651
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Spindel J, Begum H, Akdemir D, Virk P, Collard B, Redoña E, Atlin G, Jannink JL, McCouch SR. Genomic selection and association mapping in rice (Oryza sativa): effect of trait genetic architecture, training population composition, marker number and statistical model on accuracy of rice genomic selection in elite, tropical rice breeding lines. PLoS Genet 2015. [PMID: 25689273 DOI: 10.5061/dryad.7369p] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/26/2023] Open
Abstract
Genomic Selection (GS) is a new breeding method in which genome-wide markers are used to predict the breeding value of individuals in a breeding population. GS has been shown to improve breeding efficiency in dairy cattle and several crop plant species, and here we evaluate for the first time its efficacy for breeding inbred lines of rice. We performed a genome-wide association study (GWAS) in conjunction with five-fold GS cross-validation on a population of 363 elite breeding lines from the International Rice Research Institute's (IRRI) irrigated rice breeding program and herein report the GS results. The population was genotyped with 73,147 markers using genotyping-by-sequencing. The training population, statistical method used to build the GS model, number of markers, and trait were varied to determine their effect on prediction accuracy. For all three traits, genomic prediction models outperformed prediction based on pedigree records alone. Prediction accuracies ranged from 0.31 and 0.34 for grain yield and plant height to 0.63 for flowering time. Analyses using subsets of the full marker set suggest that using one marker every 0.2 cM is sufficient for genomic selection in this collection of rice breeding materials. RR-BLUP was the best performing statistical method for grain yield where no large effect QTL were detected by GWAS, while for flowering time, where a single very large effect QTL was detected, the non-GS multiple linear regression method outperformed GS models. For plant height, in which four mid-sized QTL were identified by GWAS, random forest produced the most consistently accurate GS models. Our results suggest that GS, informed by GWAS interpretations of genetic architecture and population structure, could become an effective tool for increasing the efficiency of rice breeding as the costs of genotyping continue to decline.
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Affiliation(s)
- Jennifer Spindel
- Department of Plant Breeding and Genetics, Cornell University, Ithaca, New York, United States of America
| | - Hasina Begum
- International Rice Research Institute, Los Baños, Philippines
| | - Deniz Akdemir
- Department of Plant Breeding and Genetics, Cornell University, Ithaca, New York, United States of America
| | - Parminder Virk
- International Center for Tropical Agriculture, Cali, Colombia
| | | | | | - Gary Atlin
- Bill & Melinda Gates Foundation, Seattle, Washington, United States of America
| | - Jean-Luc Jannink
- Department of Plant Breeding and Genetics, Cornell University, Ithaca, New York, United States of America; US Department of Agriculture-Agricultural Research Service (USDA-ARS), Ithaca, New York, United States of America
| | - Susan R McCouch
- Department of Plant Breeding and Genetics, Cornell University, Ithaca, New York, United States of America
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652
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Lee YG, Jeong N, Kim JH, Lee K, Kim KH, Pirani A, Ha BK, Kang ST, Park BS, Moon JK, Kim N, Jeong SC. Development, validation and genetic analysis of a large soybean SNP genotyping array. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2015; 81:625-36. [PMID: 25641104 DOI: 10.1111/tpj.12755] [Citation(s) in RCA: 58] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/08/2014] [Revised: 11/18/2014] [Accepted: 12/18/2014] [Indexed: 05/19/2023]
Abstract
Cultivated soybean (Glycine max) suffers from a narrow germplasm relative to other crop species, probably because of under-use of wild soybean (Glycine soja) as a breeding resource. Use of a single nucleotide polymorphism (SNP) genotyping array is a promising method for dissecting cultivated and wild germplasms to identify important adaptive genes through high-density genetic mapping and genome-wide association studies. Here we describe a large soybean SNP array for use in diversity analyses, linkage mapping and genome-wide association analyses. More than four million high-quality SNPs identified from high-depth genome re-sequencing of 16 soybean accessions and low-depth genome re-sequencing of 31 soybean accessions were used to select 180,961 SNPs for creation of the Axiom(®) SoyaSNP array. Validation analysis for a set of 222 diverse soybean lines showed that 170,223 markers were of good quality for genotyping. Phylogenetic and allele frequency analyses of the validation set data indicated that accessions showing an intermediate morphology between cultivated and wild soybeans collected in Korea were natural hybrids. More than 90 unanchored scaffolds in the current soybean reference sequence were assigned to chromosomes using this array. Finally, dense average spacing and preferential distribution of the SNPs in gene-rich chromosomal regions suggest that this array may be suitable for genome-wide association studies of soybean germplasm. Taken together, these results suggest that use of this array may be a powerful method for soybean genetic analyses relating to many aspects of soybean breeding.
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Affiliation(s)
- Yun-Gyeong Lee
- Korean Bioinformation Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon, 305-806, Korea; Department of Bioinformatics, University of Science and Technology, Daejeon, 305-806, Korea
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653
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Kumar V, Singh A, Mithra SVA, Krishnamurthy SL, Parida SK, Jain S, Tiwari KK, Kumar P, Rao AR, Sharma SK, Khurana JP, Singh NK, Mohapatra T. Genome-wide association mapping of salinity tolerance in rice (Oryza sativa). DNA Res 2015; 22:133-45. [PMID: 25627243 PMCID: PMC4401324 DOI: 10.1093/dnares/dsu046] [Citation(s) in RCA: 147] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2014] [Accepted: 12/26/2014] [Indexed: 02/07/2023] Open
Abstract
Salinity tolerance in rice is highly desirable to sustain production in areas rendered saline due to various reasons. It is a complex quantitative trait having different components, which can be dissected effectively by genome-wide association study (GWAS). Here, we implemented GWAS to identify loci controlling salinity tolerance in rice. A custom-designed array based on 6,000 single nucleotide polymorphisms (SNPs) in as many stress-responsive genes, distributed at an average physical interval of <100 kb on 12 rice chromosomes, was used to genotype 220 rice accessions using Infinium high-throughput assay. Genetic association was analysed with 12 different traits recorded on these accessions under field conditions at reproductive stage. We identified 20 SNPs (loci) significantly associated with Na+/K+ ratio, and 44 SNPs with other traits observed under stress condition. The loci identified for various salinity indices through GWAS explained 5–18% of the phenotypic variance. The region harbouring Saltol, a major quantitative trait loci (QTLs) on chromosome 1 in rice, which is known to control salinity tolerance at seedling stage, was detected as a major association with Na+/K+ ratio measured at reproductive stage in our study. In addition to Saltol, we also found GWAS peaks representing new QTLs on chromosomes 4, 6 and 7. The current association mapping panel contained mostly indica accessions that can serve as source of novel salt tolerance genes and alleles. The gene-based SNP array used in this study was found cost-effective and efficient in unveiling genomic regions/candidate genes regulating salinity stress tolerance in rice.
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Affiliation(s)
- Vinod Kumar
- National Research Centre on Plant Biotechnology, New Delhi 110012, India
| | - Anshuman Singh
- National Research Centre on Plant Biotechnology, New Delhi 110012, India
| | - S V Amitha Mithra
- National Research Centre on Plant Biotechnology, New Delhi 110012, India
| | - S L Krishnamurthy
- Central Soil Salinity Research Institute, Karnal, Haryana 132001, India
| | - Swarup K Parida
- National Research Centre on Plant Biotechnology, New Delhi 110012, India
| | - Sourabh Jain
- National Research Centre on Plant Biotechnology, New Delhi 110012, India
| | - Kapil K Tiwari
- National Research Centre on Plant Biotechnology, New Delhi 110012, India
| | - Pankaj Kumar
- National Research Centre on Plant Biotechnology, New Delhi 110012, India
| | - Atmakuri R Rao
- Indian Agricultural Statistics Research Institute, New Delhi 110012, India
| | - S K Sharma
- Central Soil Salinity Research Institute, Karnal, Haryana 132001, India
| | | | - Nagendra K Singh
- National Research Centre on Plant Biotechnology, New Delhi 110012, India
| | - Trilochan Mohapatra
- National Research Centre on Plant Biotechnology, New Delhi 110012, India Central Rice Research Institute, Cuttack, Odisha 753006, India
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654
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Abstract
In plant and animal breeding studies a distinction is made between the genetic value (additive plus epistatic genetic effects) and the breeding value (additive genetic effects) of an individual since it is expected that some of the epistatic genetic effects will be lost due to recombination. In this article, we argue that the breeder can take advantage of the epistatic marker effects in regions of low recombination. The models introduced here aim to estimate local epistatic line heritability by using genetic map information and combining local additive and epistatic effects. To this end, we have used semiparametric mixed models with multiple local genomic relationship matrices with hierarchical designs. Elastic-net postprocessing was used to introduce sparsity. Our models produce good predictive performance along with useful explanatory information.
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655
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Maccaferri M, Zhang J, Bulli P, Abate Z, Chao S, Cantu D, Bossolini E, Chen X, Pumphrey M, Dubcovsky J. A genome-wide association study of resistance to stripe rust (Puccinia striiformis f. sp. tritici) in a worldwide collection of hexaploid spring wheat (Triticum aestivum L.). G3 (BETHESDA, MD.) 2015; 5:449-65. [PMID: 25609748 PMCID: PMC4349098 DOI: 10.1534/g3.114.014563] [Citation(s) in RCA: 168] [Impact Index Per Article: 18.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/18/2014] [Accepted: 01/17/2015] [Indexed: 02/01/2023]
Abstract
New races of Puccinia striiformis f. sp. tritici (Pst), the causal pathogen of wheat stripe rust, show high virulence to previously deployed resistance genes and are responsible for large yield losses worldwide. To identify new sources of resistance we performed a genome-wide association study (GWAS) using a worldwide collection of 1000 spring wheat accessions. Adult plants were evaluated under field conditions in six environments in the western United States, and seedlings were tested with four Pst races. A single-nucleotide polymorphism (SNP) Infinium 9K-assay provided 4585 SNPs suitable for GWAS. High correlations among environments and high heritabilities were observed for stripe rust infection type and severity. Greater levels of Pst resistance were observed in a subpopulation from Southern Asia than in other groups. GWAS identified 97 loci that were significant for at least three environments, including 10 with an experiment-wise adjusted Bonferroni probability < 0.10. These 10 quantitative trait loci (QTL) explained 15% of the phenotypic variation in infection type, a percentage that increased to 45% when all QTL were considered. Three of these 10 QTL were mapped far from previously identified Pst resistance genes and QTL, and likely represent new resistance loci. The other seven QTL mapped close to known resistance genes and allelism tests will be required to test their relationships. In summary, this study provides an integrated view of stripe rust resistance resources in spring wheat and identifies new resistance loci that will be useful to diversify the current set of resistance genes deployed to control this devastating disease.
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Affiliation(s)
- Marco Maccaferri
- Department of Plant Sciences, University of California, Davis, California 95616 Department of Agricultural Sciences (DipSA), University of Bologna, Bologna 40127, Italy
| | - Junli Zhang
- Department of Plant Sciences, University of California, Davis, California 95616
| | - Peter Bulli
- Department of Crop and Soil Sciences, Washington State University, Pullman, Washington 99164-6420
| | - Zewdie Abate
- Department of Plant Sciences, University of California, Davis, California 95616
| | - Shiaoman Chao
- USDA-ARS, 1605 Albrecht Blvd, Fargo, North Dakota 58105
| | - Dario Cantu
- Department of Viticulture and Enology, University of California, Davis, California 95616
| | - Eligio Bossolini
- Department of Plant Sciences, University of California, Davis, California 95616
| | - Xianming Chen
- USDA-ARS, Wheat Genetics, Quality Physiology, and Disease Research Unit, and Department of Plant Pathology, Washington State University, Pullman, Washington 99164
| | - Michael Pumphrey
- Department of Crop and Soil Sciences, Washington State University, Pullman, Washington 99164-6420
| | - Jorge Dubcovsky
- Department of Plant Sciences, University of California, Davis, California 95616 Howard Hughes Medical Institute, Chevy Chase, Maryland 20815
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656
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Salvi S, Tuberosa R. The crop QTLome comes of age. Curr Opin Biotechnol 2015; 32:179-185. [PMID: 25614069 DOI: 10.1016/j.copbio.2015.01.001] [Citation(s) in RCA: 75] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2014] [Revised: 12/31/2014] [Accepted: 01/02/2015] [Indexed: 12/15/2022]
Abstract
Recent progress in genomics and phenomics allows for a more accurate and comprehensive characterization of the Quantitative Trait Loci (QTLs)—hereafter defined 'QTLome' as a whole—that govern the variation targeted in breeding programs. High-density genotyping now provides unambiguous identification of QTL alleles, and for several traits beneficial alleles at major QTLs have already been deployed in marker-assisted breeding. However, the amount of QTLome information is enormous and approaches to distill and translate this information to breeders remain to be refined. Improved QTL meta-analyses, better estimation of QTL effects, improved crop modelling and full sharing of raw QTL data will enable a more effective exploitation of the QTLome.
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Affiliation(s)
- Silvio Salvi
- Department of Agricultural Sciences, University of Bologna, Viale Fanin 44, 40127 Bologna, Italy.
| | - Roberto Tuberosa
- Department of Agricultural Sciences, University of Bologna, Viale Fanin 44, 40127 Bologna, Italy
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657
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658
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Hayward AC, Tollenaere R, Dalton-Morgan J, Batley J. Molecular marker applications in plants. Methods Mol Biol 2015; 1245:13-27. [PMID: 25373746 DOI: 10.1007/978-1-4939-1966-6_2] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
Individuals within a population of a sexually reproducing species will have some degree of heritable genomic variation caused by mutations, insertion/deletions (INDELS), inversions, duplications, and translocations. Such variation can be detected and screened using molecular, or genetic, markers. By definition, molecular markers are genetic loci that can be easily tracked and quantified in a population and may be associated with a particular gene or trait of interest. This chapter will review the current major applications of molecular markers in plants.
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Affiliation(s)
- Alice C Hayward
- School of Agriculture and Food Sciences, University of Queensland, Brisbane, QLD, Australia
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659
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Luo J, Jobling SA, Millar A, Morell MK, Li Z. Allelic effects on starch structure and properties of six starch biosynthetic genes in a rice recombinant inbred line population. RICE (NEW YORK, N.Y.) 2015; 8:15. [PMID: 25844120 DOI: 10.1186./s12284-015-0046-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Received: 08/28/2014] [Accepted: 01/28/2015] [Indexed: 05/22/2023]
Abstract
BACKGROUND The genetic diversity of six starch biosynthetic genes (Wx, SSI, SSIIa, SBEI, SBEIIa and SBEIIb) in indica and japonica rices opens an opportunity to produce a new variety with more favourable grain starch quality. However, there is limited information about the effects of these six gene allele combinations on starch structure and properties. A recombinant inbred line population from a cross between indica and japonica varieties offers opportunities to combine specific alleles of the six genes. RESULTS The allelic (indica vs japonica) effects of six starch biosynthetic genes on starch structure, functional properties, and abundance of granule bound proteins in rice grains were investigated in a common genetic background using a recombinant inbred line population. The indica Wx (Wxi) allele played a major role while indica SSI (SSIi), japonica SSIIa (SSIIaj) and indica SBEI (SBEIi) alleles had minor roles on the increase of amylose content. SSIIaj and japonica SBEIIb (SBEIIbj) alleles had a major and a minor role on high ratio of ∑DP ≤ 10 to ∑DP ≤ 24 fractions (RCL10/24), respectively. Both major alleles (Wxi and SSIIaj) reduced peak viscosity (PV), onset, peak and end gelatinization temperatures (GTs) of amylopectin, and increased amylose-lipid complex dissociation enthalpy compared with their counterpart-alleles, respectively. SBEIIai and SBEIIbj decreased PV, whereas SSIi and SBEIIbj decreased FV. SBEIi reduced setback viscosity and gelatinization enthalpy. RCL10/24 of chain length distribution in amylopectin is negatively correlated with PV and BD of paste property and GTs of thermal properties. We also report RILs with superior starch properties combining Wxi, SSIj, SSIIaj, SBEIi and SBEIIbj alleles. Additionally, a clear relation is drawn to starch biosynthetic gene alleles, starch structure, properties, and abundance of granule bound starch biosynthetic enzymes inside starch granules. CONCLUSIONS Rice Wxi and SSIIaj alleles play major roles, while SSIi, SBEIi, SBEIIai and SBEIIbj alleles have minor roles in the determination of starch properties between indica and japonica rice through starch structural modification. The combination of these alleles is a key factor for starch quality improvement in rice breeding programs. RCL10/24 value is critical for starch structure and property determination.
