Cloning and Analysis of a Disease Resistance Gene Homolog from Soybean

Conserved domains e.g. nucleotide binding site (NBS) were found in several cloned plant disease resistance genes. Based on the NBS domain, resistance gene analogs (RGAs) have been isolated previously and were used as probes to screen a soybean (Glycine max L. Merr.) cDNA library. A full-length cDNA, KR3, was obtained by screening the library and rapid amplification of cDNA ends (RACE) method. Sequence analysis revealed that the cDNA is 2 353 bp in length and the open reading frame (ORF) codes for a polypeptide of 636 amino acids with a Toll-Interleukin-1 receptor (TIR) and a NBS domain. Sequence alignment showed that it was similar to N gene of tobacco. The phylogenetic tree analysis of R proteins with NBS from higher plants was performed. The KR3 gene has low copies in soybean genome and its expression was induced by exogenous salicylic acid (SA).

An Integrated QTL Map of Fungal Disease Resistance in Soybean (Glycine max L. Merr):A Method of Meta-Analysis for Mining R Genes

Diseases caused by fungal pathogens account for approximately 50% of all soybean disease losses around the world. Conflicting results of fungal disease resistance QTLs from different populations often occurred. The objectives of this study were to： （i） evaluate evidence for reported fungal disease resistance QTLs associations in soybean and （ii） extract relatively reliable and useful information from the ＂real＂ QTLs and mine putative genes in soybean. An integrated map of fungal disease resistance QTLs in soybean was established with soymap 2 published in 2004 as a reference map. QTLs of fungal disease resistance developed from each of separate populations in recent 10 years were integrated into a combinative map for gene cloning and marker assisted selection in soybean. 107 QTLs from different maps were integrated and projected to the reference map with the software BioMercator 2.1. A method of meta-analysis was used to narrow down the confidence interval, and 23 ＂real＂ QTLs and their corresponding markers were obtained from 12 linkage groups （LG）, respectively. Two published R genes were found in these ＂real＂ QTLs intervals. Sequences in the ＂real＂ QTLs intervals were predicted by GENSCAN, and these predicted genes were annotated in Goblet. 228 resistance gene analogs （RGAs） in 12 different terms were mined. The results will lay the foundation for a bioinformatics platform combining abundant QTLs, and offer the basis for marker assisted selection and gene cloning in soybean.

Using Deep Learning for Soybean Pest and Disease Classification in Farmland

To accurately identify soybean pests and diseases, in this paper, a kind of deep convolution network model was used to determine whether or not a soybean crop possessed pests and diseases. The proposed deep convolution network could learn the highdimensional feature representation of images by using their depth. An inception module was used to construct a neural network. In the inception module, multiscale convolution kernels were used to extract the distributed characteristics of soybean pests and diseases at different scales and to perform cascade fusion. The model then trained the SoftMax classifier in a uniformed framework. This realized the model of soybean pests and diseases so as to verify the effectiveness of this method. In this study, 800 images of soybean leaf images were taken as the experimental objects. Of these 800 images, 400 were selected for network training, and the remaining 400 images were used for the network test. Furthermore, the classical convolutional neural network was optimized. The accuracies before and after optimization were 96.25% and 95.81%, respectively, in terms of extracting image features. This type of research might be applied to achieve a degree of automation in agricultural field management.

Bioinformatics Analysis of Disease Resistance Gene PR1 and Its Genetic Transformation in Soybeans and Cultivation of Multi-resistant Materials

