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Song Q, Quigley C, He R, Wang D, Nguyen H, Miranda C, Li Z. Development and implementation of nested single-nucleotide polymorphism (SNP) assays for breeding and genetic research applications. THE PLANT GENOME 2024:e20491. [PMID: 39034885 DOI: 10.1002/tpg2.20491] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/19/2024] [Revised: 06/18/2024] [Accepted: 06/20/2024] [Indexed: 07/23/2024]
Abstract
SoySNP50K and SoySNP6K are commonly used for soybean (Glycine max) genotyping. The SoySNP50K assay has been used to genetically analyze the entire USDA Soybean Germplasm Collection, while the SoySNP6K assay, containing a subset of 6000 single-nucleotide polymorphisms (SNPs) from SoySNP50K, has been used for quantitative trait loci mapping of different traits. To meet the needs for genomic selection, selection of parents for crosses, and characterization of breeding populations, especially early selection of ideal offspring from thousands of lines, we developed two assays, SoySNP3K and SoySNP1K, containing 3072 and 1252 SNPs, respectively, based on SoySNP50K and SoySNP6K mark sets. These two assays also contained the trait markers reported or contributed by soybean breeders. The SNPs in the SoySNP3K are a subset from SoySNP6K, while the SNPs in the SoySNP1K are a subset from SoySNP3K. These SNPs were chosen to reduce the SNP number in the large linkage blocks while capturing as much of the haplotype diversity as possible. They are highly polymorphic and of high quality. The mean minor allele frequencies of the SNPs in the southern and northern US elites were 0.25 and 0.27 for SoySNP3K, respectively, and 0.29 and 0.33 for SoySNP1K. The selected SNPs are a valuable source for developing targeted amplicon sequencing assay or beadchip assay in soybean. SoySNP3K and SoySNP1K assays are commercialized by Illumina Inc. and AgriPlex Genomics, respectively. Together with SoySNP50K and SoySNP6K, a series of nested assays with different marker densities will serve as additional low-cost genomic tools for genetic, genomic, and breeding research.
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Affiliation(s)
- Qijian Song
- USDA-ARS, Soybean Genomics & Improvement Laboratory, Beltsville, Maryland, USA
| | - Charles Quigley
- USDA-ARS, Soybean Genomics & Improvement Laboratory, Beltsville, Maryland, USA
| | - Ruifeng He
- USDA-ARS, Soybean Genomics & Improvement Laboratory, Beltsville, Maryland, USA
| | - Dechun Wang
- Department of Plant, Soil and Microbial Sciences, Michigan State University, East Lansing, Michigan, USA
| | - Henry Nguyen
- Molecular Genetics and Soybean Genomics Laboratory, Division of Plant Science and Technology, University of Missouri, Columbia, Missouri, USA
| | - Carrie Miranda
- Department of Plant Sciences, North Dakota State University, Fargo, North Dakota, USA
| | - Zenglu Li
- Institute of Plant Breeding, Genetics and Genomics/Department of Crop and Soil Sciences, University of Georgia, Athens, Georgia, USA
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Dwivedi SL, Heslop-Harrison P, Amas J, Ortiz R, Edwards D. Epistasis and pleiotropy-induced variation for plant breeding. PLANT BIOTECHNOLOGY JOURNAL 2024. [PMID: 38875130 DOI: 10.1111/pbi.14405] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/18/2023] [Revised: 05/07/2024] [Accepted: 05/24/2024] [Indexed: 06/16/2024]
Abstract
Epistasis refers to nonallelic interaction between genes that cause bias in estimates of genetic parameters for a phenotype with interactions of two or more genes affecting the same trait. Partitioning of epistatic effects allows true estimation of the genetic parameters affecting phenotypes. Multigenic variation plays a central role in the evolution of complex characteristics, among which pleiotropy, where a single gene affects several phenotypic characters, has a large influence. While pleiotropic interactions provide functional specificity, they increase the challenge of gene discovery and functional analysis. Overcoming pleiotropy-based phenotypic trade-offs offers potential for assisting breeding for complex traits. Modelling higher order nonallelic epistatic interaction, pleiotropy and non-pleiotropy-induced variation, and genotype × environment interaction in genomic selection may provide new paths to increase the productivity and stress tolerance for next generation of crop cultivars. Advances in statistical models, software and algorithm developments, and genomic research have facilitated dissecting the nature and extent of pleiotropy and epistasis. We overview emerging approaches to exploit positive (and avoid negative) epistatic and pleiotropic interactions in a plant breeding context, including developing avenues of artificial intelligence, novel exploitation of large-scale genomics and phenomics data, and involvement of genes with minor effects to analyse epistatic interactions and pleiotropic quantitative trait loci, including missing heritability.
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Affiliation(s)
| | - Pat Heslop-Harrison
- Key Laboratory of Plant Resources Conservation and Sustainable Utilization, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, China
- Department of Genetics and Genome Biology, Institute for Environmental Futures, University of Leicester, Leicester, UK
| | - Junrey Amas
- Centre for Applied Bioinformatics, School of Biological Sciences, University of Western Australia, Perth, WA, Australia
| | - Rodomiro Ortiz
- Department of Plant Breeding, Swedish University of Agricultural Sciences, Alnarp, Sweden
| | - David Edwards
- Centre for Applied Bioinformatics, School of Biological Sciences, University of Western Australia, Perth, WA, Australia
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Sang Y, Liu X, Yuan C, Yao T, Li Y, Wang D, Zhao H, Wang Y. Genome-wide association study on resistance of cultivated soybean to Fusarium oxysporum root rot in Northeast China. BMC PLANT BIOLOGY 2023; 23:625. [PMID: 38062401 PMCID: PMC10702129 DOI: 10.1186/s12870-023-04646-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Accepted: 11/29/2023] [Indexed: 12/18/2023]
Abstract
BACKGROUND Fusarium oxysporum is a prevalent fungal pathogen that diminishes soybean yield through seedling disease and root rot. Preventing Fusarium oxysporum root rot (FORR) damage entails on the identification of resistance genes and developing resistant cultivars. Therefore, conducting fine mapping and marker development for FORR resistance genes is of great significance for fostering the cultivation of resistant varieties. In this study, 350 soybean germplasm accessions, mainly from Northeast China, underwent genotyping using the SoySNP50K Illumina BeadChip, which includes 52,041 single nucleotide polymorphisms (SNPs). Their resistance to FORR was assessed in a greenhouse. Genome-wide association studies utilizing the general linear model, mixed linear model, compressed mixed linear model, and settlement of MLM under progressively exclusive relationship models were conducted to identify marker-trait associations while effectively controlling for population structure. RESULTS The results demonstrated that these models effectively managed population structure. Eight SNP loci significantly associated with FORR resistance in soybean were detected, primarily located on Chromosome 6. Notably, there was a strong linkage disequilibrium between the large-effect SNPs ss715595462 and ss715595463, contributing substantially to phenotypic variation. Within the genetic interval encompassing these loci, 28 genes were present, with one gene Glyma.06G088400 encoding a protein kinase family protein containing a leucine-rich repeat domain identified as a potential candidate gene in the reference genome of Williams82. Additionally, quantitative real-time reverse transcription polymerase chain reaction analysis evaluated the gene expression levels between highly resistant and susceptible accessions, focusing on primary root tissues collected at different time points after F. oxysporum inoculation. Among the examined genes, only this gene emerged as the strongest candidate associated with FORR resistance. CONCLUSIONS The identification of this candidate gene Glyma.06G088400 improves our understanding of soybean resistance to FORR and the markers strongly linked to resistance can be beneficial for molecular marker-assisted selection in breeding resistant soybean accessions against F. oxysporum.
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Affiliation(s)
- Yongsheng Sang
- Soybean Research Institute, Jilin Academy of Agricultural Sciences, National Engineering Research Center for Soybean, Changchun, 130118, Jilin, PR China
- College of Agronomy, Jilin Agricultural University, Changchun, 130118, Jilin, PR China
| | - Xiaodong Liu
- Crop Germplasm Institute, Jilin Academy of Agricultural Sciences, Changchun, 130118, Jilin, China
| | - Cuiping Yuan
- Soybean Research Institute, Jilin Academy of Agricultural Sciences, National Engineering Research Center for Soybean, Changchun, 130118, Jilin, PR China
| | - Tong Yao
- College of Agronomy, Jilin Agricultural University, Changchun, 130118, Jilin, PR China
| | - Yuqiu Li
- Soybean Research Institute, Jilin Academy of Agricultural Sciences, National Engineering Research Center for Soybean, Changchun, 130118, Jilin, PR China
| | - Dechun Wang
- Department of Plant, Soil and Microbial Sciences, Michigan State University, 1066 Bogue St., Rm. A384-E, East Lansing, MI, 48824, USA
| | - Hongkun Zhao
- Soybean Research Institute, Jilin Academy of Agricultural Sciences, National Engineering Research Center for Soybean, Changchun, 130118, Jilin, PR China.
| | - Yumin Wang
- Soybean Research Institute, Jilin Academy of Agricultural Sciences, National Engineering Research Center for Soybean, Changchun, 130118, Jilin, PR China.
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Jacquet S, Li S, Mian R, Kassem MA, Rashad L, Viera S, Reta F, Reta J, Yuan J. Evaluating the Response of Glycine soja Accessions to Fungal Pathogen Macrophomina phaseolina during Seedling Growth. PLANTS (BASEL, SWITZERLAND) 2023; 12:3807. [PMID: 38005704 PMCID: PMC10675638 DOI: 10.3390/plants12223807] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Revised: 09/27/2023] [Accepted: 10/13/2023] [Indexed: 11/26/2023]
Abstract
Charcoal rot caused by the fungal pathogen Macrophomina phaseolina (Tassi) Goid is one of various devastating soybean (Glycine max (L.) Merr.) diseases, which can severely reduce crop yield. The investigation into the genetic potential for charcoal rot resistance of wild soybean (Glycine soja) accessions will enrich our understanding of the impact of soybean domestication on disease resistance; moreover, the identified charcoal rot-resistant lines can be used to improve soybean resistance to charcoal rot. The objective of this study was to evaluate the resistance of wild soybean accessions to M. phaseolina at the seedling stage and thereby select the disease-resistant lines. The results show that the fungal pathogen infection reduced the growth of the root and hypocotyl in most G. soja accessions. The accession PI 507794 displayed the highest level of resistance response to M. phaseolina infection among the tested wild soybean accessions, while PI 487431 and PI 483660B were susceptible to charcoal rot in terms of the reduction in root and hypocotyl growth. The mean values of the root and hypocotyl parameters in PI 507794 were significantly higher (p < 0.05) than those of PI 487431 and PI 483460B. A analysis of the resistance of wild soybean accessions to M. phaseolina using the root and hypocotyl as the assessment parameters at the early seedling stage provides an alternative way to rapidly identify potential resistant genotypes and facilitate breeding for soybean resistance to charcoal rot.
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Affiliation(s)
- Shirley Jacquet
- Department of Biological and Forensic Sciences, Fayetteville State University, Fayetteville, NC 28301, USA; (S.J.); (M.A.K.); (L.R.); (S.V.); (F.R.); (J.R.)
| | - Shuxian Li
- Crop Genetics Research Unit, United States Department of Agriculture, Agricultural Research Service (USDA, ARS), 141 Experiment Station Road, P.O. Box 345, Stoneville, MS 38776, USA;
| | - Rouf Mian
- Soybean and Nitrogen Fixation Research Unit, United States Department of Agriculture, Agricultural Research Service (USDA, ARS), 3127 Ligon St., Raleigh, NC 27607, USA;
| | - My Abdelmajid Kassem
- Department of Biological and Forensic Sciences, Fayetteville State University, Fayetteville, NC 28301, USA; (S.J.); (M.A.K.); (L.R.); (S.V.); (F.R.); (J.R.)
| | - Layla Rashad
- Department of Biological and Forensic Sciences, Fayetteville State University, Fayetteville, NC 28301, USA; (S.J.); (M.A.K.); (L.R.); (S.V.); (F.R.); (J.R.)
| | - Sonia Viera
- Department of Biological and Forensic Sciences, Fayetteville State University, Fayetteville, NC 28301, USA; (S.J.); (M.A.K.); (L.R.); (S.V.); (F.R.); (J.R.)
| | - Francisco Reta
- Department of Biological and Forensic Sciences, Fayetteville State University, Fayetteville, NC 28301, USA; (S.J.); (M.A.K.); (L.R.); (S.V.); (F.R.); (J.R.)
| | - Juan Reta
- Department of Biological and Forensic Sciences, Fayetteville State University, Fayetteville, NC 28301, USA; (S.J.); (M.A.K.); (L.R.); (S.V.); (F.R.); (J.R.)
| | - Jiazheng Yuan
- Department of Biological and Forensic Sciences, Fayetteville State University, Fayetteville, NC 28301, USA; (S.J.); (M.A.K.); (L.R.); (S.V.); (F.R.); (J.R.)
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Sang Y, Zhao H, Liu X, Yuan C, Qi G, Li Y, Dong L, Wang Y, Wang D, Wang Y, Dong Y. Genome-wide association study of powdery mildew resistance in cultivated soybean from Northeast China. FRONTIERS IN PLANT SCIENCE 2023; 14:1268706. [PMID: 38023859 PMCID: PMC10651740 DOI: 10.3389/fpls.2023.1268706] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Accepted: 10/17/2023] [Indexed: 12/01/2023]
Abstract
Powdery mildew (PMD), caused by the pathogen Microsphaera diffusa, leads to substantial yield decreases in susceptible soybean under favorable environmental conditions. Effective prevention of soybean PMD damage can be achieved by identifying resistance genes and developing resistant cultivars. In this study, we genotyped 331 soybean germplasm accessions, primarily from Northeast China, using the SoySNP50K BeadChip, and evaluated their resistance to PMD in a greenhouse setting. To identify marker-trait associations while effectively controlling for population structure, we conducted genome-wide association studies utilizing factored spectrally transformed linear mixed models, mixed linear models, efficient mixed-model association eXpedited, and compressed mixed linear models. The results revealed seven single nucleotide polymorphism (SNP) loci strongly associated with PMD resistance in soybean. Among these, one SNP was localized on chromosome (Chr) 14, and six SNPs with low linkage disequilibrium were localized near or in the region of previously mapped genes on Chr 16. In the reference genome of Williams82, we discovered 96 genes within the candidate region, including 17 resistance (R)-like genes, which were identified as potential candidate genes for PMD resistance. In addition, we performed quantitative real-time reverse transcription polymerase chain reaction analysis to evaluate the gene expression levels in highly resistant and susceptible genotypes, focusing on leaf tissues collected at different times after M. diffusa inoculation. Among the examined genes, three R-like genes, including Glyma.16G210800, Glyma.16G212300, and Glyma.16G213900, were identified as strong candidates associated with PMD resistance. This discovery can significantly enhance our understanding of soybean resistance to PMD. Furthermore, the significant SNPs strongly associated with resistance can serve as valuable markers for genetic improvement in breeding M. diffusa-resistant soybean cultivars.
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Affiliation(s)
- Yongsheng Sang
- College of Agronomy, Jilin Agricultural University, Changchun, Jilin, China
- Soybean Institute, Jilin Academy of Agricultural Sciences, Changchun, Jilin, China
| | - Hongkun Zhao
- Soybean Institute, Jilin Academy of Agricultural Sciences, Changchun, Jilin, China
| | - Xiaodong Liu
- Crop Germplasm Institute, Jilin Academy of Agricultural Sciences, Changchun, Jilin, China
| | - Cuiping Yuan
- Soybean Institute, Jilin Academy of Agricultural Sciences, Changchun, Jilin, China
| | - Guangxun Qi
- Soybean Institute, Jilin Academy of Agricultural Sciences, Changchun, Jilin, China
| | - Yuqiu Li
- Soybean Institute, Jilin Academy of Agricultural Sciences, Changchun, Jilin, China
| | - Lingchao Dong
- Soybean Institute, Jilin Academy of Agricultural Sciences, Changchun, Jilin, China
| | - Yingnan Wang
- Soybean Institute, Jilin Academy of Agricultural Sciences, Changchun, Jilin, China
| | - Dechun Wang
- Department of Plant, Soil and Microbial Sciences, Michigan State University, East Lansing, MI, United States
| | - Yumin Wang
- Soybean Institute, Jilin Academy of Agricultural Sciences, Changchun, Jilin, China
| | - Yingshan Dong
- College of Agronomy, Jilin Agricultural University, Changchun, Jilin, China
- Soybean Institute, Jilin Academy of Agricultural Sciences, Changchun, Jilin, China
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Patel S, Patel J, Bowen K, Koebernick J. Deciphering the genetic architecture of resistance to Corynespora cassiicola in soybean ( Glycine max L.) by integrating genome-wide association mapping and RNA-Seq analysis. FRONTIERS IN PLANT SCIENCE 2023; 14:1255763. [PMID: 37828935 PMCID: PMC10565807 DOI: 10.3389/fpls.2023.1255763] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/09/2023] [Accepted: 09/04/2023] [Indexed: 10/14/2023]
Abstract
Target spot caused by Corynespora cassiicola is a problematic disease in tropical and subtropical soybean (Glycine max) growing regions. Although resistant soybean genotypes have been identified, the genetic mechanisms underlying target spot resistance has not yet been studied. To address this knowledge gap, this is the first genome-wide association study (GWAS) conducted using the SoySNP50K array on a panel of 246 soybean accessions, aiming to unravel the genetic architecture of resistance. The results revealed significant associations of 14 and 33 loci with resistance to LIM01 and SSTA C. cassiicola isolates, respectively, with six loci demonstrating consistent associations across both isolates. To identify potential candidate genes within GWAS-identified loci, dynamic transcriptome profiling was conducted through RNA-Seq analysis. The analysis involved comparing gene expression patterns between resistant and susceptible genotypes, utilizing leaf tissue collected at different time points after inoculation. Integrating results of GWAS and RNA-Seq analyses identified 238 differentially expressed genes within a 200 kb region encompassing significant quantitative trait loci (QTLs) for disease severity ratings. These genes were involved in defense response to pathogen, innate immune response, chitinase activity, histone H3-K9 methylation, salicylic acid mediated signaling pathway, kinase activity, and biosynthesis of flavonoid, jasmonic acid, phenylpropanoid, and wax. In addition, when combining results from this study with previous GWAS research, 11 colocalized regions associated with disease resistance were identified for biotic and abiotic stress. This finding provides valuable insight into the genetic resources that can be harnessed for future breeding programs aiming to enhance soybean resistance against target spot and other diseases simultaneously.
