Feeding of Riptortus pedestris on soybean plants, the primary cause of soybean staygreen syndrome in the Huang-Huai-Hai river basin

Staygreen syndrome or Zhengqing in soybean has recently become a major issue for Chinese growers in the Huang-Huai-Hai river basin.Although previous studies revealed that staygreen can be induced when pods/seeds are damaged, it is unknown whether virus infection or insect infestation causes staygreen.To determine whether viral infection causes staygreen, a survey of soybean staygreen incidence in the Huang-Huai-Hai river basin was conducted in 2016 and 2017.Diseased samples were collected and analyzed using DAS-ELISA for Soybean mosaic virus, Watermelon mosaic virus, Bean pod mottle virus, Cucumber mosaic virus, and Bean common mosaic virus.The survey showed that the severity of soybean staygreen syndrome was most prevalent in Beijing, Henan, Shaanxi, and some parts of Shandong provinces, with yield losses from 0 to nearly 100%, but only a small fraction of samples were positive for the tested viruses.A field cage experiment and an insecticide treatment field trial were conducted to determine the contribution of the bean bug, Riptortus pedestris, to staygreen incidence.The field cage experiment showed that R.pedestris treatment resulted in shorter plants, more empty pods, increased numbers of abnormal seeds, and decreased yields.The field experiment showed that there were fewer R.pedestris and less soybean staygreen incidence in fields treated with insecticide than in untreated control fields.Together, these results suggest that R.pedestris infestation rather than virus infection induces staygreen syndrome and that growers in this region can mitigate staygreen syndrome via bean bug control.

Physiological and molecular studies of staygreen caused by pod removal and seed injury in soybean

Leaves provide substances and signals for pod and seed development in soybean.However,the regulatory feedbacks of pod and seed to leaf development remain unclear.We investigated the effects of pod and seed on leaf senescence by conducting pod removal and seed injury experiments.Pod removal and seed injury delayed leaf senescence and caused the staygreen phenotype of leaves.There were dosage effects of pod number on the extent of staygreen in depodded plants.The concentrations of chlorophyll(SPAD value,an index of relative chlorophyll content),soluble protein,and soluble sugar in the leaves of depodded plants were higher than those of intact plants.During seed development,the content of IAA decreased,while that of ABA increased.This trend was more pronounced in intact than in depodded and seed-injured plants.The GA3/ABA ratio decreased gradually in all treatments.The content of GA3 was relatively stable and was higher in intact than in depodded plants.The expression levels of four senescence-related genes,Gm SARK,Gm SGR1,Gm CYN1,and Gm NAC,declined in depodded or seed-injured treatments and were positively correlated with the number of leaves retained on plants.Gm FT2 a,the major flowering-promoting gene,was expressed at a higher level while E1,a key flowering inhibitory gene,was expressed at a lower level in depodded than in intact plants.We propose that the pod or seed can regulate leaf development.When the seed is aborted owing to disease infection or pest attack,the leaves stay green because of the absence of the seed signals for senescence.

Identification of novel QTL associated with soybean isoflavone content

Soybean isoflavones are essential secondary metabolites synthesized in the phenylpropanoid pathway and benefit human health. In the present study, highresolution QTL mapping for isoflavone components was performed using specific-locus amplified fragment sequencing(SLAF-seq) with a recombinant inbred line(RIL) population(F5:7) derived from a cross between two cultivated soybean varieties, Luheidou 2(LHD2) and Nanhuizao(NHZ). Using a high-density genetic map comprising 3541 SLAF markers and the isoflavone contents of soybean seeds in the 200 lines in four environments, 24 stable QTL were identified for isoflavone components, explaining 4.2%–21.2% of phenotypic variation.Of these QTL, four novel stable QTL(qG8, qMD19, qMG18, and qTIF19) were identified for genistin, malonyldaidzin, malonylgenistin, and total isoflavones, respectively. Gene annotation revealed three genes involved in isoflavone biosynthesis(Gm4CL, GmIFR, and GmCHR) and 13 MYB-like genes within genomic regions corresponding to stable QTL intervals, suggesting candidate genes underlying these loci. Nine epistatic QTL were identified for isoflavone components, explaining 4.7%–15.6% of phenotypic variation. These results will facilitate understanding the genetic basis of isoflavone accumulation in soybean seeds. The stable QTL and tightly linked SLAF markers may be used for markerassisted selection in soybean breeding programs.

