151
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Hallingbäck HR, Fogelqvist J, Powers SJ, Turrion‐Gomez J, Rossiter R, Amey J, Martin T, Weih M, Gyllenstrand N, Karp A, Lagercrantz U, Hanley SJ, Berlin S, Rönnberg‐Wästljung A. Association mapping in Salix viminalis L. (Salicaceae) - identification of candidate genes associated with growth and phenology. GLOBAL CHANGE BIOLOGY. BIOENERGY 2016; 8:670-685. [PMID: 27547245 PMCID: PMC4973673 DOI: 10.1111/gcbb.12280] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/12/2014] [Accepted: 04/14/2015] [Indexed: 05/06/2023]
Abstract
Willow species (Salix) are important as short-rotation biomass crops for bioenergy, which creates a demand for faster genetic improvement and breeding through deployment of molecular marker-assisted selection (MAS). To find markers associated with important adaptive traits, such as growth and phenology, for use in MAS, we genetically dissected the trait variation of a Salix viminalis (L.) population of 323 accessions. The accessions were sampled throughout northern Europe and were established at two field sites in Pustnäs, Sweden, and at Woburn, UK, offering the opportunity to assess the impact of genotype-by-environment interactions (G × E) on trait-marker associations. Field measurements were recorded for growth and phenology traits. The accessions were genotyped using 1536 SNP markers developed from phenology candidate genes and from genes previously observed to be differentially expressed in contrasting environments. Association mapping between 1233 of these SNPs and the measured traits was performed taking into account population structure and threshold selection bias. At a false discovery rate (FDR) of 0.2, 29 SNPs were associated with bud burst, leaf senescence, number of shoots or shoot diameter. The percentage of accession variation (Radj2) explained by these associations ranged from 0.3% to 4.4%, suggesting that the studied traits are controlled by many loci of limited individual impact. Despite this, a SNP in the EARLY FLOWERING 3 gene was repeatedly associated (FDR < 0.2) with bud burst. The rare homozygous genotype exhibited 0.4-1.0 lower bud burst scores than the other genotype classes on a five-grade scale. Consequently, this marker could be promising for use in MAS and the gene deserves further study. Otherwise, associations were less consistent across sites, likely due to their small Radj2 estimates and to considerable G × E interactions indicated by multivariate association analyses and modest trait accession correlations across sites (0.32-0.61).
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Affiliation(s)
- Henrik R. Hallingbäck
- Department of Plant BiologyUppsala BioCenterSwedish University of Agricultural Sciences and Linnean Center for Plant BiologyP.O. Box 7043750 07UppsalaSweden
| | - Johan Fogelqvist
- Department of Plant BiologyUppsala BioCenterSwedish University of Agricultural Sciences and Linnean Center for Plant BiologyP.O. Box 7043750 07UppsalaSweden
| | - Stephen J. Powers
- Computational and Systems Biology DepartmentRothamsted ResearchHarpendenHertsAL5 2JQUK
| | | | - Rachel Rossiter
- AgroEcology DepartmentRothamsted ResearchHarpendenHertsAL5 2JQUK
| | - Joanna Amey
- AgroEcology DepartmentRothamsted ResearchHarpendenHertsAL5 2JQUK
| | - Tom Martin
- Department of Plant BiologyUppsala BioCenterSwedish University of Agricultural Sciences and Linnean Center for Plant BiologyP.O. Box 7043750 07UppsalaSweden
| | - Martin Weih
- Department of Crop Production EcologySwedish University of Agricultural Sciences and Linnean Center for Plant BiologyP.O. Box 7043750 07UppsalaSweden
| | - Niclas Gyllenstrand
- Department of Plant BiologyUppsala BioCenterSwedish University of Agricultural Sciences and Linnean Center for Plant BiologyP.O. Box 7043750 07UppsalaSweden
| | - Angela Karp
- AgroEcology DepartmentRothamsted ResearchHarpendenHertsAL5 2JQUK
| | - Ulf Lagercrantz
- Department of Plant Ecology and EvolutionEvolutionary Biology CentreUppsala University752 36UppsalaSweden
| | - Steven J. Hanley
- AgroEcology DepartmentRothamsted ResearchHarpendenHertsAL5 2JQUK
| | - Sofia Berlin
- Department of Plant BiologyUppsala BioCenterSwedish University of Agricultural Sciences and Linnean Center for Plant BiologyP.O. Box 7043750 07UppsalaSweden
| | - Ann‐Christin Rönnberg‐Wästljung
- Department of Plant BiologyUppsala BioCenterSwedish University of Agricultural Sciences and Linnean Center for Plant BiologyP.O. Box 7043750 07UppsalaSweden
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152
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Prasanth VV, Basava KR, Babu MS, V.G.N. VT, Devi SJSR, Mangrauthia SK, Voleti SR, Sarla N. Field level evaluation of rice introgression lines for heat tolerance and validation of markers linked to spikelet fertility. PHYSIOLOGY AND MOLECULAR BIOLOGY OF PLANTS : AN INTERNATIONAL JOURNAL OF FUNCTIONAL PLANT BIOLOGY 2016; 22:179-92. [PMID: 27436910 PMCID: PMC4938818 DOI: 10.1007/s12298-016-0350-6] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/23/2015] [Revised: 03/13/2016] [Accepted: 03/28/2016] [Indexed: 05/14/2023]
Abstract
Rice lines derived from wild species and mutants can serve as a good resource for favorable alleles for heat tolerance. In all, 48 stable lines including 17 KMR3/O. rufipogon introgression lines (KMR3 ILs), 15 Swarna/O. nivara ILs (Swarna ILs) along with their parents, Nagina 22 (N22) and its 4 EMS induced mutants and 7 varieties were evaluated for heat tolerance under irrigated conditions under field in two seasons, wet season 2012 using poly cover house method and dry season 2013 using late sown method. Spikelet fertility (SF), yield per plant (YP) and heat susceptibility index (HSI) for these two traits were considered as criteria to assess heat tolerance compared to control. Four KMR3 ILs and eight Swarna ILs were identified as heat tolerant based on SF and YP and their HSIs in both wet and dry seasons. S-65 and S-70 showed low SF and high YP consistently in response to heat in both seasons. We provide evidence that SF alone may not be the best criterion to assess heat tolerance and including YP is important as lines with low SF but high YP and vice versa were identified under heat stress. Out of 49 SSR markers linked to spikelet fertility, 18 were validated for five traits. RM229 in wet season and RM430 and RM210 in dry season were significantly associated with both SF and its HSI under heat stress. RM430 was also significantly associated with both YP and its HSI in dry season. Thirty two candidate genes were identified close to nine markers associated with traits under heat stress.
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Affiliation(s)
- V. Vishnu Prasanth
- ICAR - Indian Institute of Rice Research (Directorate of Rice Research), Rajendranagar, Hyderabad, Telangana 500030 India
| | - Kumari Ramana Basava
- ICAR - Indian Institute of Rice Research (Directorate of Rice Research), Rajendranagar, Hyderabad, Telangana 500030 India
| | - M. Suchandranath Babu
- ICAR - Indian Institute of Rice Research (Directorate of Rice Research), Rajendranagar, Hyderabad, Telangana 500030 India
| | - Venkata Tripura V.G.N.
- ICAR - Indian Institute of Rice Research (Directorate of Rice Research), Rajendranagar, Hyderabad, Telangana 500030 India
| | - S. J. S. Rama Devi
- ICAR - Indian Institute of Rice Research (Directorate of Rice Research), Rajendranagar, Hyderabad, Telangana 500030 India
| | - S. K. Mangrauthia
- ICAR - Indian Institute of Rice Research (Directorate of Rice Research), Rajendranagar, Hyderabad, Telangana 500030 India
| | - S. R. Voleti
- ICAR - Indian Institute of Rice Research (Directorate of Rice Research), Rajendranagar, Hyderabad, Telangana 500030 India
| | - N. Sarla
- ICAR - Indian Institute of Rice Research (Directorate of Rice Research), Rajendranagar, Hyderabad, Telangana 500030 India
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153
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Osorio-Guarín JA, Enciso-Rodríguez FE, González C, Fernández-Pozo N, Mueller LA, Barrero LS. Association analysis for disease resistance to Fusarium oxysporum in cape gooseberry (Physalis peruviana L). BMC Genomics 2016; 17:248. [PMID: 26988219 PMCID: PMC4797340 DOI: 10.1186/s12864-016-2568-7] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2015] [Accepted: 03/07/2016] [Indexed: 11/26/2022] Open
Abstract
BACKGROUND Vascular wilt caused by Fusarium oxysporum is the most important disease in cape gooseberry (Physalis peruviana L.) in Colombia. The development of resistant cultivars is considered one of the most cost-effective means to reduce the impact of this disease. In order to do so, it is necessary to provide breeders with molecular markers and promising germplasm for introgression of different resistance loci as part of breeding schemes. Here we described an association mapping study in cape gooseberry with the goal to: (i) select promising materials for use in plant breeding and (ii) identify SNPs associated with the cape gooseberry resistance response to the F. oxysporum pathogen under greenhouse conditions, as potential markers for cape gooseberry breeding. RESULTS We found a total of 21 accessions with different resistance responses within a diversity panel of 100 cape gooseberry accessions. A total of 60,663 SNPs were also identified within the same panel by means of GBS (Genotyping By Sequencing). Model-based population structure and neighbor-joining analyses showed three populations comprising the cape gooseberry panel. After correction for population structure and kinship, we identified SNPs markers associated with the resistance response against F. oxysporum. The identification of markers was based on common tags using the reference genomes of tomato and potato as well as the root/stem transcriptome of cape gooseberry. By comparing their location with the tomato genome, 16 SNPs were found in genes involved in defense/resistance response to pathogens, likewise when compared with the genome of potato, 12 markers were related. CONCLUSIONS The work presented herein provides the first association mapping study in cape gooseberry showing both the identification of promising accessions with resistance response phenotypes and the identification of a set of SNP markers mapped to defense/resistance response genes of reference genomes. Thus, the work also provides new knowledge on candidate genes involved in the P. peruviana - F. oxysporum pathosystem as a foundation for further validation in marker-assisted selection. The results have important implications for conservation and breeding strategies in cape gooseberry.
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Affiliation(s)
- Jaime A. Osorio-Guarín
- />Tibaitatá Research Center, Colombian Corporation for Agricultural Research, Corpoica, Km 14 vía Mosquera, Bogotá, Colombia
| | - Felix E. Enciso-Rodríguez
- />Tibaitatá Research Center, Colombian Corporation for Agricultural Research, Corpoica, Km 14 vía Mosquera, Bogotá, Colombia
| | - Carolina González
- />Tibaitatá Research Center, Colombian Corporation for Agricultural Research, Corpoica, Km 14 vía Mosquera, Bogotá, Colombia
| | | | | | - Luz Stella Barrero
- />Agrobiodiversity Department, National Direction of Research and Development, Corpoica, Km 14 vía Mosquera, Bogotá, Colombia
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154
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Sul JH, Bilow M, Yang WY, Kostem E, Furlotte N, He D, Eskin E. Accounting for Population Structure in Gene-by-Environment Interactions in Genome-Wide Association Studies Using Mixed Models. PLoS Genet 2016; 12:e1005849. [PMID: 26943367 PMCID: PMC4778803 DOI: 10.1371/journal.pgen.1005849] [Citation(s) in RCA: 38] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2015] [Accepted: 01/18/2016] [Indexed: 01/09/2023] Open
Abstract
Although genome-wide association studies (GWASs) have discovered numerous novel genetic variants associated with many complex traits and diseases, those genetic variants typically explain only a small fraction of phenotypic variance. Factors that account for phenotypic variance include environmental factors and gene-by-environment interactions (GEIs). Recently, several studies have conducted genome-wide gene-by-environment association analyses and demonstrated important roles of GEIs in complex traits. One of the main challenges in these association studies is to control effects of population structure that may cause spurious associations. Many studies have analyzed how population structure influences statistics of genetic variants and developed several statistical approaches to correct for population structure. However, the impact of population structure on GEI statistics in GWASs has not been extensively studied and nor have there been methods designed to correct for population structure on GEI statistics. In this paper, we show both analytically and empirically that population structure may cause spurious GEIs and use both simulation and two GWAS datasets to support our finding. We propose a statistical approach based on mixed models to account for population structure on GEI statistics. We find that our approach effectively controls population structure on statistics for GEIs as well as for genetic variants.