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Affiliation(s)
- Sejal Patel
- Department of Crop, Soil and Environmental Sciences, Auburn University, Auburn, AL, United States
| | - Jinesh Patel
- Department of Crop, Soil and Environmental Sciences, Auburn University, Auburn, AL, United States
| | - Kira Bowen
- Department of Entomology and Plant Pathology, Auburn University, Auburn, AL, United States
| | - Jenny Koebernick
- Department of Crop, Soil and Environmental Sciences, Auburn University, Auburn, AL, United States
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Alseekh S, Karakas E, Zhu F, Wijesingha Ahchige M, Fernie AR. Plant biochemical genetics in the multiomics era. JOURNAL OF EXPERIMENTAL BOTANY 2023; 74:4293-4307. [PMID: 37170864 PMCID: PMC10433942 DOI: 10.1093/jxb/erad177] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Accepted: 05/09/2023] [Indexed: 05/13/2023]
Abstract
Our understanding of plant biology has been revolutionized by modern genetics and biochemistry. However, biochemical genetics can be traced back to the foundation of Mendelian genetics; indeed, one of Mendel's milestone discoveries of seven characteristics of pea plants later came to be ascribed to a mutation in a starch branching enzyme. Here, we review both current and historical strategies for the elucidation of plant metabolic pathways and the genes that encode their component enzymes and regulators. We use this historical review to discuss a range of classical genetic phenomena including epistasis, canalization, and heterosis as viewed through the lens of contemporary high-throughput data obtained via the array of approaches currently adopted in multiomics studies.
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Affiliation(s)
- Saleh Alseekh
- Max Planck Institute of Molecular Plant Physiology, 14476 Potsdam-Golm, Germany
- Center of Plant Systems Biology and Biotechnology, Plovdiv, Bulgaria
| | - Esra Karakas
- Max Planck Institute of Molecular Plant Physiology, 14476 Potsdam-Golm, Germany
| | - Feng Zhu
- National R&D Center for Citrus Preservation, Key Laboratory of Horticultural Plant Biology, Ministry of Education, Huazhong Agricultural University, 430070 Wuhan, China
| | | | - Alisdair R Fernie
- Max Planck Institute of Molecular Plant Physiology, 14476 Potsdam-Golm, Germany
- Center of Plant Systems Biology and Biotechnology, Plovdiv, Bulgaria
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Wang N, Zhang W, Wang X, Zheng Z, Bai D, Li K, Zhao X, Xiang J, Liang Z, Qian Y, Wang W, Shi Y. Genome-Wide Association Study of Xian Rice Grain Shape and Weight in Different Environments. PLANTS (BASEL, SWITZERLAND) 2023; 12:2549. [PMID: 37447110 PMCID: PMC10347298 DOI: 10.3390/plants12132549] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Revised: 06/29/2023] [Accepted: 07/03/2023] [Indexed: 07/15/2023]
Abstract
Drought is one of the key environmental factors affecting the growth and yield potential of rice. Grain shape, on the other hand, is an important factor determining the appearance, quality, and yield of rice grains. Here, we re-sequenced 275 Xian accessions and then conducted a genome-wide association study (GWAS) on six agronomic traits with the 404,411 single nucleotide polymorphisms (SNPs) derived by the best linear unbiased prediction (BLUP) for each trait. Under two years of drought stress (DS) and normal water (NW) treatments, a total of 16 QTLs associated with rice grain shape and grain weight were detected on chromosomes 1, 2, 3, 4, 5, 7, 8, 11, and 12. In addition, these QTLs were analyzed by haplotype analysis and functional annotation, and one clone (GSN1) and five new candidate genes were identified in the candidate interval. The findings provide important genetic information for the molecular improvement of grain shape and weight in rice.
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Affiliation(s)
- Nansheng Wang
- College of Agronomy, Anhui Agricultural University, Hefei 230000, China; (N.W.); (W.Z.); (X.W.); (Z.Z.); (D.B.); (K.L.); (X.Z.); (J.X.); (Z.L.); (Y.Q.)
| | - Wanyang Zhang
- College of Agronomy, Anhui Agricultural University, Hefei 230000, China; (N.W.); (W.Z.); (X.W.); (Z.Z.); (D.B.); (K.L.); (X.Z.); (J.X.); (Z.L.); (Y.Q.)
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Xinchen Wang
- College of Agronomy, Anhui Agricultural University, Hefei 230000, China; (N.W.); (W.Z.); (X.W.); (Z.Z.); (D.B.); (K.L.); (X.Z.); (J.X.); (Z.L.); (Y.Q.)
| | - Zhenzhen Zheng
- College of Agronomy, Anhui Agricultural University, Hefei 230000, China; (N.W.); (W.Z.); (X.W.); (Z.Z.); (D.B.); (K.L.); (X.Z.); (J.X.); (Z.L.); (Y.Q.)
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Di Bai
- College of Agronomy, Anhui Agricultural University, Hefei 230000, China; (N.W.); (W.Z.); (X.W.); (Z.Z.); (D.B.); (K.L.); (X.Z.); (J.X.); (Z.L.); (Y.Q.)
| | - Keyang Li
- College of Agronomy, Anhui Agricultural University, Hefei 230000, China; (N.W.); (W.Z.); (X.W.); (Z.Z.); (D.B.); (K.L.); (X.Z.); (J.X.); (Z.L.); (Y.Q.)
| | - Xueyu Zhao
- College of Agronomy, Anhui Agricultural University, Hefei 230000, China; (N.W.); (W.Z.); (X.W.); (Z.Z.); (D.B.); (K.L.); (X.Z.); (J.X.); (Z.L.); (Y.Q.)
| | - Jun Xiang
- College of Agronomy, Anhui Agricultural University, Hefei 230000, China; (N.W.); (W.Z.); (X.W.); (Z.Z.); (D.B.); (K.L.); (X.Z.); (J.X.); (Z.L.); (Y.Q.)
| | - Zhaojie Liang
- College of Agronomy, Anhui Agricultural University, Hefei 230000, China; (N.W.); (W.Z.); (X.W.); (Z.Z.); (D.B.); (K.L.); (X.Z.); (J.X.); (Z.L.); (Y.Q.)
| | - Yingzhi Qian
- College of Agronomy, Anhui Agricultural University, Hefei 230000, China; (N.W.); (W.Z.); (X.W.); (Z.Z.); (D.B.); (K.L.); (X.Z.); (J.X.); (Z.L.); (Y.Q.)
| | - Wensheng Wang
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Yingyao Shi
- College of Agronomy, Anhui Agricultural University, Hefei 230000, China; (N.W.); (W.Z.); (X.W.); (Z.Z.); (D.B.); (K.L.); (X.Z.); (J.X.); (Z.L.); (Y.Q.)
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Zhang G, Bi Z, Jiang J, Lu J, Li K, Bai D, Wang X, Zhao X, Li M, Zhao X, Wang W, Xu J, Li Z, Zhang F, Shi Y. Genome-wide association and epistasis studies reveal the genetic basis of saline-alkali tolerance at the germination stage in rice. FRONTIERS IN PLANT SCIENCE 2023; 14:1170641. [PMID: 37251777 PMCID: PMC10213895 DOI: 10.3389/fpls.2023.1170641] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Accepted: 04/10/2023] [Indexed: 05/31/2023]
Abstract
Introduction Saline-alkali stress is one of the main abiotic factors limiting rice production worldwide. With the widespread use of rice direct seeding technology, it has become increasingly important to improve rice saline-alkali tolerance at the germination stage. Methods To understand the genetic basis of saline-alkali tolerance and facilitate breeding efforts for developing saline-alkali tolerant rice varieties, the genetic basis of rice saline-alkali tolerance was dissected by phenotyping seven germination-related traits of 736 diverse rice accessions under the saline-alkali stress and control conditions using genome-wide association and epistasis analysis (GWAES). Results Totally, 165 main-effect quantitative trait nucleotides (QTNs) and 124 additional epistatic QTNs were identified as significantly associated with saline-alkali tolerance, which explained a significant portion of the total phenotypic variation of the saline-alkali tolerance traits in the 736 rice accessions. Most of these QTNs were located in genomic regions either harboring saline-alkali tolerance QTNs or known genes for saline-alkali tolerance reported previously. Epistasis as an important genetic basis of rice saline-alkali tolerance was validated by genomic best linear unbiased prediction in which inclusion of both main-effect and epistatic QTNs showed a consistently better prediction accuracy than either main-effect or epistatic QTNs alone. Candidate genes for two pairs of important epistatic QTNs were suggested based on combined evidence from the high-resolution mapping plus their reported molecular functions. The first pair included a glycosyltransferase gene LOC_Os02g51900 (UGT85E1) and an E3 ligase gene LOC_Os04g01490 (OsSIRP4), while the second pair comprised an ethylene-responsive transcriptional factor, AP59 (LOC_Os02g43790), and a Bcl-2-associated athanogene gene, OsBAG1 (LOC_Os09g35630) for salt tolerance. Detailed haplotype analyses at both gene promoter and CDS regions of these candidate genes for important QTNs identified favorable haplotype combinations with large effects on saline-alkali tolerance, which can be used to improve rice saline-alkali tolerance by selective introgression. Discussion Our findings provided saline-alkali tolerant germplasm resources and valuable genetic information to be used in future functional genomic and breeding efforts of rice saline-alkali tolerance at the germination stage.
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Affiliation(s)
- Guogen Zhang
- College of Agronomy, Anhui Agricultural University, Hefei, Anhui, China
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Zhiyuan Bi
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Jing Jiang
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Jingbing Lu
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Keyang Li
- College of Agronomy, Anhui Agricultural University, Hefei, Anhui, China
| | - Di Bai
- College of Agronomy, Anhui Agricultural University, Hefei, Anhui, China
| | - Xinchen Wang
- College of Agronomy, Anhui Agricultural University, Hefei, Anhui, China
| | - Xueyu Zhao
- College of Agronomy, Anhui Agricultural University, Hefei, Anhui, China
| | - Min Li
- College of Agronomy, Anhui Agricultural University, Hefei, Anhui, China
| | - Xiuqin Zhao
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Wensheng Wang
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
- National Nanfan Research Institute (Sanya), Chinese Academy of Agricultural Sciences, Sanya, Hainan, China
| | - Jianlong Xu
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Zhikang Li
- College of Agronomy, Anhui Agricultural University, Hefei, Anhui, China
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Fan Zhang
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
- National Nanfan Research Institute (Sanya), Chinese Academy of Agricultural Sciences, Sanya, Hainan, China
| | - Yingyao Shi
- College of Agronomy, Anhui Agricultural University, Hefei, Anhui, China
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10
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Hong J, Su S, Wang L, Bai S, Xu J, Li Z, Betts N, Liang W, Wang W, Shi J, Zhang D. Combined genome-wide association study and epistasis analysis reveal multifaceted genetic architectures of plant height in Asian cultivated rice. PLANT, CELL & ENVIRONMENT 2023; 46:1295-1311. [PMID: 36734269 DOI: 10.1111/pce.14557] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Revised: 01/08/2023] [Accepted: 02/01/2023] [Indexed: 06/18/2023]
Abstract
Plant height (PH) in rice (Oryza sativa) is an important trait for its adaptation and agricultural performance. Discovery of the semi-dwarf1 (SD1) mutation initiated the Green Revolution, boosting rice yield and fitness, but the underlying genetic regulation of PH in rice remains largely unknown. Here, we performed genome-wide association study (GWAS) and identified 12 non-repetitive QTL/genes regulating PH variation in 619 Asian cultivated rice accessions. One of these was an SD1 structural variant, not normally detected in standard GWAS analyses. Given the strong effect of SD1 on PH, we also divided 619 accessions into subgroups harbouring distinct SD1 haplotypes, and found a further 85 QTL/genes for PH, revealing genetic heterogeneity that may be missed by analysing a broad, diverse population. Moreover, we uncovered two epistatic interaction networks of PH-associated QTL/genes in the japonica (Geng)-dominant SD1NIP subgroup. In one of them, the hub QTL/gene qphSN1.4/GAMYB interacted with qphSN3.1/OsINO80, qphSN3.4/HD16/EL1, qphSN6.2/LOC_Os06g11130, and qphSN10.2/MADS56. Sequence variations in GAMYB and MADS56 were associated with their expression levels and PH variations, and MADS56 was shown to physically interact with MADS57 to coregulate expression of gibberellin (GA) metabolic genes OsGA2ox3 and Elongated Uppermost Internode1 (EUI1). Our study uncovered the multifaceted genetic architectures of rice PH, and provided novel and abundant genetic resources for breeding semi-dwarf rice and new candidates for further mechanistic studies on regulation of PH in rice.
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Affiliation(s)
- Jun Hong
- Joint International Research Laboratory of Metabolic and Developmental Sciences, State Key Laboratory of Hybrid Rice, School of Life Sciences and Biotechnology, Yazhou Bay Institute of Deepsea Sci-Tech, Shanghai Jiao Tong University, Shanghai, China
| | - Su Su
- Joint International Research Laboratory of Metabolic and Developmental Sciences, State Key Laboratory of Hybrid Rice, School of Life Sciences and Biotechnology, Yazhou Bay Institute of Deepsea Sci-Tech, Shanghai Jiao Tong University, Shanghai, China
| | - Li Wang
- Joint International Research Laboratory of Metabolic and Developmental Sciences, State Key Laboratory of Hybrid Rice, School of Life Sciences and Biotechnology, Yazhou Bay Institute of Deepsea Sci-Tech, Shanghai Jiao Tong University, Shanghai, China
| | - Shaoxing Bai
- Joint International Research Laboratory of Metabolic and Developmental Sciences, State Key Laboratory of Hybrid Rice, School of Life Sciences and Biotechnology, Yazhou Bay Institute of Deepsea Sci-Tech, Shanghai Jiao Tong University, Shanghai, China
| | - Jianlong Xu
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Zhikang Li
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Natalie Betts
- School of Agriculture, Food and Wine, University of Adelaide, Urrbrae, South Australia, Australia
| | - Wanqi Liang
- Joint International Research Laboratory of Metabolic and Developmental Sciences, State Key Laboratory of Hybrid Rice, School of Life Sciences and Biotechnology, Yazhou Bay Institute of Deepsea Sci-Tech, Shanghai Jiao Tong University, Shanghai, China
| | - Wensheng Wang
- Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Jianxin Shi
- Joint International Research Laboratory of Metabolic and Developmental Sciences, State Key Laboratory of Hybrid Rice, School of Life Sciences and Biotechnology, Yazhou Bay Institute of Deepsea Sci-Tech, Shanghai Jiao Tong University, Shanghai, China
| | - Dabing Zhang
- Joint International Research Laboratory of Metabolic and Developmental Sciences, State Key Laboratory of Hybrid Rice, School of Life Sciences and Biotechnology, Yazhou Bay Institute of Deepsea Sci-Tech, Shanghai Jiao Tong University, Shanghai, China
- School of Agriculture, Food and Wine, University of Adelaide, Urrbrae, South Australia, Australia
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11
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Bisht A, Saini DK, Kaur B, Batra R, Kaur S, Kaur I, Jindal S, Malik P, Sandhu PK, Kaur A, Gill BS, Wani SH, Kaur B, Mir RR, Sandhu KS, Siddique KHM. Multi-omics assisted breeding for biotic stress resistance in soybean. Mol Biol Rep 2023; 50:3787-3814. [PMID: 36692674 DOI: 10.1007/s11033-023-08260-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Accepted: 01/09/2023] [Indexed: 01/25/2023]
Abstract
Biotic stress is a critical factor limiting soybean growth and development. Soybean responses to biotic stresses such as insects, nematodes, fungal, bacterial, and viral pathogens are governed by complex regulatory and defense mechanisms. Next-generation sequencing has availed research techniques and strategies in genomics and post-genomics. This review summarizes the available information on marker resources, quantitative trait loci, and marker-trait associations involved in regulating biotic stress responses in soybean. We discuss the differential expression of related genes and proteins reported in different transcriptomics and proteomics studies and the role of signaling pathways and metabolites reported in metabolomic studies. Recent advances in omics technologies offer opportunities to reshape and improve biotic stress resistance in soybean by altering gene regulation and/or other regulatory networks. We suggest using 'integrated omics' to precisely understand how soybean responds to different biotic stresses. We also discuss the potential challenges of integrating multi-omics for the functional analysis of genes and their regulatory networks and the development of biotic stress-resistant cultivars. This review will help direct soybean breeding programs to develop resistance against different biotic stresses.