In agricultural production,a single insect-resistant and disease-resistant variety can no longer meet the demand.In this study,the expression vector pCAMBIA-3301-PR1 containing the disease-resistant gene PR1 was constructed by means of genetic engineering,and the PR1 gene was genetically transformed to contain the PR1 gene through the pollen tube method.In CryAb-8Like transgenic high-generation T7 receptor soybean,a new material that is resistant to insects and diseases is obtained.For T2 transformed plants,routine PCR detection,Southern Blot hybridization,fluorescence quantitative PCR detection,indoor and outdoor pest resistance identification and indoor disease resistance identification were performed.The results showed that there were 9 positive plants in the routine PCR test of T2 generation.In Southern Blot hybridization,both PR1 and CryAb-8Like genes are integrated in soybeans in the form of single copies.Fluorescence quantitative PCR showed that the expression levels of PR1 and CryAb-8Like genes are different in different tissues.The average expression levels of PR1 gene in plant roots,stems,and leaves are 2.88,1.54,and 5.26,respectively.CryAb-8Like genes are found in roots,stems,and leaves.The average expression levels were 1.36,1.39,and 4.25,respectively.The insectivorous rate of the CryAb-8Like gene in outdoor plants with positive insect resistance identification was 3.78%.The disc partition method was used indoors for pest resistance identification,and the bud length of transformed plants increased significantly.The average mortality rate of untransformed plants in indoor disease resistance identification was as high as 56.66%,and the average mortality rate of plants transformed with PR1 gene was 10.00%,and disease resistance was significantly improved.Therefore,a new material with resistance to diseases and insects is obtained.

A Brief Introduction of Main Diseases and Insect Pests in Soybean Production in the Global Top Five Soybean Producing Countries

The United States, Brazil, Argentina, India and China are the major soybean producing countries in the world. Nearly 90% of the world^s soybean production comes from these countries. The occurrence of diseases and insect pests often lead to the reduction of soybean yield, and brings varying degree losses to these countries. This article provides an overview of the impact and measures on soybean main diseases and insect pests in the top five major soybean producing countries over the world. It is concluded that the diseases affecting the soybean yield seriously include Phakopsorapachyrhizi, Heterodera glycines, Septoria glycines, Colletotrichum spp. and Macrophominaphaseolina; and the main insect pests include Anticarsia gemmatalis, Spodoptera litura, Nezara viridula and Frankliniella occidentalis, which will provide information for key prevention and control of soybean main diseases and insect pests in these countries.

Occurrence and Control of Main Soybean Diseases and Insect Pests in Greater Mekong Sub-region

Soybean rust,soybean downy mildew,and soybean thrips,soybean pod borers,and soybean nocturnal moths are the world wide diseases and insect pests in soybean production,which pose a potential threat to soybean production in Great Mekong Sub-region（ GMS）,comprising Cambodia,Lao People＇s Democratic Republic,Myanmar,Thailand,Vietnam,and Yunnan province,the People＇s Republic of China. This paper summarized the host range,epidemiology,damage and control methods of these diseases and insect pests in GMS,with the aim to provide information basis for understanding and effective control of soybean diseases and insect pests in GMS.

Research on Automatic Diagnostic Technology of Soybean Leaf Diseases Based on Improved Transfer Learning

Soybean diseases and insect pests are important factors that affect the output and quality of the soybean,thus,it is necessary to do correct inspection and diagnosis on them.For this reason,based on improved transfer learning,a classification method of the soybean leaf diseases was proposed in this paper.In detail,this method first removed the complicated background in images and cut apart leaves from the entire image;second,the data-augmented method was applied to amplify the separated leaf disease image dataset to reduce overfitting;at last,the automatically fine-tuning convolutional neural network(AutoTun)was adopted to classify the soybean leaf diseases.The proposed method respectively reached 94.23%,93.51%and 94.91%of validation accuracy rates on VGG-16,ResNet-34 and DenseNet-121,and it was compared with the traditional fine-tuning method of transfer learning.The results indicated that the proposed method had superior to the traditional transfer learning method.