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Affiliation(s)
- Jae Hoon Sul
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, California, United States of America
| | - Michael Bilow
- Computer Science Department, University of California, Los Angeles, Los Angeles, California, United States of America
| | - Wen-Yun Yang
- Computer Science Department, University of California, Los Angeles, Los Angeles, California, United States of America
| | - Emrah Kostem
- Computer Science Department, University of California, Los Angeles, Los Angeles, California, United States of America
| | - Nick Furlotte
- Computer Science Department, University of California, Los Angeles, Los Angeles, California, United States of America
| | - Dan He
- Computer Science Department, University of California, Los Angeles, Los Angeles, California, United States of America
| | - Eleazar Eskin
- Computer Science Department, University of California, Los Angeles, Los Angeles, California, United States of America
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, California, United States of America
- * E-mail:
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155
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Arruda MP, Brown P, Brown-Guedira G, Krill AM, Thurber C, Merrill KR, Foresman BJ, Kolb FL. Genome-Wide Association Mapping of Fusarium Head Blight Resistance in Wheat using Genotyping-by-Sequencing. THE PLANT GENOME 2016; 9. [PMID: 27898754 DOI: 10.3835/plantgenome2015.04.0028] [Citation(s) in RCA: 57] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/20/2023]
Abstract
Fusarium head blight (FHB) is one of the most important wheat ( L.) diseases worldwide, and host resistance displays complex genetic control. A genome-wide association study (GWAS) was performed on 273 winter wheat breeding lines from the midwestern and eastern regions of the United States to identify chromosomal regions associated with FHB resistance. Genotyping-by-sequencing (GBS) was used to identify 19,992 single-nucleotide polymorphisms (SNPs) covering all 21 wheat chromosomes. Marker-trait associations were performed with different statistical models, the most appropriate being a compressed mixed linear model (cMLM) controlling for relatedness and population structure. Ten significant SNP-trait associations were detected on chromosomes 4A, 6A, 7A, 1D, 4D, and 7D, and multiple SNPs were associated with on chromosome 3B. Although combination of favorable alleles of these SNPs resulted in lower levels of severity (SEV), incidence (INC), and deoxynivalenol concentration (DON), lines carrying multiple beneficial alleles were in very low frequency for most traits. These SNPs can now be used for creating new breeding lines with different combinations of favorable alleles. This is one of the first GWAS using genomic resources from the International Wheat Genome Sequencing Consortium (IWGSC).
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156
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Provart NJ, Alonso J, Assmann SM, Bergmann D, Brady SM, Brkljacic J, Browse J, Chapple C, Colot V, Cutler S, Dangl J, Ehrhardt D, Friesner JD, Frommer WB, Grotewold E, Meyerowitz E, Nemhauser J, Nordborg M, Pikaard C, Shanklin J, Somerville C, Stitt M, Torii KU, Waese J, Wagner D, McCourt P. 50 years of Arabidopsis research: highlights and future directions. THE NEW PHYTOLOGIST 2016; 209:921-44. [PMID: 26465351 DOI: 10.1111/nph.13687] [Citation(s) in RCA: 118] [Impact Index Per Article: 14.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/26/2015] [Accepted: 08/24/2015] [Indexed: 05/14/2023]
Abstract
922 I. 922 II. 922 III. 925 IV. 925 V. 926 VI. 927 VII. 928 VIII. 929 IX. 930 X. 931 XI. 932 XII. 933 XIII. Natural variation and genome-wide association studies 934 XIV. 934 XV. 935 XVI. 936 XVII. 937 937 References 937 SUMMARY: The year 2014 marked the 25(th) International Conference on Arabidopsis Research. In the 50 yr since the first International Conference on Arabidopsis Research, held in 1965 in Göttingen, Germany, > 54 000 papers that mention Arabidopsis thaliana in the title, abstract or keywords have been published. We present herein a citational network analysis of these papers, and touch on some of the important discoveries in plant biology that have been made in this powerful model system, and highlight how these discoveries have then had an impact in crop species. We also look to the future, highlighting some outstanding questions that can be readily addressed in Arabidopsis. Topics that are discussed include Arabidopsis reverse genetic resources, stock centers, databases and online tools, cell biology, development, hormones, plant immunity, signaling in response to abiotic stress, transporters, biosynthesis of cells walls and macromolecules such as starch and lipids, epigenetics and epigenomics, genome-wide association studies and natural variation, gene regulatory networks, modeling and systems biology, and synthetic biology.
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Affiliation(s)
- Nicholas J Provart
- Department of Cell & Systems Biology/CAGEF, University of Toronto, Toronto, ON, M5S 3B2, Canada
| | - Jose Alonso
- Department of Plant and Microbial Biology, North Carolina State University, Raleigh, NC, 27695, USA
| | - Sarah M Assmann
- Department of Biology, Pennsylvania State University, University Park, PA, 16802, USA
| | | | - Siobhan M Brady
- Department of Plant Biology, University of California, Davis, CA, 95616, USA
| | - Jelena Brkljacic
- Arabidopsis Biological Resource Center, The Ohio State University, Columbus, OH, 43210, USA
| | - John Browse
- Institute of Biological Chemistry, Washington State University, Pullman, WA, 99164, USA
| | - Clint Chapple
- Department of Biochemistry, Purdue University, West Lafayette, IN, 47907, USA
| | - Vincent Colot
- Departement de Biologie École Normale Supérieure, Biologie Moleculaire des Organismes Photosynthetiques, F-75230, Paris, France
| | - Sean Cutler
- Department of Botany and Plant Sciences, University of California, Riverside, CA, 92507, USA
| | - Jeff Dangl
- Department of Biology and Howard Hughes Medical Institute, Department of Microbiology and Immunology, University of North Carolina, Chapel Hill, NC, 27599, USA
| | - David Ehrhardt
- Department of Plant Biology, Carnegie Institution for Science, Stanford, CA, 94305, USA
| | - Joanna D Friesner
- Department of Plant Biology, Agricultural Sustainability Institute, University of California, Davis, CA, 95616, USA
| | - Wolf B Frommer
- Department of Plant Biology, Carnegie Institution for Science, Stanford, CA, 94305, USA
| | - Erich Grotewold
- Center for Applied Plant Science, The Ohio State University, Columbus, OH, 43210, USA
| | - Elliot Meyerowitz
- Division of Biology and Biological Engineering and Howard Hughes Medical Institute, California Institute of Technology, Pasadena, CA, 91125, USA
| | - Jennifer Nemhauser
- Department of Biology, University of Washington, Seattle, WA, 98195, USA
| | - Magnus Nordborg
- Gregor Mendel Institute of Molecular Plant Biology, A-1030, Vienna, Austria
| | - Craig Pikaard
- Department of Biology, Indiana University, Bloomington, IN, 47405, USA
| | - John Shanklin
- Biology Department, Brookhaven National Laboratory, Upton, NY, 11973, USA
| | - Chris Somerville
- Energy Biosciences Institute, University of California, Berkeley, CA, 94704, USA
| | - Mark Stitt
- Metabolic Networks Department, Max Planck Institute for Molecular Plant Physiology, D-14476, Potsdam, Germany
| | - Keiko U Torii
- Department of Biology, University of Washington, Seattle, WA, 98195, USA
| | - Jamie Waese
- Department of Cell & Systems Biology/CAGEF, University of Toronto, Toronto, ON, M5S 3B2, Canada
| | - Doris Wagner
- Department of Biology, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Peter McCourt
- Department of Cell & Systems Biology/CAGEF, University of Toronto, Toronto, ON, M5S 3B2, Canada
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157
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Association mapping for drought tolerance in barley at the reproductive stage. C R Biol 2016; 339:51-9. [DOI: 10.1016/j.crvi.2015.12.002] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2015] [Revised: 12/18/2015] [Accepted: 12/19/2015] [Indexed: 11/19/2022]
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158
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Liu X, Huang M, Fan B, Buckler ES, Zhang Z. Iterative Usage of Fixed and Random Effect Models for Powerful and Efficient Genome-Wide Association Studies. PLoS Genet 2016; 12:e1005767. [PMID: 26828793 PMCID: PMC4734661 DOI: 10.1371/journal.pgen.1005767] [Citation(s) in RCA: 687] [Impact Index Per Article: 85.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2015] [Accepted: 12/03/2015] [Indexed: 12/05/2022] Open
Abstract
False positives in a Genome-Wide Association Study (GWAS) can be effectively controlled by a fixed effect and random effect Mixed Linear Model (MLM) that incorporates population structure and kinship among individuals to adjust association tests on markers; however, the adjustment also compromises true positives. The modified MLM method, Multiple Loci Linear Mixed Model (MLMM), incorporates multiple markers simultaneously as covariates in a stepwise MLM to partially remove the confounding between testing markers and kinship. To completely eliminate the confounding, we divided MLMM into two parts: Fixed Effect Model (FEM) and a Random Effect Model (REM) and use them iteratively. FEM contains testing markers, one at a time, and multiple associated markers as covariates to control false positives. To avoid model over-fitting problem in FEM, the associated markers are estimated in REM by using them to define kinship. The P values of testing markers and the associated markers are unified at each iteration. We named the new method as Fixed and random model Circulating Probability Unification (FarmCPU). Both real and simulated data analyses demonstrated that FarmCPU improves statistical power compared to current methods. Additional benefits include an efficient computing time that is linear to both number of individuals and number of markers. Now, a dataset with half million individuals and half million markers can be analyzed within three days.
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Affiliation(s)
- Xiaolei Liu
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, Hubei, China
- Institute for Genomic Diversity, Cornell University, Ithaca, New York, United States of America
| | - Meng Huang
- Department of Crop and Soil Sciences, Washington State University, Pullman, Washington, United States of America
| | - Bin Fan
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, Hubei, China
| | - Edward S. Buckler
- Institute for Genomic Diversity, Cornell University, Ithaca, New York, United States of America
- United States Department of Agriculture (USDA)–Agricultural Research Service (ARS), Ithaca, New York, United States of America
| | - Zhiwu Zhang
- Department of Crop and Soil Sciences, Washington State University, Pullman, Washington, United States of America
- Department of Animal Sciences, Northeast Agricultural University, Harbin, Heilongjiang, China
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159
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Kiseleva AA, Shcherban AB, Leonova IN, Frenkel Z, Salina EA. Identification of new heading date determinants in wheat 5B chromosome. BMC PLANT BIOLOGY 2016; 16 Suppl 1:8. [PMID: 26821813 PMCID: PMC4895781 DOI: 10.1186/s12870-015-0688-x] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2023]
Abstract
BACKGROUND Variability of heading date may assist in wheat adaptation to local environments. Thereafter, discovery of new heading date determinants is important for cereal improvement. In this study we used common wheat cultivar Chinese Spring (CS) and the substitution line of CS with 5B chromosome from T. dicoccoides (CS-5Bdic), different in their heading date by two weeks, to detect determinants of heading date on 5B chromosome. RESULTS The possible influence of the VRN-B1 gene, the most powerful regulator of flowering, located on 5B chromosome, to differences in heading time between CS and CS-5Bdic was studied. The sequencing of this gene from CS-5Bdic showed that an insertion of a nucleotide triplet produced an additional amino acid in the corresponding protein. No changes in the transcription levels of each homoeologous VRN-1 loci were found in CS-5Bdic by comparison with CS. To ascertain the loci determining heading date difference, a set of 116 recombinant inbred 5В chromosomal lines as a result of hybridization of CS with CS-5Bdic were developed and their heading dates were estimated. Using the Illumina Infinium 15 k Wheat platform, 379 5B-specific polymorphic markers were detected and a genetic map with 82 skeletal markers was constructed. Phenotype (heading date) - genotype association analysis revealed seventy eight markers in pericentromeric region of 5B chromosome significantly associated with heading date variation. Based on this estimation and synteny with model crop genomes we identified the three best candidate genes: WRKY, ERF/AP2 and FHY3/FAR1. CONCLUSIONS We supposed that the difference in activity of WRKY, ERF/AP2 and/or FHY3/FAR1 transcription factors between CS and CS-5Bdic to be a probable reason for the observed difference in heading dates. Data obtained in this study provide a good basis for the subsequent investigation of heading time pathways in wheat.
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Affiliation(s)
- Antonina A Kiseleva
- The Federal Research Center "Institute of Cytology and Genetics of Siberian Branch of the Russian Academy of Sciences", Prospekt Lavrentyeva 10, Novosibirsk, 630090, Russian Federation.
| | - Andrey B Shcherban
- The Federal Research Center "Institute of Cytology and Genetics of Siberian Branch of the Russian Academy of Sciences", Prospekt Lavrentyeva 10, Novosibirsk, 630090, Russian Federation
| | - Irina N Leonova
- The Federal Research Center "Institute of Cytology and Genetics of Siberian Branch of the Russian Academy of Sciences", Prospekt Lavrentyeva 10, Novosibirsk, 630090, Russian Federation
| | - Zeev Frenkel
- Institute of Evolution, University of Haifa, Mount Carmel, Haifa, 31905, Israel
| | - Elena A Salina
- The Federal Research Center "Institute of Cytology and Genetics of Siberian Branch of the Russian Academy of Sciences", Prospekt Lavrentyeva 10, Novosibirsk, 630090, Russian Federation
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160
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Liu J, Wang W, Mei D, Wang H, Fu L, Liu D, Li Y, Hu Q. Characterizing Variation of Branch Angle and Genome-Wide Association Mapping in Rapeseed (Brassica napus L.). FRONTIERS IN PLANT SCIENCE 2016; 7:21. [PMID: 26870051 PMCID: PMC4740498 DOI: 10.3389/fpls.2016.00021] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/01/2015] [Accepted: 01/08/2016] [Indexed: 05/20/2023]
Abstract
Changes in the rapeseed branch angle alter plant architecture, allowing more efficient light capture as planting density increases. In this study, a natural population of rapeseed was grown in three environments and evaluated for branch angle trait to characterize their phenotypic patterns and genotype with a 60K Brassica Infinium SNP array. Significant phenotypic variation was observed from 20 to 70°. As a result, 25 significant quantitative trait loci (QTL) associated with branch angle were identified on chromosomes A2, A3, A7, C3, C5, and C7 by the MLM model in TASSEL 4.0. Orthologs of the functional candidate genes involved in branch angle were identified. Among the key QTL, the peak SNPs were close to the key orthologous genes BnaA.Lazy1 and BnaC.Lazy1 on A3 and C3 homologous genome blocks. With the exception of Lazy (LA) orthologous genes, SQUMOSA PROMOTER BINDING PROTEIN LIKE 14 (SPL14) and an auxin-responsive GRETCHEN HAGEN 3 (GH3) genes from Arabidopsis thaliana were identified close to two clusters of SNPs on the A7 and C7 chromosomes. These findings on multiple novel loci and candidate genes of branch angle will be useful for further understanding and genetic improvement of plant architecture in rapeseed.