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Affiliation(s)
- Ashita Bisht
- Department of Plant Breeding and Genetics, Punjab Agricultural University, 141004, Ludhiana, India
- CSK Himachal Pradesh Krishi Vishvavidyalaya, Highland Agricultural Research and Extension Centre, 175142, Kukumseri, Lahaul and Spiti, India
| | - Dinesh Kumar Saini
- Department of Plant Breeding and Genetics, Punjab Agricultural University, 141004, Ludhiana, India.
| | - Baljeet Kaur
- Department of Plant Breeding and Genetics, Punjab Agricultural University, 141004, Ludhiana, India
| | - Ritu Batra
- Department of Genetics and Plant Breeding, Chaudhary Charan Singh University, 25004, Meerut, India
| | - Sandeep Kaur
- Department of Plant Breeding and Genetics, Punjab Agricultural University, 141004, Ludhiana, India
| | - Ishveen Kaur
- Agriculture, Environmental and Sustainability Sciences, College of sciences, University of Texas Rio Grande Valley, 78539, Edinburg, TX, USA
| | - Suruchi Jindal
- Division of Molecular Biology and Genetic Engineering, School of Bioengineering and Biosciences, Lovely Professional University, Phagwara, India
| | - Palvi Malik
- , Gurdev Singh Khush Institute of Genetics, Plant Breeding and Biotechnology, Punjab Agricultural University,, 141004, Ludhiana, India
| | - Pawanjit Kaur Sandhu
- Department of Chemistry, University of British Columbia, V1V 1V7, Okanagan, Kelowna, Canada
| | - Amandeep Kaur
- Division of Molecular Biology and Genetic Engineering, School of Bioengineering and Biosciences, Lovely Professional University, Phagwara, India
| | - Balwinder Singh Gill
- Department of Plant Breeding and Genetics, Punjab Agricultural University, 141004, Ludhiana, India
| | - Shabir Hussain Wani
- MRCFC Khudwani, Sher-e-Kashmir University of Agricultural Sciences and Technology, Kashmir, Shalimar, India
| | - Balwinder Kaur
- Department of Entomology, UF/IFAS Research and Education Center, 33430, Belle Glade, Florida, USA
| | - Reyazul Rouf Mir
- Division of Genetics and Plant Breeding, Faculty of Agriculture, SKUAST-Kashmir, 193201, India
| | - Karansher Singh Sandhu
- Department of Crop and Soil Sciences, Washington State University, 99163, Pullman, WA, USA.
| | - Kadambot H M Siddique
- The UWA Institute of Agriculture, The University of Western Australia, 6001, Perth, WA, Australia.
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12
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Genome-wide association study reveals novel loci and a candidate gene for resistance to frogeye leaf spot (Cercospora sojina) in soybean. Mol Genet Genomics 2023; 298:441-454. [PMID: 36602595 DOI: 10.1007/s00438-022-01986-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2022] [Accepted: 12/16/2022] [Indexed: 01/06/2023]
Abstract
Frogeye leaf spot, caused by the fungus Cercospora sojina, is a threat to soybeans in the southeastern and midwestern United States that can be controlled by crop genetic resistance. Limited genetic resistance to the disease has been reported, and only three sources of resistance have been used in modern soybean breeding. To discover novel sources and identify the genomic locations of resistance that could be used in soybean breeding, a GWAS was conducted using a panel of 329 soybean accessions selected to maximize genetic diversity. Accessions were phenotyped using a 1-5 visual rating and by using image analysis to count lesion number and measure the percent of leaf area diseased. Eight novel loci on eight chromosomes were identified for three traits utilizing the FarmCPU or BLINK models, of which a locus on chromosome 11 was highly significant across all model-trait combinations. KASP markers were designed using the SoySNP50K Beadchip and variant information from 65 of the accessions that have been sequenced to target SNPs in the gene model Glyma.11g230400, a LEUCINE-RICH REPEAT RECEPTOR-LIKE PROTEIN KINASE. The association of a KASP marker, GSM990, designed to detect a missense mutation in the gene was the most significant with all three traits in a genome-wide association, and the marker may be useful to select for resistance to frogeye leaf spot in soybean breeding.
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13
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Hong H, Li M, Chen Y, Wang H, Wang J, Guo B, Gao H, Ren H, Yuan M, Han Y, Qiu L. Genome-wide association studies for soybean epicotyl length in two environments using 3VmrMLM. FRONTIERS IN PLANT SCIENCE 2022; 13:1033120. [PMID: 36452100 PMCID: PMC9704727 DOI: 10.3389/fpls.2022.1033120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Accepted: 10/04/2022] [Indexed: 06/17/2023]
Abstract
Germination of soybean seed is the imminent vital process after sowing. The status of plumular axis and radicle determine whether soybean seed can emerge normally. Epicotyl, an organ between cotyledons and first functional leaves, is essential for soybean seed germination, seedling growth and early morphogenesis. Epicotyl length (EL) is a quantitative trait controlled by multiple genes/QTLs. Here, the present study analyzes the phenotypic diversity and genetic basis of EL using 951 soybean improved cultivars and landraces from Asia, America, Europe and Africa. 3VmrMLM was used to analyze the associations between EL in 2016 and 2020 and 1,639,846 SNPs for the identification of QTNs and QTN-by-environment interactions (QEIs)".A total of 180 QTNs and QEIs associated with EL were detected. Among them, 74 QTNs (ELS_Q) and 16 QEIs (ELS_QE) were identified to be associated with ELS (epicotyl length of single plant emergence), and 60 QTNs (ELT_Q) and 30 QEIs (ELT_QE) were identified to be associated with ELT (epicotyl length of three seedlings). Based on transcript abundance analysis, GO (Gene Ontology) enrichment and haplotype analysis, ten candidate genes were predicted within nine genic SNPs located in introns, upstream or downstream, which were supposed to be directly or indirectly involved in the process of seed germination and seedling development., Of 10 candidate genes, two of them (Glyma.04G122400 and Glyma.18G183600) could possibly affect epicotyl length elongation. These results indicate the genetic basis of EL and provides a valuable basis for specific functional studies of epicotyl traits.
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Affiliation(s)
- Huilong Hong
- Key Laboratory of Soybean Biology in Chinese Ministry of Education (key Laboratory of Soybean Biology and Breeding/Genetics of Chinese Agriculture Ministry), Northeast Agricultural University, Harbin, China
- Institute of Crop Science, National Key Facility for Crop Gene Resources and Genetic Improvement (NFCRI) Chinese Academy of Agricultural Sciences, Beijing, China
| | - Mei Li
- Crop Information Center, College of Plant Science and Technology, Huazhong Agricultural University, Wuhan, China
| | - Yijie Chen
- College of Agriculture, Yangtze University, Jingzhou, China
| | - Haorang Wang
- Jiangsu Xuhuai Regional Institute of Agricultural Sciences, Xuzhou, China
| | - Jun Wang
- College of Agriculture, Yangtze University, Jingzhou, China
| | - Bingfu Guo
- Nanchang Branch of National Center of Oil crops Improvement, Jiangxi Province Key Laboratory of Oil crops Biology, Crops Research Institute of Jiangxi Academy of Agricultural Sciences, Nanchang, China
| | - Huawei Gao
- Institute of Crop Science, National Key Facility for Crop Gene Resources and Genetic Improvement (NFCRI) Chinese Academy of Agricultural Sciences, Beijing, China
| | - Honglei Ren
- Soybean Research Institute, Heilongjiang Academy of Agricultural Sciences, Harbin, China
| | - Ming Yuan
- Qiqihar Branch of Heilongjiang Academy of Agricultural Sciences, Qiqihar, China
| | - Yingpeng Han
- Key Laboratory of Soybean Biology in Chinese Ministry of Education (key Laboratory of Soybean Biology and Breeding/Genetics of Chinese Agriculture Ministry), Northeast Agricultural University, Harbin, China
| | - Lijuan Qiu
- Institute of Crop Science, National Key Facility for Crop Gene Resources and Genetic Improvement (NFCRI) Chinese Academy of Agricultural Sciences, Beijing, China
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14
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Lin F, Chhapekar SS, Vieira CC, Da Silva MP, Rojas A, Lee D, Liu N, Pardo EM, Lee YC, Dong Z, Pinheiro JB, Ploper LD, Rupe J, Chen P, Wang D, Nguyen HT. Breeding for disease resistance in soybean: a global perspective. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2022; 135:3773-3872. [PMID: 35790543 PMCID: PMC9729162 DOI: 10.1007/s00122-022-04101-3] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/21/2021] [Accepted: 04/11/2022] [Indexed: 05/29/2023]
Abstract
KEY MESSAGE This review provides a comprehensive atlas of QTLs, genes, and alleles conferring resistance to 28 important diseases in all major soybean production regions in the world. Breeding disease-resistant soybean [Glycine max (L.) Merr.] varieties is a common goal for soybean breeding programs to ensure the sustainability and growth of soybean production worldwide. However, due to global climate change, soybean breeders are facing strong challenges to defeat diseases. Marker-assisted selection and genomic selection have been demonstrated to be successful methods in quickly integrating vertical resistance or horizontal resistance into improved soybean varieties, where vertical resistance refers to R genes and major effect QTLs, and horizontal resistance is a combination of major and minor effect genes or QTLs. This review summarized more than 800 resistant loci/alleles and their tightly linked markers for 28 soybean diseases worldwide, caused by nematodes, oomycetes, fungi, bacteria, and viruses. The major breakthroughs in the discovery of disease resistance gene atlas of soybean were also emphasized which include: (1) identification and characterization of vertical resistance genes reside rhg1 and Rhg4 for soybean cyst nematode, and exploration of the underlying regulation mechanisms through copy number variation and (2) map-based cloning and characterization of Rps11 conferring resistance to 80% isolates of Phytophthora sojae across the USA. In this review, we also highlight the validated QTLs in overlapping genomic regions from at least two studies and applied a consistent naming nomenclature for these QTLs. Our review provides a comprehensive summary of important resistant genes/QTLs and can be used as a toolbox for soybean improvement. Finally, the summarized genetic knowledge sheds light on future directions of accelerated soybean breeding and translational genomics studies.
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Affiliation(s)
- Feng Lin
- Department of Plant, Soil and Microbial Sciences, Michigan State University, East Lansing, MI 48824 USA
| | - Sushil Satish Chhapekar
- Division of Plant Sciences and National Center for Soybean Biotechnology, University of Missouri-Columbia, Columbia, MO 65211 USA
| | - Caio Canella Vieira
- Division of Plant Sciences and National Center for Soybean Biotechnology, University of Missouri-Columbia, Columbia, MO 65211 USA
- Fisher Delta Research Center, University of Missouri, Portageville, MO 63873 USA
| | - Marcos Paulo Da Silva
- Department of Entomology and Plant Pathology, University of Arkansas, Fayetteville, AR 72701 USA
| | - Alejandro Rojas
- Department of Entomology and Plant Pathology, University of Arkansas, Fayetteville, AR 72701 USA
| | - Dongho Lee
- Division of Plant Sciences and National Center for Soybean Biotechnology, University of Missouri-Columbia, Columbia, MO 65211 USA
- Fisher Delta Research Center, University of Missouri, Portageville, MO 63873 USA
| | - Nianxi Liu
- Soybean Research Institute, Jilin Academy of Agricultural Sciences, Changchun,, 130033 Jilin China
| | - Esteban Mariano Pardo
- Instituto de Tecnología Agroindustrial del Noroeste Argentino (ITANOA) [Estación Experimental Agroindustrial Obispo Colombres (EEAOC) – Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET)], Av. William Cross 3150, C.P. T4101XAC, Las Talitas, Tucumán, Argentina
| | - Yi-Chen Lee
- Fisher Delta Research Center, University of Missouri, Portageville, MO 63873 USA
| | - Zhimin Dong
- Soybean Research Institute, Jilin Academy of Agricultural Sciences, Changchun,, 130033 Jilin China
| | - Jose Baldin Pinheiro
- Departamento de Genética, Escola Superior de Agricultura “Luiz de Queiroz” (ESALQ/USP), PO Box 9, Piracicaba, SP 13418-900 Brazil
| | - Leonardo Daniel Ploper
- Instituto de Tecnología Agroindustrial del Noroeste Argentino (ITANOA) [Estación Experimental Agroindustrial Obispo Colombres (EEAOC) – Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET)], Av. William Cross 3150, C.P. T4101XAC, Las Talitas, Tucumán, Argentina
| | - John Rupe
- Department of Entomology and Plant Pathology, University of Arkansas, Fayetteville, AR 72701 USA
| | - Pengyin Chen
- Division of Plant Sciences and National Center for Soybean Biotechnology, University of Missouri-Columbia, Columbia, MO 65211 USA
- Fisher Delta Research Center, University of Missouri, Portageville, MO 63873 USA
| | - Dechun Wang
- Department of Plant, Soil and Microbial Sciences, Michigan State University, East Lansing, MI 48824 USA
| | - Henry T. Nguyen
- Division of Plant Sciences and National Center for Soybean Biotechnology, University of Missouri-Columbia, Columbia, MO 65211 USA
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15
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Rairdin A, Fotouhi F, Zhang J, Mueller DS, Ganapathysubramanian B, Singh AK, Dutta S, Sarkar S, Singh A. Deep learning-based phenotyping for genome wide association studies of sudden death syndrome in soybean. FRONTIERS IN PLANT SCIENCE 2022; 13:966244. [PMID: 36340398 PMCID: PMC9634489 DOI: 10.3389/fpls.2022.966244] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Accepted: 09/26/2022] [Indexed: 06/07/2023]
Abstract
Using a reliable and accurate method to phenotype disease incidence and severity is essential to unravel the complex genetic architecture of disease resistance in plants, and to develop disease resistant cultivars. Genome-wide association studies (GWAS) involve phenotyping large numbers of accessions, and have been used for a myriad of traits. In field studies, genetic accessions are phenotyped across multiple environments and replications, which takes a significant amount of labor and resources. Deep Learning (DL) techniques can be effective for analyzing image-based tasks; thus DL methods are becoming more routine for phenotyping traits to save time and effort. This research aims to conduct GWAS on sudden death syndrome (SDS) of soybean [Glycine max L. (Merr.)] using disease severity from both visual field ratings and DL-based (using images) severity ratings collected from 473 accessions. Images were processed through a DL framework that identified soybean leaflets with SDS symptoms, and then quantified the disease severity on those leaflets into a few classes with mean Average Precision of 0.34 on unseen test data. Both visual field ratings and image-based ratings identified significant single nucleotide polymorphism (SNP) markers associated with disease resistance. These significant SNP markers are either in the proximity of previously reported candidate genes for SDS or near potentially novel candidate genes. Four previously reported SDS QTL were identified that contained a significant SNPs, from this study, from both a visual field rating and an image-based rating. The results of this study provide an exciting avenue of using DL to capture complex phenotypic traits from images to get comparable or more insightful results compared to subjective visual field phenotyping of traits for disease symptoms.
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Affiliation(s)
- Ashlyn Rairdin
- Department of Agronomy, Iowa State University, Ames, IA, United States
| | - Fateme Fotouhi
- Department of Mechanical Engineering, Iowa State University, Ames, IA, United States
- Department of Computer Science, Iowa State University, Ames, IA, United States
| | - Jiaoping Zhang
- Department of Agronomy, Iowa State University, Ames, IA, United States
| | - Daren S. Mueller
- Department of Plant Pathology and Microbiology, Iowa State University, Ames, IA, United States
| | | | - Asheesh K. Singh
- Department of Agronomy, Iowa State University, Ames, IA, United States
| | - Somak Dutta
- Department of Statistics, Iowa State University, Ames, IA, United States
| | - Soumik Sarkar
- Department of Mechanical Engineering, Iowa State University, Ames, IA, United States
- Department of Computer Science, Iowa State University, Ames, IA, United States
| | - Arti Singh
- Department of Agronomy, Iowa State University, Ames, IA, United States
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16
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Lin F, Li W, McCoy AG, Wang K, Jacobs J, Zhang N, Huo X, Wani SH, Gu C, Chilvers MI, Wang D. Identification and characterization of pleiotropic and epistatic QDRL conferring partial resistance to Pythium irregulare and P. sylvaticum in soybean. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2022; 135:3571-3582. [PMID: 36087141 DOI: 10.1007/s00122-022-04201-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Accepted: 08/17/2022] [Indexed: 06/15/2023]
Abstract
Pleiotropic and epistatic quantitative disease resistance loci (QDRL) were identified for soybean partial resistance to different isolates of Pythium irregulare and Pythium sylvaticum. Pythium root rot is an important seedling disease of soybean [Glycine max (L.) Merr.], a crop grown worldwide for protein and oil content. Pythium irregulare and P. sylvaticum are two of the most prevalent and aggressive Pythium species in soybean producing regions in the North Central U.S. Few studies have been conducted to identify soybean resistance for management against these two pathogens. In this study, a mapping population (derived from E13390 x E13901) with 228 F4:5 recombinant inbred lines were screened against P. irregulare isolate MISO 11-6 and P. sylvaticum isolate C-MISO2-2-30 for QDRL mapping. Correlation analysis indicated significant positive correlations between soybean responses to the two pathogens, and a pleiotropic QDRL (qPirr16.1) was identified. Further investigation found that the qPirr16.1 imparts dominant resistance against P. irregulare, but recessive resistance against P. sylvaticum. In addition, two QDRL, qPsyl15.1, and qPsyl18.1 were identified for partial resistance to P. sylvaticum. Further analysis revealed epistatic interactions between qPirr16.1 and qPsyl15.1 for RRW and DRX, whereas qPsyl18.1 contributed resistance to RSE. Marker-assisted resistance spectrum analysis using F6:7 progeny lines verified the resistance of qPirr16.1 against four additional P. irregulare isolates. Intriguingly, although the epistatic interaction of qPirr16.1 and qPsyl15.1 can be confirmed using two additional isolates of P. sylvaticum, the interaction appears to be suppressed for the other two P. sylvaticum isolates. An 'epistatic gene-for-gene' model was proposed to explain the isolate-specific epistatic interactions. The integration of the QDRL into elite soybean lines containing all the desirable alleles has been initiated.