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Affiliation(s)
- Jixun Luo
- CSIRO Agriculture Flagship, GPO Box 1600, Canberra, ACT 2601 Australia ; College of Medicine, Biology and Environment, Australian National University, Canberra, ACT 0200 Australia
| | - Stephen A Jobling
- CSIRO Agriculture Flagship, GPO Box 1600, Canberra, ACT 2601 Australia
| | - Anthony Millar
- College of Medicine, Biology and Environment, Australian National University, Canberra, ACT 0200 Australia
| | - Matthew K Morell
- CSIRO Agriculture Flagship, GPO Box 1600, Canberra, ACT 2601 Australia ; International Rice Research Institute, Maligaya, Muñoz, Nueva Ecija Philippines
| | - Zhongyi Li
- CSIRO Agriculture Flagship, GPO Box 1600, Canberra, ACT 2601 Australia
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660
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Dhanapal AP, Ray JD, Singh SK, Hoyos-Villegas V, Smith JR, Purcell LC, Andy King C, Cregan PB, Song Q, Fritschi FB. Genome-wide association study (GWAS) of carbon isotope ratio (δ13C) in diverse soybean [Glycine max (L.) Merr.] genotypes. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2015. [PMID: 25367378 DOI: 10.1007/s00122-014-2419-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 05/10/2023]
Abstract
Using genome-wide association studies, 39 SNP markers likely tagging 21 different loci for carbon isotope ratio (δ (13) C) were identified in soybean. Water deficit stress is a major factor limiting soybean [Glycine max (L.) Merr.] yield. Soybean genotypes with improved water use efficiency (WUE) may be used to develop cultivars with increased yield under drought. A collection of 373 diverse soybean genotypes was grown in four environments (2 years and two locations) and characterized for carbon isotope ratio (δ(13)C) as a surrogate measure of WUE. Population structure was assessed based on 12,347 single nucleotide polymorphisms (SNPs), and genome-wide association studies (GWAS) were conducted to identify SNPs associated with δ(13)C. Across all four environments, δ(13)C ranged from a minimum of -30.55‰ to a maximum of -27.74‰. Although δ(13)C values were significantly different between the two locations in both years, results were consistent among genotypes across years and locations. Diversity analysis indicated that eight subpopulations could contain all individuals and revealed that within-subpopulation diversity, rather than among-subpopulation diversity, explained most (80%) of the diversity among the 373 genotypes. A total of 39 SNPs that showed a significant association with δ(13)C in at least two environments or for the average across all environments were identified by GWAS. Fifteen of these SNPs were located within a gene. The 39 SNPs likely tagged 21 different loci and demonstrated that markers for δ(13)C can be identified in soybean using GWAS. Further research is necessary to confirm the marker associations identified and to evaluate their usefulness for selecting genotypes with increased WUE.
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661
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Dong X, Gao Y, Chen W, Wang W, Gong L, Liu X, Luo J. Spatiotemporal distribution of phenolamides and the genetics of natural variation of hydroxycinnamoyl spermidine in rice. MOLECULAR PLANT 2015; 8:111-21. [PMID: 25578276 DOI: 10.1016/j.molp.2014.11.003] [Citation(s) in RCA: 85] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/02/2014] [Accepted: 09/02/2014] [Indexed: 05/03/2023]
Abstract
Phenolamides constitute a diverse class of secondary metabolites that are found ubiquitously in plants and have been implicated to play an important role in a wide range of biological processes, such as plant development and defense. However, spatiotemporal accumulation patterns of phenolamides in rice, one of the most important crops, are not available, and no gene responsible for phenolamide biosynthesis has been identified in this species. In this study, we report the comprehensive metabolic profiling and natural variation analysis of phenolamides in a collection of rice germplasm using a liquid chromatography-mass spectrometry-based targeted metabolomics method. Spatiotemporal controlled accumulations were observed for most phenolamides, together with their differential accumulations between the two major subspecies of rice. Further metabolic genome-wide association study (mGWAS) in rice leaf and in vivo metabolic analysis of the transgenic plants identified Os12g27220 and Os12g27254 as two spermidine hydroxycinnamoyl transferases that might underlie the natural variation of levels of spermidine conjugates in rice. Our work demonstrates that gene-to-metabolite analysis by mGWAS provides a useful tool for functional gene identification and omics-based crop genetic improvement.
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Affiliation(s)
- Xuekui Dong
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Yanqiang Gao
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Wei Chen
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Wensheng Wang
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Liang Gong
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Xianqing Liu
- College of Life Science and Technology, Huazhong Agricultural University, Wuhan 430070, China
| | - Jie Luo
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China.
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662
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Zhang J, Mason AS, Wu J, Liu S, Zhang X, Luo T, Redden R, Batley J, Hu L, Yan G. Identification of Putative Candidate Genes for Water Stress Tolerance in Canola (Brassica napus). FRONTIERS IN PLANT SCIENCE 2015; 6:1058. [PMID: 26640475 PMCID: PMC4661274 DOI: 10.3389/fpls.2015.01058] [Citation(s) in RCA: 49] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/16/2015] [Accepted: 11/13/2015] [Indexed: 05/20/2023]
Abstract
Drought stress can directly inhibit seedling establishment in canola (Brassica napus), resulting in lower plant densities and reduced yields. To dissect this complex trait, 140 B. napus accessions were phenotyped under normal (0.0 MPa, S0) and water-stressed conditions simulated by polyethylene glycol (PEG) 6000 (-0.5 MPa, S5) in a hydroponic system. Phenotypic variation and heritability indicated that the root to shoot length ratio was a reliable indicator for water stress tolerance. Thereafter, 66 accessions (16 water stress tolerant, 34 moderate and 16 sensitive lines) were genotyped using 25,495 Brassica single nucleotide polymorphisms (SNPs). Genome-wide association studies (GWAS) identified 16 loci significantly associated with water stress response. Two B. napus accessions were used for RNA sequencing, with differentially-expressed genes under normal and water-stressed conditions examined. By combining differentially-expressed genes detected by RNA sequencing with significantly associated loci from GWAS, 79 candidate genes were identified, of which eight were putatively associated with drought tolerance based on gene ontology of Arabidopsis. Functional validation of these genes may confirm key drought-related genes for selection and breeding in B. napus. Our results provide insight into the genetic basis of water stress tolerance in canola.
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Affiliation(s)
- Jing Zhang
- Ministry of Agriculture (MOA) Key Laboratory of Crop Ecophysiology and Farming System in the Middle Reaches of the Yangtze River, College of Plant Science and Technology, Huazhong Agricultural UniversityWuhan, China
- Centre for Plant Genetics and Breeding, School of Plant Biology, Faculty of Science and The UWA Institute of Agriculture, The University of Western AustraliaPerth, WA, Australia
| | - Annaliese S. Mason
- Plant Breeding Department, IFZ Research Centre for Biosystems, Land Use and Nutrition, Justus Liebig UniversityGiessen, Germany
- School of Agriculture and Food Sciences and Centre for Integrative Legume Research, The University of QueenslandBrisbane, QLD, Australia
| | - Jian Wu
- National Key Laboratory of Crop Genetic Improvement, College of Plant Science and Technology, Huazhong Agricultural UniversityWuhan, China
| | - Sheng Liu
- National Key Laboratory of Crop Genetic Improvement, College of Plant Science and Technology, Huazhong Agricultural UniversityWuhan, China
| | - Xuechen Zhang
- Centre for Plant Genetics and Breeding, School of Plant Biology, Faculty of Science and The UWA Institute of Agriculture, The University of Western AustraliaPerth, WA, Australia
| | - Tao Luo
- Ministry of Agriculture (MOA) Key Laboratory of Crop Ecophysiology and Farming System in the Middle Reaches of the Yangtze River, College of Plant Science and Technology, Huazhong Agricultural UniversityWuhan, China
| | - Robert Redden
- Australian Grains Genebank, Department of Economic Development Jobs Transport and ResourcesHorsham, VIC, Australia
| | - Jacqueline Batley
- Centre for Plant Genetics and Breeding, School of Plant Biology, Faculty of Science and The UWA Institute of Agriculture, The University of Western AustraliaPerth, WA, Australia
- School of Agriculture and Food Sciences and Centre for Integrative Legume Research, The University of QueenslandBrisbane, QLD, Australia
| | - Liyong Hu
- Ministry of Agriculture (MOA) Key Laboratory of Crop Ecophysiology and Farming System in the Middle Reaches of the Yangtze River, College of Plant Science and Technology, Huazhong Agricultural UniversityWuhan, China
- *Correspondence: Liyong Hu
| | - Guijun Yan
- Centre for Plant Genetics and Breeding, School of Plant Biology, Faculty of Science and The UWA Institute of Agriculture, The University of Western AustraliaPerth, WA, Australia
- Guijun Yan
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663
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Matsuda F, Nakabayashi R, Yang Z, Okazaki Y, Yonemaru JI, Ebana K, Yano M, Saito K. Metabolome-genome-wide association study dissects genetic architecture for generating natural variation in rice secondary metabolism. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2015; 81:13-23. [PMID: 25267402 PMCID: PMC4309412 DOI: 10.1111/tpj.12681] [Citation(s) in RCA: 108] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/24/2014] [Revised: 09/19/2014] [Accepted: 09/19/2014] [Indexed: 05/18/2023]
Abstract
Plants produce structurally diverse secondary (specialized) metabolites to increase their fitness for survival under adverse environments. Several bioactive compounds for new drugs have been identified through screening of plant extracts. In this study, genome-wide association studies (GWAS) were conducted to investigate the genetic architecture behind the natural variation of rice secondary metabolites. GWAS using the metabolome data of 175 rice accessions successfully identified 323 associations among 143 single nucleotide polymorphisms (SNPs) and 89 metabolites. The data analysis highlighted that levels of many metabolites are tightly associated with a small number of strong quantitative trait loci (QTLs). The tight association may be a mechanism generating strains with distinct metabolic composition through the crossing of two different strains. The results indicate that one plant species produces more diverse phytochemicals than previously expected, and plants still contain many useful compounds for human applications.
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Affiliation(s)
- Fumio Matsuda
- RIKEN Center for Sustainable Resource Science1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Japan
- Department of Bioinformatic Engineering, Graduate School of Information Science and Technology, Osaka University1-5 Yamadaoka, Suita, Osaka, Japan
| | - Ryo Nakabayashi
- RIKEN Center for Sustainable Resource Science1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Japan
| | - Zhigang Yang
- RIKEN Center for Sustainable Resource Science1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Japan
| | - Yozo Okazaki
- RIKEN Center for Sustainable Resource Science1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Japan
| | - Jun-ichi Yonemaru
- National Institute of Agrobiological Sciences2-1-2 Kannondai, Tsukuba, Ibaraki, Japan
| | - Kaworu Ebana
- National Institute of Agrobiological Sciences2-1-2 Kannondai, Tsukuba, Ibaraki, Japan
| | - Masahiro Yano
- National Institute of Agrobiological Sciences2-1-2 Kannondai, Tsukuba, Ibaraki, Japan
| | - Kazuki Saito
- RIKEN Center for Sustainable Resource Science1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Japan
- Graduate School of Pharmaceutical Sciences, Chiba UniversityInohana 1-8-1, Chuo-ku, Chiba, Japan
- *For correspondence (e-mail )
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Isidro J, Jannink JL, Akdemir D, Poland J, Heslot N, Sorrells ME. Training set optimization under population structure in genomic selection. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2015; 128:145-58. [PMID: 25367380 PMCID: PMC4282691 DOI: 10.1007/s00122-014-2418-4] [Citation(s) in RCA: 164] [Impact Index Per Article: 18.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/07/2014] [Accepted: 10/12/2014] [Indexed: 05/17/2023]
Abstract
Population structure must be evaluated before optimization of the training set population. Maximizing the phenotypic variance captured by the training set is important for optimal performance. The optimization of the training set (TRS) in genomic selection has received much interest in both animal and plant breeding, because it is critical to the accuracy of the prediction models. In this study, five different TRS sampling algorithms, stratified sampling, mean of the coefficient of determination (CDmean), mean of predictor error variance (PEVmean), stratified CDmean (StratCDmean) and random sampling, were evaluated for prediction accuracy in the presence of different levels of population structure. In the presence of population structure, the most phenotypic variation captured by a sampling method in the TRS is desirable. The wheat dataset showed mild population structure, and CDmean and stratified CDmean methods showed the highest accuracies for all the traits except for test weight and heading date. The rice dataset had strong population structure and the approach based on stratified sampling showed the highest accuracies for all traits. In general, CDmean minimized the relationship between genotypes in the TRS, maximizing the relationship between TRS and the test set. This makes it suitable as an optimization criterion for long-term selection. Our results indicated that the best selection criterion used to optimize the TRS seems to depend on the interaction of trait architecture and population structure.
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665
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Ueda Y, Frimpong F, Qi Y, Matthus E, Wu L, Höller S, Kraska T, Frei M. Genetic dissection of ozone tolerance in rice (Oryza sativa L.) by a genome-wide association study. JOURNAL OF EXPERIMENTAL BOTANY 2015; 66:293-306. [PMID: 25371505 PMCID: PMC4265164 DOI: 10.1093/jxb/eru419] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/20/2023]
Abstract
Tropospheric ozone causes various negative effects on plants and affects the yield and quality of agricultural crops. Here, we report a genome-wide association study (GWAS) in rice (Oryza sativa L.) to determine candidate loci associated with ozone tolerance. A diversity panel consisting of 328 accessions representing all subgroups of O. sativa was exposed to ozone stress at 60 nl l(-1) for 7h every day throughout the growth season, or to control conditions. Averaged over all genotypes, ozone significantly affected biomass-related traits (plant height -1.0%, shoot dry weight -15.9%, tiller number -8.3%, grain weight -9.3%, total panicle weight -19.7%, single panicle weight -5.5%) and biochemical/physiological traits (symptom formation, SPAD value -4.4%, foliar lignin content +3.4%). A wide range of genotypic variance in response to ozone stress were observed in all phenotypes. Association mapping based on more than 30 000 single-nucleotide polymorphism (SNP) markers yielded 16 significant markers throughout the genome by applying a significance threshold of P<0.0001. Furthermore, by determining linkage disequilibrium blocks associated with significant SNPs, we gained a total of 195 candidate genes for these traits. The following sequence analysis revealed a number of novel polymorphisms in two candidate genes for the formation of visible leaf symptoms, a RING and an EREBP gene, both of which are involved in cell death and stress defence reactions. This study demonstrated substantial natural variation of responses to ozone in rice and the possibility of using GWAS in elucidating the genetic factors underlying ozone tolerance.
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Affiliation(s)
- Yoshiaki Ueda
- Institute of Crop Science and Resource Conservation (INRES), University of Bonn, Karlrobert-Kreiten Strasse 13, 53115 Bonn, Germany
| | - Felix Frimpong
- Institute of Crop Science and Resource Conservation (INRES), University of Bonn, Karlrobert-Kreiten Strasse 13, 53115 Bonn, Germany
| | - Yitao Qi
- Key Laboratory of Crop Genetics & Physiology of Jiangsu Province, Yangzhou University, Yangzhou 225009, PR China
| | - Elsa Matthus
- Institute of Crop Science and Resource Conservation (INRES), University of Bonn, Karlrobert-Kreiten Strasse 13, 53115 Bonn, Germany
| | - Linbo Wu
- Institute of Crop Science and Resource Conservation (INRES), University of Bonn, Karlrobert-Kreiten Strasse 13, 53115 Bonn, Germany
| | - Stefanie Höller
- Institute of Crop Science and Resource Conservation (INRES), University of Bonn, Karlrobert-Kreiten Strasse 13, 53115 Bonn, Germany
| | - Thorsten Kraska
- Campus Klein-Altendorf, University of Bonn, Klein-Altendorf 2, 53359 Rheinbach, Germany
| | - Michael Frei
- Institute of Crop Science and Resource Conservation (INRES), University of Bonn, Karlrobert-Kreiten Strasse 13, 53115 Bonn, Germany
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666
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Naegele RP, Tomlinson AJ, Hausbeck MK. Evaluation of a Diverse, Worldwide Collection of Wild, Cultivated, and Landrace Pepper (Capsicum annuum) for Resistance to Phytophthora Fruit Rot, Genetic Diversity, and Population Structure. PHYTOPATHOLOGY 2015; 105:110-118. [PMID: 25054617 DOI: 10.1094/phyto-02-14-0031-r] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
Abstract
Pepper is the third most important solanaceous crop in the United States and fourth most important worldwide. To identify sources of resistance for commercial breeding, 170 pepper genotypes from five continents and 45 countries were evaluated for Phytophthora fruit rot resistance using two isolates of Phytophthora capsici. Genetic diversity and population structure were assessed on a subset of 157 genotypes using 23 polymorphic simple sequence repeats. Partial resistance and isolate-specific interactions were identified in the population at both 3 and 5 days postinoculation (dpi). Plant introductions (PIs) 640833 and 566811 were the most resistant lines evaluated at 5 dpi to isolates 12889 and OP97, with mean lesion areas less than Criollo de Morelos. Genetic diversity was moderate (0.44) in the population. The program STRUCTURE inferred four genetic clusters with moderate to very great differentiation among clusters. Most lines evaluated were susceptible or moderately susceptible at 5 dpi, and no lines evaluated were completely resistant to Phytophthora fruit rot. Significant population structure was detected when pepper varieties were grouped by predefined categories of disease resistance, continent, and country of origin. Moderately resistant or resistant PIs to both isolates of P. capsici at 5 dpi were in genetic clusters one and two.