Genomic Selection for Frogeye Leaf Spot Resistance in Soybean

Soybean frogeye leaf spot(FLS) disease is a global disease affecting soybean yield, especially in the soybean growing area of Heilongjiang Province. In order to realize genomic selection breeding for FLS resistance of soybean, least absolute shrinkage and selection operator(LASSO) regression and stepwise regression were combined, and a genomic selection model was established for 40 002 SNP markers covering soybean genome and relative lesion area of soybean FLS. As a result, 68 molecular markers controlling soybean FLS were detected accurately, and the phenotypic contribution rate of these markers reached 82.45%. In this study, a model was established, which could be used directly to evaluate the resistance of soybean FLS and to select excellent offspring. This research method could also provide ideas and methods for other plants to breeding in disease resistance.

A LAMP-assay-based specific microbiota analysis reveals community dynamics and potential interactions of 13 major soybean root pathogens

Soybean root diseases are associated with numerous fungal and oomycete pathogens;however,the community dynamics and interactions of these pathogens are largely unknown.We performed 13 loop-mediated isothermal amplification(LAMP)assays that targeted specific soybean root pathogens,and traditional isolation assays.A total of 159 samples were collected from three locations in the Huang-Huai-Hai region of China at three soybean growth stages(30,60,and 90 days after planting)in 2016.In LAMP results,we found that pathogen communities differed slightly among locations,but changed dramatically between soybean growth stages.Phytophthora sojae,Rhizoctonia solani,and Fusarium oxysporum were most frequently detected at the early stage,whereas Phomopsis longicolla,Fusarium equiseti,and Fusarium virguliforme were most common in the later stages.Most samples(86%)contained two to six pathogen species.Interestingly,the less detectable species tended to exist in the samples containing more detected species,and some pathogens preferentially co-occurred in diseased tissue,including P.sojae–R.solani–F.oxysporum and F.virguliforme–Calonectria ilicicola,implying potential interactions during infection.The LAMP detection results were confirmed by traditional isolation methods.The isolated strains exhibited different virulence to soybean,further implying a beneficial interaction among some pathogens.

Identification of QTLs Associated with Resistance to Pseudomonas syringae pv.Glycinea in Soybean(Glycine max(L.)Merr)

Soybean bacterial spot disease caused by Pseudomonas syringae pv.Glycinea which is a bacterial disease seriously affects soybean yield.Ten soybean germplasms and recombinant inbred lines(RILs)population were used to identify the resistant trait after inoculated with P.sg(P.sgneau001)in this study.High-density genetic mapping was obtained by specific length amplified fragment sequencing(SLAF-seq)of 149 RILs population which was derived from the crossing between Charleston and Dongnong594.The results indicated that 10 germplasm resources had four resistant germplasms included highly resistant cultivar Charleston,four susceptible varieties included Dongnong594 and two moderately resistant cultivars.Five quantitative trait locus(QTLs)were detected in RILs population by the composite interval mapping(CIM)method,and located on Linkage Group(LG)D1b(chromosome two),LG C2(chromosome six)and LG H(chromosome 12),respectively.LOD scores ranged from 2.68 to 4.95 and the phenotypic variation percentage was from 6%to 11%.Six candidate genes were detected,according to the result of gene annotation information.Four of them had relationship with protein kinase activity,protein phosphorylation and leucine rich repeat(LRR)transmembrane protein,which had high expression after inoculated with P.sg by qRT-PCR.

高产抗病大豆新品种吉育513的选育及栽培技术

为给优质高产大豆品种的研发提供参考和借鉴,吉林省农业科学院大豆研究所2009年以吉育47为母本,以铁97124-1-1为父本,配制杂交组合,采用系谱法选育出高产抗病大豆新品种吉育513。2019—2020年参加国家北方春大豆中晚熟组区域试验,平均产量3248.5 kg·hm^(-2),比对照吉育72增产6.1%。2020年参加生产试验,平均产量3301.5 kg·hm^(-2),比对照吉育72增产12.1%。2021年通过国家农作物品种审定委员会审定,审定编号为国审豆20210032。该品种具有高产、稳产和抗病等优良特性,特别适合在吉林省南中部、辽宁省东部和北部、宁夏回族自治区北部、山西省北部、河北省承德地区以及甘肃省张掖地区进行春季播种。该品种是通过传统育种技术与肥力优化筛选相结合的育种模式选育而成的,这种选育模式将对我国大豆产业的未来发展产生深远而积极的影响,如果优化有机和无机的配施比例,吉育513将更能发挥其高产潜力。