The prevalence of deleterious mutations during the domestication and improvement of soybean

Soybean(Glycine max L.)is a protein and oil crop grown worldwide.Its fitness may be reduced by deleterious mutations,whose identification and purging is desirable for crop breeding.In the published whole-genome re-sequenced data of 2214 soybean accessions,including 221 wild soybean,1132 landrace cultivars and 861 improved soybean lines,we identified 115,275 deleterious single-nucleotide polymorphisms(SNPs).Numbers of deleterious alleles increased from wild soybeans to landraces and decreased from landraces to modern improved lines.Genes in selective-sweep regions showed fewer deleterious mutations than the remaining genes.Deleterious mutations explained 4.3%-48%more phenotypic variation than randomly selected SNPs for resistance to soybean cyst nematode race 2(SCN2),soybean cyst nematode race 3(SCN3)and soybean mosaic virus race 3(SMV3).These findings illustrate how mutation load has shifted during soybean domestication,expansion and improvement and provide candidate sites for breeding out deleterious mutations in soybean by genome editing and/or conventional breeding focused on the selection of progeny with fewer deleterious alleles.

Identification of transgene insertions in two genetically modified soybeans using high throughput next generation sequencing

Genetically modified(GM) organisms are widely adopted. However, their safety assessments and control are still of special concern to the public. Identifying and localizing transgene insertion is an essentially prerequisite step. In this study, 2 independent transgene soybean lines were selected(LB4-AtDCGS-1-20-5-2 and CGS-ZG11) as typical cases. Both lines contained expression cassette of At-DCGS that encoding a feedback-insensitive cystathionine gamma-synthase to produce higher level methionine(Met). LB4-AtDCGS-1-20-5-2 was whole genome sequenced with one paired-end 500 bp library and two mate-paired 1 kb and 2 kb libraries using Illumina HiSeq sequencing platform. CGS-ZG11 was sequenced with only one paired-end 500 bp library. Both genomes were assembled,and 2 scaffold sequences(1 for each line) were screened out by aligning with transgene.Then the transgene insertion and its flanking regions in soybean genome were further identified and confirmed by PCR cloning and Sanger sequencing. Results showed that these 2 transgene lines had single copy of inserted transgene. Their transgene insertion contents were identified, which facilitates further safety assessment. These results indicated that genome assembly using high throughput sequencing is a powerful tool for identifying transgene insertions, even with limited knowledge.

Spatial differences in soybean bioactive components across China and their influence by weather factors

Bioactive components are partially responsible for the nutritional and health benefits of soybeans. Four major bioactive components: isoflavones, oligosaccharides, phospholipids,and saponins, were quantified in 763 soybean samples collected from widely distributed regions across China from 2010 to 2013. A majority of the tested bioactive components showed generally declining trends from the north(high latitude) to the south(low latitude).A positive relationship between total oligosaccharides(TO) and altitude was observed. Total isoflavones(TI), phospholipids(TP) and TO were negatively correlated with cumulative temperature above or equal to 15 °C(AT15) and mean daily temperature(MDT), but positively correlated with diurnal temperature range(DTR) and hours of sunshine(HS).Total saponins(TS) were negatively correlated with MDT but positively correlated with rainfall(RF), whereas TO were negatively correlated with RF. Path-coefficient analysis showed that, besides genotype differences, temperature and HS during the reproductive period influenced TI and TP contents, while temperature and RF influenced TS and TO. The effects of weather factors on soybean bioactive components in diverse regions of China were characterized. These findings will be helpful in promoting soybean production for functional food purposes.

