|
|
|
题名
|
作者
|
年代
|
出处
|
被引量
|
| 1 | Exploration of presence/absence variation and corresponding polymorphic markers in soybean genome显示文摘This study was designed to reveal the genome‐wide distribution of presence/absence variation(PAV) and to establish a database of polymorphic PAV markers in soybean. The 33 soybean whole‐genome sequences were compared to each other with that of Williams 82 as a reference genome. A total of 33,127 PAVs were detected and 28,912 PAV markers with their primer sequences were designed as the database NJAUSoyPAV_1.0. The PAVs scattered on whole genome while only 518(1.8%) overlapped with simple sequence repeats(SSRs) in BARCSOYSSR_1.0database. In a random sample of 800 PAVs, 713(89.13%) showed polymorphism among the 12 differential genotypes. Using 126 PAVs and 108 SSRs to test a Chinese soybean germplasm collection composed of 828 Glycine soja Sieb. et Zucc. and Glycine max(L.) Merr. accessions, the per locus allele number and its variation appeared less in PAVs than in SSRs. The distinctness among alleles/bands of PCR(polymerase chain reaction) products showed better in PAVs than in SSRs, potential in accurate marker‐assisted allele selection. The association mapping results showed SSR t PAV was more powerful than any single marker systems.The NJAUSoyPAV_1.0 database has enriched the source of PCR markers, and may fit the materials with a range of per locus allele numbers, if jointly used with SSR markers. | Yufeng Wang Jiangjie Lu Shouyi Chen Liping Shu Reid G.Palmer Guangnan Xing Yan Li Shouping Yang Deyue Yu Tuanjie Zhao Junyi Gai | 2014 | Journal of Integrative Plant Biology2014，56，10： | 5 |
| 2 | Detecting the QTL-allele system controlling seed-flooding tolerance in a nested association mapping population of soybean显示文摘Soil flooding stress,including seed-flooding,is a key issue in soybean production in highrainfall and poorly drained areas.A nested association mapping(NAM)population comprising 230 lines of two recombinant inbred line(RIL)populations with a common parent was established and tested for seed-flooding tolerance using relative seedling length as indicator in two environments.The population was genotyped using RAD-seq(restriction site-associated DNA sequencing)to generate 6137 SNPLDB(SNP linkage disequilibrium block)markers.Using RTM-GWAS(restricted two-stage multi-locus multiallele genome-wide association study),26 main-effect QTL with 63 alleles and 12 QEI(QTL×environment)QTL with 27 alleles in a total of 33 QTL with 78 alleles(12 dual-effect alleles)were identified,explaining respectively 50.95%and 14.79%of phenotypic variation.The QTL-alleles were organized into main-effect and QEI matrices to show the genetic architecture of seed-flooding tolerance of the three parents and the NAM population.From the main-effect matrix,the best genotype was predicted to have genotypic value 1.924,compared to the parental value range 0.652–1.069,and 33 candidate genes involved in six biological processes were identified and confirmed byχ2 test.The results may provide a way to match the breeding by design strategy. | Muhammad Jaffer Ali Guangnan Xing Jianbo He Tuanjie Zhao Junyi Gai | 2020 | The Crop Journal2020，8，5： | 3 |
| 3 | R_(SC3)K of soybean cv. Kefeng No.1 confers resistance to soybean mosaic virus by interacting with the viral protein P3显示文摘Soybean mosaic virus(SMV) is one of the most devastating viral pathogens of soybean(Glycine max(L.) Merr). In total, 22 Chinese SMV strains(SC1–SC22) have been classified based on the responses of 10 soybean cultivars to these pathogens. However, although several SMVresistance loci in soybean have been identified, no gene conferring SMV resistance in the resistant soybean cultivar(cv.) Kefeng No.1 has been cloned and verified. Here, using F_(2)-derived F_(3)(F_(2:3)) and recombinant inbred line(RIL) populations from a cross between Kefeng No.1 and susceptible soybean cv. Nannong 1138-2, we localized the gene in Kefeng No.1 that mediated resistance to SMV-SC3 strain to a 90-kb interval on chromosome 2. To study the functions of candidate genes in this interval, we performed Bean pod mottle virus(BPMV)-induced gene silencing(VIGS). We identified a recombinant gene(which we named R_(SC3)K) harboring an internal deletion of a genomic DNA fragment partially flanking the LOC100526921 and LOC100812666 reference genes as the SMV-SC3 resistance gene.By shuffling genes between infectious SMV DNA clones based on the avirulent isolate SC3 and virulent isolate 1129, we determined that the viral protein P3 is the avirulence determinant mediating SMV-SC3 resistance on Kefeng No.1. P3 interacts with RNase proteins encoded by R_(SC3)K, LOC100526921, and LOC100812666. The recombinant R_(SC3)K conveys much higher anti-SMV activity than LOC100526921 and LOC100812666, although those two genes also encode proteins that inhibit SMV accumulation, as revealed by gene silencing in a susceptible cultivar and by overexpression in Nicotiana benthamiana. These findings demonstrate that R_(SC3)K mediates the resistance of Kefeng No.1 to SMV-SC3 and that SMV resistance of soybean is determined by the antiviral activity of RNase proteins. | Tongtong Jin Jinlong Yin Tao Wang Song Xue Bowen Li Tingxuan Zong Yunhua Yang Hui Liu Mengzhuo Liu Kai Xu Liqun Wang Guangnan Xing Haijian Zhi Kai Li | 2023 | Journal of Integrative Plant Biology2023，65，3： | 2 |