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Affiliation(s)
- Feng Lin
- Department of Plant, Soil and Microbial Sciences, Michigan State University, 1066 Bogue Street, Rm. A384-E, East Lansing, MI, 48824-1325, USA
| | - Wenlong Li
- Department of Plant, Soil and Microbial Sciences, Michigan State University, 1066 Bogue Street, Rm. A384-E, East Lansing, MI, 48824-1325, USA
- North China Key Laboratory for Germplasm Resources of Education Ministry, Hebei Agricultural University, Lekai South Street 2596, Baoding, 071001, Hebei Province, China
| | - Austin G McCoy
- Department of Plant, Soil and Microbial Sciences, Michigan State University, 1066 Bogue Street, Rm. A384-E, East Lansing, MI, 48824-1325, USA
| | - Kelly Wang
- Department of Plant, Soil and Microbial Sciences, Michigan State University, 1066 Bogue Street, Rm. A384-E, East Lansing, MI, 48824-1325, USA
| | - Janette Jacobs
- Department of Plant, Soil and Microbial Sciences, Michigan State University, 1066 Bogue Street, Rm. A384-E, East Lansing, MI, 48824-1325, USA
| | - Na Zhang
- Department of Plant, Soil and Microbial Sciences, Michigan State University, 1066 Bogue Street, Rm. A384-E, East Lansing, MI, 48824-1325, USA
| | - Xiaobo Huo
- North China Key Laboratory for Germplasm Resources of Education Ministry, Hebei Agricultural University, Lekai South Street 2596, Baoding, 071001, Hebei Province, China
| | - Shabir H Wani
- Mountain Research Centre for Field Crops, Sher-E-Kashmir University of Agricultural Sciences and Technology of Kashmir, Khudwani, Anantnag, 192101, J&K, India
| | - Cuihua Gu
- Department of Plant, Soil and Microbial Sciences, Michigan State University, 1066 Bogue Street, Rm. A384-E, East Lansing, MI, 48824-1325, USA
| | - Martin I Chilvers
- Department of Plant, Soil and Microbial Sciences, Michigan State University, 1066 Bogue Street, Rm. A384-E, East Lansing, MI, 48824-1325, USA
| | - Dechun Wang
- Department of Plant, Soil and Microbial Sciences, Michigan State University, 1066 Bogue Street, Rm. A384-E, East Lansing, MI, 48824-1325, USA.
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17
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Hohenfeld CS, Passos AR, de Carvalho HWL, de Oliveira SAS, de Oliveira EJ. Genome-wide association study and selection for field resistance to cassava root rot disease and productive traits. PLoS One 2022; 17:e0270020. [PMID: 35709238 PMCID: PMC9202857 DOI: 10.1371/journal.pone.0270020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Accepted: 06/02/2022] [Indexed: 12/04/2022] Open
Abstract
Cassava root rot disease is caused by a complex of soil-borne pathogens and has high economic impacts because it directly affects the tuberous roots, which are the main commercial product. This study aimed to evaluate cassava genotypes for resistance to root rot disease in a field with a previous history of high disease incidence. It also aimed to identify possible genomic regions associated with field resistance based on genome-wide association studies. A total of 148 genotypes from Embrapa Mandioca and Fruticultura were evaluated over two years, including improved materials and curated germplasms. Analysis of phenotypic data was conducted, as well as a genomic association analysis, based on the general linear model, mixed linear model, and fixed and random model circulating probability unification. The observed high disease index (ω) was directly correlated with genotype survival, affecting plant height, shoot yield, and fresh root yield. The genotypes were grouped into five clusters, which were classified according to level of root rot resistance (i.e., extremely susceptible, susceptible, moderately susceptible, moderately resistant, and resistant). The 10 genotypes with the best performance in the field were selected as potential progenitors for the development of segregating progenies. Estimates of genomic kinship between these genotypes ranged from -0.183 to 0.671. The genotypes BGM-1171 and BGM-1190 showed the lowest degree of kinship with the other selected sources of resistance. The genotypes BGM-0209, BGM-0398, and BGM-0659 showed negative kinship values with most elite varieties, while BGM-0659 presented negative kinship with all landraces. A genome-wide association analysis detected five significant single nucleotide polymorphisms related to defense mechanisms against biotic and abiotic stresses, with putative association with fresh root yield in soil infested with root rot pathogens. These findings can be utilized to develop molecular selection for root rot resistance in cassava.
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Zhang M, Lu N, Jiang L, Liu B, Fei Y, Ma W, Shi C, Wang J. Multiple dynamic models reveal the genetic architecture for growth in height of Catalpa bungei in the field. TREE PHYSIOLOGY 2022; 42:1239-1255. [PMID: 34940852 DOI: 10.1093/treephys/tpab171] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Accepted: 12/19/2021] [Indexed: 06/14/2023]
Abstract
Growth in height (GH) is a critical determinant for tree survival and development in forests and can be depicted using logistic growth curves. Our understanding of the genetic mechanism underlying dynamic GH, however, is limited, particularly under field conditions. We applied two mapping models (Funmap and FVTmap) to find quantitative trait loci responsible for dynamic GH and two epistatic models (2HiGWAS and 1HiGWAS) to detect epistasis in Catalpa bungei grown in the field. We identified 13 co-located quantitative trait loci influencing the growth curve by Funmap and three heterochronic parameters (the timing of the inflection point, maximum acceleration and maximum deceleration) by FVTmap. The combined use of FVTmap and Funmap reduced the number of candidate genes by >70%. We detected 76 significant epistatic interactions, amongst which a key gene, COMT14, co-located by three models (but not 1HiGWAS) interacted with three other genes, implying that a novel network of protein interaction centered on COMT14 may control the dynamic GH of C. bungei. These findings provide new insights into the genetic mechanisms underlying the dynamic growth in tree height in natural environments and emphasize the necessity of incorporating multiple dynamic models for screening more reliable candidate genes.
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Affiliation(s)
- Miaomiao Zhang
- State Key Laboratory of Tree Genetics and Breeding, Key Laboratory of Tree Breeding and Cultivation of State Forestry Administration, Research Institute of Forestry, Chinese Academy of Forestry, Beijing 100091, China
| | - Nan Lu
- State Key Laboratory of Tree Genetics and Breeding, Key Laboratory of Tree Breeding and Cultivation of State Forestry Administration, Research Institute of Forestry, Chinese Academy of Forestry, Beijing 100091, China
| | - Libo Jiang
- School of Life Sciences and Medicine, Shandong University of Technology, Zibo 255049, China
| | - Bingyang Liu
- State Key Laboratory of Tree Genetics and Breeding, Key Laboratory of Tree Breeding and Cultivation of State Forestry Administration, Research Institute of Forestry, Chinese Academy of Forestry, Beijing 100091, China
| | - Yue Fei
- State Key Laboratory of Tree Genetics and Breeding, Key Laboratory of Tree Breeding and Cultivation of State Forestry Administration, Research Institute of Forestry, Chinese Academy of Forestry, Beijing 100091, China
| | - Wenjun Ma
- State Key Laboratory of Tree Genetics and Breeding, Key Laboratory of Tree Breeding and Cultivation of State Forestry Administration, Research Institute of Forestry, Chinese Academy of Forestry, Beijing 100091, China
| | - Chaozhong Shi
- State Key Laboratory of Tree Genetics and Breeding, Key Laboratory of Tree Breeding and Cultivation of State Forestry Administration, Research Institute of Forestry, Chinese Academy of Forestry, Beijing 100091, China
| | - Junhui Wang
- State Key Laboratory of Tree Genetics and Breeding, Key Laboratory of Tree Breeding and Cultivation of State Forestry Administration, Research Institute of Forestry, Chinese Academy of Forestry, Beijing 100091, China
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19
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Genetic and Genomic Resources for Soybean Breeding Research. PLANTS 2022; 11:plants11091181. [PMID: 35567182 PMCID: PMC9101001 DOI: 10.3390/plants11091181] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Revised: 04/21/2022] [Accepted: 04/22/2022] [Indexed: 11/17/2022]
Abstract
Soybean (Glycine max) is a legume species of significant economic and nutritional value. The yield of soybean continues to increase with the breeding of improved varieties, and this is likely to continue with the application of advanced genetic and genomic approaches for breeding. Genome technologies continue to advance rapidly, with an increasing number of high-quality genome assemblies becoming available. With accumulating data from marker arrays and whole-genome resequencing, studying variations between individuals and populations is becoming increasingly accessible. Furthermore, the recent development of soybean pangenomes has highlighted the significant structural variation between individuals, together with knowledge of what has been selected for or lost during domestication and breeding, information that can be applied for the breeding of improved cultivars. Because of this, resources such as genome assemblies, SNP datasets, pangenomes and associated databases are becoming increasingly important for research underlying soybean crop improvement.
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20
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Zhang M, Liu S, Wang Z, Yuan Y, Zhang Z, Liang Q, Yang X, Duan Z, Liu Y, Kong F, Liu B, Ren B, Tian Z. Progress in soybean functional genomics over the past decade. PLANT BIOTECHNOLOGY JOURNAL 2022; 20:256-282. [PMID: 34388296 PMCID: PMC8753368 DOI: 10.1111/pbi.13682] [Citation(s) in RCA: 58] [Impact Index Per Article: 29.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/09/2021] [Revised: 08/04/2021] [Accepted: 08/09/2021] [Indexed: 05/24/2023]
Abstract
Soybean is one of the most important oilseed and fodder crops. Benefiting from the efforts of soybean breeders and the development of breeding technology, large number of germplasm has been generated over the last 100 years. Nevertheless, soybean breeding needs to be accelerated to meet the needs of a growing world population, to promote sustainable agriculture and to address future environmental changes. The acceleration is highly reliant on the discoveries in gene functional studies. The release of the reference soybean genome in 2010 has significantly facilitated the advance in soybean functional genomics. Here, we review the research progress in soybean omics (genomics, transcriptomics, epigenomics and proteomics), germplasm development (germplasm resources and databases), gene discovery (genes that are responsible for important soybean traits including yield, flowering and maturity, seed quality, stress resistance, nodulation and domestication) and transformation technology during the past decade. At the end, we also briefly discuss current challenges and future directions.
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Affiliation(s)
- Min Zhang
- State Key Laboratory of Plant Cell and Chromosome EngineeringInstitute of Genetics and Developmental BiologyInnovative Academy for Seed DesignChinese Academy of SciencesBeijingChina
| | - Shulin Liu
- State Key Laboratory of Plant Cell and Chromosome EngineeringInstitute of Genetics and Developmental BiologyInnovative Academy for Seed DesignChinese Academy of SciencesBeijingChina
| | - Zhao Wang
- State Key Laboratory of Plant Cell and Chromosome EngineeringInstitute of Genetics and Developmental BiologyInnovative Academy for Seed DesignChinese Academy of SciencesBeijingChina
- University of Chinese Academy of SciencesBeijingChina
| | - Yaqin Yuan
- State Key Laboratory of Plant Cell and Chromosome EngineeringInstitute of Genetics and Developmental BiologyInnovative Academy for Seed DesignChinese Academy of SciencesBeijingChina
- University of Chinese Academy of SciencesBeijingChina
| | - Zhifang Zhang
- State Key Laboratory of Plant Cell and Chromosome EngineeringInstitute of Genetics and Developmental BiologyInnovative Academy for Seed DesignChinese Academy of SciencesBeijingChina
- University of Chinese Academy of SciencesBeijingChina
| | - Qianjin Liang
- State Key Laboratory of Plant Cell and Chromosome EngineeringInstitute of Genetics and Developmental BiologyInnovative Academy for Seed DesignChinese Academy of SciencesBeijingChina
- University of Chinese Academy of SciencesBeijingChina
| | - Xia Yang
- State Key Laboratory of Plant Cell and Chromosome EngineeringInstitute of Genetics and Developmental BiologyInnovative Academy for Seed DesignChinese Academy of SciencesBeijingChina
- University of Chinese Academy of SciencesBeijingChina
| | - Zongbiao Duan
- State Key Laboratory of Plant Cell and Chromosome EngineeringInstitute of Genetics and Developmental BiologyInnovative Academy for Seed DesignChinese Academy of SciencesBeijingChina
- University of Chinese Academy of SciencesBeijingChina
| | - Yucheng Liu
- State Key Laboratory of Plant Cell and Chromosome EngineeringInstitute of Genetics and Developmental BiologyInnovative Academy for Seed DesignChinese Academy of SciencesBeijingChina
| | - Fanjiang Kong
- Innovative Center of Molecular Genetics and EvolutionSchool of Life SciencesGuangzhou UniversityGuangzhouChina
| | - Baohui Liu
- Innovative Center of Molecular Genetics and EvolutionSchool of Life SciencesGuangzhou UniversityGuangzhouChina
| | - Bo Ren
- State Key Laboratory of Plant GenomicsInstitute of Genetics and Developmental BiologyInnovative Academy for Seed DesignChinese Academy of SciencesBeijingChina
- University of Chinese Academy of SciencesBeijingChina
| | - Zhixi Tian
- State Key Laboratory of Plant Cell and Chromosome EngineeringInstitute of Genetics and Developmental BiologyInnovative Academy for Seed DesignChinese Academy of SciencesBeijingChina
- University of Chinese Academy of SciencesBeijingChina
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21
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Bashyal BM, Rohith M, Parmar P, Darshan K, Sunani SK, Aggarwal R. Biology and Management of Ustilaginoidea virens Causing False Smut Disease of Rice (Oryza sativa L.). Fungal Biol 2022. [DOI: 10.1007/978-981-16-8877-5_2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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22
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Almeida-Silva F, Venancio TM. Integration of genome-wide association studies and gene coexpression networks unveils promising soybean resistance genes against five common fungal pathogens. Sci Rep 2021; 11:24453. [PMID: 34961779 PMCID: PMC8712514 DOI: 10.1038/s41598-021-03864-x] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2021] [Accepted: 12/03/2021] [Indexed: 12/15/2022] Open
Abstract
Soybean is one of the most important legume crops worldwide. However, soybean yield is dramatically affected by fungal diseases, leading to economic losses of billions of dollars yearly. Here, we integrated publicly available genome-wide association studies and transcriptomic data to prioritize candidate genes associated with resistance to Cadophora gregata, Fusarium graminearum, Fusarium virguliforme, Macrophomina phaseolina, and Phakopsora pachyrhizi. We identified 188, 56, 11, 8, and 3 high-confidence candidates for resistance to F. virguliforme, F. graminearum, C. gregata, M. phaseolina and P. pachyrhizi, respectively. The prioritized candidate genes are highly conserved in the pangenome of cultivated soybeans and are heavily biased towards fungal species-specific defense responses. The vast majority of the prioritized candidate resistance genes are related to plant immunity processes, such as recognition, signaling, oxidative stress, systemic acquired resistance, and physical defense. Based on the number of resistance alleles, we selected the five most resistant accessions against each fungal species in the soybean USDA germplasm. Interestingly, the most resistant accessions do not reach the maximum theoretical resistance potential. Hence, they can be further improved to increase resistance in breeding programs or through genetic engineering. Finally, the coexpression network generated here is available in a user-friendly web application ( https://soyfungigcn.venanciogroup.uenf.br/ ) and an R/Shiny package ( https://github.com/almeidasilvaf/SoyFungiGCN ) that serve as a public resource to explore soybean-pathogenic fungi interactions at the transcriptional level.
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Affiliation(s)
- Fabricio Almeida-Silva
- Laboratório de Química e Função de Proteínas e Peptídeos, Centro de Biociências e Biotecnologia, Universidade Estadual do Norte Fluminense Darcy Ribeiro, Av. Alberto Lamego 2000, P5, sala 217, Campos dos Goytacazes, RJ, Brazil.
| | - Thiago M Venancio
- Laboratório de Química e Função de Proteínas e Peptídeos, Centro de Biociências e Biotecnologia, Universidade Estadual do Norte Fluminense Darcy Ribeiro, Av. Alberto Lamego 2000, P5, sala 217, Campos dos Goytacazes, RJ, Brazil.
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23
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Shook JM, Zhang J, Jones SE, Singh A, Diers BW, Singh AK. Meta-GWAS for quantitative trait loci identification in soybean. G3 (BETHESDA, MD.) 2021; 11:jkab117. [PMID: 33856425 PMCID: PMC8495947 DOI: 10.1093/g3journal/jkab117] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/12/2020] [Accepted: 04/02/2021] [Indexed: 01/03/2023]
Abstract
We report a meta-Genome Wide Association Study involving 73 published studies in soybean [Glycine max L. (Merr.)] covering 17,556 unique accessions, with improved statistical power for robust detection of loci associated with a broad range of traits. De novo GWAS and meta-analysis were conducted for composition traits including fatty acid and amino acid composition traits, disease resistance traits, and agronomic traits including seed yield, plant height, stem lodging, seed weight, seed mottling, seed quality, flowering timing, and pod shattering. To examine differences in detectability and test statistical power between single- and multi-environment GWAS, comparison of meta-GWAS results to those from the constituent experiments were performed. Using meta-GWAS analysis and the analysis of individual studies, we report 483 peaks at 393 unique loci. Using stringent criteria to detect significant marker-trait associations, 59 candidate genes were identified, including 17 agronomic traits loci, 19 for seed-related traits, and 33 for disease reaction traits. This study identified potentially valuable candidate genes that affect multiple traits. The success in narrowing down the genomic region for some loci through overlapping mapping results of multiple studies is a promising avenue for community-based studies and plant breeding applications.