Time series canopy phenotyping enables the identification of genetic variants controlling dynamic phenotypes in soybean

Advances in plant phenotyping technologies are dramatically reducing the marginal costs of collecting multiple phenotypic measurements across several time points.Yet,most current approaches and best statistical practices implemented to link genetic and phenotypic variation in plants have been developed in an era of single-time-point data.Here,we used time-series phenotypic data collected with an unmanned aircraft system for a large panel of soybean(Glycine max(L.)Merr.)varieties to identify previously uncharacterized loci.Specifically,we focused on the dissection of canopy coverage(CC)variation from this rich data set.We also inferred the speed of canopy closure,an additional dimension of CC,from the time-series data,as it may represent an important trait for weed control.Genome-wide association studies(GWASs)identified 35 loci exhibiting dynamic associations with CC across developmental stages.The time-series data enabled the identification of 10 known flowering time and plant height quantitative trait loci(QTLs)detected in previous studies of adult plants and the identification of novel QTLs influencing CC.These novel QTLs were disproportionately likely to act earlier in development,which may explain why they were missed in previous single-time-point studies.Moreover,this time-series data set contributed to the high accuracy of the GWASs,which we evaluated by permutation tests,as evidenced by the repeated identification of loci across multiple time points.Two novel loci showed evidence of adaptive selection during domestication,with different genotypes/haplotypes favored in different geographic regions.In summary,the time-series data,with soybean CC as an example,improved the accuracy and statistical power to dissect the genetic basis of traits and offered a promising opportunity for crop breeding with quantitative growth curves.

Genome-wide signatures of the geographic expansion and breeding of soybean

Soybean is a leguminous crop that provides oil and protein. Exploring the genomic signatures of soybean evolution is crucial for breeding varieties with improved adaptability to environmental extremes. We analyzed the genome sequences of 2,214 soybeans and proposed a soybean evolutionary route, i.e., the expansion of annual wild soybean(Glycine soja Sieb. & Zucc.) from southern China and its domestication in central China, followed by the expansion and local breeding selection of its landraces(G. max(L.) Merr.). We observed that the genetic introgression in soybean landraces was mostly derived from sympatric rather than allopatric wild populations during the geographic expansion. Soybean expansion and breeding were accompanied by the positive selection of flowering time genes, including GmSPA3c. Our study sheds light on the evolutionary history of soybean and provides valuable genetic resources for its future breeding.

A new distinct geminivirus causes soybean stay-green disease

Dear Editor,Plant viruses make up almost half of the plant disease-causing pathogens,affecting crop yields and the global economy(Savary et al.,2019).Soybean(Glycine max)is one of the most valuable legume crops in the world,supplying 25%of the global edible oil and two-thirds of the global concentrated protein for livestock feeding.Recently,the outbreak of soybean stay-green syndrome with delayed leaf senescence(stay-green),flat pods,and increased number of abnormal seeds has swept the soybean production in the Huang-Huai-Hai region of China,resulting in huge yield losses(Xu et al.,2019).This disease has become an epidemic and prominent problem in soybean production and is still expanding its geography,including North America,posing a serious threat to soybean production(Harbach et al.,2016;Zhang et al.,2016;Li et al.,2019).However,the cause of soybean stay-green syndrome remains obscure.

SoySNP618K array:A high-resolution single nucleotide polymorphism platform as a valuable genomic resource for soybean genetics and breeding

Innovations in genomics have enabled the development of low-cost,high-resolution,single nucleotide polymorphism(SNP)genotyping arrays that accelerate breeding progress and support basic research in crop science.Here,we developed and validated the Soy SNP618 K array(618,888 SNPs)for the important crop soybean.The SNPs were selected from whole-genome resequencing data containing 2,214 diverse soybean accessions;29.34%of the SNPs mapped to genic regions representing 86.85%of the 56,044annotated high-confidence genes.Identity-by-state analyses of 318 soybeans revealed 17 redundant accessions,highlighting the potential of the Soy SNP618 K array in supporting gene bank management.The patterns of population stratification and genomic regions enriched through domestication were highly consistent with previous findings based on resequencing data,suggesting that the ascertainment bias in the Soy SNP618 K array was largely compensated for.Genome-wide association mapping in combination with reported quantitative trait loci enabled fine-mapping of genes known to influence flowering time,E2 and Gm PRR3 b,and of a new candidate gene,Gm VIP5.Moreover,genomic prediction of flowering and maturity time in 502 recombinant inbred lines was highly accurate(>0.65).Thus,the Soy SNP618 K array is a valuable genomic tool that can be used to address many questions in applied breeding,germplasm management,and basic crop research.