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667
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Dhanapal AP, Ray JD, Singh SK, Hoyos-Villegas V, Smith JR, Purcell LC, Andy King C, Cregan PB, Song Q, Fritschi FB. Genome-wide association study (GWAS) of carbon isotope ratio (δ13C) in diverse soybean [Glycine max (L.) Merr.] genotypes. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2015; 128:73-91. [PMID: 25367378 DOI: 10.1007/s00122-014-2413-9] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/14/2014] [Accepted: 10/11/2014] [Indexed: 05/10/2023]
Abstract
KEY MESSAGE Using genome-wide association studies, 39 SNP markers likely tagging 21 different loci for carbon isotope ratio (δ (13) C) were identified in soybean. Water deficit stress is a major factor limiting soybean [Glycine max (L.) Merr.] yield. Soybean genotypes with improved water use efficiency (WUE) may be used to develop cultivars with increased yield under drought. A collection of 373 diverse soybean genotypes was grown in four environments (2 years and two locations) and characterized for carbon isotope ratio (δ(13)C) as a surrogate measure of WUE. Population structure was assessed based on 12,347 single nucleotide polymorphisms (SNPs), and genome-wide association studies (GWAS) were conducted to identify SNPs associated with δ(13)C. Across all four environments, δ(13)C ranged from a minimum of -30.55‰ to a maximum of -27.74‰. Although δ(13)C values were significantly different between the two locations in both years, results were consistent among genotypes across years and locations. Diversity analysis indicated that eight subpopulations could contain all individuals and revealed that within-subpopulation diversity, rather than among-subpopulation diversity, explained most (80%) of the diversity among the 373 genotypes. A total of 39 SNPs that showed a significant association with δ(13)C in at least two environments or for the average across all environments were identified by GWAS. Fifteen of these SNPs were located within a gene. The 39 SNPs likely tagged 21 different loci and demonstrated that markers for δ(13)C can be identified in soybean using GWAS. Further research is necessary to confirm the marker associations identified and to evaluate their usefulness for selecting genotypes with increased WUE.
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668
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Gao F, Wen W, Liu J, Rasheed A, Yin G, Xia X, Wu X, He Z. Genome-Wide Linkage Mapping of QTL for Yield Components, Plant Height and Yield-Related Physiological Traits in the Chinese Wheat Cross Zhou 8425B/Chinese Spring. FRONTIERS IN PLANT SCIENCE 2015; 6:1099. [PMID: 26734019 PMCID: PMC4683206 DOI: 10.3389/fpls.2015.01099] [Citation(s) in RCA: 128] [Impact Index Per Article: 14.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/25/2015] [Accepted: 11/22/2015] [Indexed: 05/18/2023]
Abstract
Identification of genes for yield components, plant height (PH), and yield-related physiological traits and tightly linked molecular markers is of great importance in marker-assisted selection (MAS) in wheat breeding. In the present study, 246 F8 RILs derived from the cross of Zhou 8425B/Chinese Spring were genotyped using the high-density Illumina iSelect 90K single nucleotide polymorphism (SNP) assay. Field trials were conducted at Zhengzhou and Zhoukou of Henan Province, during the 2012-2013 and 2013-2014 cropping season under irrigated conditions, providing data for four environments. Analysis of variance (ANOVA) of agronomic and physiological traits revealed significant differences (P < 0.01) among RILs, environments, and RILs × environments interactions. Broad-sense heritabilities of all traits including thousand kernel weight (TKW), PH, spike length (SL), kernel number per spike (KNS), spike number/m(2) (SN), normalized difference in vegetation index at anthesis (NDVI-A) and at 10 days post-anthesis (NDVI-10), SPAD value of chlorophyll content at anthesis (Chl-A) and at 10 days post-anthesis (Chl-10) ranged between 0.65 and 0.94. A linkage map spanning 3609.4 cM was constructed using 5636 polymorphic SNP markers, with an average chromosome length of 171.9 cM and marker density of 0.64 cM/marker. A total of 866 SNP markers were newly mapped to the hexaploid wheat linkage map. Eighty-six QTL for yield components, PH, and yield-related physiological traits were detected on 18 chromosomes except 1D, 5D, and 6D, explaining 2.3-33.2% of the phenotypic variance. Ten stable QTL were identified across four environments, viz. QTKW.caas-6A.1, QTKW.caas-7AL, QKNS.caas-4AL, QSN.caas-1AL.1, QPH.caas-4BS.2, QPH.caas-4DS.1, QSL.caas-4AS, QSL.caas-4AL.1, QChl-A.caas-5AL, and QChl-10.caas-5BL. Meanwhile, 10 QTL-rich regions were found on chromosome 1BS, 2AL (2), 3AL, 4AL (2), 4BS, 4DS, 5BL, and 7AL exhibiting pleiotropic effects. These QTL or QTL clusters are tightly linked to SNP markers, with genetic distances to the closest SNPs ranging from 0 to 1.5 cM, and could serve as target regions for fine mapping, candidate gene discovery, and MAS in wheat breeding.
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Affiliation(s)
- Fengmei Gao
- Key Laboratory of Soybean Biology, Soybean Research Institute, Ministry of Education, Northeast Agricultural UniversityHarbin, China
- National Wheat Improvement Center, Institute of Crop Science, Chinese Academy of Agricultural SciencesBeijing, China
- Keshan Sub-Academy, Heilongjiang Academy of Agricultural SciencesKeshan, China
| | - Weie Wen
- National Wheat Improvement Center, Institute of Crop Science, Chinese Academy of Agricultural SciencesBeijing, China
| | - Jindong Liu
- National Wheat Improvement Center, Institute of Crop Science, Chinese Academy of Agricultural SciencesBeijing, China
| | - Awais Rasheed
- National Wheat Improvement Center, Institute of Crop Science, Chinese Academy of Agricultural SciencesBeijing, China
- International Maize and Wheat Improvement Center (CIMMYT) China Office, c/o Chinese Academy of Agricultural SciencesBeijing, China
| | - Guihong Yin
- Zhoukou Academy of Agricultural SciencesZhoukou, China
| | - Xianchun Xia
- National Wheat Improvement Center, Institute of Crop Science, Chinese Academy of Agricultural SciencesBeijing, China
| | - Xiaoxia Wu
- Key Laboratory of Soybean Biology, Soybean Research Institute, Ministry of Education, Northeast Agricultural UniversityHarbin, China
- *Correspondence: Xiaoxia Wu
| | - Zhonghu He
- National Wheat Improvement Center, Institute of Crop Science, Chinese Academy of Agricultural SciencesBeijing, China
- International Maize and Wheat Improvement Center (CIMMYT) China Office, c/o Chinese Academy of Agricultural SciencesBeijing, China
- Zhonghu He
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Qian L, Qian W, Snowdon RJ. Sub-genomic selection patterns as a signature of breeding in the allopolyploid Brassica napus genome. BMC Genomics 2014; 15:1170. [PMID: 25539568 PMCID: PMC4367848 DOI: 10.1186/1471-2164-15-1170] [Citation(s) in RCA: 86] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2014] [Accepted: 12/18/2014] [Indexed: 02/07/2023] Open
Abstract
Background High-density single-nucleotide polymorphism (SNP) genotyping arrays are a powerful tool for genome-wide association studies and can give valuable insight into patterns of population structure and linkage disequilibrium (LD). In this study we used the Brassica 60kSNP Illumina consortium genotyping array to assess the influence of selection and breeding for important agronomic traits on LD and haplotype structure in a diverse panel of 203 Chinese semi-winter rapeseed (Brassica napus) breeding lines. Results Population structure and principal coordinate analysis, using a subset of the SNPs, revealed diversification into three subpopulations and one mixed population, reflecting targeted introgressions from external gene pools during breeding. Pairwise LD analysis within the A- and C-subgenomes of allopolyploid B. napus revealed that mean LD, at a threshold of r2 = 0.1, decayed on average around ten times more rapidly in the A-subgenome (0.25-0.30 Mb) than in the C-subgenome (2.00-2.50 Mb). A total of 3,097 conserved haplotype blocks were detected over a total length of 182.49 Mb (15.17% of the genome). The mean size of haplotype blocks was considerably longer in the C-subgenome (102.85 Kb) than in the A-subgenome (33.51 Kb), and extremely large conserved haplotype blocks were found on a number of C-genome chromosomes. Comparative sequence analysis revealed conserved blocks containing homoloeogous quantitative trait loci (QTL) for seed erucic acid and glucosinolate content, two key seed quality traits under strong agronomic selection. Interestingly, C-subgenome QTL were associated with considerably greater conservation of LD than their corresponding A-subgenome homoeologues. Conclusions The data we present in this paper provide evidence for strong selection of large chromosome regions associated with important rapeseed seed quality traits conferred by C-subgenome QTL. This implies that an increase in genetic diversity and recombination within the C-genome is particularly important for breeding. The resolution of genome-wide association studies is also expected to vary greatly across different genome regions. Electronic supplementary material The online version of this article (doi:10.1186/1471-2164-15-1170) contains supplementary material, which is available to authorized users.
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Affiliation(s)
| | | | - Rod J Snowdon
- Department of Plant Breeding, IFZ Research Centre for Biosystems, Land Use and Nutrition, Justus Liebig University, Heinrich-Buff-Ring 26-32, 35392 Giessen, Germany.
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670
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Abstract
Heritability is a central parameter in quantitative genetics, from both an evolutionary and a breeding perspective. For plant traits heritability is traditionally estimated by comparing within- and between-genotype variability. This approach estimates broad-sense heritability and does not account for different genetic relatedness. With the availability of high-density markers there is growing interest in marker-based estimates of narrow-sense heritability, using mixed models in which genetic relatedness is estimated from genetic markers. Such estimates have received much attention in human genetics but are rarely reported for plant traits. A major obstacle is that current methodology and software assume a single phenotypic value per genotype, hence requiring genotypic means. An alternative that we propose here is to use mixed models at the individual plant or plot level. Using statistical arguments, simulations, and real data we investigate the feasibility of both approaches and how these affect genomic prediction with the best linear unbiased predictor and genome-wide association studies. Heritability estimates obtained from genotypic means had very large standard errors and were sometimes biologically unrealistic. Mixed models at the individual plant or plot level produced more realistic estimates, and for simulated traits standard errors were up to 13 times smaller. Genomic prediction was also improved by using these mixed models, with up to a 49% increase in accuracy. For genome-wide association studies on simulated traits, the use of individual plant data gave almost no increase in power. The new methodology is applicable to any complex trait where multiple replicates of individual genotypes can be scored. This includes important agronomic crops, as well as bacteria and fungi.
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671
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Phung NTP, Mai CD, Mournet P, Frouin J, Droc G, Ta NK, Jouannic S, Lê LT, Do VN, Gantet P, Courtois B. Characterization of a panel of Vietnamese rice varieties using DArT and SNP markers for association mapping purposes. BMC PLANT BIOLOGY 2014; 14:371. [PMID: 25524444 PMCID: PMC4279583 DOI: 10.1186/s12870-014-0371-7] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/21/2014] [Accepted: 12/08/2014] [Indexed: 05/20/2023]
Abstract
BACKGROUND The development of genome-wide association studies (GWAS) in crops has made it possible to mine interesting alleles hidden in gene bank resources. However, only a small fraction of the rice genetic diversity of any given country has been exploited in the studies with worldwide sampling conducted to date. This study presents the development of a panel of rice varieties from Vietnam for GWAS purposes. RESULTS The panel, initially composed of 270 accessions, was characterized for simple agronomic traits (maturity class, grain shape and endosperm type) commonly used to classify rice varieties. We first genotyped the panel using Diversity Array Technology (DArT) markers. We analyzed the panel structure, identified two subpanels corresponding to the indica and japonica sub-species and selected 182 non-redundant accessions. However, the number of usable DArT markers (241 for an initial library of 6444 clones) was too small for GWAS purposes. Therefore, we characterized the panel of 182 accessions with 25,971 markers using genotyping by sequencing. The same indica and japonica subpanels were identified. The indica subpanel was further divided into six populations (I1 to I6) using a model-based approach. The japonica subpanel, which was more highly differentiated, was divided into 4 populations (J1 to J4), including a temperate type (J2). Passport data and phenotypic traits were used to characterize these populations. Some populations were exclusively composed of glutinous types (I3 and J2). Some of the upland rice varieties appeared to belong to indica populations, which is uncommon in this region of the world. Linkage disequilibrium decayed faster in the indica subpanel (r2 below 0.2 at 101 kb) than in the japonica subpanel (r2 below 0.2 at 425 kb), likely because of the strongest differentiation of the japonica subpanel. A matrix adapted for GWAS was built by eliminating the markers with a minor allele frequency below 5% and imputing the missing data. This matrix contained 21,814 markers. A GWAS was conducted on time to flowering to prove the utility of this panel. CONCLUSIONS This publicly available panel constitutes an important resource giving access to original allelic diversity. It will be used for GWAS on root and panicle traits.
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Affiliation(s)
- Nhung Thi Phuong Phung
- />Agricultural Genetics Institute, National Key Laboratory for Plant Cell Biotechnology, LMI RICE, Hanoi, Vietnam
| | - Chung Duc Mai
- />Agricultural Genetics Institute, National Key Laboratory for Plant Cell Biotechnology, LMI RICE, Hanoi, Vietnam
- />University of Science and Technology of Hanoi, LMI RICE, Hanoi, Vietnam
| | | | | | - Gaëtan Droc
- />Cirad, UMR-AGAP, 34398 Montpellier, France
| | - Nhung Kim Ta
- />Agricultural Genetics Institute, National Key Laboratory for Plant Cell Biotechnology, LMI RICE, Hanoi, Vietnam
- />IRD, UMR-DIADE, LMI RICE, Hanoi, Vietnam
- />Université Montpellier 2, UMR DIADE, 34095 Montpellier, France
| | | | | | - Vinh Nang Do
- />Agricultural Genetics Institute, National Key Laboratory for Plant Cell Biotechnology, LMI RICE, Hanoi, Vietnam
| | - Pascal Gantet
- />IRD, UMR-DIADE, LMI RICE, Hanoi, Vietnam
- />Université Montpellier 2, UMR DIADE, 34095 Montpellier, France
- />University of Science and Technology of Hanoi, LMI RICE, Hanoi, Vietnam
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672
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Bargsten JW, Nap JP, Sanchez-Perez GF, van Dijk ADJ. Prioritization of candidate genes in QTL regions based on associations between traits and biological processes. BMC PLANT BIOLOGY 2014; 14:330. [PMID: 25492368 PMCID: PMC4274756 DOI: 10.1186/s12870-014-0330-3] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/15/2014] [Accepted: 11/10/2014] [Indexed: 05/18/2023]
Abstract
BACKGROUND Elucidation of genotype-to-phenotype relationships is a major challenge in biology. In plants, it is the basis for molecular breeding. Quantitative Trait Locus (QTL) mapping enables to link variation at the trait level to variation at the genomic level. However, QTL regions typically contain tens to hundreds of genes. In order to prioritize such candidate genes, we show that we can identify potentially causal genes for a trait based on overrepresentation of biological processes (gene functions) for the candidate genes in the QTL regions of that trait. RESULTS The prioritization method was applied to rice QTL data, using gene functions predicted on the basis of sequence- and expression-information. The average reduction of the number of genes was over ten-fold. Comparison with various types of experimental datasets (including QTL fine-mapping and Genome Wide Association Study results) indicated both statistical significance and biological relevance of the obtained connections between genes and traits. A detailed analysis of flowering time QTLs illustrates that genes with completely unknown function are likely to play a role in this important trait. CONCLUSIONS Our approach can guide further experimentation and validation of causal genes for quantitative traits. This way it capitalizes on QTL data to uncover how individual genes influence trait variation.