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Affiliation(s)
| | - Jiaoping Zhang
- Department of Agronomy, Iowa State University, Ames, IA 50011, USA
| | - Sarah E Jones
- Department of Agronomy, Iowa State University, Ames, IA 50011, USA
| | - Arti Singh
- Department of Agronomy, Iowa State University, Ames, IA 50011, USA
| | - Brian W Diers
- Department of Crop Sciences, University of Illinois, Urbana, IL 61801, USA
| | - Asheesh K Singh
- Department of Agronomy, Iowa State University, Ames, IA 50011, USA
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24
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Baetsen-Young A, Chen H, Shiu SH, Day B. Contrasting transcriptional responses to Fusarium virguliforme colonization in symptomatic and asymptomatic hosts. THE PLANT CELL 2021; 33:224-247. [PMID: 33681966 PMCID: PMC8136916 DOI: 10.1093/plcell/koaa021] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Accepted: 11/06/2020] [Indexed: 06/12/2023]
Abstract
The broad host range of Fusarium virguliforme represents a unique comparative system to identify and define differentially induced responses between an asymptomatic monocot host, maize (Zea mays), and a symptomatic eudicot host, soybean (Glycine max). Using a temporal, comparative transcriptome-based approach, we observed that early gene expression profiles of root tissue from infected maize suggest that pathogen tolerance coincides with the rapid induction of senescence dampening transcriptional regulators, including ANACs (Arabidopsis thaliana NAM/ATAF/CUC protein) and Ethylene-Responsive Factors. In contrast, the expression of senescence-associated processes in soybean was coincident with the appearance of disease symptom development, suggesting pathogen-induced senescence as a key pathway driving pathogen susceptibility in soybean. Based on the analyses described herein, we posit that root senescence is a primary contributing factor underlying colonization and disease progression in symptomatic versus asymptomatic host-fungal interactions. This process also supports the lifestyle and virulence of F. virguliforme during biotrophy to necrotrophy transitions. Further support for this hypothesis lies in comprehensive co-expression and comparative transcriptome analyses, and in total, supports the emerging concept of necrotrophy-activated senescence. We propose that F. virguliforme conditions an environment within symptomatic hosts, which favors susceptibility through transcriptomic reprogramming, and as described herein, the induction of pathways associated with senescence during the necrotrophic stage of fungal development.
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Affiliation(s)
- Amy Baetsen-Young
- Department of Plant, Soil and Microbial Sciences, Michigan State University, East Lansing, MI 48824, USA
| | - Huan Chen
- Plant Resilience Institute, Michigan State University, East Lansing, MI 48824, USA
- Graduate Program in Genetics and Genome Sciences, Michigan State University, East Lansing, MI 48824, USA
- Graduate Program in Molecular Plant Sciences, Michigan State University, East Lansing, MI 48824, USA
| | - Shin-Han Shiu
- Graduate Program in Genetics and Genome Sciences, Michigan State University, East Lansing, MI 48824, USA
- Graduate Program in Molecular Plant Sciences, Michigan State University, East Lansing, MI 48824, USA
- Department of Plant Biology, Michigan State University, East Lansing, MI 48824, USA
- Department of Computational Mathematics, Science, and Engineering, Michigan State University, East Lansing, MI 48824, USA
| | - Brad Day
- Department of Plant, Soil and Microbial Sciences, Michigan State University, East Lansing, MI 48824, USA
- Plant Resilience Institute, Michigan State University, East Lansing, MI 48824, USA
- Graduate Program in Genetics and Genome Sciences, Michigan State University, East Lansing, MI 48824, USA
- Graduate Program in Molecular Plant Sciences, Michigan State University, East Lansing, MI 48824, USA
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25
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Wang A, Jiang Y, Shu X, Zha Z, Yin D, Liu Y, Zhang D, Xu D, Jiao C, Jia X, Ye X, Li S, Deng Q, Wang S, Zhu J, Liang Y, Zou T, Liu H, Wang L, Zhu J, Li P, Zhang Z, Zheng A. Genome-wide association study-based identification genes influencing agronomic traits in rice (Oryza sativa L.). Genomics 2021; 113:1396-1406. [PMID: 33711454 DOI: 10.1016/j.ygeno.2021.03.016] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2020] [Revised: 01/19/2021] [Accepted: 03/07/2021] [Indexed: 11/20/2022]
Abstract
Rice is one of the most important cereal crops, providing the daily dietary intake for approximately 50% of the global human population. Here, we re-sequenced 259 rice accessions, generating 1371.65 Gb of raw data. Furthermore, we performed genome-wide association studies (GWAS) on 13 agronomic traits using 2.8 million single nucleotide polymorphisms (SNPs) characterized in 259 rice accessions. Phenotypic data and best linear unbiased prediction (BLUP) values of each of the 13 traits over two years of each trait were used for the GWAS. The results showed that 816 SNP signals were significantly associated with the 13 agronomic traits. Then we detected candidate genes related to target traits within 200 kb upstream and downstream of the associated SNP loci, based on linkage disequilibrium (LD) blocks in the whole rice genome. These candidate genes were further identified through haplotype block constructions. This comprehensive study provides a timely and important genomic resource for breeding high yielding rice cultivars.
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Affiliation(s)
- Aijun Wang
- College of Agronomy, Sichuan Agricultural University, Chengdu, China; State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Chengdu, China; Rice Research Institute of Sichuan Agricultural University, Chengdu, China
| | - Yuqi Jiang
- College of Agronomy, Sichuan Agricultural University, Chengdu, China; State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Chengdu, China; Rice Research Institute of Sichuan Agricultural University, Chengdu, China
| | - Xinyue Shu
- College of Agronomy, Sichuan Agricultural University, Chengdu, China; State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Chengdu, China; Rice Research Institute of Sichuan Agricultural University, Chengdu, China
| | - Zhongping Zha
- Food Crop Institute, Hubei Academy of Agricultural Sciences, Wuhan, China
| | - Desuo Yin
- Food Crop Institute, Hubei Academy of Agricultural Sciences, Wuhan, China
| | - Yao Liu
- College of Agronomy, Sichuan Agricultural University, Chengdu, China
| | - Danhua Zhang
- College of Agronomy, Sichuan Agricultural University, Chengdu, China
| | - Deze Xu
- Food Crop Institute, Hubei Academy of Agricultural Sciences, Wuhan, China
| | - Chengzhi Jiao
- Novogene Bioinformatics Institute, Beijing 100083, China
| | - Xiaomei Jia
- Rice Research Institute of Sichuan Agricultural University, Chengdu, China
| | - Xiaoying Ye
- Rice Research Institute of Sichuan Agricultural University, Chengdu, China
| | - Shuangcheng Li
- Rice Research Institute of Sichuan Agricultural University, Chengdu, China
| | - Qiming Deng
- Rice Research Institute of Sichuan Agricultural University, Chengdu, China
| | - Shiquan Wang
- Rice Research Institute of Sichuan Agricultural University, Chengdu, China
| | - Jun Zhu
- Rice Research Institute of Sichuan Agricultural University, Chengdu, China
| | - Yueyang Liang
- Rice Research Institute of Sichuan Agricultural University, Chengdu, China
| | - Ting Zou
- Rice Research Institute of Sichuan Agricultural University, Chengdu, China
| | - Huainian Liu
- Rice Research Institute of Sichuan Agricultural University, Chengdu, China
| | - Lingxia Wang
- Rice Research Institute of Sichuan Agricultural University, Chengdu, China
| | - Jianqing Zhu
- Rice Research Institute of Sichuan Agricultural University, Chengdu, China
| | - Ping Li
- Rice Research Institute of Sichuan Agricultural University, Chengdu, China
| | - Zaijun Zhang
- Food Crop Institute, Hubei Academy of Agricultural Sciences, Wuhan, China.
| | - Aiping Zheng
- College of Agronomy, Sichuan Agricultural University, Chengdu, China; State Key Laboratory of Crop Gene Exploration and Utilization in Southwest China, Chengdu, China; Rice Research Institute of Sichuan Agricultural University, Chengdu, China.
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26
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Singh NK, Dutta A, Puccetti G, Croll D. Tackling microbial threats in agriculture with integrative imaging and computational approaches. Comput Struct Biotechnol J 2020; 19:372-383. [PMID: 33489007 PMCID: PMC7787954 DOI: 10.1016/j.csbj.2020.12.018] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Revised: 12/08/2020] [Accepted: 12/13/2020] [Indexed: 11/29/2022] Open
Abstract
Pathogens and pests are one of the major threats to agricultural productivity worldwide. For decades, targeted resistance breeding was used to create crop cultivars that resist pathogens and environmental stress while retaining yields. The often decade-long process of crossing, selection, and field trials to create a new cultivar is challenged by the rapid rise of pathogens overcoming resistance. Similarly, antimicrobial compounds can rapidly lose efficacy due to resistance evolution. Here, we review three major areas where computational, imaging and experimental approaches are revolutionizing the management of pathogen damage on crops. Recognizing and scoring plant diseases have dramatically improved through high-throughput imaging techniques applicable both under well-controlled greenhouse conditions and directly in the field. However, computer vision of complex disease phenotypes will require significant improvements. In parallel, experimental setups similar to high-throughput drug discovery screens make it possible to screen thousands of pathogen strains for variation in resistance and other relevant phenotypic traits. Confocal microscopy and fluorescence can capture rich phenotypic information across pathogen genotypes. Through genome-wide association mapping approaches, phenotypic data helps to unravel the genetic architecture of stress- and virulence-related traits accelerating resistance breeding. Finally, joint, large-scale screenings of trait variation in crops and pathogens can yield fundamental insights into how pathogens face trade-offs in the adaptation to resistant crop varieties. We discuss how future implementations of such innovative approaches in breeding and pathogen screening can lead to more durable disease control.
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Affiliation(s)
- Nikhil Kumar Singh
- Laboratory of Evolutionary Genetics, Institute of Biology, University of Neuchâtel, CH-2000 Neuchâtel, Switzerland
| | - Anik Dutta
- Laboratory of Evolutionary Genetics, Institute of Biology, University of Neuchâtel, CH-2000 Neuchâtel, Switzerland
- Plant Pathology, Institute of Integrative Biology, ETH Zurich, CH-8092 Zurich, Switzerland
| | - Guido Puccetti
- Laboratory of Evolutionary Genetics, Institute of Biology, University of Neuchâtel, CH-2000 Neuchâtel, Switzerland
- Syngenta Crop Protection AG, CH-4332 Stein, Switzerland
| | - Daniel Croll
- Laboratory of Evolutionary Genetics, Institute of Biology, University of Neuchâtel, CH-2000 Neuchâtel, Switzerland
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27
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Tong H, Madison I, Long TA, Williams CM. Computational solutions for modeling and controlling plant response to abiotic stresses: a review with focus on iron deficiency. CURRENT OPINION IN PLANT BIOLOGY 2020; 57:8-15. [PMID: 32619968 DOI: 10.1016/j.pbi.2020.05.006] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/30/2020] [Revised: 05/15/2020] [Accepted: 05/23/2020] [Indexed: 06/11/2023]
Abstract
Computational solutions enable plant scientists to model protein-mediated stress responses and characterize novel gene functions that coordinate responses to a variety of abiotic stress conditions. Recently, density functional theory was used to study proteins active sites and elucidate enzyme conversion mechanisms involved in iron deficiency responsive signaling pathways. Computational approaches for protein homology modeling and the kinetic modeling of signaling pathways have also resolved the identity and function in proteins involved in iron deficiency signaling pathways. Significant changes in gene relationships under other stress conditions, such as heat or drought stress, have been recently identified using differential network analysis, suggesting that stress tolerance is achieved through asynchronous control. Moreover, the increasing development and use of statistical modeling and systematic modeling of transcriptomic data have provided significant insight into the gene regulatory mechanisms associated with abiotic stress responses. These types of in silico approaches have facilitated the plant science community's future goals of developing multi-scale models of responses to iron deficiency stress and other abiotic stress conditions.
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Affiliation(s)
- Haonan Tong
- Electrical and Computer Engineering, North Carolina State University, Raleigh, USA
| | - Imani Madison
- Plant and Microbial Biology, North Carolina State University, Raleigh, USA
| | - Terri A Long
- Plant and Microbial Biology, North Carolina State University, Raleigh, USA.
| | - Cranos M Williams
- Electrical and Computer Engineering, North Carolina State University, Raleigh, USA.
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28
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Falk KG, Jubery TZ, O'Rourke JA, Singh A, Sarkar S, Ganapathysubramanian B, Singh AK. Soybean Root System Architecture Trait Study through Genotypic, Phenotypic, and Shape-Based Clusters. PLANT PHENOMICS (WASHINGTON, D.C.) 2020; 2020:1925495. [PMID: 33313543 PMCID: PMC7706349 DOI: 10.34133/2020/1925495] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/24/2019] [Accepted: 04/16/2020] [Indexed: 05/24/2023]
Abstract
We report a root system architecture (RSA) traits examination of a larger scale soybean accession set to study trait genetic diversity. Suffering from the limitation of scale, scope, and susceptibility to measurement variation, RSA traits are tedious to phenotype. Combining 35,448 SNPs with an imaging phenotyping platform, 292 accessions (replications = 14) were studied for RSA traits to decipher the genetic diversity. Based on literature search for root shape and morphology parameters, we used an ideotype-based approach to develop informative root (iRoot) categories using root traits. The RSA traits displayed genetic variability for root shape, length, number, mass, and angle. Soybean accessions clustered into eight genotype- and phenotype-based clusters and displayed similarity. Genotype-based clusters correlated with geographical origins. SNP profiles indicated that much of US origin genotypes lack genetic diversity for RSA traits, while diverse accession could infuse useful genetic variation for these traits. Shape-based clusters were created by integrating convolution neural net and Fourier transformation methods, enabling trait cataloging for breeding and research applications. The combination of genetic and phenotypic analyses in conjunction with machine learning and mathematical models provides opportunities for targeted root trait breeding efforts to maximize the beneficial genetic diversity for future genetic gains.
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Affiliation(s)
- Kevin G. Falk
- Department of Agronomy, Iowa State University, Ames, Iowa, USA
| | | | - Jamie A. O'Rourke
- Department of Agronomy, Iowa State University, Ames, Iowa, USA
- USDA-Agricultural Research Service, Corn Insects and Crop Genetics Research Unit, Ames, Iowa, USA
| | - Arti Singh
- Department of Agronomy, Iowa State University, Ames, Iowa, USA
| | - Soumik Sarkar
- Department of Mechanical Engineering, Iowa State University, Ames, Iowa, USA
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Kofsky J, Zhang H, Song BH. Genetic Architecture of Early Vigor Traits in Wild Soybean. Int J Mol Sci 2020; 21:E3105. [PMID: 32354037 PMCID: PMC7247153 DOI: 10.3390/ijms21093105] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2020] [Accepted: 04/24/2020] [Indexed: 01/13/2023] Open
Abstract
A worldwide food shortage has been projected as a result of the current increase in global population and climate change. In order to provide sufficient food to feed more people, we must develop crops that can produce higher yields. Plant early vigor traits, early growth rate (EGR), early plant height (EPH), inter-node length, and node count are important traits that are related to crop yield. Glycine soja, the wild counterpart to cultivated soybean, Glycine max, harbors much higher genetic diversity and can grow in diverse environments. It can also cross easily with cultivated soybean. Thus, it holds a great potential in developing soybean cultivars with beneficial agronomic traits. In this study, we used 225 wild soybean accessions originally from diverse environments across its geographic distribution in East Asia. We quantified the natural variation of several early vigor traits, investigated the relationships among them, and dissected the genetic basis of these traits by applying a Genome-Wide Association Study (GWAS) with genome-wide single nucleotide polymorphism (SNP) data. Our results showed positive correlation between all early vigor traits studied. A total of 12 SNPs significantly associated with EPH were identified with 4 shared with EGR. We also identified two candidate genes, Glyma.07G055800.1 and Glyma.07G055900.1, playing important roles in influencing trait variation in both EGR and EPH in G. soja.
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Affiliation(s)
| | | | - Bao-Hua Song
- Department of Biological Sciences, University of North Carolina at Charlotte, Charlotte, NC 28223, USA; (J.K.); (H.Z.)
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Chang HX, Wen Z, Tan R, Dong H, Wickland DP, Wang D, Chilvers MI. Linkage Mapping for Foliar Necrosis of Soybean Sudden Death Syndrome. PHYTOPATHOLOGY 2020; 110:907-915. [PMID: 31821112 DOI: 10.1094/phyto-09-19-0330-r] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Sudden death syndrome (SDS) foliar symptoms consist of foliar chlorosis, foliar necrosis, leaf marginal curling, and premature defoliation, but resistance screening has been evaluated mostly based on the overall SDS foliar severity rather than on a specific foliar symptom. This study generated an F2 population derived from crossing the susceptible variety Sloan and the resistant germplasm line PI 243518, which exhibits resistance to both foliar chlorosis and necrosis. A total of 400 F2 lines were evaluated for foliar chlorosis, foliar necrosis, and overall SDS foliar symptoms, separately. Genotyping-by-sequencing was applied to obtain single nucleotide polymorphisms (SNPs) in the F2 population, and linkage mapping using 135 F2 lines with 969 high-quality SNPs identified a locus on chromosome 13 for foliar necrosis and SDS foliar symptoms. The locus partially overlaps with loci previously reported for SDS on chromosome 13, which is the third time the region from 15.98 to 21.00 Mbp has been reproduced independently and therefore qualifies this locus for a new nomenclature proposed as Rfv13-02. In summary, this study generated a new biparental population that enables not only the discovery of a locus for foliar necrosis and SDS foliar symptoms on chromosome 13 but also the potential for advanced exploration of SDS foliar resistance derived from the germplasm line PI 243518.