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Affiliation(s)
- Jia Liu
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Oil Crops Research Institute of the Chinese Academy of Agricultural SciencesWuhan, China
| | - Wenxiang Wang
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Oil Crops Research Institute of the Chinese Academy of Agricultural SciencesWuhan, China
| | - Desheng Mei
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Oil Crops Research Institute of the Chinese Academy of Agricultural SciencesWuhan, China
| | - Hui Wang
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Oil Crops Research Institute of the Chinese Academy of Agricultural SciencesWuhan, China
| | - Li Fu
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Oil Crops Research Institute of the Chinese Academy of Agricultural SciencesWuhan, China
| | - Daoming Liu
- Agricultural Sciences Institute of Lu'an MunicipalLu'an, China
| | - Yunchang Li
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Oil Crops Research Institute of the Chinese Academy of Agricultural SciencesWuhan, China
| | - Qiong Hu
- Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Oil Crops Research Institute of the Chinese Academy of Agricultural SciencesWuhan, China
- *Correspondence: Qiong Hu
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161
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Su J, Fan S, Li L, Wei H, Wang C, Wang H, Song M, Zhang C, Gu L, Zhao S, Mao G, Wang C, Pang C, Yu S. Detection of Favorable QTL Alleles and Candidate Genes for Lint Percentage by GWAS in Chinese Upland Cotton. FRONTIERS IN PLANT SCIENCE 2016; 7:1576. [PMID: 27818672 PMCID: PMC5073211 DOI: 10.3389/fpls.2016.01576] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/21/2016] [Accepted: 10/06/2016] [Indexed: 05/18/2023]
Abstract
Improving cotton yield is a major breeding goal for Chinese upland cotton. Lint percentage is an important yield component and a critical economic index for cotton cultivars, and raising the lint percentage has a close relationship to improving cotton lint yield. To investigate the genetic architecture of lint percentage, a diversity panel consisting of 355 upland cotton accessions was grown, and the lint percentage was measured in four different environments. Genotyping was performed with specific-locus amplified fragment sequencing (SLAF-seq). Twelve single-nucleotide polymorphisms (SNPs) associated with lint percentage were detected via a genome-wide association study (GWAS), in which five SNP loci distributed on chromosomes At3 (A02) and At4 (A08) and contained two major-effect QTLs, which were detected in the best linear unbiased predictions (BLUPs) and in more than three environments simultaneously. Furthermore, favorable haplotypes (FHs) of two major-effect QTLs and 47 putative candidate genes in the two linkage disequilibrium (LD) blocks of these associated loci were identified. The expression levels of these putative candidate genes were estimated using RNA-seq data from ten upland cotton tissues. We found that Gh_A02G1268 was very highly expressed during the early fiber development stage, whereas the gene was poorly expressed in the seed. These results implied that Gh_A02G1268 may determine the lint percentage by regulating seed and fiber development. The favorable QTL alleles and candidate genes for lint percentage identified in this study will have high potential for improving lint yield in future Chinese cotton breeding programs.
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Affiliation(s)
- Junji Su
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of CAASAnyang, China
- Department of Plant Sciences, College of Agronomy, Northwest A&F UniversityYangling, China
| | - Shuli Fan
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of CAASAnyang, China
| | - Libei Li
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of CAASAnyang, China
| | - Hengling Wei
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of CAASAnyang, China
| | - Caixiang Wang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of CAASAnyang, China
| | - Hantao Wang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of CAASAnyang, China
| | - Meizhen Song
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of CAASAnyang, China
| | - Chi Zhang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of CAASAnyang, China
| | - Lijiao Gu
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of CAASAnyang, China
| | - Shuqi Zhao
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of CAASAnyang, China
| | - Guangzhi Mao
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of CAASAnyang, China
| | - Chengshe Wang
- Department of Plant Sciences, College of Agronomy, Northwest A&F UniversityYangling, China
| | - Chaoyou Pang
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of CAASAnyang, China
- *Correspondence: Chaoyou Pang
| | - Shuxun Yu
- State Key Laboratory of Cotton Biology, Institute of Cotton Research of CAASAnyang, China
- Department of Plant Sciences, College of Agronomy, Northwest A&F UniversityYangling, China
- Shuxun Yu
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162
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Francisco M, Joseph B, Caligagan H, Li B, Corwin JA, Lin C, Kerwin RE, Burow M, Kliebenstein DJ. Genome Wide Association Mapping in Arabidopsis thaliana Identifies Novel Genes Involved in Linking Allyl Glucosinolate to Altered Biomass and Defense. FRONTIERS IN PLANT SCIENCE 2016; 7:1010. [PMID: 27462337 PMCID: PMC4940622 DOI: 10.3389/fpls.2016.01010] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/20/2016] [Accepted: 06/27/2016] [Indexed: 05/17/2023]
Abstract
A key limitation in modern biology is the ability to rapidly identify genes underlying newly identified complex phenotypes. Genome wide association studies (GWAS) have become an increasingly important approach for dissecting natural variation by associating phenotypes with genotypes at a genome wide level. Recent work is showing that the Arabidopsis thaliana defense metabolite, allyl glucosinolate (GSL), may provide direct feedback regulation, linking defense metabolism outputs to the growth, and defense responses of the plant. However, there is still a need to identify genes that underlie this process. To start developing a deeper understanding of the mechanism(s) that modulate the ability of exogenous allyl GSL to alter growth and defense, we measured changes in plant biomass and defense metabolites in a collection of natural 96 A. thaliana accessions fed with 50 μM of allyl GSL. Exogenous allyl GSL was introduced exclusively to the roots and the compound transported to the leaf leading to a wide range of heritable effects upon plant biomass and endogenous GSL accumulation. Using natural variation we conducted GWAS to identify a number of new genes which potentially control allyl responses in various plant processes. This is one of the first instances in which this approach has been successfully utilized to begin dissecting a novel phenotype to the underlying molecular/polygenic basis.
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Affiliation(s)
- Marta Francisco
- Department of Plant Sciences, University of California, DavisDavis, CA, USA
- Group of Genetics, Breeding and Biochemistry of Brassicas, Department of Plant Genetics, Misión Biológica de Galicia, Spanish Council for Scientific ResearchPontevedra, Spain
| | - Bindu Joseph
- Department of Plant Sciences, University of California, DavisDavis, CA, USA
| | - Hart Caligagan
- Department of Plant Sciences, University of California, DavisDavis, CA, USA
| | - Baohua Li
- Department of Plant Sciences, University of California, DavisDavis, CA, USA
| | - Jason A. Corwin
- Department of Plant Sciences, University of California, DavisDavis, CA, USA
| | - Catherine Lin
- Department of Plant Sciences, University of California, DavisDavis, CA, USA
| | - Rachel E. Kerwin
- Department of Plant Sciences, University of California, DavisDavis, CA, USA
| | - Meike Burow
- DynaMo Center, University of CopenhagenCopenhagen, Denmark
| | - Daniel J. Kliebenstein
- Department of Plant Sciences, University of California, DavisDavis, CA, USA
- DynaMo Center, University of CopenhagenCopenhagen, Denmark
- *Correspondence: Daniel J. Kliebenstein
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163
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Hsu SK, Tung CW. Genetic Mapping of Anaerobic Germination-Associated QTLs Controlling Coleoptile Elongation in Rice. RICE (NEW YORK, N.Y.) 2015; 8:38. [PMID: 26699727 PMCID: PMC4689725 DOI: 10.1186/s12284-015-0072-3] [Citation(s) in RCA: 46] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/10/2015] [Accepted: 12/16/2015] [Indexed: 05/04/2023]
Abstract
BACKGROUND Increasing numbers of rice farmers are adopting direct-seeding methods to save on costs associated with labor and transplanting. Successful seedling establishment in flooded conditions requires rapid coleoptile growth to ensure access to oxygen near the water surface. It is important that the natural variations in coleoptile growth of submerged rice plants are identified. RESULTS Coleoptile responses of submerged plants at the germination stage were analyzed in diverse rice accessions and recombinant inbred lines. Several genomic regions identified from a genome-wide association analysis were significantly associated with anaerobic germination, with many that corresponded to published quantitative trait locus (QTL) intervals. In the recombinant inbred line population derived from a cross between japonica and indica varieties, only one unique and strong signal explaining about 27 % of the phenotypic variation was detected. Distinct haplotypes associated with variations in coleoptile length were identified in diverse germplasm. CONCLUSIONS We demonstrated the value of combining genome-wide association analysis and biparental QTL mapping approaches to identify chromosomal regions regulating coleoptile elongation in submerged rice plants. The significant genomic regions detected in this study are potential candidates for incorporation into elite cultivars to improve seedling survival during anaerobic germination. Future studies that map the QTLs and investigate the effects and functions of candidate genes may lead to new rice varieties that can be used in direct-seeding systems.
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Affiliation(s)
- Sheng-Kai Hsu
- Department of Agronomy, National Taiwan University, No. 1, Sec. 4, Roosevelt Rd, Taipei, 10617, Taiwan.
| | - Chih-Wei Tung
- Department of Agronomy, National Taiwan University, No. 1, Sec. 4, Roosevelt Rd, Taipei, 10617, Taiwan.
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164
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Liu Y, Wang L, Deng M, Li Z, Lu Y, Wang J, Wei Y, Zheng Y. Genome-wide association study of phosphorus-deficiency-tolerance traits in Aegilops tauschii. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2015; 128:2203-12. [PMID: 26187748 DOI: 10.1007/s00122-015-2578-x] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/06/2015] [Accepted: 07/01/2015] [Indexed: 05/19/2023]
Abstract
Using GWAS, 13 significant SNPs distributed on six of the seven Aegilops tauschii chromosomes (all but 5D) were identified, and several candidate P-deficiency-responsive genes were proposed from searches of public databases. Aegilops tauschii, the wheat (Triticum aestivum) D-genome progenitor, possesses numerous genes for stress resistance, including genes for tolerance of phosphorus (P) deficiency. Investigation of the genetic architecture of A. tauschii will help in developing P-deficiency-tolerant varieties of wheat. We evaluated nine traits in a population of 380 A. tauschii specimens under conditions with and without P application, and we performed genome-wide association studies for these traits using single nucleotide polymorphism (SNP) chips containing 7185 markers. Using a general linear model, we identified 119 SNPs that were significantly associated with all nine traits, and a mixed linear model revealed 18 SNPs associated with all traits. Both models detected 13 significant markers distributed on six of the seven A. tauschii chromosomes (all but 5D). Searches of public databases revealed several candidate/flanking genes related to P-deficiency tolerance. These genes were grouped in five categories by the types of proteins they encoded: defense response proteins, enzymes, promoters and transcription factors, storage proteins, or proteins triggered by P deficiency. The identified SNPs and genes contain essential information for cloning genes related to P-deficiency tolerance in A. tauschii and wheat, and they provide a foundation for breeding P-deficiency tolerant wheat cultivars.
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Affiliation(s)
- Yaxi Liu
- Triticeae Research Institute, Sichuan Agricultural University, Wenjiang, Chengdu, 611130, China.
| | - Lang Wang
- Triticeae Research Institute, Sichuan Agricultural University, Wenjiang, Chengdu, 611130, China.
| | - Mei Deng
- Triticeae Research Institute, Sichuan Agricultural University, Wenjiang, Chengdu, 611130, China.
| | - Zhanyi Li
- Triticeae Research Institute, Sichuan Agricultural University, Wenjiang, Chengdu, 611130, China.
| | - Yanli Lu
- Maize Research Institute, Sichuan Agricultural University, Wenjiang, Chengdu, 611130, China.
| | - Jirui Wang
- Triticeae Research Institute, Sichuan Agricultural University, Wenjiang, Chengdu, 611130, China.
| | - Yuming Wei
- Triticeae Research Institute, Sichuan Agricultural University, Wenjiang, Chengdu, 611130, China.
| | - Youliang Zheng
- Triticeae Research Institute, Sichuan Agricultural University, Wenjiang, Chengdu, 611130, China.
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165
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Abstract
Darwin's theory of evolution by natural selection is the foundation of modern biology. However, it has proven remarkably difficult to demonstrate at the genetic, genomic, and population level exactly how wild species adapt to their natural environments. We discuss how one can use large sets of multiple genome sequences from wild populations to understand adaptation, with an emphasis on the small herbaceous plant Arabidopsis thaliana. We present motivation for such studies; summarize progress in describing whole-genome, species-wide sequence variation; and then discuss what insights have emerged from these resources, either based on sequence information alone or in combination with phenotypic data. We conclude with thoughts on opportunities with other plant species and the impact of expected progress in sequencing technology and genome engineering for studying adaptation in nature.