The Physiological Effects of Soybean Protein on Renal Function

Various physiological effects have already been reported for soy protein,and we herein review its protective effects on renal function.Kidney disease is a serious condition that can develop in association with diabetes and aging.Previous studies in animal models and human clinical trials have suggested that soy protein may have a suppressive effect against damage to the renal function.In the present review,we provide an overview of the previous findings and reports that a proprietary soy protein isolate(Fuji Oil Co.Ltd.)has protective effects on the renal function.In particular,soy protein helps to prevent kidney disease that arises as acomplication of diabetes and aging.

利用高世代转录组测序挖掘控制南方大豆皱叶症候选基因

【目的】南方大豆皱叶症(southern soybean crinkle leaf disease,SSCLD)严重时可导致大豆减产40%左右,利用高世代分离群体转录组测序技术(high-generation segregating populations RNA-seq,HGRNA-seq)挖掘控制SSCLD的候选基因,为揭示SSCLD发生的分子机制提供数据支撑。【方法】以2个南方皱叶症症级差异材料及其衍生的F2:7株系为研究材料,对双亲进行重测序,对12个F2:7单株(7个皱叶,5个正常叶)进行单个样本转录组测序,利用转录组及亲本的SNP/InDel数据进行混池法定位分析,利用转录组表达量差异数据进行GO和KEGG功能注释和富集分析,并在定位区间附近开发7个KASP分子标记,利用230个F2群体构建局部连锁图谱,对转录组数据定位结果进行验证。联合基因定位和转录组分析结果,筛选控制SSCLD的候选基因。【结果】利用混池法把控制皱叶症的基因位点CL12定位在大豆第12染色体末端39231651—40705115 bp的1473464 bp区间内,利用F2群体将控制皱叶症的基因定位于39743275—40948295 bp的1205020 bp区间内,与混池法定位结果基本一致。GO注释结果显示,代谢过程包括免疫系统过程,以及对刺激的反应等,细胞组分主要与膜等相关,KEGG注释结果显示,生物系统通路中主要包括植物-病原菌互作和环境适应等通路。GO富集的表达差异基因主要同跨膜受体蛋白活性、蛋白磷酸化及信号受体活性等方面相关,KEGG富集到的最多差异表达基因(differently expressed genes,DEGs)主要在植物-病原菌互作和植物MAPK信号通路上。结合南方大豆皱叶症诱因特点,选择定位候选区间内与抗病等相关且在外显子上存在非同义突变或表达量有差异的基因作为候选基因,结合qRT-PCR验证,最终确定GLYMA_12G223100、GLYMA_12G223900、GLYMA_12G224100、GLYMA_12G231800和GLYMA_12G233000等5个基因为控制南方大豆皱叶症的候选基因。【结论】HGRNA-seq实现了RNA-seq和BSA-seq相结合,成功挖掘了控制SSCLD的候选基因。

高蛋白抗病大豆品种陇豆6号选育报告

满足国内消费者对大豆及豆制品的需求,缩小我国大豆的产需缺口,培育并推广具有丰产性、广适性和抗病性等特点的大豆品种已成为大豆育种的重中之重。陇豆6号是由甘肃省农业科学院作物研究所以中黄12作母本、邯豆3号作父本,经有性杂交选育而成的大豆新品种。2022—2023年参加甘肃省大豆区域试验,折合平均产量3419.9 kg/hm^(2),较对照品种增产。2023年参加甘肃省生产试验,折合平均产量3196.4 kg/hm^(2),较对照品种陇豆2号增产10.1%。该品种籽粒含粗蛋白达459.7 g/kg、粗脂肪205.4 g/kg。陇豆6号丰产性好,适应性强,抗倒伏,田间长势和落叶性较好,属于高蛋白品种,抗花叶病毒病、中抗灰斑病,适宜在甘肃省大豆中晚熟及晚熟品种类型区种植。