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Affiliation(s)
- Hao-Xun Chang
- Department of Plant Pathology and Microbiology, National Taiwan University, Taipei 10617, Taiwan
| | - Zixiang Wen
- Department of Plant, Soil and Microbial Sciences, Michigan State University, East Lansing, MI 48823, U.S.A
| | - Ruijuan Tan
- Department of Plant, Soil and Microbial Sciences, Michigan State University, East Lansing, MI 48823, U.S.A
| | - Hongxu Dong
- Plant Genome Mapping Laboratory, University of Georgia, Athens, GA 30605, U.S.A
| | - Daniel P Wickland
- Department of Health Sciences Research, Mayo Clinic, Jacksonville, FL 32224, U.S.A
| | - Dechun Wang
- Department of Plant, Soil and Microbial Sciences, Michigan State University, East Lansing, MI 48823, U.S.A
| | - Martin I Chilvers
- Department of Plant, Soil and Microbial Sciences, Michigan State University, East Lansing, MI 48823, U.S.A
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Zhang J, Singh AK. Genetic Control and Geo-Climate Adaptation of Pod Dehiscence Provide Novel Insights into Soybean Domestication. G3 (BETHESDA, MD.) 2020; 10:545-554. [PMID: 31836621 PMCID: PMC7003073 DOI: 10.1534/g3.119.400876] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/12/2019] [Accepted: 11/29/2019] [Indexed: 01/20/2023]
Abstract
Loss of pod dehiscence was a key step in soybean [Glycine max (L.) Merr.] domestication. Genome-wide association analysis for soybean shattering identified loci harboring Pdh1, NST1A and SHAT1-5 Pairwise epistatic interactions were observed, and the dehiscent Pdh1 overcomes resistance conferred by NST1A or SHAT1-5 locus. Further candidate gene association analysis identified a nonsense mutation in NST1A associated with pod dehiscence. Geographic analysis showed that in Northeast China (NEC), indehiscence at both Pdh1 and NST1A were required in cultivated soybean, while indehiscent Pdh1 alone is capable of preventing shattering in Huang-Huai-Hai (HHH) valleys. Indehiscent Pdh1 allele was only identified in wild soybean (Glycine soja L.) accession from HHH valleys suggesting that it may have originated in this region. No specific indehiscence was required in Southern China. Geo-climatic investigation revealed strong correlation between relative humidity and frequency of indehiscent Pdh1 across China. This study demonstrates that epistatic interaction between Pdh1 and NST1A fulfills a pivotal role in determining the level of resistance against pod dehiscence, and humidity shapes the distribution of indehiscent alleles. Our results give further evidence to the hypothesis that HHH valleys was at least one of the origin centers of cultivated soybean.
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Affiliation(s)
- Jiaoping Zhang
- Department of Agronomy, Iowa State University, Ames, IA 50011
| | - Asheesh K Singh
- Department of Agronomy, Iowa State University, Ames, IA 50011
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Assefa T, Zhang J, Chowda-Reddy RV, Moran Lauter AN, Singh A, O’Rourke JA, Graham MA, Singh AK. Deconstructing the genetic architecture of iron deficiency chlorosis in soybean using genome-wide approaches. BMC PLANT BIOLOGY 2020; 20:42. [PMID: 31992198 PMCID: PMC6988307 DOI: 10.1186/s12870-020-2237-5] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/18/2019] [Accepted: 01/03/2020] [Indexed: 05/09/2023]
Abstract
BACKGROUND Iron (Fe) is an essential micronutrient for plant growth and development. Iron deficiency chlorosis (IDC), caused by calcareous soils or high soil pH, can limit iron availability, negatively affecting soybean (Glycine max) yield. This study leverages genome-wide association study (GWAS) and a genome-wide epistatic study (GWES) with previous gene expression studies to identify regions of the soybean genome important in iron deficiency tolerance. RESULTS A GWAS and a GWES were performed using 460 diverse soybean PI lines from 27 countries, in field and hydroponic iron stress conditions, using more than 36,000 single nucleotide polymorphism (SNP) markers. Combining this approach with available RNA-sequencing data identified significant markers, genomic regions, and novel genes associated with or responding to iron deficiency. Sixty-nine genomic regions associated with IDC tolerance were identified across 19 chromosomes via the GWAS, including the major-effect quantitative trait locus (QTL) on chromosome Gm03. Cluster analysis of significant SNPs in this region deconstructed this historically prominent QTL into four distinct linkage blocks, enabling the identification of multiple candidate genes for iron chlorosis tolerance. The complementary GWES identified SNPs in this region interacting with nine other genomic regions, providing the first evidence of epistatic interactions impacting iron deficiency tolerance. CONCLUSIONS This study demonstrates that integrating cutting edge genome wide association (GWA), genome wide epistasis (GWE), and gene expression studies is a powerful strategy to identify novel iron tolerance QTL and candidate loci from diverse germplasm. Crops, unlike model species, have undergone selection for thousands of years, constraining and/or enhancing stress responses. Leveraging genomics-enabled approaches to study these adaptations is essential for future crop improvement.
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Affiliation(s)
- Teshale Assefa
- Department of Agronomy, Iowa State University, Ames, IA USA
| | - Jiaoping Zhang
- Department of Agronomy, Iowa State University, Ames, IA USA
| | | | - Adrienne N. Moran Lauter
- United States Department of Agriculture, Agricultural Research Service, Corn Insects and Crop Genetics Research Unit and Department of Agronomy, Iowa State University, Ames, IA USA
| | - Arti Singh
- Department of Agronomy, Iowa State University, Ames, IA USA
| | - Jamie A. O’Rourke
- United States Department of Agriculture, Agricultural Research Service, Corn Insects and Crop Genetics Research Unit and Department of Agronomy, Iowa State University, Ames, IA USA
| | - Michelle A. Graham
- United States Department of Agriculture, Agricultural Research Service, Corn Insects and Crop Genetics Research Unit and Department of Agronomy, Iowa State University, Ames, IA USA
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Kim KH, Kim JY, Lim WJ, Jeong S, Lee HY, Cho Y, Moon JK, Kim N. Genome-wide association and epistatic interactions of flowering time in soybean cultivar. PLoS One 2020; 15:e0228114. [PMID: 31968016 PMCID: PMC6975553 DOI: 10.1371/journal.pone.0228114] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2019] [Accepted: 01/07/2020] [Indexed: 12/02/2022] Open
Abstract
Genome-wide association studies (GWAS) have enabled the discovery of candidate markers that play significant roles in various complex traits in plants. Recently, with increased interest in the search for candidate markers, studies on epistatic interactions between single nucleotide polymorphism (SNP) markers have also increased, thus enabling the identification of more candidate markers along with GWAS on single-variant-additive-effect. Here, we focused on the identification of candidate markers associated with flowering time in soybean (Glycine max). A large population of 2,662 cultivated soybean accessions was genotyped using the 180k Axiom® SoyaSNP array, and the genomic architecture of these accessions was investigated to confirm the population structure. Then, GWAS was conducted to evaluate the association between SNP markers and flowering time. A total of 93 significant SNP markers were detected within 59 significant genes, including E1 and E3, which are the main determinants of flowering time. Based on the GWAS results, multilocus epistatic interactions were examined between the significant and non-significant SNP markers. Two significant and 16 non-significant SNP markers were discovered as candidate markers affecting flowering time via interactions with each other. These 18 candidate SNP markers mapped to 18 candidate genes including E1 and E3, and the 18 candidate genes were involved in six major flowering pathways. Although further biological validation is needed, our results provide additional information on the existing flowering time markers and present another option to marker-assisted breeding programs for regulating flowering time of soybean.
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Affiliation(s)
- Kyoung Hyoun Kim
- Genome Editing Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon, Republic of Korea
- Department of Bioinformatics, KRIBB School of Bioscience, University of Science and Technology (UST), Daejeon, Republic of Korea
| | - Jae-Yoon Kim
- Genome Editing Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon, Republic of Korea
- Department of Bioinformatics, KRIBB School of Bioscience, University of Science and Technology (UST), Daejeon, Republic of Korea
| | - Won-Jun Lim
- Genome Editing Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon, Republic of Korea
- Department of Bioinformatics, KRIBB School of Bioscience, University of Science and Technology (UST), Daejeon, Republic of Korea
| | - Seongmun Jeong
- Genome Editing Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon, Republic of Korea
| | - Ho-Yeon Lee
- Genome Editing Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon, Republic of Korea
- Department of Bioinformatics, KRIBB School of Bioscience, University of Science and Technology (UST), Daejeon, Republic of Korea
| | - Youngbum Cho
- Genome Editing Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon, Republic of Korea
- Department of Bioinformatics, KRIBB School of Bioscience, University of Science and Technology (UST), Daejeon, Republic of Korea
| | - Jung-Kyung Moon
- National Institute of Agricultural Sciences, Rural Development Administration, Jeonju, Republic of Korea
| | - Namshin Kim
- Genome Editing Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon, Republic of Korea
- Department of Bioinformatics, KRIBB School of Bioscience, University of Science and Technology (UST), Daejeon, Republic of Korea
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Liu Q, Hobbs HA, Domier LL. Genome-wide association study of the seed transmission rate of soybean mosaic virus and associated traits using two diverse population panels. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2019; 132:3413-3424. [PMID: 31630210 DOI: 10.1007/s00122-019-03434-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/10/2019] [Accepted: 09/17/2019] [Indexed: 06/10/2023]
Abstract
KEY MESSAGE Genome-wide association analyses identified candidates for genes involved in restricting virus movement into embryonic tissues, suppressing virus-induced seed coat mottling and preserving yield in soybean plants infected with soybean mosaic virus. Soybean mosaic virus (SMV) causes significant reductions in soybean yield and seed quality. Because seedborne infections can serve as primary sources of inoculum for SMV infections, resistance to SMV seed transmission provides a means to limit the impacts of SMV. In this study, two diverse population panels, Pop1 and Pop2, composed of 409 and 199 soybean plant introductions, respectively, were evaluated for SMV seed transmission rate, seed coat mottling, and seed yield from SMV-infected plants. The phenotypic data and genotypic data from the SoySNP50K dataset were analyzed using GAPIT and rrBLUP. For SMV seed transmission rate, a single locus was identified on chromosome 9 in Pop1. For SMV-induced seed coat mottling, loci were identified on chromosome 9 in Pop1 and on chromosome 3 in Pop2. For seed yield from SMV-infected plants, a single locus was identified on chromosome 3 in Pop2 that was within the map interval of a previously described quantitative trait locus for seed number. The high linkage disequilibrium regions surrounding the markers on chromosomes 3 and 9 contained a predicted nonsense-mediated RNA decay gene, multiple pectin methylesterase inhibitor genes (involved in restricting virus movement), two chalcone synthase genes, and a homolog of the yeast Rtf1 gene (involved in RNA-mediated transcriptional gene silencing). The results of this study provided additional insight into the genetic architecture of these three important traits, suggested candidate genes for downstream functional validation, and suggested that genomic prediction would outperform marker-assisted selection for two of the four trait-marker associations.
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Affiliation(s)
- Qiong Liu
- Department of Crop Sciences, University of Illinois, Urbana, IL, 61801, USA
| | - Houston A Hobbs
- Department of Crop Sciences, University of Illinois, Urbana, IL, 61801, USA
| | - Leslie L Domier
- Soybean/Maize Germplasm, Pathology, and Genetics Research Unit, United States Department of Agriculture-Agricultural Research Service, Urbana, IL, 61801, USA.
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Zhang L, Huang W, Peng D, Liu S. Comparative genomic analyses of two segregating mutants reveal seven genes likely involved in resistance to Fusarium equiseti in soybean via whole genome re-sequencing. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2019; 132:2997-3008. [PMID: 31338526 DOI: 10.1007/s00122-019-03401-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/03/2019] [Accepted: 07/11/2019] [Indexed: 06/10/2023]
Abstract
KEY MESSAGE The candidate genes involved in resistance to Fusarium equiseti in soybean PI 437654 were identified through comparative genomic analyses of mutants via whole genome re-sequencing. The fungus Fusarium infects each stage of the growth and development of soybean and causes soybean (Glycine max (L.)) seed and root rot and seedling damping-off and wilt with a large quantity of annual yield loss worldwide. It is very important to identify the resistant genes in soybean to prevent and control this pathogen. One Fusarium equiseti isolate was previously identified to be incompatible with 'PI 437654' but compatible with a Chinese soybean cultivar 'Zhonghuang 13'. In this study, with the infection of this isolate on the seedling roots of developed PI 437654 mutants, 6 mutants were identified from 500 mutants to significantly alter their phenotypes to F. equiseti compared to wild-type PI 437654. Then, two identified segregating mutants were selected to directly perform whole genome re-sequencing. Finally, through comparative genomic analyses 7 genes including one cluster of 4 nucleotide binding site-leucine-rich repeat genes on one genomic region of chromosome 7, a 60S ribosomal protein L12 gene and 2 uncharacterized genes were identified to be likely involved in the resistance to F. equiseti. These genes will facilitate the breeding of resistant germplasm resources and the identification of resistance of soybean to Fusarium spp.
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Affiliation(s)
- Liuping Zhang
- State Key Laboratory for Biology of Plant Diseases and Insect Pests, Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing, 100193, People's Republic of China
| | - Wenkun Huang
- State Key Laboratory for Biology of Plant Diseases and Insect Pests, Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing, 100193, People's Republic of China
| | - Deliang Peng
- State Key Laboratory for Biology of Plant Diseases and Insect Pests, Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing, 100193, People's Republic of China
| | - Shiming Liu
- State Key Laboratory for Biology of Plant Diseases and Insect Pests, Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing, 100193, People's Republic of China.
- College of Plant Protection, Hunan Agricultural University, Changsha, 410128, People's Republic of China.
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Nagasubramanian K, Jones S, Singh AK, Sarkar S, Singh A, Ganapathysubramanian B. Plant disease identification using explainable 3D deep learning on hyperspectral images. PLANT METHODS 2019; 15:98. [PMID: 31452674 PMCID: PMC6702735 DOI: 10.1186/s13007-019-0479-8] [Citation(s) in RCA: 81] [Impact Index Per Article: 16.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/26/2019] [Accepted: 08/06/2019] [Indexed: 05/20/2023]
Abstract
BACKGROUND Hyperspectral imaging is emerging as a promising approach for plant disease identification. The large and possibly redundant information contained in hyperspectral data cubes makes deep learning based identification of plant diseases a natural fit. Here, we deploy a novel 3D deep convolutional neural network (DCNN) that directly assimilates the hyperspectral data. Furthermore, we interrogate the learnt model to produce physiologically meaningful explanations. We focus on an economically important disease, charcoal rot, which is a soil borne fungal disease that affects the yield of soybean crops worldwide. RESULTS Based on hyperspectral imaging of inoculated and mock-inoculated stem images, our 3D DCNN has a classification accuracy of 95.73% and an infected class F1 score of 0.87. Using the concept of a saliency map, we visualize the most sensitive pixel locations, and show that the spatial regions with visible disease symptoms are overwhelmingly chosen by the model for classification. We also find that the most sensitive wavelengths used by the model for classification are in the near infrared region (NIR), which is also the commonly used spectral range for determining the vegetative health of a plant. CONCLUSION The use of an explainable deep learning model not only provides high accuracy, but also provides physiological insight into model predictions, thus generating confidence in model predictions. These explained predictions lend themselves for eventual use in precision agriculture and research application using automated phenotyping platforms.
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Affiliation(s)
| | - Sarah Jones
- Department of Agronomy, Iowa State University, Ames, IA USA
| | - Asheesh K. Singh
- Department of Agronomy, Iowa State University, Ames, IA USA
- Plant Sciences Institute, Iowa State University, Ames, IA USA
| | - Soumik Sarkar
- Department of Mechanical Engineering, Iowa State University, Ames, IA USA
- Plant Sciences Institute, Iowa State University, Ames, IA USA
- Department of Computer Science, Iowa State University, Ames, IA USA
| | - Arti Singh
- Department of Agronomy, Iowa State University, Ames, IA USA
| | - Baskar Ganapathysubramanian
- Department of Electrical and Computer Engineering, Iowa State University, Ames, IA USA
- Department of Mechanical Engineering, Iowa State University, Ames, IA USA
- Plant Sciences Institute, Iowa State University, Ames, IA USA
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Assefa T, Otyama PI, Brown AV, Kalberer SR, Kulkarni RS, Cannon SB. Genome-wide associations and epistatic interactions for internode number, plant height, seed weight and seed yield in soybean. BMC Genomics 2019; 20:527. [PMID: 31242867 PMCID: PMC6595607 DOI: 10.1186/s12864-019-5907-7] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2019] [Accepted: 06/17/2019] [Indexed: 01/29/2023] Open
Abstract
BACKGROUND Breeding programs benefit from information about marker-trait associations for many traits, whether the goal is to place those traits under active selection or to maintain them through background selection. Association studies are also important for identifying accessions bearing potentially useful alleles by characterizing marker-trait associations and allelic states across germplasm collections. This study reports the results of a genome-wide association study and evaluation of epistatic interactions for four agronomic and seed-related traits in soybean. RESULTS Using 419 diverse soybean accessions, together with genotyping data from the SoySNP50K Illumina Infinium BeadChip, we identified marker-trait associations for internode number (IN), plant height (PH), seed weight (SW), and seed yield per plant (SYP). We conducted a genome-wide epistatic study (GWES), identifying candidate genes that show evidence of SNP-SNP interactions. Although these candidate genes will require further experimental validation, several appear to be involved in developmental processes related to the respective traits. For IN and PH, these include the Dt1 determinacy locus (a soybean meristematic transcription factor), as well as a pectinesterase gene and a squamosa promoter binding gene that in other plants are involved in cell elongation and the vegetative-to-reproductive transition, respectively. For SW, candidate genes include an ortholog of the AP2 gene, which in other species is involved in maintaining seed size, embryo size, seed weight and seed yield. Another SW candidate gene is a histidine phosphotransfer protein - orthologs of which are involved in cytokinin-mediated seed weight regulating pathways. The SYP association loci overlap with regions reported in previous QTL studies to be involved in seed yield. CONCLUSIONS This study further confirms the utility of GWAS and GWES approaches for identifying marker-trait associations and interactions within a diverse germplasm collection.