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Affiliation(s)
- Joachim W Bargsten
- />Applied Bioinformatics, Bioscience, Plant Sciences Group, Wageningen University and Research Centre, Wageningen, The Netherlands
- />Netherlands Bioinformatics Centre (NBIC), Nijmegen, The Netherlands
- />Laboratory for Plant Breeding, Plant Sciences Group, Wageningen University and Research Centre, Wageningen, The Netherlands
| | - Jan-Peter Nap
- />Applied Bioinformatics, Bioscience, Plant Sciences Group, Wageningen University and Research Centre, Wageningen, The Netherlands
- />Netherlands Bioinformatics Centre (NBIC), Nijmegen, The Netherlands
| | - Gabino F Sanchez-Perez
- />Applied Bioinformatics, Bioscience, Plant Sciences Group, Wageningen University and Research Centre, Wageningen, The Netherlands
- />Laboratory of Bioinformatics, Plant Sciences Group, Wageningen University and Research Centre, Wageningen, The Netherlands
| | - Aalt DJ van Dijk
- />Applied Bioinformatics, Bioscience, Plant Sciences Group, Wageningen University and Research Centre, Wageningen, The Netherlands
- />Biometris, Wageningen University and Research Centre, Wageningen, The Netherlands
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673
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Schatz MC, Maron LG, Stein JC, Wences AH, Gurtowski J, Biggers E, Lee H, Kramer M, Antoniou E, Ghiban E, Wright MH, Chia JM, Ware D, McCouch SR, McCombie WR. Whole genome de novo assemblies of three divergent strains of rice, Oryza sativa, document novel gene space of aus and indica. Genome Biol 2014. [PMID: 25468217 PMCID: PMC4268812 DOI: 10.1186/s13059-014-0506-z] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
Background The use of high throughput genome-sequencing technologies has uncovered a large extent of structural variation in eukaryotic genomes that makes important contributions to genomic diversity and phenotypic variation. When the genomes of different strains of a given organism are compared, whole genome resequencing data are typically aligned to an established reference sequence. However, when the reference differs in significant structural ways from the individuals under study, the analysis is often incomplete or inaccurate. Results Here, we use rice as a model to demonstrate how improvements in sequencing and assembly technology allow rapid and inexpensive de novo assembly of next generation sequence data into high-quality assemblies that can be directly compared using whole genome alignment to provide an unbiased assessment. Using this approach, we are able to accurately assess the ‘pan-genome’ of three divergent rice varieties and document several megabases of each genome absent in the other two. Conclusions Many of the genome-specific loci are annotated to contain genes, reflecting the potential for new biological properties that would be missed by standard reference-mapping approaches. We further provide a detailed analysis of several loci associated with agriculturally important traits, including the S5 hybrid sterility locus, the Sub1 submergence tolerance locus, the LRK gene cluster associated with improved yield, and the Pup1 cluster associated with phosphorus deficiency, illustrating the utility of our approach for biological discovery. All of the data and software are openly available to support further breeding and functional studies of rice and other species. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0506-z) contains supplementary material, which is available to authorized users.
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674
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Ruggieri V, Francese G, Sacco A, D’Alessandro A, Rigano MM, Parisi M, Milone M, Cardi T, Mennella G, Barone A. An association mapping approach to identify favourable alleles for tomato fruit quality breeding. BMC PLANT BIOLOGY 2014; 14:337. [PMID: 25465385 PMCID: PMC4266912 DOI: 10.1186/s12870-014-0337-9] [Citation(s) in RCA: 57] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/09/2014] [Accepted: 11/17/2014] [Indexed: 05/20/2023]
Abstract
BACKGROUND Genome Wide Association Studies (GWAS) have been recently used to dissect complex quantitative traits and identify candidate genes affecting phenotype variation of polygenic traits. In order to map loci controlling variation in tomato marketable and nutritional fruit traits, we used a collection of 96 cultivated genotypes, including Italian, Latin American, and other worldwide-spread landraces and varieties. Phenotyping was carried out by measuring ten quality traits and metabolites in red ripe fruits. In parallel, genotyping was carried out by using the Illumina Infinium SolCAP array, which allows data to be collected from 7,720 single nucleotide polymorphism (SNP) markers. RESULTS The Mixed Linear Model used to detect associations between markers and traits allowed population structure and relatedness to be evidenced within our collection, which have been taken into consideration for association analysis. GWAS identified 20 SNPs that were significantly associated with seven out of ten traits considered. In particular, our analysis revealed two markers associated with phenolic compounds, three with ascorbic acid, β-carotene and trans-lycopene, six with titratable acidity, and only one with pH and fresh weight. Co-localization of a group of associated loci with candidate genes/QTLs previously reported in other studies validated the approach. Moreover, 19 putative genes in linkage disequilibrium with markers were found. These genes might be involved in the biosynthetic pathways of the traits analyzed or might be implied in their transcriptional regulation. Finally, favourable allelic combinations between associated loci were identified that could be pyramided to obtain new improved genotypes. CONCLUSIONS Our results led to the identification of promising candidate loci controlling fruit quality that, in the future, might be transferred into tomato genotypes by Marker Assisted Selection or genetic engineering, and highlighted that intraspecific variability might be still exploited for enhancing tomato fruit quality.
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Affiliation(s)
- Valentino Ruggieri
- />Department of Agricultural Sciences, University of Naples Federico II, Via Università 100, 80055 Portici, Italy
| | - Gianluca Francese
- />Consiglio per la Ricerca e la Sperimentazione in Agricoltura - Centro di Ricerca per l’Orticoltura (CRA-ORT), Via Cavalleggeri 25, 84098 Pontecagnano, SA Italy
| | - Adriana Sacco
- />Department of Agricultural Sciences, University of Naples Federico II, Via Università 100, 80055 Portici, Italy
| | - Antonietta D’Alessandro
- />Consiglio per la Ricerca e la Sperimentazione in Agricoltura - Centro di Ricerca per l’Orticoltura (CRA-ORT), Via Cavalleggeri 25, 84098 Pontecagnano, SA Italy
| | - Maria Manuela Rigano
- />Department of Agricultural Sciences, University of Naples Federico II, Via Università 100, 80055 Portici, Italy
| | - Mario Parisi
- />Consiglio per la Ricerca e la Sperimentazione in Agricoltura - Centro di Ricerca per l’Orticoltura (CRA-ORT), Via Cavalleggeri 25, 84098 Pontecagnano, SA Italy
| | - Marco Milone
- />Consiglio per la Ricerca e la Sperimentazione in Agricoltura - Centro di Ricerca per l’Orticoltura (CRA-ORT), Via Cavalleggeri 25, 84098 Pontecagnano, SA Italy
| | - Teodoro Cardi
- />Consiglio per la Ricerca e la Sperimentazione in Agricoltura - Centro di Ricerca per l’Orticoltura (CRA-ORT), Via Cavalleggeri 25, 84098 Pontecagnano, SA Italy
| | - Giuseppe Mennella
- />Consiglio per la Ricerca e la Sperimentazione in Agricoltura - Centro di Ricerca per l’Orticoltura (CRA-ORT), Via Cavalleggeri 25, 84098 Pontecagnano, SA Italy
| | - Amalia Barone
- />Department of Agricultural Sciences, University of Naples Federico II, Via Università 100, 80055 Portici, Italy
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Chao DY, Chen Y, Chen J, Shi S, Chen Z, Wang C, Danku JM, Zhao FJ, Salt DE. Genome-wide association mapping identifies a new arsenate reductase enzyme critical for limiting arsenic accumulation in plants. PLoS Biol 2014; 12:e1002009. [PMID: 25464340 PMCID: PMC4251824 DOI: 10.1371/journal.pbio.1002009] [Citation(s) in RCA: 152] [Impact Index Per Article: 15.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2014] [Accepted: 10/21/2014] [Indexed: 12/17/2022] Open
Abstract
Inorganic arsenic is a carcinogen, and its ingestion through foods such as rice presents a significant risk to human health. Plants chemically reduce arsenate to arsenite. Using genome-wide association (GWA) mapping of loci controlling natural variation in arsenic accumulation in Arabidopsis thaliana allowed us to identify the arsenate reductase required for this reduction, which we named High Arsenic Content 1 (HAC1). Complementation verified the identity of HAC1, and expression in Escherichia coli lacking a functional arsenate reductase confirmed the arsenate reductase activity of HAC1. The HAC1 protein accumulates in the epidermis, the outer cell layer of the root, and also in the pericycle cells surrounding the central vascular tissue. Plants lacking HAC1 lose their ability to efflux arsenite from roots, leading to both increased transport of arsenic into the central vascular tissue and on into the shoot. HAC1 therefore functions to reduce arsenate to arsenite in the outer cell layer of the root, facilitating efflux of arsenic as arsenite back into the soil to limit both its accumulation in the root and transport to the shoot. Arsenate reduction by HAC1 in the pericycle may play a role in limiting arsenic loading into the xylem. Loss of HAC1-encoded arsenic reduction leads to a significant increase in arsenic accumulation in shoots, causing an increased sensitivity to arsenate toxicity. We also confirmed the previous observation that the ACR2 arsenate reductase in A. thaliana plays no detectable role in arsenic metabolism. Furthermore, ACR2 does not interact epistatically with HAC1, since arsenic metabolism in the acr2 hac1 double mutant is disrupted in an identical manner to that described for the hac1 single mutant. Our identification of HAC1 and its associated natural variation provides an important new resource for the development of low arsenic-containing food such as rice.
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Affiliation(s)
- Dai-Yin Chao
- National Key Laboratory of Plant Molecular Genetics (NKLPMG), Institute of Plant Physiology and Ecology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China
- Institute of Biological and Environmental Sciences, University of Aberdeen, Aberdeen, United Kingdom
- * E-mail: (DYC); (FJZ); (DES)
| | - Yi Chen
- Sustainable Soils and Grassland Systems Department, Rothamsted Research, Harpenden, Hertfordshire, United Kingdom
| | - Jiugeng Chen
- National Key Laboratory of Plant Molecular Genetics (NKLPMG), Institute of Plant Physiology and Ecology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Shulin Shi
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, College of Resources and Environmental Sciences, Nanjing Agricultural University, Nanjing, China
| | - Ziru Chen
- National Key Laboratory of Plant Molecular Genetics (NKLPMG), Institute of Plant Physiology and Ecology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Chengcheng Wang
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, College of Resources and Environmental Sciences, Nanjing Agricultural University, Nanjing, China
| | - John M. Danku
- Institute of Biological and Environmental Sciences, University of Aberdeen, Aberdeen, United Kingdom
| | - Fang-Jie Zhao
- State Key Laboratory of Crop Genetics and Germplasm Enhancement, College of Resources and Environmental Sciences, Nanjing Agricultural University, Nanjing, China
- Rothamsted Research, Harpenden, Hertfordshire, United Kingdom
- * E-mail: (DYC); (FJZ); (DES)
| | - David E. Salt
- Institute of Biological and Environmental Sciences, University of Aberdeen, Aberdeen, United Kingdom
- * E-mail: (DYC); (FJZ); (DES)
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676
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Chen D, Neumann K, Friedel S, Kilian B, Chen M, Altmann T, Klukas C. Dissecting the phenotypic components of crop plant growth and drought responses based on high-throughput image analysis. THE PLANT CELL 2014; 26:4636-55. [PMID: 25501589 PMCID: PMC4311194 DOI: 10.1105/tpc.114.129601] [Citation(s) in RCA: 178] [Impact Index Per Article: 17.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/03/2014] [Revised: 11/20/2014] [Accepted: 11/21/2014] [Indexed: 05/18/2023]
Abstract
Significantly improved crop varieties are urgently needed to feed the rapidly growing human population under changing climates. While genome sequence information and excellent genomic tools are in place for major crop species, the systematic quantification of phenotypic traits or components thereof in a high-throughput fashion remains an enormous challenge. In order to help bridge the genotype to phenotype gap, we developed a comprehensive framework for high-throughput phenotype data analysis in plants, which enables the extraction of an extensive list of phenotypic traits from nondestructive plant imaging over time. As a proof of concept, we investigated the phenotypic components of the drought responses of 18 different barley (Hordeum vulgare) cultivars during vegetative growth. We analyzed dynamic properties of trait expression over growth time based on 54 representative phenotypic features. The data are highly valuable to understand plant development and to further quantify growth and crop performance features. We tested various growth models to predict plant biomass accumulation and identified several relevant parameters that support biological interpretation of plant growth and stress tolerance. These image-based traits and model-derived parameters are promising for subsequent genetic mapping to uncover the genetic basis of complex agronomic traits. Taken together, we anticipate that the analytical framework and analysis results presented here will be useful to advance our views of phenotypic trait components underlying plant development and their responses to environmental cues.
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Affiliation(s)
- Dijun Chen
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), D-06466 Gatersleben, Germany Department of Bioinformatics, College of Life Sciences, Zhejiang University, Hangzhou 310058, P.R. China
| | - Kerstin Neumann
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), D-06466 Gatersleben, Germany
| | - Swetlana Friedel
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), D-06466 Gatersleben, Germany
| | - Benjamin Kilian
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), D-06466 Gatersleben, Germany
| | - Ming Chen
- Department of Bioinformatics, College of Life Sciences, Zhejiang University, Hangzhou 310058, P.R. China
| | - Thomas Altmann
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), D-06466 Gatersleben, Germany
| | - Christian Klukas
- Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), D-06466 Gatersleben, Germany
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677
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Kumar B, Talukdar A, Bala I, Verma K, Lal SK, Sapra RL, Namita B, Chander S, Tiwari R. Population structure and association mapping studies for important agronomic traits in soybean. J Genet 2014; 93:775-84. [PMID: 25572236] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/04/2023]
Abstract
The present study was carried out with a set of 96 diverse soybean genotypes with the objectives of analysing the population structure and to identify molecular markers associated with important agronomic traits. Large phenotypic variability was observed for the agronomic traits under study indicating suitability of the genotypes for association studies. The maximum values for plant height, pods per plant, seeds per pod, 100-seed weight and seed yield per plant were approximately two and half to three times more than the minimum values for the genotypes. Seed yield per plant was found to be significantly correlated with pods per plant (r = 0.77), 100-seed weight (r = 0.35) and days to maturity (r = 0.23). The population structure studies depicted the presence of seven subpopulations which nearly corresponded with the source of geographical origin of the genotypes. Linkage disequilibrium (LD) between the linked markers decreased with the increased distance, and a substantial drop in LD decay values was observed between 30 and 35 cM. Genomewide marker-traits association analysis carried out using general linear (GLM) and mixed linear models (MLM) identified six genomic regions (two of them were common in both) on chromosomes 6, 7, 8, 13, 15 and 17, which were found to be significantly associated with various important traits viz., plant height, pods per plant, 100-seed weight, plant growth habit, average number of seeds per pod, days to 50% flowering and days to maturity. The phenotypic variation explained by these loci ranged from 6.09 to 13.18% and 4.25 to 9.01% in the GLM and MLM studies, respectively. In conclusion, association mapping (AM) in soybean could be a viable alternative to conventional QTL mapping approach.
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Affiliation(s)
- Bhupender Kumar
- Cummings's Laboratory, Directorate of Maize Research, Pusa Campus, New Delhi 110 012, India.