| 4 | Differential SW16.1 allelic effects and genetic backgrounds contributed to increased seed weight after soybean domestication显示文摘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 domaincontaining 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. | Xianlian Chen Cheng Liu Pengfei Guo Xiaoshuai Hao Yongpeng Pan Kai Zhang Wusheng Liu Lizhi Zhao Wei Luo Jianbo He Yanzhu Su Ting Jin Fenfen Jiang Si Wang Fangdong Liu Rongzhou Xie Changgen Zhen Wei Han Guangnan Xing Wubin Wang Shancen Zhao Yan Li Junyi Gai | 2023 | Journal of Integrative Plant Biology2023，65，7： | 1 |
| 5 | Genome-wide signatures of the geographic expansion and breeding of soybean显示文摘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. | Ying-Hui Li Chao Qin Li Wang Chengzhi Jiao Huilong Hong Yu Tian Yanfei Li Guangnan Xing Jun Wang Yongzhe Gu Xingpeng Gao Delin Li Hongyu Li Zhangxiong Liu Xin Jing Beibei Feng Tao Zhao Rongxia Guan Yong Guo Jun Liu Zhe Yan Lijuan Zhang Tianli Ge Xiangkong Li Xiaobo Wang Hongmei Qiu Wanhai Zhang Xiaoyan Luan Yingpeng Han Dezhi Han Ruzhen Chang Yalong Guo Jochen C.Reif Scott A.Jackson Bin Liu Shilin Tian Li-juan Qiu | 2023 | Science China(Life Sciences)2023，66，2： | 1 |
| 6 | Geographic differentiation and phylogeographic relationships among world soybean populations显示文摘A fast-growing protein and oil crop,soybean was domesticated in ancient China and disseminated early in Asia and afterwards to other continents,in particular the Americas in recent centuries.After adaptation,locally developed landraces and cultivars formed a diversity of geographic-populations.In an investigation of their phylogeographic features,marker-derived traits were combined with geography-related photo-and temperaturesensitive traits to study 13 geographic-populations comprising 371 accessions.Extreme differentiation among geographic-populations was observed for flowering date(33–94 days),maturity date(79–181 days),and main stem node number(6–25 nodes).Restriction-site associated DNA sequencing revealed strong genetic differentiation among these geographic-populations,including genetic richness(alleles,35,242–44,986)and specific-present alleles(SPAs,0–67).More SPAs(28–67)emerged in some secondary and tertiary centers than in centers of origin(8–11).Phenotypic and genotypic clustering divided 11 of the 13 geographic-populations into the same five sets of sensitivity-similar geographic-populations and grouped the populations of northeast China and northern North America rather than center-of-origin populations as secondary centers,indicating the importance of geography-related traits in determining genetic differences among geographic-populations.A model of four soybean dissemination paths is presented:from the center of origin to the north,east,and south in Asia and from northeast China to Europe and the Americas.These findings provide a detailed phylogeographic understanding of worldwide soybeans. | Xueqin Liu Jianbo He Yufeng Wang Guangnan Xing Yan Li Shouping Yang Tuanjie Zhao Junyi Gai | 2020 | The Crop Journal2020，8，2： | 1 |
| 7 | Genome-wide association with transcriptomics reveals a shade-tolerance gene network in soybean显示文摘Shade tolerance is essential for soybeans in inter/relay cropping systems.A genome-wide association study(GWAS)integrated with transcriptome sequencing was performed to identify genes and construct a genetic network governing the trait in a set of recombinant inbred lines derived from two soybean parents with contrasting shade tolerance.An improved GWAS procedure,restricted two-stage multi-locus genome-wide association study based on gene/allele sequence markers(GASM-RTM-GWAS),identified 140 genes and their alleles associated with shade-tolerance index(STI),146 with relative pith cell length(RCL),and nine with both.Annotation of these genes by biological categories allowed the construction of a protein–protein interaction network by 187 genes,of which half were differentially expressed under shading and non-shading conditions as well as at different growth stages.From the identified genes,three ones jointly identified for both traits by both GWAS and transcriptome and two genes with maximum links were chosen as beginners for entrance into the network.Altogether,both STI and RCL gene systems worked for shade-tolerance with genes interacted each other,this confirmed that shadetolerance is regulated by more than single group of interacted genes,involving multiple biological functions as a gene network. | Yanzhu Su Xiaoshuai Hao Weiying Zeng Zhenguang Lai Yongpeng Pan Can Wang Pengfei Guo Zhipeng Zhang Jianbo He Guangnan Xing Wubin Wang Jiaoping Zhang Zudong Sun Junyi Gai | 2024 | The Crop Journal2024，12，1： | 0 |
您所在的机构暂未开通此部分的功能，请联系管理员