大豆芽期拟茎点种腐病鉴定体系构建及抗性种质筛选

【目的】以具有拟茎点种腐病不同抗性水平的大豆为试材,建立准确快速的大豆芽期室内病害鉴定体系,并基于170份自然群体大豆筛选出高抗病性品种,为大豆拟茎点种腐病的快速高通量鉴定和抗性品种培育提供方法及材料基础。【方法】选取已报道拟茎点种腐病抗性品种齐黄34、感病品种Williams,以及中作09-560、z13-631-2、ZDD26268、辰溪青皮豆1和通县黄豆,挑选各品种大小均一、种皮完好的种子,经过消毒后于黑暗中发芽,在不同萌发时长后分别接种拟茎点种腐病病原菌24、48、72和96 h,统计不同侵染时长下种子表层的菌丝覆盖率与种子腐烂率,确定评价大豆拟茎点种腐病的最适鉴定时期。随后,以该时期的种子表层菌丝覆盖率和种子腐烂率作为评价指标,对自然群体170份不同大豆种质进行抗性鉴定,并划分5个抗病等级,筛选出高抗病性品种。【结果】以种子表层的菌丝覆盖率和种子腐烂率作为评价指标,发现不同抗性水平的大豆在萌发96 h后接种拟茎点种腐病病原菌表现出最为明显的表型差异;进一步比较侵染24、48、72和96 h后的发病情况,发现侵染72 h后的不同品种之间抗病差异最为明显,因此,确定萌发96 h后的芽期大豆侵染72 h为评价不同品种拟茎点种腐病抗性水平的最适时期,随后对170份大豆自然品种进行拟茎点种腐病抗性鉴定,并划为高抗、中抗、中感、感病、高感5个抗病等级,其中Ⅰ级(高抗)品种30个、Ⅱ级(中抗)品种51个、Ⅲ级(中感)品种71个、Ⅳ级(感病)品种4个、Ⅴ级(高感)品种14个,表明大豆种质资源对拟茎点种腐病抗性存在广泛变异。【结论】以萌发96 h后的芽期大豆侵染病原菌72 h作为最佳鉴定时期、种子表层的菌丝覆盖率和种子腐烂率作为拟茎点种腐病的评价指标,该鉴定体系具有较高的准确性与可靠性,可为不同品种室内快速高通量鉴定提供有效方法,进一步筛选出30个高抗种质可为抗病品种选育提供材料基础。

基于文献计量学的大豆根部病害研究动态及可视化分析

选取Web of Science核心合集数据库2000—2022年大豆根部病害相关领域的文献,基于文献计量学方法结合Vosviewer软件研究大豆根部病害现状和发展趋势。结果表明:2000—2022年期间共发表相关文章1245篇,发文量呈逐年递增趋势;发文量居于前两位的国家分别是美国和中国;发文量最多的机构来源于美国,其次是中国;发文量最多的期刊是Plant Disease,其次是Molecular Plant Microbe Interactions和BMC Plant Biology Crop;国际上发文量最高的研究者是Dorrance Anne E.,其次是Mitchum Melissa Goellner,国内的研究者发文量最高的是王源超教授,其次是邢邯教授。关键词分析表明,研究主要集中在病原物鉴定及其感染大豆植株的机制和大豆抗病相关基因挖掘等方面。近年来关于病害防治相关的研究不断增多,对生物防治、田间管理方法等方面进行了深入探索。