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678
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Cormier F, Le Gouis J, Dubreuil P, Lafarge S, Praud S. A genome-wide identification of chromosomal regions determining nitrogen use efficiency components in wheat (Triticum aestivum L.). TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2014; 127:2679-93. [PMID: 25326179 DOI: 10.1007/s00122-014-2407-7] [Citation(s) in RCA: 49] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/03/2014] [Accepted: 10/03/2014] [Indexed: 05/25/2023]
Abstract
This study identified 333 genomic regions associated to 28 traits related to nitrogen use efficiency in European winter wheat using genome-wide association in a 214-varieties panel experimented in eight environments. Improving nitrogen use efficiency is a key factor to sustainably ensure global production increase. However, while high-throughput screening methods remain at a developmental stage, genetic progress may be mainly driven by marker-assisted selection. The objective of this study was to identify chromosomal regions associated with nitrogen use efficiency-related traits in bread wheat (Triticum aestivum L.) using a genome-wide association approach. Two hundred and fourteen European elite varieties were characterised for 28 traits related to nitrogen use efficiency in eight environments in which two different nitrogen fertilisation levels were tested. The genome-wide association study was carried out using 23,603 SNP with a mixed model for taking into account parentage relationships among varieties. We identified 1,010 significantly associated SNP which defined 333 chromosomal regions associated with at least one trait and found colocalisations for 39 % of these chromosomal regions. A method based on linkage disequilibrium to define the associated region was suggested and discussed with reference to false positive rate. Through a network approach, colocalisations were analysed and highlighted the impact of genomic regions controlling nitrogen status at flowering, precocity, and nitrogen utilisation on global agronomic performance. We were able to explain 40 ± 10 % of the total genetic variation. Numerous colocalisations with previously published genomic regions were observed with such candidate genes as Ppd-D1, Rht-D1, NADH-Gogat, and GSe. We highlighted selection pressure on yield and nitrogen utilisation discussing allele frequencies in associated regions.
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Affiliation(s)
- Fabien Cormier
- Centre de recherche de Chappes, Biogemma, Route d'Ennezat CS90126, 63720, Chappes, France
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679
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Wang C, Yang Y, Yuan X, Xu Q, Feng Y, Yu H, Wang Y, Wei X. Genome-wide association study of blast resistance in indica rice. BMC PLANT BIOLOGY 2014; 14:311. [PMID: 25403621 PMCID: PMC4239320 DOI: 10.1186/s12870-014-0311-6] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/16/2014] [Accepted: 10/27/2014] [Indexed: 05/19/2023]
Abstract
BACKGROUND Rice blast disease is one of the most serious and recurrent problems in rice-growing regions worldwide. Most resistance genes were identified by linkage mapping using genetic populations. We extensively examined 16 rice blast strains and a further genome-wide association study based on genotyping 0.8 million single nucleotide polymorphism variants across 366 diverse indica accessions. RESULTS Totally, thirty associated loci were identified. The strongest signal (Chr11_6526998, P =1.17 × 10-17) was located within the gene Os11g0225100, one of the rice Pia-blast resistance gene. Another association signal (Chr11_30606558) was detected around the QTL Pif. Our study identified the gene Os11g0704100, a disease resistance protein containing nucleotide binding site-leucine rich repeat domain, as the main candidate gene of Pif. In order to explore the potential mechanism underlying the blast resistance, we further examined a locus in chromosome 12, which was associated with CH149 (P =7.53 × 10-15). The genes, Os12g0424700 and Os12g0427000, both described as kinase-like domain containing protein, were presumed to be required for the full function of this locus. Furthermore, we found some association on chromosome 3, in which it has not been reported any loci associated with rice blast resistance. In addition, we identified novel functional candidate genes, which might participate in the resistance regulation. CONCLUSIONS This work provides the basis of further study of the potential function of these candidate genes. A subset of true associations would be weakly associated with outcome in any given GWAS; therefore, large-scale replication is necessary to confirm our results. Future research will focus on validating the effects of these candidate genes and their functional variants using genetic transformation and transferred DNA insertion mutant screens, to verify that these genes engender resistance to blast disease in rice.
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Affiliation(s)
- Caihong Wang
- />State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, 310006 China
| | - Yaolong Yang
- />State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, 310006 China
- />College of Agricultural Sciences, Jiangxi Agricultural University, Nanchang, 330045 China
| | - Xiaoping Yuan
- />State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, 310006 China
| | - Qun Xu
- />State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, 310006 China
| | - Yue Feng
- />State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, 310006 China
| | - Hanyong Yu
- />State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, 310006 China
| | - Yiping Wang
- />State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, 310006 China
| | - Xinghua Wei
- />State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, 310006 China
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680
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Shrestha R, Gómez-Ariza J, Brambilla V, Fornara F. Molecular control of seasonal flowering in rice, arabidopsis and temperate cereals. ANNALS OF BOTANY 2014; 114:1445-58. [PMID: 24651369 PMCID: PMC4204779 DOI: 10.1093/aob/mcu032] [Citation(s) in RCA: 91] [Impact Index Per Article: 9.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/01/2013] [Accepted: 02/04/2014] [Indexed: 05/18/2023]
Abstract
BACKGROUND Rice (Oryza sativa) and Arabidopsis thaliana have been widely used as model systems to understand how plants control flowering time in response to photoperiod and cold exposure. Extensive research has resulted in the isolation of several regulatory genes involved in flowering and for them to be organized into a molecular network responsive to environmental cues. When plants are exposed to favourable conditions, the network activates expression of florigenic proteins that are transported to the shoot apical meristem where they drive developmental reprogramming of a population of meristematic cells. Several regulatory factors are evolutionarily conserved between rice and arabidopsis. However, other pathways have evolved independently and confer specific characteristics to flowering responses. SCOPE This review summarizes recent knowledge on the molecular mechanisms regulating daylength perception and flowering time control in arabidopsis and rice. Similarities and differences are discussed between the regulatory networks of the two species and they are compared with the regulatory networks of temperate cereals, which are evolutionarily more similar to rice but have evolved in regions where exposure to low temperatures is crucial to confer competence to flower. Finally, the role of flowering time genes in expansion of rice cultivation to Northern latitudes is discussed. CONCLUSIONS Understanding the mechanisms involved in photoperiodic flowering and comparing the regulatory networks of dicots and monocots has revealed how plants respond to environmental cues and adapt to seasonal changes. The molecular architecture of such regulation shows striking similarities across diverse species. However, integration of specific pathways on a basal scheme is essential for adaptation to different environments. Artificial manipulation of flowering time by means of natural genetic resources is essential for expanding the cultivation of cereals across different environments.
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Affiliation(s)
- Roshi Shrestha
- University of Milan, Department of Biosciences, Via Celoria 26, 20133 Milan, Italy
| | - Jorge Gómez-Ariza
- University of Milan, Department of Biosciences, Via Celoria 26, 20133 Milan, Italy
| | - Vittoria Brambilla
- University of Milan, Department of Biosciences, Via Celoria 26, 20133 Milan, Italy
| | - Fabio Fornara
- University of Milan, Department of Biosciences, Via Celoria 26, 20133 Milan, Italy
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681
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Zhang P, Liu X, Tong H, Lu Y, Li J. Association mapping for important agronomic traits in core collection of rice (Oryza sativa L.) with SSR markers. PLoS One 2014; 9:e111508. [PMID: 25360796 PMCID: PMC4216065 DOI: 10.1371/journal.pone.0111508] [Citation(s) in RCA: 40] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2014] [Accepted: 09/30/2014] [Indexed: 12/25/2022] Open
Abstract
Mining elite genes within rice landraces is of importance for the improvement of cultivated rice. An association mapping for 12 agronomic traits was carried out using a core collection of rice consisting of 150 landraces (Panel 1) with 274 simple sequence repeat (SSR) markers, and the mapping results were further verified using a Chinese national rice micro-core collection (Panel 2) and a collection from a global molecular breeding program (Panel 3). Our results showed that (1) 76 significant (P<0.05) trait-marker associations were detected using mixed linear model (MLM) within Panel 1 in two years, among which 32% were identical with previously mapped QTLs, and 11 significant associations had >10% explained ratio of genetic variation; (2) A total of seven aforementioned trait-marker associations were verified within Panel 2 and 3 when using a general linear model (GLM) and 55 SSR markers of the 76 significant trait-marker associations. However, no significant trait-marker association was found to be identical within three panels when using the MLM model; (3) several desirable alleles of the loci which showed significant trait-marker associations were identified. The research provided important information for further mining these elite genes within rice landraces and using them for rice breeding.
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Affiliation(s)
- Peng Zhang
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, South China Agricultural University, Guangzhou, China
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
| | - Xiangdong Liu
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, South China Agricultural University, Guangzhou, China
| | - Hanhua Tong
- State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, China
| | - Yonggen Lu
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, South China Agricultural University, Guangzhou, China
| | - Jinquan Li
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-bioresources, South China Agricultural University, Guangzhou, China
- Department of Plant Breeding and Genetics, Max Planck Institute for Plant Breeding Research, Cologne, Germany
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682
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Agarwal P, Parida SK, Mahto A, Das S, Mathew IE, Malik N, Tyagi AK. Expanding frontiers in plant transcriptomics in aid of functional genomics and molecular breeding. Biotechnol J 2014; 9:1480-92. [PMID: 25349922 DOI: 10.1002/biot.201400063] [Citation(s) in RCA: 45] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2014] [Revised: 09/02/2014] [Accepted: 10/01/2014] [Indexed: 12/30/2022]
Abstract
The transcript pool of a plant part, under any given condition, is a collection of mRNAs that will pave the way for a biochemical reaction of the plant to stimuli. Over the past decades, transcriptome study has advanced from Northern blotting to RNA sequencing (RNA-seq), through other techniques, of which real-time quantitative polymerase chain reaction (PCR) and microarray are the most significant ones. The questions being addressed by such studies have also matured from a solitary process to expression atlas and marker-assisted genetic enhancement. Not only genes and their networks involved in various developmental processes of plant parts have been elucidated, but also stress tolerant genes have been highlighted. The transcriptome of a plant with altered expression of a target gene has given information about the downstream genes. Marker information has been used for breeding improved varieties. Fortunately, the data generated by transcriptome analysis has been made freely available for ample utilization and comparison. The review discusses this wide variety of transcriptome data being generated in plants, which includes developmental stages, abiotic and biotic stress, effect of altered gene expression, as well as comparative transcriptomics, with a special emphasis on microarray and RNA-seq. Such data can be used to determine the regulatory gene networks, which can subsequently be utilized for generating improved plant varieties.
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Affiliation(s)
- Pinky Agarwal
- National Institute of Plant Genome Research, Aruna Asaf Ali Marg, New Delhi, India
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683
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Saxena MS, Bajaj D, Das S, Kujur A, Kumar V, Singh M, Bansal KC, Tyagi AK, Parida SK. An integrated genomic approach for rapid delineation of candidate genes regulating agro-morphological traits in chickpea. DNA Res 2014; 21:695-710. [PMID: 25335477 PMCID: PMC4263302 DOI: 10.1093/dnares/dsu031] [Citation(s) in RCA: 55] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Abstract
The identification and fine mapping of robust quantitative trait loci (QTLs)/genes governing important agro-morphological traits in chickpea still lacks systematic efforts at a genome-wide scale involving wild Cicer accessions. In this context, an 834 simple sequence repeat and single-nucleotide polymorphism marker-based high-density genetic linkage map between cultivated and wild parental accessions (Cicer arietinum desi cv. ICC 4958 and Cicer reticulatum wild cv. ICC 17160) was constructed. This inter-specific genetic map comprising eight linkage groups spanned a map length of 949.4 cM with an average inter-marker distance of 1.14 cM. Eleven novel major genomic regions harbouring 15 robust QTLs (15.6–39.8% R2 at 4.2–15.7 logarithm of odds) associated with four agro-morphological traits (100-seed weight, pod and branch number/plant and plant hairiness) were identified and mapped on chickpea chromosomes. Most of these QTLs showed positive additive gene effects with effective allelic contribution from ICC 4958, particularly for increasing seed weight (SW) and pod and branch number. One robust SW-influencing major QTL region (qSW4.2) has been narrowed down by combining QTL mapping with high-resolution QTL region-specific association analysis, differential expression profiling and gene haplotype-based association/LD mapping. This enabled to delineate a strong SW-regulating ABI3VP1 transcription factor (TF) gene at trait-specific QTL interval and consequently identified favourable natural allelic variants and superior high seed weight-specific haplotypes in the upstream regulatory region of this gene showing increased transcript expression during seed development. The genes (TFs) harbouring diverse trait-regulating QTLs, once validated and fine-mapped by our developed rapid integrated genomic approach and through gene/QTL map-based cloning, can be utilized as potential candidates for marker-assisted genetic enhancement of chickpea.
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Affiliation(s)
- Maneesha S Saxena
- National Institute of Plant Genome Research (NIPGR), Aruna Asaf Ali Marg, New Delhi 110067, India
| | - Deepak Bajaj
- National Institute of Plant Genome Research (NIPGR), Aruna Asaf Ali Marg, New Delhi 110067, India
| | - Shouvik Das
- National Institute of Plant Genome Research (NIPGR), Aruna Asaf Ali Marg, New Delhi 110067, India
| | - Alice Kujur
- National Institute of Plant Genome Research (NIPGR), Aruna Asaf Ali Marg, New Delhi 110067, India
| | - Vinod Kumar
- National Research Centre on Plant Biotechnology (NRCPB), New Delhi 110012, India
| | - Mohar Singh
- National Bureau of Plant Genetic Resources (NBPGR), New Delhi 110012, India
| | - Kailash C Bansal
- National Bureau of Plant Genetic Resources (NBPGR), New Delhi 110012, India
| | - Akhilesh K Tyagi
- National Institute of Plant Genome Research (NIPGR), Aruna Asaf Ali Marg, New Delhi 110067, India
| | - Swarup K Parida
- National Institute of Plant Genome Research (NIPGR), Aruna Asaf Ali Marg, New Delhi 110067, India
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684
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Dixit S, Huang BE, Sta Cruz MT, Maturan PT, Ontoy JCE, Kumar A. QTLs for tolerance of drought and breeding for tolerance of abiotic and biotic stress: an integrated approach. PLoS One 2014; 9:e109574. [PMID: 25314587 PMCID: PMC4196913 DOI: 10.1371/journal.pone.0109574] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2014] [Accepted: 09/01/2014] [Indexed: 11/29/2022] Open
Abstract
Background The coupling of biotic and abiotic stresses leads to high yield losses in rainfed rice (Oryza sativa L.) growing areas. While several studies target these stresses independently, breeding strategies to combat multiple stresses seldom exist. This study reports an integrated strategy that combines QTL mapping and phenotypic selection to develop rice lines with high grain yield (GY) under drought stress and non-stress conditions, and tolerance of rice blast. Methodology A blast-tolerant BC2F3-derived population was developed from the cross of tropical japonica cultivar Moroberekan (blast- and drought-tolerant) and high-yielding indica variety Swarna (blast- and drought-susceptible) through phenotypic selection for blast tolerance at the BC2F2 generation. The population was studied for segregation distortion patterns and QTLs for GY under drought were identified along with study of epistatic interactions for the trait. Results Segregation distortion, in favour of Moroberekan, was observed at 50 of the 59 loci. Majority of these marker loci co-localized with known QTLs for blast tolerance or NBS-LRR disease resistance genes. Despite the presence of segregation distortion, high variation for DTF, PH and GY was observed and several QTLs were identified under drought stress and non-stress conditions for the three traits. Epistatic interactions were also detected for GY which explained a large proportion of phenotypic variance observed in the population. Conclusions This strategy allowed us to identify QTLs for GY along with rapid development of high-yielding purelines tolerant to blast and drought with considerably reduced efforts. Apart from this, it also allowed us to study the effects of the selection cycle for blast tolerance. The developed lines were screened at IRRI and in the target environment, and drought and blast tolerant lines with high yield were identified. With tolerance to two major stresses and high yield potential, these lines may provide yield stability in rainfed rice areas.
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Affiliation(s)
- Shalabh Dixit
- International Rice Research Institute (IRRI), Los Baños, Laguna, Philippines
| | - B. Emma Huang
- Computational Informatics, CSIRO, Dutton Park, Queensland, Australia
| | - Ma. Teresa Sta Cruz
- International Rice Research Institute (IRRI), Los Baños, Laguna, Philippines
| | - Paul T. Maturan
- International Rice Research Institute (IRRI), Los Baños, Laguna, Philippines
| | | | - Arvind Kumar
- International Rice Research Institute (IRRI), Los Baños, Laguna, Philippines
- * E-mail:
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685
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Unique Genotypic Differences Discovered among Indigenous Bangladeshi Rice Landraces. Int J Genomics 2014; 2014:210328. [PMID: 25301195 PMCID: PMC4180204 DOI: 10.1155/2014/210328] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2014] [Accepted: 08/10/2014] [Indexed: 11/17/2022] Open
Abstract
Bangladesh is a reservoir of diverse rice germplasm and is home to many landraces with unique, important traits. Molecular characterization of these landraces is of value for their identification, preservation, and potential use in breeding programs. Thirty-eight rice landraces from different regions of Bangladesh including some high yielding BRRI varieties were analyzed by 34 polymorphic microsatellite markers yielding a total of 258 reproducible alleles. The analysis could locate 34 unique identifiers for 21 genotypes, making the latter potentially amenable to identity verification. An identity map for these genotypes was constructed with all the 12 chromosomes of the rice genome. Polymorphism information content (PIC) scores of the 34 SSR markers were 0.098 to 0.89 where on average 7.5 alleles were observed. A dendogram constructed using UPGMA clustered the varieties into two major groups and five subgroups. In some cases, the clustering matched with properties like aromaticity, stickiness, salt tolerance, and photoperiod insensitivity. The results will help breeders to work towards the proper utilization of these landraces for parental selection and linkage map construction for discovery of useful alleles.
