 wild-soybean-specific alleles and 89 cultivated-soybean-specific alleles in the 346 soybean accessions, and these alleles accounted for 35.28% of all the alleles in the sample. Principal coordinates analysis and phylogenetic analysis based on Neis genetic distance indicated that all the accessions could be classified into two major clusters, corresponding to wild and cultivated soybeans. These results will increase our understanding of the genetic differences and relationships between wild and cultivated soybeans and provide information to develop future breeding strategies to improve soybean yield.