江苏省大豆豆荚真菌病害的病原菌分离与鉴定

真菌引起的大豆豆荚病害直接影响大豆籽粒及鲜食豆荚的产量和品质,为了解江苏省大豆豆荚病害的主要致病菌,本研究从南京、淮安、徐州、南通、盐城的大豆种植区内采集了78份有明显病斑的豆荚,通过病原菌组织分离与纯化得到112种病原菌。通过对比ITS与TUB2序列,112种病原菌被分为半知菌亚门的5个属:镰刀菌属(Fusarium spp.)、炭疽菌属(Colletotrichum spp.)、拟茎点霉属(Diaporthe spp.)、黑孢菌属(Nigrospora spp.)和色二孢属(Lasiodiplodia spp.)。其中镰刀菌属占比最高,占65.18%。从每个属中选择1个病原菌进行形态学观察以及柯赫氏法则验证,并结合分子生物学鉴定和系统演化分析。结果证明5个分离物分别属于层出镰刀菌(F.proliferatum)、平头炭疽菌(C.truncatum)、大豆拟茎点霉菌(D.longicolla)、球黑孢菌(N.sphaerica)和假可可毛色二孢菌(L.pseudotheobromae)。本研究明确了为害江苏省大豆豆荚的主要病原菌,为大豆豆荚真菌病害的有效防控提供理论依据。

大豆类病变皱叶突变体NT301遗传分析和2对基因定位

通过研究类病变突变体,挖掘抗病基因,利用分子设计育种的方法快速培育优良抗病大豆新品种,可减轻化学农药对环境的污染,降低病害的抗药性。本研究以^(60)Coγ诱变获得的类病变皱叶突变体NT301为父本,分别与W82、KF1和KF35进行杂交,构建了F_(2)和F_(2:3)分离群体,通过SSR标记和SNP分析,将目标基因1(rl1)缩小到18号染色体937 kb区间内,包含66个候选基因,将目标基因2(rl2)缩小到8号染色体130 kb区间内,包含15个候选基因。接着,本研究利用基因芯片技术对近等基因系进行了基因表达谱研究,得到了差异表达基因参与的KEGG调控通路。另外对8号染色体的15个候选基因进行半定量与荧光定量RT-PCR表达分析发现,只有基因Glyma.08G332500在突变体NT301与野生型中的差异达到了4倍,推测Glyma.08G332500基因是突变体NT301的候选基因。

大豆根腐病致病病原菌及其抗性研究进展

文章综述大豆根腐病病原菌鉴定与分布、抗病性鉴定与抗病基因挖掘研究现状,从栽培措施、化学防治、定向育种、生物防治方面总结根腐病防治方法,展望未来研究方向,旨在为提高大豆产量提供科学依据。

大豆种子携带病原菌对8种杀菌剂的敏感性

为筛选对大豆种子携带病原菌具有良好抑制效果的杀菌剂,采用菌丝生长速率法测定了从内蒙古大豆种子内部分离的4个属和种子表面分离的8个属的病原菌对不同作用机制杀菌剂的敏感性。结果表明,3种甾醇14α脱甲基酶抑制剂咪鲜胺、戊唑醇、氯氟醚菌唑对供试病原菌均有良好的抑制作用,其中氯氟醚菌唑抑菌效果最强,对所有供试病原菌的EC50值均小于3.73μg/mL。琥珀酸脱氢酶抑制剂氟吡菌酰胺对部分供试病原菌有较好的抑菌活性;线粒体呼吸链复合物III抑制剂嘧菌酯对除链格孢属Alternaria、Boeremia属外的多数供试病原菌具有良好的抑菌活性,EC50值介于0.01~5.53μg/mL之间;解偶联抑制剂氟啶胺仅对种子内部分离的织球壳属Plectosphaella无抑菌活性,对于其他供试病原菌的EC50值均小于3.39μg/mL。多菌灵和咯菌腈对多数供试病原菌抑菌活性良好,但对于链格孢属和织球壳属病原菌无抑菌作用。综上,可推荐使用咪鲜胺、戊唑醇、氯氟醚菌唑等甾醇14α脱甲基酶抑制剂与其他药剂科学复配来进行种子处理以防治大豆种子携带病原菌引起的主要病害。