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686
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Combining high-throughput phenotyping and genome-wide association studies to reveal natural genetic variation in rice. Nat Commun 2014; 5:5087. [PMID: 25295980 PMCID: PMC4214417 DOI: 10.1038/ncomms6087] [Citation(s) in RCA: 295] [Impact Index Per Article: 29.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2014] [Accepted: 08/26/2014] [Indexed: 02/06/2023] Open
Abstract
Even as the study of plant genomics rapidly develops through the use of high-throughput sequencing techniques, traditional plant phenotyping lags far behind. Here we develop a high-throughput rice phenotyping facility (HRPF) to monitor 13 traditional agronomic traits and 2 newly defined traits during the rice growth period. Using genome-wide association studies (GWAS) of the 15 traits, we identify 141 associated loci, 25 of which contain known genes such as the Green Revolution semi-dwarf gene, SD1. Based on a performance evaluation of the HRPF and GWAS results, we demonstrate that high-throughput phenotyping has the potential to replace traditional phenotyping techniques and can provide valuable gene identification information. The combination of the multifunctional phenotyping tools HRPF and GWAS provides deep insights into the genetic architecture of important traits.
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687
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Yang W, Guo Z, Huang C, Duan L, Chen G, Jiang N, Fang W, Feng H, Xie W, Lian X, Wang G, Luo Q, Zhang Q, Liu Q, Xiong L. Combining high-throughput phenotyping and genome-wide association studies to reveal natural genetic variation in rice. Nat Commun 2014. [PMID: 25295980 DOI: 10.1038/ncomm6087s] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/10/2023] Open
Abstract
Even as the study of plant genomics rapidly develops through the use of high-throughput sequencing techniques, traditional plant phenotyping lags far behind. Here we develop a high-throughput rice phenotyping facility (HRPF) to monitor 13 traditional agronomic traits and 2 newly defined traits during the rice growth period. Using genome-wide association studies (GWAS) of the 15 traits, we identify 141 associated loci, 25 of which contain known genes such as the Green Revolution semi-dwarf gene, SD1. Based on a performance evaluation of the HRPF and GWAS results, we demonstrate that high-throughput phenotyping has the potential to replace traditional phenotyping techniques and can provide valuable gene identification information. The combination of the multifunctional phenotyping tools HRPF and GWAS provides deep insights into the genetic architecture of important traits.
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Affiliation(s)
- Wanneng Yang
- 1] Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan 430074, China [2] National Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, Huazhong Agricultural University, Wuhan 430070, China [3] MoE Key Laboratory for Biomedical Photonics, Department of Biomedical Engineering, Huazhong University of Science and Technology, Wuhan 430074, China [4] College of Engineering, Huazhong Agricultural University, Wuhan 430070, China
| | - Zilong Guo
- National Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, Huazhong Agricultural University, Wuhan 430070, China
| | - Chenglong Huang
- 1] Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan 430074, China [2] MoE Key Laboratory for Biomedical Photonics, Department of Biomedical Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Lingfeng Duan
- 1] Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan 430074, China [2] MoE Key Laboratory for Biomedical Photonics, Department of Biomedical Engineering, Huazhong University of Science and Technology, Wuhan 430074, China [3] College of Engineering, Huazhong Agricultural University, Wuhan 430070, China
| | - Guoxing Chen
- MOA Key Laboratory of Crop Ecophysiology and Farming System in the Middle Reaches of the Yangtze River, Huazhong Agricultural University, Wuhan 430070, China
| | - Ni Jiang
- 1] Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan 430074, China [2] MoE Key Laboratory for Biomedical Photonics, Department of Biomedical Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Wei Fang
- 1] Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan 430074, China [2] MoE Key Laboratory for Biomedical Photonics, Department of Biomedical Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Hui Feng
- 1] Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan 430074, China [2] MoE Key Laboratory for Biomedical Photonics, Department of Biomedical Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Weibo Xie
- National Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, Huazhong Agricultural University, Wuhan 430070, China
| | - Xingming Lian
- National Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, Huazhong Agricultural University, Wuhan 430070, China
| | - Gongwei Wang
- National Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, Huazhong Agricultural University, Wuhan 430070, China
| | - Qingming Luo
- 1] Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan 430074, China [2] MoE Key Laboratory for Biomedical Photonics, Department of Biomedical Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Qifa Zhang
- National Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, Huazhong Agricultural University, Wuhan 430070, China
| | - Qian Liu
- 1] Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan 430074, China [2] MoE Key Laboratory for Biomedical Photonics, Department of Biomedical Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Lizhong Xiong
- National Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, Huazhong Agricultural University, Wuhan 430070, China
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688
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Renny-Byfield S, Wendel JF. Doubling down on genomes: polyploidy and crop plants. AMERICAN JOURNAL OF BOTANY 2014; 101:1711-25. [PMID: 25090999 DOI: 10.3732/ajb.1400119] [Citation(s) in RCA: 205] [Impact Index Per Article: 20.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/18/2023]
Abstract
Polyploidy, or whole genome multiplication, is ubiquitous among angiosperms. Many crop species are relatively recent allopolyploids, resulting from interspecific hybridization and polyploidy. Thus, an appreciation of the evolutionary consequences of (allo)polyploidy is central to our understanding of crop plant domestication, agricultural improvement, and the evolution of angiosperms in general. Indeed, many recent insights into plant biology have been gleaned from polyploid crops, including, but not limited to wheat, tobacco, sugarcane, apple, and cotton. A multitude of evolutionary processes affect polyploid genomes, including rapid and substantial genome reorganization, transgressive gene expression alterations, gene fractionation, gene conversion, genome downsizing, and sub- and neofunctionalization of duplicate genes. Often these genomic changes are accompanied by heterosis, robustness, and the improvement of crop yield, relative to closely related diploids. Historically, however, the genome-wide analysis of polyploid crops has lagged behind those of diploid crops and other model organisms. This lag is partly due to the difficulties in genome assembly, resulting from the genomic complexities induced by combining two or more evolutionarily diverged genomes into a single nucleus and by the significant size of polyploid genomes. In this review, we explore the role of polyploidy in angiosperm evolution, the domestication process and crop improvement. We focus on the potential of modern technologies, particularly next-generation sequencing, to inform us on the patterns and processes governing polyploid crop improvement and phenotypic change subsequent to domestication.
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Affiliation(s)
- Simon Renny-Byfield
- Ecology, Evolution and Organismal Biology, Iowa State University, Ames, Iowa 50011 USA
| | - Jonathan F Wendel
- Ecology, Evolution and Organismal Biology, Iowa State University, Ames, Iowa 50011 USA
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689
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Orjuela J, Sabot F, Chéron S, Vigouroux Y, Adam H, Chrestin H, Sanni K, Lorieux M, Ghesquière A. An extensive analysis of the African rice genetic diversity through a global genotyping. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2014; 127:2211-23. [PMID: 25119871 DOI: 10.1007/s00122-014-2374-z] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/16/2013] [Accepted: 07/29/2014] [Indexed: 05/04/2023]
Abstract
We present here the first curated collection of wild and cultivated African rice species. For that, we designed specific SNPs and were able to structure these very low diverse species. Oryza glaberrima, the cultivated African rice, is endemic from Africa. This species and its direct ancestor, O. barthii, are valuable tool for improvement of Asian rice O. sativa in terms of abiotic and biotic stress resistance. However, only a few limited studies about the genetic diversity of these species were performed. In the present paper, and for the first time at such extend, we genotyped 279 O. glaberrima, selected both for their impact in current breeding and for their geographical distribution, and 101 O. barthii, chosen based on their geographic origin, using a set of 235 SNPs specifically designed for African rice diversity. Using those data, we were able to structure the individuals from our sample in three populations for O. barthii, related to geography, and two populations in O. glaberrima; these two last populations cannot be linked however to any currently phenotyped trait. Moreover, we were also able to identify misclassification in O. glaberrima as well as in O. barthii and identified new form of O. sativa from the set of African varieties.
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Affiliation(s)
- Julie Orjuela
- DIADE UMR IRD/UM2, 911 Avenue Agropolis, BP 64501, 34394, Montpellier Cedex 5, France
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690
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Zhao H, Yao W, Ouyang Y, Yang W, Wang G, Lian X, Xing Y, Chen L, Xie W. RiceVarMap: a comprehensive database of rice genomic variations. Nucleic Acids Res 2014; 43:D1018-22. [PMID: 25274737 PMCID: PMC4384008 DOI: 10.1093/nar/gku894] [Citation(s) in RCA: 174] [Impact Index Per Article: 17.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
Abstract
Rice Variation Map (RiceVarMap, http:/ricevarmap.ncpgr.cn) is a database of rice genomic variations. The database provides comprehensive information of 6 551 358 single nucleotide polymorphisms (SNPs) and 1 214 627 insertions/deletions (INDELs) identified from sequencing data of 1479 rice accessions. The SNP genotypes of all accessions were imputed and evaluated, resulting in an overall missing data rate of 0.42% and an estimated accuracy greater than 99%. The SNP/INDEL genotypes of all accessions are available for online query and download. Users can search SNPs/INDELs by identifiers of the SNPs/INDELs, genomic regions, gene identifiers and keywords of gene annotation. Allele frequencies within various subpopulations and the effects of the variation that may alter the protein sequence of a gene are also listed for each SNP/INDEL. The database also provides geographical details and phenotype images for various rice accessions. In particular, the database provides tools to construct haplotype networks and design PCR-primers by taking into account surrounding known genomic variations. These data and tools are highly useful for exploring genetic variations and evolution studies of rice and other species.
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Affiliation(s)
- Hu Zhao
- National Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Wen Yao
- National Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Yidan Ouyang
- National Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Wanneng Yang
- National Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Gongwei Wang
- National Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Xingming Lian
- National Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Yongzhong Xing
- National Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Lingling Chen
- National Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Weibo Xie
- National Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
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691
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Unterseer S, Bauer E, Haberer G, Seidel M, Knaak C, Ouzunova M, Meitinger T, Strom TM, Fries R, Pausch H, Bertani C, Davassi A, Mayer KF, Schön CC. A powerful tool for genome analysis in maize: development and evaluation of the high density 600 k SNP genotyping array. BMC Genomics 2014; 15:823. [PMID: 25266061 PMCID: PMC4192734 DOI: 10.1186/1471-2164-15-823] [Citation(s) in RCA: 160] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2014] [Accepted: 09/23/2014] [Indexed: 02/07/2023] Open
Abstract
Background High density genotyping data are indispensable for genomic analyses of complex traits in animal and crop species. Maize is one of the most important crop plants worldwide, however a high density SNP genotyping array for analysis of its large and highly dynamic genome was not available so far. Results We developed a high density maize SNP array composed of 616,201 variants (SNPs and small indels). Initially, 57 M variants were discovered by sequencing 30 representative temperate maize lines and then stringently filtered for sequence quality scores and predicted conversion performance on the array resulting in the selection of 1.2 M polymorphic variants assayed on two screening arrays. To identify high-confidence variants, 285 DNA samples from a broad genetic diversity panel of worldwide maize lines including the samples used for sequencing, important founder lines for European maize breeding, hybrids, and proprietary samples with European, US, semi-tropical, and tropical origin were used for experimental validation. We selected 616 k variants according to their performance during validation, support of genotype calls through sequencing data, and physical distribution for further analysis and for the design of the commercially available Affymetrix® Axiom® Maize Genotyping Array. This array is composed of 609,442 SNPs and 6,759 indels. Among these are 116,224 variants in coding regions and 45,655 SNPs of the Illumina® MaizeSNP50 BeadChip for study comparison. In a subset of 45,974 variants, apart from the target SNP additional off-target variants are detected, which show only a minor bias towards intermediate allele frequencies. We performed principal coordinate and admixture analyses to determine the ability of the array to detect and resolve population structure and investigated the extent of LD within a worldwide validation panel. Conclusions The high density Affymetrix® Axiom® Maize Genotyping Array is optimized for European and American temperate maize and was developed based on a diverse sample panel by applying stringent quality filter criteria to ensure its suitability for a broad range of applications. With 600 k variants it is the largest currently publically available genotyping array in crop species. Electronic supplementary material The online version of this article (doi:10.1186/1471-2164-15-823) contains supplementary material, which is available to authorized users.
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Affiliation(s)
| | - Eva Bauer
- Plant Breeding, Centre of Life and Food Sciences Weihenstephan, Technische Universität München, 85354 Freising, Germany.
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692
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Saxena MS, Bajaj D, Kujur A, Das S, Badoni S, Kumar V, Singh M, Bansal KC, Tyagi AK, Parida SK. Natural allelic diversity, genetic structure and linkage disequilibrium pattern in wild chickpea. PLoS One 2014; 9:e107484. [PMID: 25222488 PMCID: PMC4164632 DOI: 10.1371/journal.pone.0107484] [Citation(s) in RCA: 44] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2014] [Accepted: 08/11/2014] [Indexed: 01/23/2023] Open
Abstract
Characterization of natural allelic diversity and understanding the genetic structure and linkage disequilibrium (LD) pattern in wild germplasm accessions by large-scale genotyping of informative microsatellite and single nucleotide polymorphism (SNP) markers is requisite to facilitate chickpea genetic improvement. Large-scale validation and high-throughput genotyping of genome-wide physically mapped 478 genic and genomic microsatellite markers and 380 transcription factor gene-derived SNP markers using gel-based assay, fluorescent dye-labelled automated fragment analyser and matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) mass array have been performed. Outcome revealed their high genotyping success rate (97.5%) and existence of a high level of natural allelic diversity among 94 wild and cultivated Cicer accessions. High intra- and inter-specific polymorphic potential and wider molecular diversity (11-94%) along with a broader genetic base (13-78%) specifically in the functional genic regions of wild accessions was assayed by mapped markers. It suggested their utility in monitoring introgression and transferring target trait-specific genomic (gene) regions from wild to cultivated gene pool for the genetic enhancement. Distinct species/gene pool-wise differentiation, admixed domestication pattern, and differential genome-wide recombination and LD estimates/decay observed in a six structured population of wild and cultivated accessions using mapped markers further signifies their usefulness in chickpea genetics, genomics and breeding.