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Affiliation(s)
- Detlef Weigel
- Max Planck Institute for Developmental Biology, 72076 Tübingen, Germany;
| | - Magnus Nordborg
- Gregor Mendel Institute, Austrian Academy of Sciences, Vienna Biocenter, 1030 Vienna, Austria;
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166
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Qin P, Wang L, Liu K, Mao S, Li Z, Gao S, Shi H, Liu Y. Genomewide association study of Aegilops tauschii traits under seedling-stage cadmium stress. ACTA ACUST UNITED AC 2015. [DOI: 10.1016/j.cj.2015.04.005] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
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167
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Sasaki E, Zhang P, Atwell S, Meng D, Nordborg M. "Missing" G x E Variation Controls Flowering Time in Arabidopsis thaliana. PLoS Genet 2015; 11:e1005597. [PMID: 26473359 PMCID: PMC4608753 DOI: 10.1371/journal.pgen.1005597] [Citation(s) in RCA: 58] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2015] [Accepted: 09/18/2015] [Indexed: 11/18/2022] Open
Abstract
Understanding how genetic variation interacts with the environment is essential for understanding adaptation. In particular, the life cycle of plants is tightly coordinated with local environmental signals through complex interactions with the genetic variation (G x E). The mechanistic basis for G x E is almost completely unknown. We collected flowering time data for 173 natural inbred lines of Arabidopsis thaliana from Sweden under two growth temperatures (10°C and 16°C), and observed massive G x E variation. To identify the genetic polymorphisms underlying this variation, we conducted genome-wide scans using both SNPs and local variance components. The SNP-based scan identified several variants that had common effects in both environments, but found no trace of G x E effects, whereas the scan using local variance components found both. Furthermore, the G x E effects appears to be concentrated in a small fraction of the genome (0.5%). Our conclusion is that G x E effects in this study are mostly due to large numbers of allele or haplotypes at a small number of loci, many of which correspond to previously identified flowering time genes.
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Affiliation(s)
- Eriko Sasaki
- Gregor Mendel Institute, Austrian Academy of Sciences, Vienna Biocenter (VBC), Vienna, Austria
| | - Pei Zhang
- Gregor Mendel Institute, Austrian Academy of Sciences, Vienna Biocenter (VBC), Vienna, Austria
- Molecular and Computational Biology, University of Southern California, Los Angeles, California, United States of America
| | - Susanna Atwell
- Molecular and Computational Biology, University of Southern California, Los Angeles, California, United States of America
| | - Dazhe Meng
- Gregor Mendel Institute, Austrian Academy of Sciences, Vienna Biocenter (VBC), Vienna, Austria
- Molecular and Computational Biology, University of Southern California, Los Angeles, California, United States of America
| | - Magnus Nordborg
- Gregor Mendel Institute, Austrian Academy of Sciences, Vienna Biocenter (VBC), Vienna, Austria
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168
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Campbell MT, Knecht AC, Berger B, Brien CJ, Wang D, Walia H. Integrating Image-Based Phenomics and Association Analysis to Dissect the Genetic Architecture of Temporal Salinity Responses in Rice. PLANT PHYSIOLOGY 2015; 168:1476-89. [PMID: 26111541 PMCID: PMC4528749 DOI: 10.1104/pp.15.00450] [Citation(s) in RCA: 56] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/25/2015] [Accepted: 06/25/2015] [Indexed: 05/18/2023]
Abstract
Salinity affects a significant portion of arable land and is particularly detrimental for irrigated agriculture, which provides one-third of the global food supply. Rice (Oryza sativa), the most important food crop, is salt sensitive. The genetic resources for salt tolerance in rice germplasm exist but are underutilized due to the difficulty in capturing the dynamic nature of physiological responses to salt stress. The genetic basis of these physiological responses is predicted to be polygenic. In an effort to address this challenge, we generated temporal imaging data from 378 diverse rice genotypes across 14 d of 90 mm NaCl stress and developed a statistical model to assess the genetic architecture of dynamic salinity-induced growth responses in rice germplasm. A genomic region on chromosome 3 was strongly associated with the early growth response and was captured using visible range imaging. Fluorescence imaging identified four genomic regions linked to salinity-induced fluorescence responses. A region on chromosome 1 regulates both the fluorescence shift indicative of the longer term ionic stress and the early growth rate decline during salinity stress. We present, to our knowledge, a new approach to capture the dynamic plant responses to its environment and elucidate the genetic basis of these responses using a longitudinal genome-wide association model.
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Affiliation(s)
- Malachy T Campbell
- Department of Agronomy and Horticulture (M.T.C., H.W.), Holland Computing Center (A.C.K.), and Department of Statistics (D.W.), University of Nebraska, Lincoln, Nebraska 68583;The Plant Accelerator, Australian Plant Phenomics Facility, University of Adelaide, Urrbrae, South Australia 5064, Australia (B.B.); andPhenomics and Bioinformatics Research Centre, University of South Australia, Adelaide, South Australia 5001, Australia (C.J.B.)
| | - Avi C Knecht
- Department of Agronomy and Horticulture (M.T.C., H.W.), Holland Computing Center (A.C.K.), and Department of Statistics (D.W.), University of Nebraska, Lincoln, Nebraska 68583;The Plant Accelerator, Australian Plant Phenomics Facility, University of Adelaide, Urrbrae, South Australia 5064, Australia (B.B.); andPhenomics and Bioinformatics Research Centre, University of South Australia, Adelaide, South Australia 5001, Australia (C.J.B.)
| | - Bettina Berger
- Department of Agronomy and Horticulture (M.T.C., H.W.), Holland Computing Center (A.C.K.), and Department of Statistics (D.W.), University of Nebraska, Lincoln, Nebraska 68583;The Plant Accelerator, Australian Plant Phenomics Facility, University of Adelaide, Urrbrae, South Australia 5064, Australia (B.B.); andPhenomics and Bioinformatics Research Centre, University of South Australia, Adelaide, South Australia 5001, Australia (C.J.B.)
| | - Chris J Brien
- Department of Agronomy and Horticulture (M.T.C., H.W.), Holland Computing Center (A.C.K.), and Department of Statistics (D.W.), University of Nebraska, Lincoln, Nebraska 68583;The Plant Accelerator, Australian Plant Phenomics Facility, University of Adelaide, Urrbrae, South Australia 5064, Australia (B.B.); andPhenomics and Bioinformatics Research Centre, University of South Australia, Adelaide, South Australia 5001, Australia (C.J.B.)
| | - Dong Wang
- Department of Agronomy and Horticulture (M.T.C., H.W.), Holland Computing Center (A.C.K.), and Department of Statistics (D.W.), University of Nebraska, Lincoln, Nebraska 68583;The Plant Accelerator, Australian Plant Phenomics Facility, University of Adelaide, Urrbrae, South Australia 5064, Australia (B.B.); andPhenomics and Bioinformatics Research Centre, University of South Australia, Adelaide, South Australia 5001, Australia (C.J.B.)
| | - Harkamal Walia
- Department of Agronomy and Horticulture (M.T.C., H.W.), Holland Computing Center (A.C.K.), and Department of Statistics (D.W.), University of Nebraska, Lincoln, Nebraska 68583;The Plant Accelerator, Australian Plant Phenomics Facility, University of Adelaide, Urrbrae, South Australia 5064, Australia (B.B.); andPhenomics and Bioinformatics Research Centre, University of South Australia, Adelaide, South Australia 5001, Australia (C.J.B.)
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169
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Campbell MT, Knecht AC, Berger B, Brien CJ, Wang D, Walia H. Integrating Image-Based Phenomics and Association Analysis to Dissect the Genetic Architecture of Temporal Salinity Responses in Rice. PLANT PHYSIOLOGY 2015; 168:1476-1489. [PMID: 26111541 DOI: 10.1104/pp15.00450] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Received: 03/25/2015] [Accepted: 06/25/2015] [Indexed: 05/26/2023]
Abstract
Salinity affects a significant portion of arable land and is particularly detrimental for irrigated agriculture, which provides one-third of the global food supply. Rice (Oryza sativa), the most important food crop, is salt sensitive. The genetic resources for salt tolerance in rice germplasm exist but are underutilized due to the difficulty in capturing the dynamic nature of physiological responses to salt stress. The genetic basis of these physiological responses is predicted to be polygenic. In an effort to address this challenge, we generated temporal imaging data from 378 diverse rice genotypes across 14 d of 90 mm NaCl stress and developed a statistical model to assess the genetic architecture of dynamic salinity-induced growth responses in rice germplasm. A genomic region on chromosome 3 was strongly associated with the early growth response and was captured using visible range imaging. Fluorescence imaging identified four genomic regions linked to salinity-induced fluorescence responses. A region on chromosome 1 regulates both the fluorescence shift indicative of the longer term ionic stress and the early growth rate decline during salinity stress. We present, to our knowledge, a new approach to capture the dynamic plant responses to its environment and elucidate the genetic basis of these responses using a longitudinal genome-wide association model.
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Affiliation(s)
- Malachy T Campbell
- Department of Agronomy and Horticulture (M.T.C., H.W.), Holland Computing Center (A.C.K.), and Department of Statistics (D.W.), University of Nebraska, Lincoln, Nebraska 68583;The Plant Accelerator, Australian Plant Phenomics Facility, University of Adelaide, Urrbrae, South Australia 5064, Australia (B.B.); andPhenomics and Bioinformatics Research Centre, University of South Australia, Adelaide, South Australia 5001, Australia (C.J.B.)
| | - Avi C Knecht
- Department of Agronomy and Horticulture (M.T.C., H.W.), Holland Computing Center (A.C.K.), and Department of Statistics (D.W.), University of Nebraska, Lincoln, Nebraska 68583;The Plant Accelerator, Australian Plant Phenomics Facility, University of Adelaide, Urrbrae, South Australia 5064, Australia (B.B.); andPhenomics and Bioinformatics Research Centre, University of South Australia, Adelaide, South Australia 5001, Australia (C.J.B.)
| | - Bettina Berger
- Department of Agronomy and Horticulture (M.T.C., H.W.), Holland Computing Center (A.C.K.), and Department of Statistics (D.W.), University of Nebraska, Lincoln, Nebraska 68583;The Plant Accelerator, Australian Plant Phenomics Facility, University of Adelaide, Urrbrae, South Australia 5064, Australia (B.B.); andPhenomics and Bioinformatics Research Centre, University of South Australia, Adelaide, South Australia 5001, Australia (C.J.B.)
| | - Chris J Brien
- Department of Agronomy and Horticulture (M.T.C., H.W.), Holland Computing Center (A.C.K.), and Department of Statistics (D.W.), University of Nebraska, Lincoln, Nebraska 68583;The Plant Accelerator, Australian Plant Phenomics Facility, University of Adelaide, Urrbrae, South Australia 5064, Australia (B.B.); andPhenomics and Bioinformatics Research Centre, University of South Australia, Adelaide, South Australia 5001, Australia (C.J.B.)
| | - Dong Wang
- Department of Agronomy and Horticulture (M.T.C., H.W.), Holland Computing Center (A.C.K.), and Department of Statistics (D.W.), University of Nebraska, Lincoln, Nebraska 68583;The Plant Accelerator, Australian Plant Phenomics Facility, University of Adelaide, Urrbrae, South Australia 5064, Australia (B.B.); andPhenomics and Bioinformatics Research Centre, University of South Australia, Adelaide, South Australia 5001, Australia (C.J.B.)
| | - Harkamal Walia
- Department of Agronomy and Horticulture (M.T.C., H.W.), Holland Computing Center (A.C.K.), and Department of Statistics (D.W.), University of Nebraska, Lincoln, Nebraska 68583;The Plant Accelerator, Australian Plant Phenomics Facility, University of Adelaide, Urrbrae, South Australia 5064, Australia (B.B.); andPhenomics and Bioinformatics Research Centre, University of South Australia, Adelaide, South Australia 5001, Australia (C.J.B.)
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170
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Diapari M, Sindhu A, Bett K, Deokar A, Warkentin TD, Tar'an B. Genetic diversity and association mapping of iron and zinc concentrations in chickpea (Cicer arietinum L.). Genome 2015; 57:459-68. [PMID: 25434748 DOI: 10.1139/gen-2014-0108] [Citation(s) in RCA: 55] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
Chickpea (Cicer arietinum L.) is the world's second most important pulse crop after common bean. Chickpea has historically been an important daily staple in the diet of millions of people, especially in the developing countries. Current chickpea breeding programs have mainly been directed toward high yield, biotic and abiotic stress resilience that has increased global production, but less attention has been directed toward improving micronutrient concentrations in seeds. In an effort to develop micronutrient-dense chickpea lines, a study to examine the variability and to identify SNP alleles associated with seed iron and zinc concentrations was conducted using 94 diverse accessions of chickpea. The results indicated that there is substantial variability present in chickpea germplasm for seed iron and zinc concentrations. In the current set of germplasm, zinc is negatively correlated with grain yield across all locations and years; whereas the negative correlation between iron and grain yield was only significant at the Elrose locality. Eight SNP loci associated with iron and (or) zinc concentrations in chickpea seeds were identified. One SNP located on chromosome 1 (chr1) is associated with both iron and zinc concentrations. On chr4, three SNPs associated with zinc concentration and two SNPs for iron concentration were identified. Two additional SNP loci, one on chr6 and the other on chr7, were also found to be associated with iron and zinc concentrations, respectively. The results show potential opportunity for molecular breeding for improvement of seed iron and zinc concentrations in chickpea.