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Affiliation(s)
- Teshale Assefa
- ORISE Fellow, USDA-ARS, Corn Insects and Crop Genetics Research Unit, Ames, Iowa USA
| | - Paul I. Otyama
- Agronomy Department, Iowa State University, Ames, IA USA
| | - Anne V. Brown
- USDA-ARS, Corn Insects and Crop Genetics Research Unit, Ames, Iowa USA
| | - Scott R. Kalberer
- USDA-ARS, Corn Insects and Crop Genetics Research Unit, Ames, Iowa USA
| | | | - Steven B. Cannon
- USDA-ARS, Corn Insects and Crop Genetics Research Unit, Ames, Iowa USA
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Miao C, Yang J, Schnable JC. Optimising the identification of causal variants across varying genetic architectures in crops. PLANT BIOTECHNOLOGY JOURNAL 2019; 17:893-905. [PMID: 30320953 PMCID: PMC6587547 DOI: 10.1111/pbi.13023] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/28/2018] [Revised: 09/28/2018] [Accepted: 10/10/2018] [Indexed: 05/11/2023]
Abstract
Association studies use statistical links between genetic markers and the phenotype variation across many individuals to identify genes controlling variation in the target phenotype. However, this approach, particularly conducted on a genome-wide scale (GWAS), has limited power to identify the genes responsible for variation in traits controlled by complex genetic architectures. In this study, we employ real-world genotype datasets from four crop species with distinct minor allele frequency distributions, population structures and linkage disequilibrium patterns. We demonstrate that different GWAS statistical approaches provide favourable trade-offs between power and accuracy for traits controlled by different types of genetic architectures. FarmCPU provides the most favourable outcomes for moderately complex traits while a Bayesian approach adopted from genomic prediction provides the most favourable outcomes for extremely complex traits. We assert that by estimating the complexity of genetic architectures for target traits and selecting an appropriate statistical approach for the degree of complexity detected, researchers can substantially improve the ability to dissect the genetic factors controlling complex traits such as flowering time, plant height and yield component.
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Affiliation(s)
- Chenyong Miao
- Department of Agronomy and HorticultureUniversity of Nebraska‐LincolnLincolnNEUSA
- Center for Plant Science InnovationUniversity of Nebraska‐LincolnLincolnNEUSA
| | - Jinliang Yang
- Department of Agronomy and HorticultureUniversity of Nebraska‐LincolnLincolnNEUSA
- Center for Plant Science InnovationUniversity of Nebraska‐LincolnLincolnNEUSA
| | - James C. Schnable
- Department of Agronomy and HorticultureUniversity of Nebraska‐LincolnLincolnNEUSA
- Center for Plant Science InnovationUniversity of Nebraska‐LincolnLincolnNEUSA
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Do TD, Vuong TD, Dunn D, Clubb M, Valliyodan B, Patil G, Chen P, Xu D, Nguyen HT, Shannon JG. Identification of new loci for salt tolerance in soybean by high-resolution genome-wide association mapping. BMC Genomics 2019; 20:318. [PMID: 31023240 PMCID: PMC6485111 DOI: 10.1186/s12864-019-5662-9] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2018] [Accepted: 03/31/2019] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Salinity is an abiotic stress that negatively affects soybean [Glycine max (L.) Merr.] seed yield. Although a major gene for salt tolerance was identified and consistently mapped to chromosome (Chr.) 3 by linkage mapping studies, it does not fully explain genetic variability for tolerance in soybean germplasm. In this study, a genome-wide association study (GWAS) was performed to map genomic regions for salt tolerance in a diverse panel of 305 soybean accessions using a single nucleotide polymorphism (SNP) dataset derived from the SoySNP50K iSelect BeadChip. A second GWAS was also conducted in a subset of 234 accessions using another 3.7 M SNP dataset derived from a whole-genome resequencing (WGRS) study. In addition, three gene-based markers (GBM) of the known gene, Glyma03g32900, on Chr. 3 were also integrated into the two datasets. Salt tolerance among soybean lines was evaluated by leaf scorch score (LSS), chlorophyll content ratio (CCR), leaf sodium content (LSC), and leaf chloride content (LCC). RESULTS For both association studies, a major locus for salt tolerance on Chr. 3 was confirmed by a number of significant SNPs, of which three gene-based SNP markers, Salt-20, Salt14056 and Salt11655, had the highest association with all four traits studied. Also, additional genomic regions on Chrs. 1, 8, and 18 were found to be associated with various traits measured in the second GWAS using the WGRS-derived SNP dataset. CONCLUSIONS A region identified on Chr. 8 was identified to be associated with all four traits and predicted as a new minor locus for salt tolerance in soybean. The candidate genes harbored in this minor locus may help reveal the molecular mechanism involved in salt tolerance and to improve tolerance in soybean cultivars. The significant SNPs will be useful for marker-assisted selection for salt tolerance in soybean breeding programs.
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Affiliation(s)
- Tuyen D. Do
- Division of Plant Sciences, University of Missouri, Columbia, MO 65211 USA
- Present address: The Cuu Long Delta Rice Research Institute, Thoi Lai District, Can Tho City, Vietnam
| | - Tri D. Vuong
- Division of Plant Sciences, University of Missouri, Columbia, MO 65211 USA
| | - David Dunn
- Division of Plant Sciences, University of Missouri, Portageville, MO 63873 USA
| | - Michael Clubb
- Division of Plant Sciences, University of Missouri, Portageville, MO 63873 USA
| | - Babu Valliyodan
- Division of Plant Sciences, University of Missouri, Columbia, MO 65211 USA
| | - Gunvant Patil
- Division of Plant Sciences, University of Missouri, Columbia, MO 65211 USA
- Present Address: Department Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN 55108 USA
| | - Pengyin Chen
- Division of Plant Sciences, University of Missouri, Portageville, MO 63873 USA
| | - Dong Xu
- Department of Electric Engineering and Computer Science, Christopher S. Bond Life Sciences Center, University of Missouri, Columbia, MO 65211 USA
| | - Henry T. Nguyen
- Division of Plant Sciences, University of Missouri, Columbia, MO 65211 USA
| | - J. Grover Shannon
- Division of Plant Sciences, University of Missouri, Portageville, MO 63873 USA
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Uthup TK, Rajamani A, Ravindran M, Saha T. Distinguishing CPT gene family members and vetting the sequence structure of a putative rubber synthesizing variant in Hevea brasiliensis. Gene 2019; 689:183-193. [PMID: 30528269 DOI: 10.1016/j.gene.2018.12.001] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2018] [Revised: 11/21/2018] [Accepted: 12/01/2018] [Indexed: 11/19/2022]
Abstract
cis-Prenyltransferases (cis-PTs) constitute a large family of enzymes conserved during evolution and present in all domains of life. cis-PTs catalyze the cis-1,4-polymerization of isoprene units to generate isoprenoids with carbon skeletons varying from C10 (neryl pyrophosphate) to C > 10,000 (natural rubber). Though the previously reported CPTs in Hevea are designated based on sequence variations, their classification was done mostly by phylogenetic analysis using a mixture of partial as well as full length sequences often excluding the UTRs. In this context an attempt was made to reclassify the CPTs strictly based on their sequence similarity and distinguish the members putatively associated with rubber biosynthesis from the others. Extensive computational analysis was carried out on CPT sequences obtained from public resources and whole genome assemblies of Hevea. Based on the results from BLAST analysis, multiple sequence alignments of protein, nucleotide and untranslated regions, open reading frame analysis, gene prediction analysis and sequence length variations, we conclude that there exists mainly three CPTs namely RubCPT1, RubCPT2 and RubCPT3 putatively associated with rubber biosynthesis in Hevea brasiliensis. The rest were categorised as variants of dehydrodolichyl diphosphate synthase (DHDDS) involved in the synthesis of dolichols having short chain isoprenoids. Analysis of the sequence structure of the most highly expressed RubCPT1 in latex revealed the allele richness and diversity of this important variant prevailing in the popular rubber clones. Haplotypes consisting of SNPs with high degree of heterozygosity were also identified. Segregation and linkage disequilibrium analysis confirmed that recombination is the major contributor towards the generation of allelic diversity rather than point mutations. Alternatively, gene expression analysis indicated the possibility of association between specific haplotypes and RubCPT1 expression in Hevea clones which may have downstream impact up to the level of rubber production. The conclusions from this study may pave way for the identification and better understanding of CPTs directly involved with natural rubber biosynthesis in Hevea and the SNP data generated may aid in the development of molecular markers putatively associated with yield in rubber.
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Affiliation(s)
- Thomas Kadampanattu Uthup
- Genome Analysis Laboratory, Rubber Research Institute of India, Rubber Board P O, Kottayam, Kerala PIN-686009, India.
| | - Anantharamanan Rajamani
- Genome Analysis Laboratory, Rubber Research Institute of India, Rubber Board P O, Kottayam, Kerala PIN-686009, India
| | - Minimol Ravindran
- Genome Analysis Laboratory, Rubber Research Institute of India, Rubber Board P O, Kottayam, Kerala PIN-686009, India
| | - Thakurdas Saha
- Genome Analysis Laboratory, Rubber Research Institute of India, Rubber Board P O, Kottayam, Kerala PIN-686009, India
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Swaminathan S, Das A, Assefa T, Knight JM, Da Silva AF, Carvalho JPS, Hartman GL, Huang X, Leandro LF, Cianzio SR, Bhattacharyya MK. Genome wide association study identifies novel single nucleotide polymorphic loci and candidate genes involved in soybean sudden death syndrome resistance. PLoS One 2019; 14:e0212071. [PMID: 30807585 PMCID: PMC6391044 DOI: 10.1371/journal.pone.0212071] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2018] [Accepted: 01/25/2019] [Indexed: 01/17/2023] Open
Abstract
Fusarium virguliforme is a soil borne root pathogen that causes sudden death syndrome (SDS) in soybean [Glycine max (L.) Merrill]. Once the fungus invades the root xylem tissues, the pathogen secretes toxins that cause chlorosis and necrosis in foliar tissues leading to defoliation, flower and pod drop and eventually death of plants. Resistance to F. virguliforme in soybean is partial and governed by over 80 quantitative trait loci (QTL). We have conducted genome-wide association study (GWAS) for a group of 254 plant introductions lines using a panel of approximately 30,000 SNPs and identified 19 single nucleotide polymorphic loci (SNPL) that are associated with 14 genomic regions encoding foliar SDS and eight SNPL associated with seven genomic regions for root rot resistance. Of the identified 27 SNPL, six SNPL for foliar SDS resistance and two SNPL for root rot resistance co-mapped to previously identified QTL for SDS resistance. This study identified 13 SNPL associated with eight novel genomic regions containing foliar SDS resistance genes and six SNPL with five novel regions for root-rot resistance. This study identified five genes carrying nonsynonymous mutations: (i) three of which mapped to previously identified QTL for foliar SDS resistance and (ii) two mapped to two novel regions containing root rot resistance genes. Of the three genes mapped to QTL for foliar SDS resistance genes, two encode LRR-receptors and third one encodes a novel protein with unknown function. Of the two genes governing root rot resistance, Glyma.01g222900.1 encodes a soybean-specific LEA protein and Glyma.10g058700.1 encodes a heparan-alpha-glucosaminide N-acetyltransferase. In the LEA protein, a conserved serine residue was substituted with asparagine; and in the heparan-alpha-glucosaminide N-acetyltransferase, a conserved histidine residue was substituted with an arginine residue. Such changes are expected to alter functions of these two proteins regulated through phosphorylation. The five genes with nonsynonymous mutations could be considered candidate SDS resistance genes and should be suitable molecular markers for breeding SDS resistance in soybean. The study also reports desirable plant introduction lines and novel genomic regions for enhancing SDS resistance in soybean.
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Affiliation(s)
| | - Anindya Das
- Department of Computer Science, Iowa State University, Ames, Iowa, United States of America
| | - Teshale Assefa
- Department of Agronomy, Iowa State University, Ames, Iowa, United States of America
| | - Joshua M. Knight
- Department of Agronomy, Iowa State University, Ames, Iowa, United States of America
| | | | - João P. S. Carvalho
- Department of Agronomy, Iowa State University, Ames, Iowa, United States of America
| | - Glen L. Hartman
- USDA and Department of Crop Sciences, University of Illinois, Urbana, Illinois, United States of America
| | - Xiaoqiu Huang
- Department of Computer Science, Iowa State University, Ames, Iowa, United States of America
| | - Leonor F. Leandro
- Department of Plant Pathology and Microbiology, Iowa State University, Ames, Iowa, United States of America
| | - Silvia R. Cianzio
- Department of Agronomy, Iowa State University, Ames, Iowa, United States of America
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Tan R, Collins PJ, Wang J, Wen Z, Boyse JF, Laurenz RG, Gu C, Jacobs JL, Song Q, Chilvers MI, Wang D. Different loci associated with root and foliar resistance to sudden death syndrome (Fusarium virguliforme) in soybean. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2019; 132:501-513. [PMID: 30446796 DOI: 10.1007/s00122-018-3237-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/21/2018] [Accepted: 11/09/2018] [Indexed: 06/09/2023]
Abstract
KEY MESSAGE Different loci associated with root resistance to F. virguliforme colonization and foliar resistance to phytotoxin damage in soybean. Use of resistant cultivars is the most efficacious approach to manage soybean sudden death syndrome (SDS), caused by Fusarium virguliforme. The objectives of this study were to (1) map the loci associated with root and foliar resistance to F. virguliforme infection and (2) decipher the relationships between root infection, foliar damage, and plot yield. A mapping population consisting of 153 F4-derived recombinant inbred lines from the cross U01-390489 × E07080 was genotyped by SoySNP6 K BeadChip assay. Both foliar damage and F. virguliforme colonization in roots were investigated in the field, and a weak positive correlation was identified between them. Foliar damage had a stronger negative correlation with plot yield than F. virguliforme colonization. Twelve loci associated with foliar damage were identified, and four of them were associated with multiple traits across environments. In contrast, only one locus associated with root resistance to F. virguliforme colonization was identified and mapped on Chromosome 18. It colocalized with the locus associated with foliar damage in the same environment. The locus on Chromosome 6, qSDS6-2, and the locus on Chromosome 18, qSDS18-1, were associated with resistance to SDS phytotoxins and resistance to F. virguliforme colonization of roots, respectively. Both loci affected plot yield. Foliar damage-related traits, especially disease index, are valuable indicators for SDS resistance breeding because of consistency of the identified loci and their stronger correlation with plot yield. The information provided by this study will facilitate marker-assisted selection to improve SDS resistance in soybean.
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Affiliation(s)
- Ruijuan Tan
- Department of Plant, Soil and Microbial Sciences, Michigan State University, 1066 Bogue St., East Lansing, MI, 48824-1325, USA
| | - Paul J Collins
- Department of Plant, Soil and Microbial Sciences, Michigan State University, 1066 Bogue St., East Lansing, MI, 48824-1325, USA
| | - Jie Wang
- Department of Plant Biology, Michigan State University, East Lansing, MI, 48824, USA
| | - Zixiang Wen
- Department of Plant, Soil and Microbial Sciences, Michigan State University, 1066 Bogue St., East Lansing, MI, 48824-1325, USA
| | - John F Boyse
- Department of Plant, Soil and Microbial Sciences, Michigan State University, 1066 Bogue St., East Lansing, MI, 48824-1325, USA
| | - Randall G Laurenz
- Department of Plant, Soil and Microbial Sciences, Michigan State University, 1066 Bogue St., East Lansing, MI, 48824-1325, USA
| | - Cuihua Gu
- Department of Plant, Soil and Microbial Sciences, Michigan State University, 1066 Bogue St., East Lansing, MI, 48824-1325, USA
| | - Janette L Jacobs
- Department of Plant, Soil and Microbial Sciences, Michigan State University, 1066 Bogue St., East Lansing, MI, 48824-1325, USA
| | - Qijian Song
- Soybean Genomics and Improvement Laboratory, Agricultural Research Service, United States Department of Agriculture, Beltsville, Maryland, 20705, USA
| | - Martin I Chilvers
- Department of Plant, Soil and Microbial Sciences, Michigan State University, 1066 Bogue St., East Lansing, MI, 48824-1325, USA
| | - Dechun Wang
- Department of Plant, Soil and Microbial Sciences, Michigan State University, 1066 Bogue St., East Lansing, MI, 48824-1325, USA.
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Liu HJ, Yan J. Crop genome-wide association study: a harvest of biological relevance. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2019; 97:8-18. [PMID: 30368955 DOI: 10.1111/tpj.14139] [Citation(s) in RCA: 112] [Impact Index Per Article: 22.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/23/2018] [Revised: 10/13/2018] [Accepted: 10/22/2018] [Indexed: 05/20/2023]
Abstract
With the advent of rapid genotyping and next-generation sequencing technologies, genome-wide association study (GWAS) has become a routine strategy for decoding genotype-phenotype associations in many species. More than 1000 such studies over the last decade have revealed substantial genotype-phenotype associations in crops and provided unparalleled opportunities to probe functional genomics. Beyond the many 'hits' obtained, this review summarizes recent efforts to increase our understanding of the genetic architecture of complex traits by focusing on non-main effects including epistasis, pleiotropy, and phenotypic plasticity. We also discuss how these achievements and the remaining gaps in our knowledge will guide future studies. Synthetic association is highlighted as leading to false causality, which is prevalent but largely underestimated. Furthermore, validation evidence is appealing for future GWAS, especially in the context of emerging genome-editing technologies.