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Affiliation(s)
- Maneesha S. Saxena
- National Institute of Plant Genome Research (NIPGR), Aruna Asaf Ali Marg, New Delhi, India
| | - Deepak Bajaj
- National Institute of Plant Genome Research (NIPGR), Aruna Asaf Ali Marg, New Delhi, India
| | - Alice Kujur
- National Institute of Plant Genome Research (NIPGR), Aruna Asaf Ali Marg, New Delhi, India
| | - Shouvik Das
- National Institute of Plant Genome Research (NIPGR), Aruna Asaf Ali Marg, New Delhi, India
| | - Saurabh Badoni
- National Institute of Plant Genome Research (NIPGR), Aruna Asaf Ali Marg, New Delhi, India
| | - Vinod Kumar
- National Research Centre on Plant Biotechnology (NRCPB), New Delhi, India
| | - Mohar Singh
- National Bureau of Plant Genetic Resources (NBPGR), New Delhi, India
| | - Kailash C. Bansal
- National Bureau of Plant Genetic Resources (NBPGR), New Delhi, India
| | - Akhilesh K. Tyagi
- National Institute of Plant Genome Research (NIPGR), Aruna Asaf Ali Marg, New Delhi, India
| | - Swarup K. Parida
- National Institute of Plant Genome Research (NIPGR), Aruna Asaf Ali Marg, New Delhi, India
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693
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Genome wide association studies using a new nonparametric model reveal the genetic architecture of 17 agronomic traits in an enlarged maize association panel. PLoS Genet 2014; 10:e1004573. [PMID: 25211220 PMCID: PMC4161304 DOI: 10.1371/journal.pgen.1004573] [Citation(s) in RCA: 225] [Impact Index Per Article: 22.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2013] [Accepted: 06/30/2014] [Indexed: 11/19/2022] Open
Abstract
Association mapping is a powerful approach for dissecting the genetic architecture of complex quantitative traits using high-density SNP markers in maize. Here, we expanded our association panel size from 368 to 513 inbred lines with 0.5 million high quality SNPs using a two-step data-imputation method which combines identity by descent (IBD) based projection and k-nearest neighbor (KNN) algorithm. Genome-wide association studies (GWAS) were carried out for 17 agronomic traits with a panel of 513 inbred lines applying both mixed linear model (MLM) and a new method, the Anderson-Darling (A-D) test. Ten loci for five traits were identified using the MLM method at the Bonferroni-corrected threshold −log10 (P) >5.74 (α = 1). Many loci ranging from one to 34 loci (107 loci for plant height) were identified for 17 traits using the A-D test at the Bonferroni-corrected threshold −log10 (P) >7.05 (α = 0.05) using 556809 SNPs. Many known loci and new candidate loci were only observed by the A-D test, a few of which were also detected in independent linkage analysis. This study indicates that combining IBD based projection and KNN algorithm is an efficient imputation method for inferring large missing genotype segments. In addition, we showed that the A-D test is a useful complement for GWAS analysis of complex quantitative traits. Especially for traits with abnormal phenotype distribution, controlled by moderate effect loci or rare variations, the A-D test balances false positives and statistical power. The candidate SNPs and associated genes also provide a rich resource for maize genetics and breeding. Genotype imputation has been used widely in the analysis of genome-wide association studies (GWAS) to boost power and fine-map associations. We developed a two-step data imputation method to meet the challenge of large proportion missing genotypes. GWAS have uncovered an extensive genetic architecture of complex quantitative traits using high-density SNP markers in maize in the past few years. Here, GWAS were carried out for 17 agronomic traits with a panel of 513 inbred lines applying both mixed linear model and a new method, the Anderson-Darling (A-D) test. We intend to show that the A-D test is a complement to current GWAS methods, especially for complex quantitative traits controlled by moderate effect loci or rare variations and with abnormal phenotype distribution. In addition, the traits associated QTL identified here provide a rich resource for maize genetics and breeding.
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694
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Wang S, Wong D, Forrest K, Allen A, Chao S, Huang BE, Maccaferri M, Salvi S, Milner SG, Cattivelli L, Mastrangelo AM, Whan A, Stephen S, Barker G, Wieseke R, Plieske J, Lillemo M, Mather D, Appels R, Dolferus R, Brown-Guedira G, Korol A, Akhunova AR, Feuillet C, Salse J, Morgante M, Pozniak C, Luo MC, Dvorak J, Morell M, Dubcovsky J, Ganal M, Tuberosa R, Lawley C, Mikoulitch I, Cavanagh C, Edwards KJ, Hayden M, Akhunov E. Characterization of polyploid wheat genomic diversity using a high-density 90,000 single nucleotide polymorphism array. PLANT BIOTECHNOLOGY JOURNAL 2014; 12:787-796. [PMID: 24646323 DOI: 10.1111/pbi.12183/pdf] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Received: 10/29/2013] [Revised: 01/29/2014] [Accepted: 02/05/2014] [Indexed: 05/29/2023]
Abstract
High-density single nucleotide polymorphism (SNP) genotyping arrays are a powerful tool for studying genomic patterns of diversity, inferring ancestral relationships between individuals in populations and studying marker-trait associations in mapping experiments. We developed a genotyping array including about 90,000 gene-associated SNPs and used it to characterize genetic variation in allohexaploid and allotetraploid wheat populations. The array includes a significant fraction of common genome-wide distributed SNPs that are represented in populations of diverse geographical origin. We used density-based spatial clustering algorithms to enable high-throughput genotype calling in complex data sets obtained for polyploid wheat. We show that these model-free clustering algorithms provide accurate genotype calling in the presence of multiple clusters including clusters with low signal intensity resulting from significant sequence divergence at the target SNP site or gene deletions. Assays that detect low-intensity clusters can provide insight into the distribution of presence-absence variation (PAV) in wheat populations. A total of 46 977 SNPs from the wheat 90K array were genetically mapped using a combination of eight mapping populations. The developed array and cluster identification algorithms provide an opportunity to infer detailed haplotype structure in polyploid wheat and will serve as an invaluable resource for diversity studies and investigating the genetic basis of trait variation in wheat.
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Affiliation(s)
- Shichen Wang
- Department of Plant Pathology, Kansas State University, Manhattan, KS, USA
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695
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Li F, Chen B, Xu K, Wu J, Song W, Bancroft I, Harper AL, Trick M, Liu S, Gao G, Wang N, Yan G, Qiao J, Li J, Li H, Xiao X, Zhang T, Wu X. Genome-wide association study dissects the genetic architecture of seed weight and seed quality in rapeseed (Brassica napus L.). DNA Res 2014; 21:355-67. [PMID: 24510440 PMCID: PMC4131830 DOI: 10.1093/dnares/dsu002] [Citation(s) in RCA: 131] [Impact Index Per Article: 13.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2013] [Accepted: 01/08/2014] [Indexed: 11/12/2022] Open
Abstract
Association mapping can quickly and efficiently dissect complex agronomic traits. Rapeseed is one of the most economically important polyploid oil crops, although its genome sequence is not yet published. In this study, a recently developed 60K Brassica Infinium(®) SNP array was used to analyse an association panel with 472 accessions. The single-nucleotide polymorphisms (SNPs) of the array were in silico mapped using 'pseudomolecules' representative of the genome of rapeseed to establish their hypothetical order and to perform association mapping of seed weight and seed quality. As a result, two significant associations on A8 and C3 of Brassica napus were detected for erucic acid content, and the peak SNPs were found to be only 233 and 128 kb away from the key genes BnaA.FAE1 and BnaC.FAE1. BnaA.FAE1 was also identified to be significantly associated with the oil content. Orthologues of Arabidopsis thaliana HAG1 were identified close to four clusters of SNPs associated with glucosinolate content on A9, C2, C7 and C9. For seed weight, we detected two association signals on A7 and A9, which were consistent with previous studies of quantitative trait loci mapping. The results indicate that our association mapping approach is suitable for fine mapping of the complex traits in rapeseed.
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Affiliation(s)
- Feng Li
- Oil Crop Research Institute, Chinese Academy of Agricultural Sciences, Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, No. 2 Xudong Second Road, Hubei Province, Wuhan 430062, China
| | - Biyun Chen
- Oil Crop Research Institute, Chinese Academy of Agricultural Sciences, Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, No. 2 Xudong Second Road, Hubei Province, Wuhan 430062, China
| | - Kun Xu
- Oil Crop Research Institute, Chinese Academy of Agricultural Sciences, Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, No. 2 Xudong Second Road, Hubei Province, Wuhan 430062, China
| | - Jinfeng Wu
- Oil Crop Research Institute, Chinese Academy of Agricultural Sciences, Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, No. 2 Xudong Second Road, Hubei Province, Wuhan 430062, China
| | - Weilin Song
- Oil Crop Research Institute, Chinese Academy of Agricultural Sciences, Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, No. 2 Xudong Second Road, Hubei Province, Wuhan 430062, China
| | - Ian Bancroft
- Department of Biology, University of York, York, UK
| | | | - Martin Trick
- John Innes Centre, Norwich Research Park, Norwich NR4 7UH, UK
| | - Shengyi Liu
- Oil Crop Research Institute, Chinese Academy of Agricultural Sciences, Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, No. 2 Xudong Second Road, Hubei Province, Wuhan 430062, China
| | - Guizhen Gao
- Oil Crop Research Institute, Chinese Academy of Agricultural Sciences, Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, No. 2 Xudong Second Road, Hubei Province, Wuhan 430062, China
| | - Nian Wang
- Oil Crop Research Institute, Chinese Academy of Agricultural Sciences, Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, No. 2 Xudong Second Road, Hubei Province, Wuhan 430062, China
| | - Guixin Yan
- Oil Crop Research Institute, Chinese Academy of Agricultural Sciences, Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, No. 2 Xudong Second Road, Hubei Province, Wuhan 430062, China
| | - Jiangwei Qiao
- Oil Crop Research Institute, Chinese Academy of Agricultural Sciences, Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, No. 2 Xudong Second Road, Hubei Province, Wuhan 430062, China
| | - Jun Li
- Oil Crop Research Institute, Chinese Academy of Agricultural Sciences, Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, No. 2 Xudong Second Road, Hubei Province, Wuhan 430062, China
| | - Hao Li
- Oil Crop Research Institute, Chinese Academy of Agricultural Sciences, Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, No. 2 Xudong Second Road, Hubei Province, Wuhan 430062, China
| | - Xin Xiao
- Oil Crop Research Institute, Chinese Academy of Agricultural Sciences, Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, No. 2 Xudong Second Road, Hubei Province, Wuhan 430062, China
| | - Tianyao Zhang
- Oil Crop Research Institute, Chinese Academy of Agricultural Sciences, Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, No. 2 Xudong Second Road, Hubei Province, Wuhan 430062, China
| | - Xiaoming Wu
- Oil Crop Research Institute, Chinese Academy of Agricultural Sciences, Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, No. 2 Xudong Second Road, Hubei Province, Wuhan 430062, China
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696
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Wang S, Wong D, Forrest K, Allen A, Chao S, Huang BE, Maccaferri M, Salvi S, Milner SG, Cattivelli L, Mastrangelo AM, Whan A, Stephen S, Barker G, Wieseke R, Plieske J, Lillemo M, Mather D, Appels R, Dolferus R, Brown‐Guedira G, Korol A, Akhunova AR, Feuillet C, Salse J, Morgante M, Pozniak C, Luo M, Dvorak J, Morell M, Dubcovsky J, Ganal M, Tuberosa R, Lawley C, Mikoulitch I, Cavanagh C, Edwards KJ, Hayden M, Akhunov E. Characterization of polyploid wheat genomic diversity using a high‐density 90 000 single nucleotide polymorphism array. PLANT BIOTECHNOLOGY JOURNAL 2014; 12:787-96. [PMID: 24646323 PMCID: PMC4265271 DOI: 10.1111/pbi.12183] [Citation(s) in RCA: 1077] [Impact Index Per Article: 107.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/29/2013] [Revised: 01/29/2014] [Accepted: 02/05/2014] [Indexed: 05/18/2023]
Affiliation(s)
- Shichen Wang
- Department of Plant Pathology Kansas State University Manhattan KS USA
| | - Debbie Wong
- Department of Environment and Primary Industry AgriBioSciences La Trobe R&D Park Bundoora Vic. Australia
| | - Kerrie Forrest
- Department of Environment and Primary Industry AgriBioSciences La Trobe R&D Park Bundoora Vic. Australia
| | - Alexandra Allen
- School of Biological Sciences University of Bristol Bristol UK
| | - Shiaoman Chao
- US Department of Agriculture–Agricultural Research Service Biosciences Research Laboratory Fargo ND USA
| | - Bevan E. Huang
- Commonwealth Scientific and Industrial Research Organization Computational Informatics and Food Futures National Research Flagship Dutton Park Qld Australia
| | - Marco Maccaferri
- Department of Agricultural Sciences University of Bologna Bologna Italy
| | - Silvio Salvi
- Department of Agricultural Sciences University of Bologna Bologna Italy
| | - Sara G. Milner
- Department of Agricultural Sciences University of Bologna Bologna Italy
| | - Luigi Cattivelli
- Consiglio per la Ricerca e la sperimentazione in Agricoltura Genomics Research Centre Fiorenzuola d'arda Italy
| | - Anna M. Mastrangelo
- Consiglio per la Ricerca e la sperimentazione in Agricoltura Cereal Research Centre Foggia Italy
| | - Alex Whan
- Commonwealth Scientific and Industrial Research Organization Plant Industry and Food Futures National Research Flagship Canberra ACT Australia
| | - Stuart Stephen
- Commonwealth Scientific and Industrial Research Organization Plant Industry and Food Futures National Research Flagship Canberra ACT Australia
| | - Gary Barker
- School of Biological Sciences University of Bristol Bristol UK
| | | | | | - Morten Lillemo
- Department of Plant Sciences Norwegian University of Life Sciences Ås Norway
| | - Diane Mather
- Waite Research Institute School of Agriculture, Food and Wine University of Adelaide Urrbrae SA Australia
| | | | - Rudy Dolferus
- Commonwealth Scientific and Industrial Research Organization Plant Industry and Food Futures National Research Flagship Canberra ACT Australia
| | - Gina Brown‐Guedira
- US Department of Agriculture–Agricultural Research Service Eastern Regional Small Grains Genotyping Laboratory Raleigh NC USA
| | - Abraham Korol
- Department of Evolutionary and Environmental Biology and Institute of Evolution University of Haifa Mount Carmel Haifa Israel
| | - Alina R. Akhunova
- K‐State Integrated Genomics Facility Kansas State University Manhattan KS USA
| | - Catherine Feuillet
- INRA – Université Blaise Pascal, UMR 1095 Genetics Diversity and Ecophysiology of Cereals Clermont‐Ferrand France
| | - Jerome Salse
- INRA – Université Blaise Pascal, UMR 1095 Genetics Diversity and Ecophysiology of Cereals Clermont‐Ferrand France
| | - Michele Morgante
- Department of Crop and Environmental Sciences University of Udine Via delle Scienze Udine Italy
| | - Curtis Pozniak
- Crop Development Centre and Department of Plant Sciences University of Saskatchewan Saskatoon SK Canada
| | - Ming‐Cheng Luo
- Department of Plant Sciences University of California Davis CA USA
| | - Jan Dvorak
- Department of Plant Sciences University of California Davis CA USA
| | - Matthew Morell
- Commonwealth Scientific and Industrial Research Organization Plant Industry and Food Futures National Research Flagship Canberra ACT Australia
| | - Jorge Dubcovsky
- Department of Plant Sciences University of California Davis CA USA
- Howard Hughes Medical Institute Chevy Chase MD USA
| | | | - Roberto Tuberosa
- Department of Agricultural Sciences University of Bologna Bologna Italy
| | | | | | - Colin Cavanagh
- Commonwealth Scientific and Industrial Research Organization Plant Industry and Food Futures National Research Flagship Canberra ACT Australia
| | | | - Matthew Hayden
- Department of Environment and Primary Industry AgriBioSciences La Trobe R&D Park Bundoora Vic. Australia
| | - Eduard Akhunov
- Department of Plant Pathology Kansas State University Manhattan KS USA
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697
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Das B, Sengupta S, Prasad M, Ghose TK. Genetic diversity of the conserved motifs of six bacterial leaf blight resistance genes in a set of rice landraces. BMC Genet 2014; 15:82. [PMID: 25016378 PMCID: PMC4105243 DOI: 10.1186/1471-2156-15-82] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2014] [Accepted: 07/10/2014] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Bacterial leaf blight (BLB) caused by the vascular pathogen Xanthomonas oryzae pv. oryzae (Xoo) is one of the most serious diseases leading to crop failure in rice growing countries. A total of 37 resistance genes against Xoo has been identified in rice. Of these, ten BLB resistance genes have been mapped on rice chromosomes, while 6 have been cloned, sequenced and characterized. Diversity analysis at the resistance gene level of this disease is scanty, and the landraces from West Bengal and North Eastern states of India have received little attention so far. The objective of this study was to assess the genetic diversity at conserved domains of 6 BLB resistance genes in a set of 22 rice accessions including landraces and check genotypes collected from the states of Assam, Nagaland, Mizoram and West Bengal. RESULTS In this study 34 pairs of primers were designed from conserved domains of 6 BLB resistance genes; Xa1, xa5, Xa21, Xa21(A1), Xa26 and Xa27. The designed primer pairs were used to generate PCR based polymorphic DNA profiles to detect and elucidate the genetic diversity of the six genes in the 22 diverse rice accessions of known disease phenotype. A total of 140 alleles were identified including 41 rare and 26 null alleles. The average polymorphism information content (PIC) value was 0.56/primer pair. The DNA profiles identified each of the rice landraces unequivocally. The amplified polymorphic DNA bands were used to calculate genetic similarity of the rice landraces in all possible pair combinations. The similarity among the rice accessions ranged from 18% to 89% and the dendrogram produced from the similarity values was divided into 2 major clusters. The conserved domains identified within the sequenced rare alleles include Leucine-Rich Repeat, BED-type zinc finger domain, sugar transferase domain and the domain of the carbohydrate esterase 4 superfamily. CONCLUSIONS This study revealed high genetic diversity at conserved domains of six BLB resistance genes in a set of 22 rice accessions. The inclusion of more genotypes from remote ecological niches and hotspots holds promise for identification of further genetic diversity at the BLB resistance genes.