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Affiliation(s)
- Marwan Diapari
- Crop Development Centre, Department of Plant Sciences, University of Saskatchewan, 51 Campus Drive, Saskatoon, SK S7N 5A8, Canada
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171
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Juliana P, Rutkoski JE, Poland JA, Singh RP, Murugasamy S, Natesan S, Barbier H, Sorrells ME. Genome-Wide Association Mapping for Leaf Tip Necrosis and Pseudo-black Chaff in Relation to Durable Rust Resistance in Wheat. THE PLANT GENOME 2015; 8:eplantgenome2015.01.0002. [PMID: 33228313 DOI: 10.3835/plantgenome2015.01.0002] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/16/2015] [Accepted: 03/30/2015] [Indexed: 06/11/2023]
Abstract
The partial rust resistance genes Lr34 and Sr2 have been used extensively in wheat (Triticum aestivum L.) improvement, as they confer exceptional durability. Interestingly, the resistance of Lr34 is associated with the expression of leaf tip necrosis (LTN) and Sr2 with pseudo-black chaff (PBC). Genome-wide association mapping using CIMMYT's stem rust resistance screening nursery (SRRSN) wheat lines was done to identify genotyping-by-sequencing (GBS) markers linked to LTN and PBC. Phenotyping for these traits was done in Ithaca, New York (fall 2011); Njoro, Kenya (main and off-seasons, 2012), and Wellington, India (winter, 2013). Using the mixed linear model (MLM), 18 GBS markers were significantly associated with LTN. While some markers were linked to loci where the durable leaf rust resistance genes Lr34 (7DS), Lr46 (1BL), and Lr68 (7BL) were mapped, significant associations were also detected with other loci on 2BL, 5B, 3BS, 4BS, and 7BS. Twelve GBS markers linked to the Sr2 locus (3BS) and loci on 2DS, 4AL, and 7DS were significantly associated with PBC. This study provides insight into the complex genetic control of LTN and PBC. Further efforts to validate and study these loci might aid in determining the nature of their association with durable resistance.
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Affiliation(s)
- Philomin Juliana
- Plant Breeding and Genetics Section, School of Integrative Plant Science, Cornell Univ., Ithaca, NY, 14853
| | - Jessica E Rutkoski
- Plant Breeding and Genetics Section, School of Integrative Plant Science, Cornell Univ., Ithaca, NY, 14853
| | - Jesse A Poland
- Dep. of Agronomy, Kansas State University, Manhattan, KS, 66506
- USDA-ARS, Manhattan, KS, 66502
| | - Ravi P Singh
- International Maize and Wheat Improvement Center (CIMMYT), Apdo, Postal 6-641, 06600, Mexico, D.F., Mexico
| | - Sivasamy Murugasamy
- Wheat Research Station, Indian Agricultural Research Institute, Wellington, 643231, Nilgiris, India
| | | | - Hugues Barbier
- Plant Breeding and Genetics Section, School of Integrative Plant Science, Cornell Univ., Ithaca, NY, 14853
| | - Mark E Sorrells
- Plant Breeding and Genetics Section, School of Integrative Plant Science, Cornell Univ., Ithaca, NY, 14853
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172
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Jighly A, Oyiga BC, Makdis F, Nazari K, Youssef O, Tadesse W, Abdalla O, Ogbonnaya FC. Genome-wide DArT and SNP scan for QTL associated with resistance to stripe rust (Puccinia striiformis f. sp. tritici) in elite ICARDA wheat (Triticum aestivum L.) germplasm. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2015; 128:1277-95. [PMID: 25851000 DOI: 10.1007/s00122-015-2504-2] [Citation(s) in RCA: 40] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/16/2014] [Accepted: 03/20/2015] [Indexed: 05/06/2023]
Abstract
Identified DArT and SNP markers including a first reported QTL on 3AS, validated large effect APR on 3BS. The different genes can be used to incorporate stripe resistance in cultivated varieties. Stripe rust [yellow rust, caused by Puccinia striiformis f. sp. tritici (Pst)] is a serious disease in wheat (Triticum aestivum). This study employed genome-wide association mapping (GWAM) to identify markers linked to stripe rust resistance genes using Diversity Arrays Technology (DArT(®)) and single-nucleotide polymorphism (SNP) Infinium 9K assays in 200 ICARDA wheat genotypes, phenotyped for seedling and adult plant resistance in two sites over two growing seasons in Syria. Only 25.8 % of the genotypes showed resistance at seedling stage while about 33 and 44 % showed moderate resistance and resistance response, respectively. Mixed-linear model adjusted for false discovery rate at p < 0.05 identified 12 DArT and 29 SNP markers on chromosome arms 3AS, 3AL, 1AL, 2AL, 2BS, 2BL, 3BS, 3BL, 5BL, 6AL, and 7DS significantly linked to Pst resistance genes. Of these, the locus on 3AS has not been previously reported to confer resistance to stripe rust in wheat. The QTL on 3AS, 3AL, 1AL, 2AL, and 2BS were effective at seedling and adult plant growth stages while those on 3BS, 3BL, 5BL, 6AL and 7DS were effective at adult plant stage. The 3BS QTL was validated in Cham-6 × Cham-8 recombinant inbred line population; composite interval analysis identified a stripe resistance QTL flanked by the DArT marker, wPt-798970, contributed by Cham-6 parent which accounted for 31.2 % of the phenotypic variation. The DArT marker "wPt-798970" lies 1.6 cM away from the 3BS QTL detected within GWAM. Epistatic interactions were also investigated; only the QTL on 1AL, 3AS and 6AL exhibited interactions with other loci. These results suggest that GWAM can be an effective approach for identifying and improving resistance to stripe rust in wheat.
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Affiliation(s)
- Abdulqader Jighly
- International Center for Agricultural Research in the Dry Areas (ICARDA), P.O. Box 5466, Aleppo, Syria
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173
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Genetic diversity, population structure, and association mapping of biomass traits in maize with simple sequence repeat markers. Genes Genomics 2015. [DOI: 10.1007/s13258-015-0309-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
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174
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Kertho A, Mamidi S, Bonman JM, McClean PE, Acevedo M. Genome-Wide Association Mapping for Resistance to Leaf and Stripe Rust in Winter-Habit Hexaploid Wheat Landraces. PLoS One 2015; 10:e0129580. [PMID: 26076040 PMCID: PMC4468153 DOI: 10.1371/journal.pone.0129580] [Citation(s) in RCA: 46] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2015] [Accepted: 05/11/2015] [Indexed: 11/18/2022] Open
Abstract
Leaf rust, caused by Puccinia triticina (Pt), and stripe rust, caused by P. striiformis f. sp. tritici (Pst), are destructive foliar diseases of wheat worldwide. Breeding for disease resistance is the preferred strategy of managing both diseases. The continued emergence of new races of Pt and Pst requires a constant search for new sources of resistance. Here we report a genome-wide association analysis of 567 winter wheat (Triticum aestivum) landrace accessions using the Infinium iSelect 9K wheat SNP array to identify loci associated with seedling resistance to five races of Pt (MDCL, MFPS, THBL, TDBG, and TBDJ) and one race of Pst (PSTv-37) frequently found in the Northern Great Plains of the United States. Mixed linear models identified 65 and eight significant markers associated with leaf rust and stripe rust, respectively. Further, we identified 31 and three QTL associated with resistance to Pt and Pst, respectively. Eleven QTL, identified on chromosomes 3A, 4A, 5A, and 6D, are previously unknown for leaf rust resistance in T. aestivum.
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Affiliation(s)
- Albert Kertho
- Department of Plant Pathology, North Dakota State University, Fargo, North Dakota, United States of America
| | - Sujan Mamidi
- Department of Plant Sciences, North Dakota State University, Fargo, North Dakota, United States of America
| | - J. Michael Bonman
- USDA-ARS, Small Grains and Potato Germplasm Research Unit, Aberdeen, Idaho, United States of America
| | - Phillip E. McClean
- Department of Plant Sciences, North Dakota State University, Fargo, North Dakota, United States of America
| | - Maricelis Acevedo
- Department of Plant Pathology, North Dakota State University, Fargo, North Dakota, United States of America
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175
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Wang Q, Xie W, Xing H, Yan J, Meng X, Li X, Fu X, Xu J, Lian X, Yu S, Xing Y, Wang G. Genetic Architecture of Natural Variation in Rice Chlorophyll Content Revealed by a Genome-Wide Association Study. MOLECULAR PLANT 2015; 8:946-57. [PMID: 25747843 DOI: 10.1016/j.molp.2015.02.014] [Citation(s) in RCA: 49] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/26/2014] [Revised: 01/24/2015] [Accepted: 02/25/2015] [Indexed: 05/21/2023]
Abstract
Chlorophyll content is one of the most important physiological traits as it is closely related to leaf photosynthesis and crop yield potential. So far, few genes have been reported to be involved in natural variation of chlorophyll content in rice (Oryza sativa) and the extent of variations explored is very limited. We conducted a genome-wide association study (GWAS) using a diverse worldwide collection of 529 O. sativa accessions. A total of 46 significant association loci were identified. Three F2 mapping populations with parents selected from the association panel were tested for validation of GWAS signals. We clearly demonstrated that Grain number, plant height, and heading date7 (Ghd7) was a major locus for natural variation of chlorophyll content at the heading stage by combining evidence from near-isogenic lines and transgenic plants. The enhanced expression of Ghd7 decreased the chlorophyll content, mainly through down-regulating the expression of genes involved in the biosynthesis of chlorophyll and chloroplast. In addition, Narrow leaf1 (NAL1) corresponded to one significant association region repeatedly detected over two years. We revealed a high degree of polymorphism in the 5' UTR and four non-synonymous SNPs in the coding region of NAL1, and observed diverse effects of the major haplotypes. The loci or candidate genes identified would help to fine-tune and optimize the antenna size of canopies in rice breeding.
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Affiliation(s)
- Quanxiu Wang
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Weibo Xie
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Hongkun Xing
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Ju Yan
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Xiangzhou Meng
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Xinglei Li
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Xiangkui Fu
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Jiuyue Xu
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Xingming Lian
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Sibin Yu
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Yongzhong Xing
- National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China
| | - Gongwei Wang
- 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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176
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George AW, Cavanagh C. Genome-wide association mapping in plants. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2015; 128:1163-74. [PMID: 25800009 DOI: 10.1007/s00122-015-2497-x] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/04/2014] [Accepted: 03/10/2015] [Indexed: 05/24/2023]
Abstract
We present new association mapping methods which address the unique challenges of analyzing genome-wide data from multi-environment plant studies. Association studies on a genome-wide scale are being performed in plants. Unlike human studies, plant studies contain replicates whose data may be recorded across different environments. Plant studies also often employ elaborate experimental designs for controlling extraneous phenotypic variation. As a result, the genome-wide analysis of data from plant studies can be challenging. In this paper, we present QK-based association mapping for the analysis of data from plant association studies. In doing so, we have developed: (a) a general multivariate QK framework for association mapping in plant studies of arbitrary complexity; (b) a new weighted two-stage analysis approach for QK-based association mapping; (c) a heuristic procedure for determining when two-stage analysis is appropriate; and (d) a Monte Carlo sampling procedure for controlling the genome-wide type I error rate. We conduct a simulation study to evaluate the performance of our genome-wide mapping technique. We also analyze data from a multi-environment association study in wheat.
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Affiliation(s)
- Andrew W George
- Digital Productivity Flagship, CSIRO, Brisbane, Qld, Australia,
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177
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Hayeck T, Zaitlen N, Loh PR, Vilhjalmsson B, Pollack S, Gusev A, Yang J, Chen GB, Goddard M, Visscher P, Patterson N, Price A. Mixed model with correction for case-control ascertainment increases association power. Am J Hum Genet 2015; 96:720-30. [PMID: 25892111 DOI: 10.1016/j.ajhg.2015.03.004] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2014] [Accepted: 03/05/2015] [Indexed: 01/06/2023] Open
Abstract
We introduce a liability-threshold mixed linear model (LTMLM) association statistic for case-control studies and show that it has a well-controlled false-positive rate and more power than existing mixed-model methods for diseases with low prevalence. Existing mixed-model methods suffer a loss in power under case-control ascertainment, but no solution has been proposed. Here, we solve this problem by using a χ(2) score statistic computed from posterior mean liabilities (PMLs) under the liability-threshold model. Each individual's PML is conditional not only on that individual's case-control status but also on every individual's case-control status and the genetic relationship matrix (GRM) obtained from the data. The PMLs are estimated with a multivariate Gibbs sampler; the liability-scale phenotypic covariance matrix is based on the GRM, and a heritability parameter is estimated via Haseman-Elston regression on case-control phenotypes and then transformed to the liability scale. In simulations of unrelated individuals, the LTMLM statistic was correctly calibrated and achieved higher power than existing mixed-model methods for diseases with low prevalence, and the magnitude of the improvement depended on sample size and severity of case-control ascertainment. In a Wellcome Trust Case Control Consortium 2 multiple sclerosis dataset with >10,000 samples, LTMLM was correctly calibrated and attained a 4.3% improvement (p = 0.005) in χ(2) statistics over existing mixed-model methods at 75 known associated SNPs, consistent with simulations. Larger increases in power are expected at larger sample sizes. In conclusion, case-control studies of diseases with low prevalence can achieve power higher than that in existing mixed-model methods.
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178
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Mohammadi M, Blake TK, Budde AD, Chao S, Hayes PM, Horsley RD, Obert DE, Ullrich SE, Smith KP. A genome-wide association study of malting quality across eight U.S. barley breeding programs. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2015; 128:705-21. [PMID: 25666272 DOI: 10.1007/s00122-015-2465-5] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/03/2014] [Accepted: 01/17/2015] [Indexed: 05/18/2023]
Abstract
We report malt quality QTLs relevant to breeding with greater precision than previous mapping studies. The distribution of favorable alleles suggests strategies for marker-assisted breeding and germplasm exchange. This study leverages the breeding data of 1,862 barley breeding lines evaluated in 97 field trials for genome-wide association study of malting quality traits in barley. The mapping panel consisted of six-row and two-row advanced breeding lines from eight breeding populations established at six public breeding programs across the United States. A total of 4,976 grain samples were subjected to micro-malting analysis and mapping of nine quality traits was conducted with 3,072 SNP markers distributed throughout the genome. Association mapping was performed for individual breeding populations and for combined six-row and two-row populations. Only 16% of the QTL we report here had been detected in prior bi-parental mapping studies. Comparison of the analyses of the combined two-row and six-row panels identified only two QTL regions that were common to both. In total, 108 and 107 significant marker-trait associations were identified in all six-row and all two-row breeding programs, respectively. A total of 102 and 65 marker-trait associations were specific to individual six-row and two-row breeding programs, respectively indicating that most marker-trait associations were breeding population specific. Combining datasets from different breeding program resulted in both the loss of some QTL that were apparent in the analyses of individual programs and the discovery of new QTL not identified in individual programs. This suggests that simply increasing sample size by pooling samples with different breeding history does not necessarily increase the power to detect associations. The genetic architecture of malting quality and the distribution of favorable alleles suggest strategies for marker-assisted selection and germplasm exchange.