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Affiliation(s)
- Hai-Jun Liu
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
| | - Jianbing Yan
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
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Fernie AR, Gutierrez-Marcos J. From genome to phenome: genome-wide association studies and other approaches that bridge the genotype to phenotype gap. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2019; 97:5-7. [PMID: 30636100 DOI: 10.1111/tpj.14219] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Affiliation(s)
- Alisdair R Fernie
- Max-Planck-Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476, Potsdam-Golm, Germany
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Sun Z, Wang X, Liu Z, Gu Q, Zhang Y, Li Z, Ke H, Yang J, Wu J, Wu L, Zhang G, Zhang C, Ma Z. A genome-wide association study uncovers novel genomic regions and candidate genes of yield-related traits in upland cotton. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2018; 131:2413-2425. [PMID: 30132023 DOI: 10.1007/s00122-018-3162-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/05/2018] [Accepted: 08/05/2018] [Indexed: 05/02/2023]
Abstract
A total of 62 SNPs associated with yield-related traits were identified by a GWAS. Based on significant SNPs, two candidate genes pleiotropically increase lint yield. Improved fibre yield is considered a constant goal of upland cotton (Gossypium hirsutum) breeding worldwide, but the understanding of the genetic basis controlling yield-related traits remains limited. To better decipher the molecular mechanism underlying these traits, we conducted a genome-wide association study to determine candidate loci associated with six yield-related traits in a population of 719 upland cotton germplasm accessions; to accomplish this, we used 10,511 single-nucleotide polymorphisms (SNPs) genotyped by an Illumina CottonSNP63K array. Six traits, including the boll number, boll weight, lint percentage, fruit branch number, seed index and lint index, were assessed in multiple environments; large variation in all phenotypes was detected across accessions. We identified 62 SNP loci that were significantly associated with different traits on chromosomes A07, D03, D05, D09, D10 and D12. A total of 689 candidate genes were screened, and 27 of them contained at least one significant SNP. Furthermore, two genes (Gh_D03G1064 and Gh_D12G2354) that pleiotropically increase lint yield were identified. These identified SNPs and candidate genes provide important insights into the genetic control underlying high yields in G. hirsutum, ultimately facilitating breeding programmes of high-yielding cotton.
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Affiliation(s)
- Zhengwen Sun
- North China Key Laboratory for Crop Germplasm Resources of Education Ministry, Key Laboratory for Crop Germplasm Resources of Hebei Province, Hebei Agricultural University, Baoding, 071001, China
| | - Xingfen Wang
- North China Key Laboratory for Crop Germplasm Resources of Education Ministry, Key Laboratory for Crop Germplasm Resources of Hebei Province, Hebei Agricultural University, Baoding, 071001, China
| | - Zhengwen Liu
- North China Key Laboratory for Crop Germplasm Resources of Education Ministry, Key Laboratory for Crop Germplasm Resources of Hebei Province, Hebei Agricultural University, Baoding, 071001, China
| | - Qishen Gu
- North China Key Laboratory for Crop Germplasm Resources of Education Ministry, Key Laboratory for Crop Germplasm Resources of Hebei Province, Hebei Agricultural University, Baoding, 071001, China
| | - Yan Zhang
- North China Key Laboratory for Crop Germplasm Resources of Education Ministry, Key Laboratory for Crop Germplasm Resources of Hebei Province, Hebei Agricultural University, Baoding, 071001, China
| | - Zhikun Li
- North China Key Laboratory for Crop Germplasm Resources of Education Ministry, Key Laboratory for Crop Germplasm Resources of Hebei Province, Hebei Agricultural University, Baoding, 071001, China
| | - Huifeng Ke
- North China Key Laboratory for Crop Germplasm Resources of Education Ministry, Key Laboratory for Crop Germplasm Resources of Hebei Province, Hebei Agricultural University, Baoding, 071001, China
| | - Jun Yang
- North China Key Laboratory for Crop Germplasm Resources of Education Ministry, Key Laboratory for Crop Germplasm Resources of Hebei Province, Hebei Agricultural University, Baoding, 071001, China
| | - Jinhua Wu
- North China Key Laboratory for Crop Germplasm Resources of Education Ministry, Key Laboratory for Crop Germplasm Resources of Hebei Province, Hebei Agricultural University, Baoding, 071001, China
| | - Liqiang Wu
- North China Key Laboratory for Crop Germplasm Resources of Education Ministry, Key Laboratory for Crop Germplasm Resources of Hebei Province, Hebei Agricultural University, Baoding, 071001, China
| | - Guiyin Zhang
- North China Key Laboratory for Crop Germplasm Resources of Education Ministry, Key Laboratory for Crop Germplasm Resources of Hebei Province, Hebei Agricultural University, Baoding, 071001, China
| | - Caiying Zhang
- North China Key Laboratory for Crop Germplasm Resources of Education Ministry, Key Laboratory for Crop Germplasm Resources of Hebei Province, Hebei Agricultural University, Baoding, 071001, China.
| | - Zhiying Ma
- North China Key Laboratory for Crop Germplasm Resources of Education Ministry, Key Laboratory for Crop Germplasm Resources of Hebei Province, Hebei Agricultural University, Baoding, 071001, China.
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Hanson AA, Lorenz AJ, Hesler LS, Bhusal SJ, Bansal R, Michel AP, Jiang GL, Koch RL. Genome-Wide Association Mapping of Host-Plant Resistance to Soybean Aphid. THE PLANT GENOME 2018; 11. [PMID: 30512046 DOI: 10.3835/plantgenome2018.02.0011] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/08/2018] [Accepted: 04/23/2018] [Indexed: 05/28/2023]
Abstract
Soybean aphid [ Matsumura (Hemiptera: Aphididae)] is the most damaging insect pest of soybean [ (L.) Merr.] in the Upper Midwest of the United States and is primarily controlled by insecticides. Soybean aphid resistance (i.e., genes) has been documented in some soybean accessions but more sources of resistance are needed. Incorporation of the resistance into marketed varieties has also been slow. Genome-wide association mapping can aid in identifying resistant accessions by correlating phenotypic data with single nucleotide polymorphisms (SNPs) across a genome. Aphid population measures from 2366 soybean accessions were collected from published studies screening cultivated soybean () and wild soybean ( Siebold & Zucc.) with aphids exhibiting Biotype 1, 2, or 3 characteristics. Genotypic data were obtained from the SoySNP50K high-density genotyping array previously used to genotype the USDA Soybean Germplasm Collection. Significant associations between SNPs and soybean aphid counts were found on 18 of the 20 soybean chromosomes. Significant SNPs were found on chromosomes 7, 8, 13, and 16 with known genes. SNPs were also significant on chromosomes 1, 2, 4 to 6, 9 to 12, 14, and 17 to 20 where genes have not yet been mapped, suggesting that many genes remain to be discovered. These SNPs can be used to determine accessions that are likely to have novel aphid resistance traits of value for breeding programs.
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Zatybekov A, Abugalieva S, Didorenko S, Rsaliyev A, Turuspekov Y. GWAS of a soybean breeding collection from South East and South Kazakhstan for resistance to fungal diseases. Vavilovskii Zhurnal Genet Selektsii 2018. [DOI: 10.18699/vj18.392] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
Soybean (Glycine max(L.) Merr) is an essential food, feed, and technical culture. In Kazakhstan the area under soybean is increasing every year, helping to solve the problem of protein deficiency in human nutrition and animal feeding. One of the main problems of soybean production is fungal diseases causing yields losses of up to 30 %. Modern genomic studies can be applied to facilitate efficient breeding research for improvement of soybean fungal disease tolerance. Therefore, the objective of this genome-wide association study (GWAS) was analysis of a soybean collection consisting of 182 accessions in relation to fungal diseases in the conditions of South East and South Kazakhstan. Field evaluation of the soybean collection suggested thatFusariumspp. andCercospora sojinaaffected plants in the South region (RIBSP), andSeptoria glycines– in the South East region (KRIAPP). The major objective of the study was identification of QTL associated with resistance to fusarium root rot (FUS), frogeye leaf spot (FLS), and brown spot (BS). GWAS using 4 442 SNP (single nucleotide polymorphism) markers of Illumina iSelect array allowed for identification of fifteen marker trait associations (MTA) resistant to the three diseases at two different stages of growth. Two QTL both for FUS (chromosomes 13 and 17) and BS (chromosomes 14 and 17) were genetically mapped, including one presumably novel QTL for BS (chromosome 17). Also, five presumably novel QTL for FLS were genetically mapped on chromosomes 2, 7, and 15. The results can be used for improvement of the local breeding projects based on marker-assisted selection approach.
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Tan R, Serven B, Collins PJ, Zhang Z, Wen Z, Boyse JF, Gu C, Chilvers MI, Diers BW, Wang D. QTL mapping and epistatic interaction analysis of field resistance to sudden death syndrome (Fusarium virguliforme) in soybean. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2018; 131:1729-1740. [PMID: 29766218 DOI: 10.1007/s00122-018-3110-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/22/2018] [Accepted: 05/07/2018] [Indexed: 06/08/2023]
Abstract
KEY MESSAGE Two interactive quantitative trait loci (QTLs) controlled the field resistance to sudden death syndrome (SDS) in soybean. The interaction between them was confirmed. Sudden death syndrome (SDS), caused by Fusarium virguliforme, is a major disease of soybean [Glycine max (L.) Merr.] in the United States. Breeding for soybean resistance to SDS is the most cost-effective method to manage the disease. The objective of this study was to identify and characterize quantitative trait loci (QTLs) underlying field resistance to SDS in a recombinant inbred line population from the cross GD2422 × LD01-5907. This population was genotyped with 1786 polymorphic single nucleotide polymorphisms (SNPs) using SoySNP6 K iSelect BeadChip and evaluated for SDS resistance in a naturally infested field. Four SDS resistance QTLs were mapped on Chromosomes 4, 8, 12 and 18. The resistant parent, LD01-5907, contributed the resistance alleles for the QTLs on Chromosomes 8 and 18 (qSDS-8 and qSDS-18), while the other parent, GD2422, provided the resistance alleles for the QTLs on Chromosomes 4 and 12 (qSDS-4 and qSDS-12). The minor QTL on Chromosome 12 (qSDS-12) is novel. The QTL on Chromosomes 8 and 18 (qSDS-8 and qSDS-18) overlapped with two soybean cyst nematode resistance-related loci, Rhg4 and Rhg1, respectively. A significant interaction between qSDS-8 and qSDS-18 was detected by disease incidence. Individual effects together with the interaction effect explained around 70% of the phenotypic variance. The epistatic interaction of qSDS-8 and qSDS-18 was confirmed by the field performance across multiple years. Furthermore, the resistance alleles at qSDS-8 and qSDS-18 were demonstrated to be recessive. The SNP markers linked to these QTLs will be useful for marker-assisted breeding to enhance the SDS resistance.
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Affiliation(s)
- Ruijuan Tan
- Department of Plant, Soil and Microbial Sciences, Michigan State University, 1066 Bogue St., East Lansing, MI, 48824-1325, USA
| | - Bradley Serven
- Department of Plant, Soil and Microbial Sciences, Michigan State University, 1066 Bogue St., East Lansing, MI, 48824-1325, USA
| | - Paul J Collins
- Department of Plant, Soil and Microbial Sciences, Michigan State University, 1066 Bogue St., East Lansing, MI, 48824-1325, USA
| | - Zhongnan Zhang
- Department of Plant, Soil and Microbial Sciences, Michigan State University, 1066 Bogue St., East Lansing, MI, 48824-1325, USA
| | - Zixiang Wen
- Department of Plant, Soil and Microbial Sciences, Michigan State University, 1066 Bogue St., East Lansing, MI, 48824-1325, USA
| | - John F Boyse
- Department of Plant, Soil and Microbial Sciences, Michigan State University, 1066 Bogue St., East Lansing, MI, 48824-1325, USA
| | - Cuihua Gu
- Department of Plant, Soil and Microbial Sciences, Michigan State University, 1066 Bogue St., East Lansing, MI, 48824-1325, USA
| | - Martin I Chilvers
- Department of Plant, Soil and Microbial Sciences, Michigan State University, 1066 Bogue St., East Lansing, MI, 48824-1325, USA
| | - Brian W Diers
- Department of Crop Sciences, University of Illinois, 1101 W. Peabody Drive, Urbana, IL, 61801, USA
| | - Dechun Wang
- Department of Plant, Soil and Microbial Sciences, Michigan State University, 1066 Bogue St., East Lansing, MI, 48824-1325, USA.
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Piaskowski J, Hardner C, Cai L, Zhao Y, Iezzoni A, Peace C. Genomic heritability estimates in sweet cherry reveal non-additive genetic variance is relevant for industry-prioritized traits. BMC Genet 2018; 19:23. [PMID: 29636022 PMCID: PMC5894190 DOI: 10.1186/s12863-018-0609-8] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2017] [Accepted: 03/22/2018] [Indexed: 11/11/2022] Open
Abstract
BACKGROUND Sweet cherry is consumed widely across the world and provides substantial economic benefits in regions where it is grown. While cherry breeding has been conducted in the Pacific Northwest for over half a century, little is known about the genetic architecture of important traits. We used a genome-enabled mixed model to predict the genetic performance of 505 individuals for 32 phenological, disease response and fruit quality traits evaluated in the RosBREED sweet cherry crop data set. Genome-wide predictions were estimated using a repeated measures model for phenotypic data across 3 years, incorporating additive, dominance and epistatic variance components. Genomic relationship matrices were constructed with high-density SNP data and were used to estimate relatedness and account for incomplete replication across years. RESULTS High broad-sense heritabilities of 0.83, 0.77, and 0.76 were observed for days to maturity, firmness, and fruit weight, respectively. Epistatic variance exceeded 40% of the total genetic variance for maturing timing, firmness and powdery mildew response. Dominance variance was the largest for fruit weight and fruit size at 34% and 27%, respectively. Omission of non-additive sources of genetic variance from the genetic model resulted in inflation of narrow-sense heritability but minimally influenced prediction accuracy of genetic values in validation. Predicted genetic rankings of individuals from single-year models were inconsistent across years, likely due to incomplete sampling of the population genetic variance. CONCLUSIONS Predicted breeding values and genetic values revealed many high-performing individuals for use as parents and the most promising selections to advance for cultivar release consideration, respectively. This study highlights the importance of using the appropriate genetic model for calculating breeding values to avoid inflation of expected parental contribution to genetic gain. The genomic predictions obtained will enable breeders to efficiently leverage the genetic potential of North American sweet cherry germplasm by identifying high quality individuals more rapidly than with phenotypic data alone.
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Affiliation(s)
- Julia Piaskowski
- Department of Horticulture, Washington State University, Pullman, WA 99164-6414 USA
| | - Craig Hardner
- Centre for Horticultural Science, Queensland Alliance for Agriculture and Food Innovation University of Queensland, Brisbane, Australia
| | - Lichun Cai
- Department of Horticulture, Michigan State University, East Lansing, MI 48824-1325 USA
| | - Yunyang Zhao
- Plants for Human Health Institute, North Carolina State University, Kannapolis, NC 28081 USA
| | - Amy Iezzoni
- Department of Horticulture, Michigan State University, East Lansing, MI 48824-1325 USA
| | - Cameron Peace
- Department of Horticulture, Washington State University, Pullman, WA 99164-6414 USA
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50
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Chang HX, Roth MG, Wang D, Cianzio SR, Lightfoot DA, Hartman GL, Chilvers MI. Integration of sudden death syndrome resistance loci in the soybean genome. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2018; 131:757-773. [PMID: 29435603 DOI: 10.1007/s00122-018-3063-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/23/2017] [Accepted: 01/19/2018] [Indexed: 05/12/2023]
Abstract
KEY MESSAGE Complexity and inconsistencies in resistance mapping publications of soybean sudden death syndrome (SDS) result in interpretation difficulty. This review integrates SDS mapping literature and proposes a new nomenclature system for reproducible SDS resistance loci. Soybean resistance to sudden death syndrome (SDS) is composed of foliar resistance to phytotoxins and root resistance to pathogen invasion. There are more than 80 quantitative trait loci (QTL) and dozens of single nucleotide polymorphisms (SNPs) associated with soybean resistance to SDS. The validity of these QTL and SNPs is questionable because of the complexity in phenotyping methodologies, the disease synergism between SDS and soybean cyst nematode (SCN), the variability from the interactions between soybean genotypes and environments, and the inconsistencies in the QTL nomenclature. This review organizes SDS mapping results and proposes the Rfv (resistance to Fusarium virguliforme) nomenclature based on supporting criteria described in the text. Among ten reproducible loci receiving our Rfv nomenclature, Rfv18-01 is mostly supported by field studies and it co-localizes to the SCN resistance locus rhg1. The possibility that Rfv18-01 is a pleiotropic resistance locus and the concern about Rfv18-01 being confounded with Rhg1 is discussed. On the other hand, Rfv06-01, Rfv06-02, Rfv09-01, Rfv13-01, and Rfv16-01 were identified both by screening soybean leaves against phytotoxic culture filtrates and by evaluating SDS severity in fields. Future phenotyping using leaf- and root-specific resistance screening methodologies may improve the precision of SDS resistance, and advanced genetic studies may further clarify the interactions among soybean genotypes, F. virguliforme, SCN, and environments. The review provides a summary of the SDS resistance literature and proposes a framework for communicating SDS resistance loci for future research considering molecular interactions and genetic breeding for soybean SDS resistance.
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Affiliation(s)
- Hao-Xun Chang
- Department of Plant, Soil and Microbial Sciences, Michigan State University, East Lansing, MI, USA
| | - Mitchell G Roth
- Department of Plant, Soil and Microbial Sciences, Michigan State University, East Lansing, MI, USA
- Genetics Program, Michigan State University, East Lansing, MI, USA
| | - Dechun Wang
- Department of Plant, Soil and Microbial Sciences, Michigan State University, East Lansing, MI, USA
| | | | - David A Lightfoot
- Department of Plant, Soil and Agricultural Systems, Southern Illinois University, Carbondale, IL, USA.
| | - Glen L Hartman
- Department of Crop Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, USA.
- USDA-Agricultural Research Service, Urbana, IL, USA.
| | - Martin I Chilvers
- Department of Plant, Soil and Microbial Sciences, Michigan State University, East Lansing, MI, USA.
- Genetics Program, Michigan State University, East Lansing, MI, USA.
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