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Affiliation(s)
| | | | | | - Tapas Kumar Ghose
- Division of Plant Biology, Bose Institute, Main Campus, 93/1 A,P,C, Road, 700009 Kolkata, West Bengal, India.
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698
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Raman H, Raman R, Kilian A, Detering F, Carling J, Coombes N, Diffey S, Kadkol G, Edwards D, McCully M, Ruperao P, Parkin IAP, Batley J, Luckett DJ, Wratten N. Genome-wide delineation of natural variation for pod shatter resistance in Brassica napus. PLoS One 2014; 9:e101673. [PMID: 25006804 PMCID: PMC4090071 DOI: 10.1371/journal.pone.0101673] [Citation(s) in RCA: 112] [Impact Index Per Article: 11.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2013] [Accepted: 06/02/2014] [Indexed: 12/18/2022] Open
Abstract
Resistance to pod shattering (shatter resistance) is a target trait for global rapeseed (canola, Brassica napus L.), improvement programs to minimise grain loss in the mature standing crop, and during windrowing and mechanical harvest. We describe the genetic basis of natural variation for shatter resistance in B. napus and show that several quantitative trait loci (QTL) control this trait. To identify loci underlying shatter resistance, we used a novel genotyping-by-sequencing approach DArT-Seq. QTL analysis detected a total of 12 significant QTL on chromosomes A03, A07, A09, C03, C04, C06, and C08; which jointly account for approximately 57% of the genotypic variation in shatter resistance. Through Genome-Wide Association Studies, we show that a large number of loci, including those that are involved in shattering in Arabidopsis, account for variation in shatter resistance in diverse B. napus germplasm. Our results indicate that genetic diversity for shatter resistance genes in B. napus is limited; many of the genes that might control this trait were not included during the natural creation of this species, or were not retained during the domestication and selection process. We speculate that valuable diversity for this trait was lost during the natural creation of B. napus. To improve shatter resistance, breeders will need to target the introduction of useful alleles especially from genotypes of other related species of Brassica, such as those that we have identified.
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Affiliation(s)
- Harsh Raman
- Graham Centre for Agricultural Innovation (an alliance between NSW Department of Primary Industries and Charles Sturt University), Wagga Wagga Agricultural Institute, Wagga Wagga, NSW, Australia
| | - Rosy Raman
- Graham Centre for Agricultural Innovation (an alliance between NSW Department of Primary Industries and Charles Sturt University), Wagga Wagga Agricultural Institute, Wagga Wagga, NSW, Australia
| | - Andrzej Kilian
- Diversity Arrays Technology Pty Ltd, University of Canberra, Bruce, ACT, Australia
| | - Frank Detering
- Diversity Arrays Technology Pty Ltd, University of Canberra, Bruce, ACT, Australia
| | - Jason Carling
- Diversity Arrays Technology Pty Ltd, University of Canberra, Bruce, ACT, Australia
| | - Neil Coombes
- Graham Centre for Agricultural Innovation (an alliance between NSW Department of Primary Industries and Charles Sturt University), Wagga Wagga Agricultural Institute, Wagga Wagga, NSW, Australia
| | - Simon Diffey
- University of Wollongong, Wollongong, NSW, Australia
| | - Gururaj Kadkol
- NSW Department of Primary Industries, Tamworth Agricultural Institute, Tamworth, NSW, Australia
| | - David Edwards
- Australian Centre for Plant Functional Genomic, School of Agriculture and Food Sciences, University of Queensland, St Lucia, QLD, Australia; School of Plant Biology, University of Western Australia, Perth, WA, Australia
| | | | - Pradeep Ruperao
- Australian Centre for Plant Functional Genomic, School of Agriculture and Food Sciences, University of Queensland, St Lucia, QLD, Australia; International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, Andhra Pradesh, India
| | | | - Jacqueline Batley
- School of Plant Biology, University of Western Australia, Perth, WA, Australia; School of Agriculture and Food Sciences, University of Queensland, St Lucia, QLD, Australia
| | - David J Luckett
- Graham Centre for Agricultural Innovation (an alliance between NSW Department of Primary Industries and Charles Sturt University), Wagga Wagga Agricultural Institute, Wagga Wagga, NSW, Australia
| | - Neil Wratten
- Graham Centre for Agricultural Innovation (an alliance between NSW Department of Primary Industries and Charles Sturt University), Wagga Wagga Agricultural Institute, Wagga Wagga, NSW, Australia
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699
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Hu H, Roach JC, Coon H, Guthery SL, Voelkerding KV, Margraf RL, Durtschi JD, Tavtigian SV, Shankaracharya, Wu W, Scheet P, Wang S, Xing J, Glusman G, Hubley R, Li H, Garg V, Moore B, Hood L, Galas DJ, Srivastava D, Reese MG, Jorde LB, Yandell M, Huff CD. A unified test of linkage analysis and rare-variant association for analysis of pedigree sequence data. Nat Biotechnol 2014; 32:663-9. [PMID: 24837662 PMCID: PMC4157619 DOI: 10.1038/nbt.2895] [Citation(s) in RCA: 86] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2013] [Accepted: 04/04/2014] [Indexed: 01/02/2023]
Abstract
High-throughput sequencing of related individuals has become an important tool for studying human disease. However, owing to technical complexity and lack of available tools, most pedigree-based sequencing studies rely on an ad hoc combination of suboptimal analyses. Here we present pedigree-VAAST (pVAAST), a disease-gene identification tool designed for high-throughput sequence data in pedigrees. pVAAST uses a sequence-based model to perform variant and gene-based linkage analysis. Linkage information is then combined with functional prediction and rare variant case-control association information in a unified statistical framework. pVAAST outperformed linkage and rare-variant association tests in simulations and identified disease-causing genes from whole-genome sequence data in three human pedigrees with dominant, recessive and de novo inheritance patterns. The approach is robust to incomplete penetrance and locus heterogeneity and is applicable to a wide variety of genetic traits. pVAAST maintains high power across studies of monogenic, high-penetrance phenotypes in a single pedigree to highly polygenic, common phenotypes involving hundreds of pedigrees.
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Affiliation(s)
- Hao Hu
- Department of Epidemiology, The University of Texas M.D. Anderson Cancer Center, Houston, Texas, USA
| | - Jared C Roach
- Institute for Systems Biology, Seattle, Washington, USA
| | - Hilary Coon
- Department of Psychiatry, University of Utah, Salt Lake City, Utah, USA
| | - Stephen L Guthery
- Department of Pediatrics, University of Utah, Salt Lake City, Utah, USA
| | - Karl V Voelkerding
- 1] Department of Pathology, University of Utah School of Medicine, Salt Lake City, Utah, USA. [2] ARUP Institute for Clinical and Experimental Pathology, ARUP Laboratories, Salt Lake City, Utah, USA
| | - Rebecca L Margraf
- ARUP Institute for Clinical and Experimental Pathology, ARUP Laboratories, Salt Lake City, Utah, USA
| | - Jacob D Durtschi
- ARUP Institute for Clinical and Experimental Pathology, ARUP Laboratories, Salt Lake City, Utah, USA
| | - Sean V Tavtigian
- Department of Oncological Sciences, Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah, USA
| | - Shankaracharya
- Department of Epidemiology, The University of Texas M.D. Anderson Cancer Center, Houston, Texas, USA
| | - Wilfred Wu
- Department of Human Genetics and USTAR Center for Genetic Discovery, University of Utah, Salt Lake City, Utah, USA
| | - Paul Scheet
- Department of Epidemiology, The University of Texas M.D. Anderson Cancer Center, Houston, Texas, USA
| | - Shuoguo Wang
- Department of Genetics, Rutgers, the State University of New Jersey, Piscataway, New Jersey, USA
| | - Jinchuan Xing
- Department of Genetics, Rutgers, the State University of New Jersey, Piscataway, New Jersey, USA
| | | | - Robert Hubley
- Institute for Systems Biology, Seattle, Washington, USA
| | - Hong Li
- Institute for Systems Biology, Seattle, Washington, USA
| | - Vidu Garg
- 1] Department of Pediatrics, The Ohio State University, Columbus, Ohio, USA. [2] Center for Cardiovascular and Pulmonary Research, Research Institute at Nationwide Children's Hospital, Columbus, Ohio, USA
| | - Barry Moore
- Department of Human Genetics and USTAR Center for Genetic Discovery, University of Utah, Salt Lake City, Utah, USA
| | - Leroy Hood
- Institute for Systems Biology, Seattle, Washington, USA
| | - David J Galas
- 1] Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg. [2] Pacific Northwest Diabetes Research Institute, Seattle, Washington, USA
| | - Deepak Srivastava
- Gladstone Institute of Cardiovascular Disease and University of California, San Francisco, San Francisco, California, USA
| | | | - Lynn B Jorde
- Department of Human Genetics and USTAR Center for Genetic Discovery, University of Utah, Salt Lake City, Utah, USA
| | - Mark Yandell
- Department of Human Genetics and USTAR Center for Genetic Discovery, University of Utah, Salt Lake City, Utah, USA
| | - Chad D Huff
- Department of Epidemiology, The University of Texas M.D. Anderson Cancer Center, Houston, Texas, USA
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700
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Sauvage C, Segura V, Bauchet G, Stevens R, Do PT, Nikoloski Z, Fernie AR, Causse M. Genome-Wide Association in Tomato Reveals 44 Candidate Loci for Fruit Metabolic Traits. PLANT PHYSIOLOGY 2014; 165:1120-1132. [PMID: 24894148 PMCID: PMC4081326 DOI: 10.1104/pp.114.241521] [Citation(s) in RCA: 146] [Impact Index Per Article: 14.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/02/2023]
Abstract
Genome-wide association studies have been successful in identifying genes involved in polygenic traits and are valuable for crop improvement. Tomato (Solanum lycopersicum) is a major crop and is highly appreciated worldwide for its health value. We used a core collection of 163 tomato accessions composed of S. lycopersicum, S. lycopersicum var cerasiforme, and Solanum pimpinellifolium to map loci controlling variation in fruit metabolites. Fruits were phenotyped for a broad range of metabolites, including amino acids, sugars, and ascorbate. In parallel, the accessions were genotyped with 5,995 single-nucleotide polymorphism markers spread over the whole genome. Genome-wide association analysis was conducted on a large set of metabolic traits that were stable over 2 years using a multilocus mixed model as a general method for mapping complex traits in structured populations and applied to tomato. We detected a total of 44 loci that were significantly associated with a total of 19 traits, including sucrose, ascorbate, malate, and citrate levels. These results not only provide a list of candidate loci to be functionally validated but also a powerful analytical approach for finding genetic variants that can be directly used for crop improvement and deciphering the genetic architecture of complex traits.
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Affiliation(s)
- Christopher Sauvage
- Institut National de la Recherche Agronomique, UR1052, Génétique et Amélioration des Fruits et Légumes, 84143 Montfavet cedex, France (C.S., G.B., R.S., M.C.);Institut National de la Recherche Agronomique, UR0588, 45075 Orleans cedex 2, France (V.S.);Syngenta Seeds, 31790 Saint Sauveur, France (G.B.);Max-Planck-Institut für Molekulare Pflanzenphysiologie, 14476 Potsdam-Golm, Germany (P.T.D., Z.N., A.R.F.); andFaculty of Biology, University of Science, Vietnam National University, Thanh Xuan, Hanoi, Vietnam (P.T.D.)
| | - Vincent Segura
- Institut National de la Recherche Agronomique, UR1052, Génétique et Amélioration des Fruits et Légumes, 84143 Montfavet cedex, France (C.S., G.B., R.S., M.C.);Institut National de la Recherche Agronomique, UR0588, 45075 Orleans cedex 2, France (V.S.);Syngenta Seeds, 31790 Saint Sauveur, France (G.B.);Max-Planck-Institut für Molekulare Pflanzenphysiologie, 14476 Potsdam-Golm, Germany (P.T.D., Z.N., A.R.F.); andFaculty of Biology, University of Science, Vietnam National University, Thanh Xuan, Hanoi, Vietnam (P.T.D.)
| | - Guillaume Bauchet
- Institut National de la Recherche Agronomique, UR1052, Génétique et Amélioration des Fruits et Légumes, 84143 Montfavet cedex, France (C.S., G.B., R.S., M.C.);Institut National de la Recherche Agronomique, UR0588, 45075 Orleans cedex 2, France (V.S.);Syngenta Seeds, 31790 Saint Sauveur, France (G.B.);Max-Planck-Institut für Molekulare Pflanzenphysiologie, 14476 Potsdam-Golm, Germany (P.T.D., Z.N., A.R.F.); andFaculty of Biology, University of Science, Vietnam National University, Thanh Xuan, Hanoi, Vietnam (P.T.D.)
| | - Rebecca Stevens
- Institut National de la Recherche Agronomique, UR1052, Génétique et Amélioration des Fruits et Légumes, 84143 Montfavet cedex, France (C.S., G.B., R.S., M.C.);Institut National de la Recherche Agronomique, UR0588, 45075 Orleans cedex 2, France (V.S.);Syngenta Seeds, 31790 Saint Sauveur, France (G.B.);Max-Planck-Institut für Molekulare Pflanzenphysiologie, 14476 Potsdam-Golm, Germany (P.T.D., Z.N., A.R.F.); andFaculty of Biology, University of Science, Vietnam National University, Thanh Xuan, Hanoi, Vietnam (P.T.D.)
| | - Phuc Thi Do
- Institut National de la Recherche Agronomique, UR1052, Génétique et Amélioration des Fruits et Légumes, 84143 Montfavet cedex, France (C.S., G.B., R.S., M.C.);Institut National de la Recherche Agronomique, UR0588, 45075 Orleans cedex 2, France (V.S.);Syngenta Seeds, 31790 Saint Sauveur, France (G.B.);Max-Planck-Institut für Molekulare Pflanzenphysiologie, 14476 Potsdam-Golm, Germany (P.T.D., Z.N., A.R.F.); andFaculty of Biology, University of Science, Vietnam National University, Thanh Xuan, Hanoi, Vietnam (P.T.D.)
| | - Zoran Nikoloski
- Institut National de la Recherche Agronomique, UR1052, Génétique et Amélioration des Fruits et Légumes, 84143 Montfavet cedex, France (C.S., G.B., R.S., M.C.);Institut National de la Recherche Agronomique, UR0588, 45075 Orleans cedex 2, France (V.S.);Syngenta Seeds, 31790 Saint Sauveur, France (G.B.);Max-Planck-Institut für Molekulare Pflanzenphysiologie, 14476 Potsdam-Golm, Germany (P.T.D., Z.N., A.R.F.); andFaculty of Biology, University of Science, Vietnam National University, Thanh Xuan, Hanoi, Vietnam (P.T.D.)
| | - Alisdair R Fernie
- Institut National de la Recherche Agronomique, UR1052, Génétique et Amélioration des Fruits et Légumes, 84143 Montfavet cedex, France (C.S., G.B., R.S., M.C.);Institut National de la Recherche Agronomique, UR0588, 45075 Orleans cedex 2, France (V.S.);Syngenta Seeds, 31790 Saint Sauveur, France (G.B.);Max-Planck-Institut für Molekulare Pflanzenphysiologie, 14476 Potsdam-Golm, Germany (P.T.D., Z.N., A.R.F.); andFaculty of Biology, University of Science, Vietnam National University, Thanh Xuan, Hanoi, Vietnam (P.T.D.)
| | - Mathilde Causse
- Institut National de la Recherche Agronomique, UR1052, Génétique et Amélioration des Fruits et Légumes, 84143 Montfavet cedex, France (C.S., G.B., R.S., M.C.);Institut National de la Recherche Agronomique, UR0588, 45075 Orleans cedex 2, France (V.S.);Syngenta Seeds, 31790 Saint Sauveur, France (G.B.);Max-Planck-Institut für Molekulare Pflanzenphysiologie, 14476 Potsdam-Golm, Germany (P.T.D., Z.N., A.R.F.); andFaculty of Biology, University of Science, Vietnam National University, Thanh Xuan, Hanoi, Vietnam (P.T.D.)
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