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Affiliation(s)
- Mohsen Mohammadi
- Department of Agronomy and Plant Genetics, University of Minnesota, 411 Borlaug Hall, 1991 Upper Buford Circle, St. Paul, MN, 55108-6026, USA
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179
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Tamang P, Neupane A, Mamidi S, Friesen T, Brueggeman R. Association mapping of seedling resistance to spot form net blotch in a worldwide collection of barley. PHYTOPATHOLOGY 2015; 105:500-8. [PMID: 25870925 DOI: 10.1094/phyto-04-14-0106-r] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
Spot form net blotch (SFNB), caused by the necrotrophic fungal pathogen Pyrenophora teres f. maculata, is an important foliar disease of barley in major production regions around the world. Deployment of adequate host resistance is challenging because the virulence of P. teres f. maculata is highly variable and characterized minor-effect resistances are typically ineffective against the diverse pathogen populations. A world barley core collection consisting of 2,062 barley accessions of diverse origin and genotype were phenotyped at the seedling stage with four P. teres f. maculata isolates collected from the United States (FGO), New Zealand (NZKF2), Australia (SG1), and Denmark (DEN 2.6). Of the 2,062 barley accessions phenotyped, 1,480 were genotyped with the Illumina barley iSelect chip and passed the quality controls with 5,954 polymorphic markers used for further association mapping analysis. Genome-wide association mapping was utilized to identify and map resistance loci from the seedling disease response data and the single nucleotide polymorphism (SNP) marker data. The best among six different regression models was identified for each isolate and association analysis was performed separately for each. A total of 138 significant (-log10P value>3.0) marker-trait associations (MTA) were detected. Using a 5 cM cutoff, a total of 10, 8, 13, and 10 quantitative trait loci (QTL) associated with SFNB resistance were identified for the FGO, SG1, NZKF2, and DEN 2.6 isolates, respectively. Loci containing from 1 to 34 MTA were identified on all seven barley chromosomes with one locus at 66 to 69 cM on chromosome 2H common to all four isolates. Six distinct loci were identified by the association mapping (AM) analysis that corresponded to previously characterized SFNB resistance QTL identified by biparental population analysis (QRpt4, QRpt6, Rpt4, Rpt6, Rpt7, and a QTL on 4H that was not given a provisional gene or QTL nomenclature). The 21 putative novel loci identified may represent a broad spectrum of resistance and or susceptibility loci. This is the first comprehensive AM study to characterize SFNB resistance loci underlying broad populations of the barley host and P. teres f. maculata pathogen.
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Affiliation(s)
- Prabin Tamang
- First, second, fourth, and fifth authors: Department of Plant Pathology, North Dakota State University, Fargo, ND 58108-6050; third author: Department of Plant Science, North Dakota State University, Fargo, ND 58108-6050; and fourth author: U.S. Department of Agriculture-Agriculture Research Service, Red River Valley Agricultural Research Center, Cereal Crops Research Unit, Fargo, ND 58102-2765
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180
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Zhang J, Song Q, Cregan PB, Nelson RL, Wang X, Wu J, Jiang GL. Genome-wide association study for flowering time, maturity dates and plant height in early maturing soybean (Glycine max) germplasm. BMC Genomics 2015; 16:217. [PMID: 25887991 PMCID: PMC4449526 DOI: 10.1186/s12864-015-1441-4] [Citation(s) in RCA: 132] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2014] [Accepted: 03/06/2015] [Indexed: 11/30/2022] Open
Abstract
BACKGROUND Soybean (Glycine max) is a photoperiod-sensitive and self-pollinated species. Days to flowering (DTF) and maturity (DTM), duration of flowering-to-maturity (DFTM) and plant height (PH) are crucial for soybean adaptability and yield. To dissect the genetic architecture of these agronomically important traits, a population consisting of 309 early maturity soybean germplasm accessions was genotyped with the Illumina Infinium SoySNP50K BeadChip and phenotyped in multiple environments. A genome-wide association study (GWAS) was conducted using a mixed linear model that involves both relative kinship and population structure. RESULTS The linkage disequilibrium (LD) decayed slowly in soybean, and a substantial difference in LD pattern was observed between euchromatic and heterochromatic regions. A total of 27, 6, 18 and 27 loci for DTF, DTM, DFTM and PH were detected via GWAS, respectively. The Dt1 gene was identified in the locus strongly associated with both DTM and PH. Ten candidate genes homologous to Arabidopsis flowering genes were identified near the peak single nucleotide polymorphisms (SNPs) associated with DTF. Four of them encode MADS-domain containing proteins. Additionally, a pectin lyase-like gene was also identified in a major-effect locus for PH where LD decayed rapidly. CONCLUSIONS This study identified multiple new loci and refined chromosomal regions of known loci associated with DTF, DTM, DFTM and/or PH in soybean. It demonstrates that GWAS is powerful in dissecting complex traits and identifying candidate genes although LD decayed slowly in soybean. The loci and trait-associated SNPs identified in this study can be used for soybean genetic improvement, especially the major-effect loci associated with PH could be used to improve soybean yield potential. The candidate genes may serve as promising targets for studies of molecular mechanisms underlying the related traits in soybean.
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Affiliation(s)
- Jiaoping Zhang
- Plant Science Department, South Dakota State University, Brookings, SD, 57006, USA.
| | - Qijian Song
- Soybean Genomics and Improvement Laboratory, US Department of Agriculture, Agricultural Research Service (USDA-ARS), 10300 Baltimore Ave, Beltsville, MD, 20705, USA.
| | - Perry B Cregan
- Soybean Genomics and Improvement Laboratory, US Department of Agriculture, Agricultural Research Service (USDA-ARS), 10300 Baltimore Ave, Beltsville, MD, 20705, USA.
| | - Randall L Nelson
- USDA-ARS, Soybean/Maize Germplasm, Pathology, and Genetics Research Unit and Department of Crop Sciences, University of Illinois, Urbana-Champaign, 1101 West Peabody Drive, Urbana, IL, 61801, USA.
| | - Xianzhi Wang
- Plant Science Department, South Dakota State University, Brookings, SD, 57006, USA.
| | - Jixiang Wu
- Plant Science Department, South Dakota State University, Brookings, SD, 57006, USA.
| | - Guo-Liang Jiang
- Plant Science Department, South Dakota State University, Brookings, SD, 57006, USA.
- Agricultural Research Station, Virginia State University, P.O. Box 9061, Petersburg, VA, 23806, USA.
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181
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A genome-wide association study in large white and landrace pig populations for number piglets born alive. PLoS One 2015; 10:e0117468. [PMID: 25781935 PMCID: PMC4363374 DOI: 10.1371/journal.pone.0117468] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2014] [Accepted: 12/25/2014] [Indexed: 11/22/2022] Open
Abstract
The number of piglets born alive (NBA) per litter is one of the most important traits in pig breeding due to its influence on production efficiency. It is difficult to improve NBA because the heritability of the trait is low and it is governed by a high number of loci with low to moderate effects. To clarify the biological and genetic background of NBA, genome-wide association studies (GWAS) were performed using 4,012 Large White and Landrace pigs from herdbook and commercial breeding companies in Germany (3), Austria (1) and Switzerland (1). The animals were genotyped with the Illumina PorcineSNP60 BeadChip. Because of population stratifications within and between breeds, clusters were formed using the genetic distances between the populations. Five clusters for each breed were formed and analysed by GWAS approaches. In total, 17 different significant markers affecting NBA were found in regions with known effects on female reproduction. No overlapping significant chromosome areas or QTL between Large White and Landrace breed were detected.
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182
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Singh NV, Abburi VL, Ramajayam D, Kumar R, Chandra R, Sharma KK, Sharma J, Babu KD, Pal RK, Mundewadikar DM, Saminathan T, Cantrell R, Nimmakayala P, Reddy UK. Genetic diversity and association mapping of bacterial blight and other horticulturally important traits with microsatellite markers in pomegranate from India. Mol Genet Genomics 2015; 290:1393-402. [PMID: 25675870 DOI: 10.1007/s00438-015-1003-0] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2015] [Accepted: 01/27/2015] [Indexed: 10/24/2022]
Abstract
This genetic diversity study aimed to estimate the population structure and explore the use of association mapping strategies to identify linked markers for bacterial resistance, growth and fruit quality in pomegranate collections from India. In total, 88 accessions including 37 cultivated types were investigated. A total of 112 alleles were amplified by use of 44 publicly available microsatellites for estimating molecular genetic diversity and population structure. Neighbor-joining analysis, model-based population structure and principal component analysis corroborated the genetic relationships among wild-type and cultivated pomegranate collections from India. Our study placed all 88 germplasm into four clusters. We identified a cultivated clade of pomegranates in close proximity to Daru types of wild-type pomegranates that grow naturally near the foothills of the Himalayas. Admixture analysis sorted various lineages of cultivated pomegranates to their respective ancestral forms. We identified four linked markers for fruit weight, titratable acidity and bacterial blight severity. PGCT001 was found associated with both fruit weight and bacterial blight, and the association with fruit weight during both seasons analyzed was significant after Bonferroni correction. This research demonstrates effectiveness of microsatellites to resolve population structure among the wild and cultivar collection of pomegranates and future use for association mapping studies.
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Affiliation(s)
- Nripendra Vikram Singh
- ICAR-National Research Center on Pomegranate, Kegaon, Solapur, Maharashtra, 413255, India
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183
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Sonah H, O'Donoughue L, Cober E, Rajcan I, Belzile F. Identification of loci governing eight agronomic traits using a GBS-GWAS approach and validation by QTL mapping in soya bean. PLANT BIOTECHNOLOGY JOURNAL 2015; 13:211-21. [PMID: 25213593 DOI: 10.1111/pbi.12249] [Citation(s) in RCA: 183] [Impact Index Per Article: 20.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/17/2014] [Revised: 06/24/2014] [Accepted: 07/29/2014] [Indexed: 05/18/2023]
Abstract
Soya bean is a major source of edible oil and protein for human consumption as well as animal feed. Understanding the genetic basis of different traits in soya bean will provide important insights for improving breeding strategies for this crop. A genome-wide association study (GWAS) was conducted to accelerate molecular breeding for the improvement of agronomic traits in soya bean. A genotyping-by-sequencing (GBS) approach was used to provide dense genome-wide marker coverage (>47,000 SNPs) for a panel of 304 short-season soya bean lines. A subset of 139 lines, representative of the diversity among these, was characterized phenotypically for eight traits under six environments (3 sites × 2 years). Marker coverage proved sufficient to ensure highly significant associations between the genes known to control simple traits (flower, hilum and pubescence colour) and flanking SNPs. Between one and eight genomic loci associated with more complex traits (maturity, plant height, seed weight, seed oil and protein) were also identified. Importantly, most of these GWAS loci were located within genomic regions identified by previously reported quantitative trait locus (QTL) for these traits. In some cases, the reported QTLs were also successfully validated by additional QTL mapping in a biparental population. This study demonstrates that integrating GBS and GWAS can be used as a powerful complementary approach to classical biparental mapping for dissecting complex traits in soya bean.
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Affiliation(s)
- Humira Sonah
- Département de Phytologie and Institut de Biologie Intégrative et des Systèmes (IBIS), Université Laval, Quebec City, QC, Canada
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184
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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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185
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Zhang J, Zhao J, Xu Y, Liang J, Chang P, Yan F, Li M, Liang Y, Zou Z. Genome-Wide Association Mapping for Tomato Volatiles Positively Contributing to Tomato Flavor. FRONTIERS IN PLANT SCIENCE 2015; 6:1042. [PMID: 26640472 PMCID: PMC4661238 DOI: 10.3389/fpls.2015.01042] [Citation(s) in RCA: 48] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/25/2015] [Accepted: 11/09/2015] [Indexed: 05/21/2023]
Abstract
Tomato volatiles, mainly derived from essential nutrients and health-promoting precursors, affect tomato flavor. Taste volatiles present a major challenge for flavor improvement and quality breeding. In this study, we performed genome-wide association studies (GWAS) to investigate potential chromosome regions associated with the tomato flavor volatiles. We observed significant variation (1200x) among the selected 28 most important volatiles in tomato based on their concentration and odor threshold importance across our sampled accessions. Using 174 tomato accessions, GWAS identified 125 significant associations (P < 0.005) among 182 SSR markers and 28 volatiles (27 volatiles with at least one significant association). Several significant associations were co-localized in previously identified quantitative trait loci (QTL). This result provides new potential candidate loci affecting the metabolism of several volatiles.
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Affiliation(s)
- Jing Zhang
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Horticulture, Northwest A&F UniversityYangling, China
- Key Laboratory of Protected Horticultural Engineering in Northwest, Ministry of AgricultureYangling, China
| | - Jiantao Zhao
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Horticulture, Northwest A&F UniversityYangling, China
- Key Laboratory of Protected Horticultural Engineering in Northwest, Ministry of AgricultureYangling, China
| | - Yao Xu
- College of Forestry, Northwest A&F UniversityYangling, China
| | - Jing Liang
- Shaanxi Jinpeng Seed Industry Co. Ltd.Yangling, China
| | - Peipei Chang
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Horticulture, Northwest A&F UniversityYangling, China
| | - Fei Yan
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Horticulture, Northwest A&F UniversityYangling, China
- Key Laboratory of Protected Horticultural Engineering in Northwest, Ministry of AgricultureYangling, China
| | - Mingjun Li
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Horticulture, Northwest A&F UniversityYangling, China
| | - Yan Liang
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Horticulture, Northwest A&F UniversityYangling, China
- *Correspondence: Yan Liang
| | - Zhirong Zou
- State Key Laboratory of Crop Stress Biology for Arid Areas, College of Horticulture, Northwest A&F UniversityYangling, China
- Key Laboratory of Protected Horticultural Engineering in Northwest, Ministry of AgricultureYangling, China
- Zhirong Zou
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186
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Zhang Y, Pan W. Principal component regression and linear mixed model in association analysis of structured samples: competitors or complements? Genet Epidemiol 2014; 39:149-55. [PMID: 25536929 DOI: 10.1002/gepi.21879] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2014] [Revised: 11/11/2014] [Accepted: 11/11/2014] [Indexed: 11/10/2022]
Abstract
Genome-wide association studies (GWAS) have been established as a major tool to identify genetic variants associated with complex traits, such as common diseases. However, GWAS may suffer from false positives and false negatives due to confounding population structures, including known or unknown relatedness. Another important issue is unmeasured environmental risk factors. Among many methods for adjusting for population structures, two approaches stand out: one is principal component regression (PCR) based on principal component analysis, which is perhaps the most popular due to its early appearance, simplicity, and general effectiveness; the other is based on a linear mixed model (LMM) that has emerged recently as perhaps the most flexible and effective, especially for samples with complex structures as in model organisms. As shown previously, the PCR approach can be regarded as an approximation to an LMM; such an approximation depends on the number of the top principal components (PCs) used, the choice of which is often difficult in practice. Hence, in the presence of population structure, the LMM appears to outperform the PCR method. However, due to the different treatments of fixed vs. random effects in the two approaches, we show an advantage of PCR over LMM: in the presence of an unknown but spatially confined environmental confounder (e.g., environmental pollution or lifestyle), the PCs may be able to implicitly and effectively adjust for the confounder whereas the LMM cannot. Accordingly, to adjust for both population structures and nongenetic confounders, we propose a hybrid method combining the use and, thus, strengths of PCR and LMM. We use real genotype data and simulated phenotypes to confirm the above points, and establish the superior performance of the hybrid method across all scenarios.
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Affiliation(s)
- Yiwei Zhang
- Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, Minnesota, United States of America
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187
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Detection of genomic loci associated with environmental variables using generalized linear mixed models. Genomics 2014; 105:69-75. [PMID: 25499197 DOI: 10.1016/j.ygeno.2014.12.001] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2014] [Revised: 11/27/2014] [Accepted: 12/05/2014] [Indexed: 11/21/2022]
Abstract
We tested the use of Generalized Linear Mixed Models to detect associations between genetic loci and environmental variables, taking into account the population structure of sampled individuals. We used a simulation approach to generate datasets under demographically and selectively explicit models. These datasets were used to analyze and optimize GLMM capacity to detect the association between markers and selective coefficients as environmental data in terms of false and true positive rates. Different sampling strategies were tested, maximizing the number of populations sampled, sites sampled per population, or individuals sampled per site, and the effect of different selective intensities on the efficiency of the method was determined. Finally, we apply these models to an Arabidopsis thaliana SNP dataset from different accessions, looking for loci associated with spring minimal temperature. We identified 25 regions that exhibit unusual correlations with the climatic variable and contain genes with functions related to temperature stress.
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188
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Bentley AR, Scutari M, Gosman N, Faure S, Bedford F, Howell P, Cockram J, Rose GA, Barber T, Irigoyen J, Horsnell R, Pumfrey C, Winnie E, Schacht J, Beauchêne K, Praud S, Greenland A, Balding D, Mackay IJ. Applying association mapping and genomic selection to the dissection of key traits in elite European wheat. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2014; 127:2619-33. [PMID: 25273129 DOI: 10.1007/s00122-014-2403-y] [Citation(s) in RCA: 40] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/30/2014] [Accepted: 09/20/2014] [Indexed: 05/18/2023]
Abstract
We show the application of association mapping and genomic selection for key breeding targets using a large panel of elite winter wheat varieties and a large volume of agronomic data. The heightening urgency to increase wheat production in line with the needs of a growing population, and in the face of climatic uncertainty, mean new approaches, including association mapping (AM) and genomic selection (GS) need to be validated and applied in wheat breeding. Key adaptive responses are the cornerstone of regional breeding. There is evidence that new ideotypes for long-standing traits such as flowering time may be required. In order to detect targets for future marker-assisted improvement and validate the practical application of GS for wheat breeding we genotyped 376 elite wheat varieties with 3,046 DArT, single nucleotide polymorphism and gene markers and measured seven traits in replicated yield trials over 2 years in France, Germany and the UK. The scale of the phenotyping exceeds the breadth of previous AM and GS studies in these key economic wheat production regions of Northern Europe. Mixed-linear modelling (MLM) detected significant marker-trait associations across and within regions. Genomic prediction using elastic net gave low to high prediction accuracies depending on the trait, and could be experimentally increased by modifying the constituents of the training population (TP). We also tested the use of differentially penalised regression to integrate candidate gene and genome-wide markers to predict traits, demonstrating the validity and simplicity of this approach. Overall, our results suggest that whilst AM offers potential for application in both research and breeding, GS represents an exciting opportunity to select key traits, and that optimisation of the TP is crucial to its successful implementation.
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Affiliation(s)
- Alison R Bentley
- The John Bingham Laboratory, NIAB, Huntingdon Road, Cambridge, CB3 0LE, UK,
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Nemli S, Asciogul TK, Kaya HB, Kahraman A, Eşiyok D, Tanyolac B. Association mapping for five agronomic traits in the common bean (Phaseolus vulgaris L.). JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE 2014; 94:3141-51. [PMID: 24659306 DOI: 10.1002/jsfa.6664] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/28/2013] [Revised: 03/16/2014] [Accepted: 03/17/2014] [Indexed: 05/28/2023]
Abstract
BACKGROUND The common bean is the most important grain legume and a major source of protein in many developing countries. We analysed the following traits: pod fibre (PF), seeds per pod (SPP), plant type (PT), growth habit (GH), and days to flowering (DF) for a set of diverse common bean accessions and determined whether such traits were associated with amplified fragment length polymorphism (AFLP), simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) markers. RESULTS In this study, 66 common bean genotypes were used and genotyped with 233 AFLP, 105 SNP and 80 SSR markers. The association analysis between markers and five traits was performed using a General Linear Model (GLM) in Trait Analysis by aSSociation, Evolution and Linkage (TASSEL). The population structure was determined using the STRUCTURE software, and seven groups (K = 7) were identified among genotypes. The associations for such traits were identified and quantified; 62 markers were associated with the five traits. CONCLUSION This study demonstrated that association mapping using a reasonable number of markers, distributed across the genome and with the appropriate number of individuals harboured to detect DNA markers linked to the traits of PF, SPP, PT, GH and DF in common bean.
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Affiliation(s)
- Seda Nemli
- Ege University -, Department of Bioengineering, Bornova-Izmir, 35100, Turkey
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190
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Reddy UK, Abburi L, Abburi VL, Saminathan T, Cantrell R, Vajja VG, Reddy R, Tomason YR, Levi A, Wehner TC, Nimmakayala P. A genome-wide scan of selective sweeps and association mapping of fruit traits using microsatellite markers in watermelon. J Hered 2014; 106:166-76. [PMID: 25425675 DOI: 10.1093/jhered/esu077] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Our genetic diversity study uses microsatellites of known map position to estimate genome level population structure and linkage disequilibrium, and to identify genomic regions that have undergone selection during watermelon domestication and improvement. Thirty regions that showed evidence of selective sweep were scanned for the presence of candidate genes using the watermelon genome browser (www.icugi.org). We localized selective sweeps in intergenic regions, close to the promoters, and within the exons and introns of various genes. This study provided an evidence of convergent evolution for the presence of diverse ecotypes with special reference to American and European ecotypes. Our search for location of linked markers in the whole-genome draft sequence revealed that BVWS00358, a GA repeat microsatellite, is the GAGA type transcription factor located in the 5' untranslated regions of a structure and insertion element that expresses a Cys2His2 Zinc finger motif, with presumed biological processes related to chitin response and transcriptional regulation. In addition, BVWS01708, an ATT repeat microsatellite, located in the promoter of a DTW domain-containing protein (Cla002761); and 2 other simple sequence repeats that association mapping link to fruit length and rind thickness.
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Affiliation(s)
- Umesh K Reddy
- From the Department of Biology, Gus R. Douglass Institute, West Virginia State University, Institute, WV 25112-1000 (Reddy, Abburi, Saminathan, Cantrell, Vajja, Reddy, Tomason, and Nimmakayala); the U.S. Vegetable Laboratory, USDA, ARS, 2875 Savannah Highway, Charleston, SC 29414 (Levi); and the Department of Horticultural Science, North Carolina State University, Raleigh, NC 27695-7609 (Wehner)
| | - Lavanya Abburi
- From the Department of Biology, Gus R. Douglass Institute, West Virginia State University, Institute, WV 25112-1000 (Reddy, Abburi, Saminathan, Cantrell, Vajja, Reddy, Tomason, and Nimmakayala); the U.S. Vegetable Laboratory, USDA, ARS, 2875 Savannah Highway, Charleston, SC 29414 (Levi); and the Department of Horticultural Science, North Carolina State University, Raleigh, NC 27695-7609 (Wehner)
| | - Venkata Lakshmi Abburi
- From the Department of Biology, Gus R. Douglass Institute, West Virginia State University, Institute, WV 25112-1000 (Reddy, Abburi, Saminathan, Cantrell, Vajja, Reddy, Tomason, and Nimmakayala); the U.S. Vegetable Laboratory, USDA, ARS, 2875 Savannah Highway, Charleston, SC 29414 (Levi); and the Department of Horticultural Science, North Carolina State University, Raleigh, NC 27695-7609 (Wehner)
| | - Thangasamy Saminathan
- From the Department of Biology, Gus R. Douglass Institute, West Virginia State University, Institute, WV 25112-1000 (Reddy, Abburi, Saminathan, Cantrell, Vajja, Reddy, Tomason, and Nimmakayala); the U.S. Vegetable Laboratory, USDA, ARS, 2875 Savannah Highway, Charleston, SC 29414 (Levi); and the Department of Horticultural Science, North Carolina State University, Raleigh, NC 27695-7609 (Wehner)
| | - Robert Cantrell
- From the Department of Biology, Gus R. Douglass Institute, West Virginia State University, Institute, WV 25112-1000 (Reddy, Abburi, Saminathan, Cantrell, Vajja, Reddy, Tomason, and Nimmakayala); the U.S. Vegetable Laboratory, USDA, ARS, 2875 Savannah Highway, Charleston, SC 29414 (Levi); and the Department of Horticultural Science, North Carolina State University, Raleigh, NC 27695-7609 (Wehner)
| | - Venkata Gopinath Vajja
- From the Department of Biology, Gus R. Douglass Institute, West Virginia State University, Institute, WV 25112-1000 (Reddy, Abburi, Saminathan, Cantrell, Vajja, Reddy, Tomason, and Nimmakayala); the U.S. Vegetable Laboratory, USDA, ARS, 2875 Savannah Highway, Charleston, SC 29414 (Levi); and the Department of Horticultural Science, North Carolina State University, Raleigh, NC 27695-7609 (Wehner)
| | - Rishi Reddy
- From the Department of Biology, Gus R. Douglass Institute, West Virginia State University, Institute, WV 25112-1000 (Reddy, Abburi, Saminathan, Cantrell, Vajja, Reddy, Tomason, and Nimmakayala); the U.S. Vegetable Laboratory, USDA, ARS, 2875 Savannah Highway, Charleston, SC 29414 (Levi); and the Department of Horticultural Science, North Carolina State University, Raleigh, NC 27695-7609 (Wehner)
| | - Yan R Tomason
- From the Department of Biology, Gus R. Douglass Institute, West Virginia State University, Institute, WV 25112-1000 (Reddy, Abburi, Saminathan, Cantrell, Vajja, Reddy, Tomason, and Nimmakayala); the U.S. Vegetable Laboratory, USDA, ARS, 2875 Savannah Highway, Charleston, SC 29414 (Levi); and the Department of Horticultural Science, North Carolina State University, Raleigh, NC 27695-7609 (Wehner)
| | - Amnon Levi
- From the Department of Biology, Gus R. Douglass Institute, West Virginia State University, Institute, WV 25112-1000 (Reddy, Abburi, Saminathan, Cantrell, Vajja, Reddy, Tomason, and Nimmakayala); the U.S. Vegetable Laboratory, USDA, ARS, 2875 Savannah Highway, Charleston, SC 29414 (Levi); and the Department of Horticultural Science, North Carolina State University, Raleigh, NC 27695-7609 (Wehner)
| | - Todd C Wehner
- From the Department of Biology, Gus R. Douglass Institute, West Virginia State University, Institute, WV 25112-1000 (Reddy, Abburi, Saminathan, Cantrell, Vajja, Reddy, Tomason, and Nimmakayala); the U.S. Vegetable Laboratory, USDA, ARS, 2875 Savannah Highway, Charleston, SC 29414 (Levi); and the Department of Horticultural Science, North Carolina State University, Raleigh, NC 27695-7609 (Wehner)
| | - Padma Nimmakayala
- From the Department of Biology, Gus R. Douglass Institute, West Virginia State University, Institute, WV 25112-1000 (Reddy, Abburi, Saminathan, Cantrell, Vajja, Reddy, Tomason, and Nimmakayala); the U.S. Vegetable Laboratory, USDA, ARS, 2875 Savannah Highway, Charleston, SC 29414 (Levi); and the Department of Horticultural Science, North Carolina State University, Raleigh, NC 27695-7609 (Wehner)
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191
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Zhang LC, Li N, Liu X, Liang J, Yan H, Zhao KB, Pu L, Shi HB, Zhang YB, Wang LG, Wang LX. A genome-wide association study of limb bone length using a Large White × Minzhu intercross population. Genet Sel Evol 2014; 46:56. [PMID: 25366846 PMCID: PMC4219012 DOI: 10.1186/s12711-014-0056-6] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2014] [Accepted: 07/28/2014] [Indexed: 11/23/2022] Open
Abstract
Background In pig, limb bone length influences ham yield and body height to a great extent and has important economic implications for pig industry. In this study, an intercross population was constructed between the indigenous Chinese Minzhu pig breed and the western commercial Large White pig breed to examine the genetic basis for variation in limb bone length. The aim of this study was to detect potential genetic variants associated with porcine limb bone length. Methods A total of 571 F2 individuals from a Large White and Minzhu intercross population were genotyped using the Illumina PorcineSNP60K Beadchip, and phenotyped for femur length (FL), humerus length (HL), hipbone length (HIPL), scapula length (SL), tibia length (TL), and ulna length (UL). A genome-wide association study was performed by applying the previously reported approach of genome-wide rapid association using mixed model and regression. Statistical significance of the associations was based on Bonferroni-corrected P-values. Results A total of 39 significant SNPs were mapped to a 11.93 Mb long region on pig chromosome 7 (SSC7). Linkage analysis of these significant SNPs revealed three haplotype blocks of 495 kb, 376 kb and 492 kb, respectively, in the 11.93 Mb region. Annotation based on the pig reference genome identified 15 genes that were located near or contained the significant SNPs in these linkage disequilibrium intervals. Conditioned analysis revealed that four SNPs, one on SSC2 and three on SSC4, showed significant associations with SL and HL, respectively. Conclusions Analysis of the 15 annotated genes that were identified in these three haplotype blocks indicated that HMGA1 and PPARD, which are expressed in limbs and influence chondrocyte cell growth and differentiation, could be considered as relevant biological candidates for limb bone length in pig, with potential applications in breeding programs. Our results may also be useful for the study of the mechanisms that underlie human limb length and body height. Electronic supplementary material The online version of this article (doi:10.1186/s12711-014-0056-6) contains supplementary material, which is available to authorized users.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | - Li-Gang Wang
- Key Laboratory of Farm Animal Genetic Resources and Germplasm Innovation of Ministry of Agriculture, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, 100193, China.
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192
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Fodor A, Segura V, Denis M, Neuenschwander S, Fournier-Level A, Chatelet P, Homa FAA, Lacombe T, This P, Le Cunff L. Genome-wide prediction methods in highly diverse and heterozygous species: proof-of-concept through simulation in grapevine. PLoS One 2014; 9:e110436. [PMID: 25365338 PMCID: PMC4217727 DOI: 10.1371/journal.pone.0110436] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2014] [Accepted: 09/19/2014] [Indexed: 11/20/2022] Open
Abstract
Nowadays, genome-wide association studies (GWAS) and genomic selection (GS) methods which use genome-wide marker data for phenotype prediction are of much potential interest in plant breeding. However, to our knowledge, no studies have been performed yet on the predictive ability of these methods for structured traits when using training populations with high levels of genetic diversity. Such an example of a highly heterozygous, perennial species is grapevine. The present study compares the accuracy of models based on GWAS or GS alone, or in combination, for predicting simple or complex traits, linked or not with population structure. In order to explore the relevance of these methods in this context, we performed simulations using approx 90,000 SNPs on a population of 3,000 individuals structured into three groups and corresponding to published diversity grapevine data. To estimate the parameters of the prediction models, we defined four training populations of 1,000 individuals, corresponding to these three groups and a core collection. Finally, to estimate the accuracy of the models, we also simulated four breeding populations of 200 individuals. Although prediction accuracy was low when breeding populations were too distant from the training populations, high accuracy levels were obtained using the sole core-collection as training population. The highest prediction accuracy was obtained (up to 0.9) using the combined GWAS-GS model. We thus recommend using the combined prediction model and a core-collection as training population for grapevine breeding or for other important economic crops with the same characteristics.
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Affiliation(s)
- Agota Fodor
- UMT Geno-Vigne, IFV-INRA-Montpellier Supagro, Montpellier, France; UMR AGAP, INRA, Montpellier, France
| | | | | | - Samuel Neuenschwander
- University of Lausanne, Department of Ecology and Evolution, Lausanne, Switzerland; University of Lausanne, Swiss Institute of Bioinformatics, Vital-IT, Lausanne, Switzerland
| | | | | | | | | | - Patrice This
- UMT Geno-Vigne, IFV-INRA-Montpellier Supagro, Montpellier, France; UMR AGAP, INRA, Montpellier, France
| | - Loic Le Cunff
- UMT Geno-Vigne, IFV-INRA-Montpellier Supagro, Montpellier, France; UMR AGAP, INRA, Montpellier, France
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193
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Li M, Liu X, Bradbury P, Yu J, Zhang YM, Todhunter RJ, Buckler ES, Zhang Z. Enrichment of statistical power for genome-wide association studies. BMC Biol 2014; 12:73. [PMID: 25322753 PMCID: PMC4210555 DOI: 10.1186/s12915-014-0073-5] [Citation(s) in RCA: 70] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2014] [Accepted: 09/09/2014] [Indexed: 01/15/2023] Open
Abstract
BACKGROUND The inheritance of most human diseases and agriculturally important traits is controlled by many genes with small effects. Identifying these genes, while simultaneously controlling false positives, is challenging. Among available statistical methods, the mixed linear model (MLM) has been the most flexible and powerful for controlling population structure and individual unequal relatedness (kinship), the two common causes of spurious associations. The introduction of the compressed MLM (CMLM) method provided additional opportunities for optimization by adding two new model parameters: grouping algorithms and number of groups. RESULTS This study introduces another model parameter to develop an enriched CMLM (ECMLM). The parameter involves algorithms to define kinship between groups (that is, kinship algorithms). The ECMLM calculates kinship using several different algorithms and then chooses the best combination between kinship algorithms and grouping algorithms. CONCLUSION Simulations show that the ECMLM increases statistical power. In some cases, the magnitude of power gained by using ECMLM instead of CMLM is larger than the improvement found by using CMLM instead of MLM.
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Affiliation(s)
- Meng Li
- />College of Horticulture, Nanjing Agricultural University, Nanjing, 210095 China
- />Institute for Genomic Diversity, Cornell University, Ithaca, New York 14853 USA
| | - Xiaolei Liu
- />Institute for Genomic Diversity, Cornell University, Ithaca, New York 14853 USA
| | - Peter Bradbury
- />United States Department of Agriculture (USDA) – Agricultural Research Service (ARS), Ithaca, New York 14853 USA
| | - Jianming Yu
- />Department of Agronomy, Kansas State University, Manhattan, Kansas 66506 USA
| | - Yuan-Ming Zhang
- />State Key Laboratory of Crop Genetics and Germplasm Enhancement/National Center for Soybean Improvement, College of Agriculture, Nanjing Agricultural University, Nanjing, 210095 China
| | - Rory J Todhunter
- />Department of Clinical Sciences, College of Veterinary Medicine, Cornell University, Ithaca, New York 14853 USA
| | - Edward S Buckler
- />Institute for Genomic Diversity, Cornell University, Ithaca, New York 14853 USA
- />United States Department of Agriculture (USDA) – Agricultural Research Service (ARS), Ithaca, New York 14853 USA
| | - Zhiwu Zhang
- />Institute for Genomic Diversity, Cornell University, Ithaca, New York 14853 USA
- />College of Agronomy, Northeast Agricultural University, Harbin, Heilongjiang 150030 China
- />Department of Crop and Soil Science, Washington State University, Pullman, WA 99164 USA
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194
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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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195
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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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196
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Wang Q, Tian F, Pan Y, Buckler ES, Zhang Z. A SUPER powerful method for genome wide association study. PLoS One 2014; 9:e107684. [PMID: 25247812 PMCID: PMC4172578 DOI: 10.1371/journal.pone.0107684] [Citation(s) in RCA: 139] [Impact Index Per Article: 13.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2014] [Accepted: 08/20/2014] [Indexed: 01/19/2023] Open
Abstract
Genome-Wide Association Studies shed light on the identification of genes underlying human diseases and agriculturally important traits. This potential has been shadowed by false positive findings. The Mixed Linear Model (MLM) method is flexible enough to simultaneously incorporate population structure and cryptic relationships to reduce false positives. However, its intensive computational burden is prohibitive in practice, especially for large samples. The newly developed algorithm, FaST-LMM, solved the computational problem, but requires that the number of SNPs be less than the number of individuals to derive a rank-reduced relationship. This restriction potentially leads to less statistical power when compared to using all SNPs. We developed a method to extract a small subset of SNPs and use them in FaST-LMM. This method not only retains the computational advantage of FaST-LMM, but also remarkably increases statistical power even when compared to using the entire set of SNPs. We named the method SUPER (Settlement of MLM Under Progressively Exclusive Relationship) and made it available within an implementation of the GAPIT software package.
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Affiliation(s)
- Qishan Wang
- School of Agriculture and Biology, Shanghai Jiaotong University, Shanghai, China
| | - Feng Tian
- National Maize Improvement Center of China, China Agricultural University, Beijing, China
| | - Yuchun Pan
- School of Agriculture and Biology, Shanghai Jiaotong University, Shanghai, China
| | - Edward S. Buckler
- United States Department of Agriculture (USDA) – Agricultural Research Service (ARS), Ithaca, New York, United States of America
- Institute for Genomic Diversity, Cornell University, Ithaca, New York, United States of America
| | - Zhiwu Zhang
- Institute for Genomic Diversity, Cornell University, Ithaca, New York, United States of America
- Department of Animal Science, Northeast Agricultural University, Harbin, China
- Department of Crop and Soil Science, Washington State University, Pullman, Washington, United States of America
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197
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Jahani M, Nematzadeh G, Dolatabadi B, Hashemi SH, Mohammadi-Nejad G. Identification and validation of functional markers in a global rice collection by association mapping. Genome 2014; 57:355-62. [PMID: 25243661 DOI: 10.1139/gen-2014-0044] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
Recent results indicate that marker-assisted selection is an effective approach to reduce the cost and to improve the efficacy and accuracy of selection in plant breeding. This study was conducted to identify and validate molecular markers linked to important breeding traits by association mapping. The association was evaluated between 81 molecular markers (STS, SSR, Indel, CAPS, and PCR-based SNP) and 15 morphological traits in a global panel of 100 rice (Oryza sativa) accessions. The population structure analysis identified three main subpopulations. Obvious kinship relationships were also detected between the rice accessions. Association analysis was performed based on the mixed linear model by considering population structure and family relatedness. In addition, the false discovery rate method was used to correct the multiple testing. A total of 47 marker-trait associations were identified, including 22 markers for 14 traits. Among all, the polymorphism at the loci DDR-GL was highly associated with grain characters (grain length, grain width, and length/width ratio). In addition, marker RM3148 was responsible for five important traits simultaneously. Results demonstrated that such informative markers can be very useful for rice breeding programs using marker-assisted selection. Moreover, the diverse populations of rice accessions are a valuable resource for association mapping of morphological traits.
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Affiliation(s)
- Mojtaba Jahani
- a Department of Agronomy and Plant Breeding, Faculty of Agriculture, Shahid Bahonar University of Kerman, P.O. Box 76169-133, Kerman, Iran
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198
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Mamidi S, Lee RK, Goos JR, McClean PE. Genome-wide association studies identifies seven major regions responsible for iron deficiency chlorosis in soybean (Glycine max). PLoS One 2014; 9:e107469. [PMID: 25225893 PMCID: PMC4166409 DOI: 10.1371/journal.pone.0107469] [Citation(s) in RCA: 79] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2014] [Accepted: 08/14/2014] [Indexed: 01/08/2023] Open
Abstract
Iron deficiency chlorosis (IDC) is a yield limiting problem in soybean (Glycine max (L.) Merr) production regions with calcareous soils. Genome-wide association study (GWAS) was performed using a high density SNP map to discover significant markers, QTL and candidate genes associated with IDC trait variation. A stepwise regression model included eight markers after considering LD between markers, and identified seven major effect QTL on seven chromosomes. Twelve candidate genes known to be associated with iron metabolism mapped near these QTL supporting the polygenic nature of IDC. A non-synonymous substitution with the highest significance in a major QTL region suggests soybean orthologs of FRE1 on Gm03 is a major gene responsible for trait variation. NAS3, a gene that encodes the enzyme nicotianamine synthase which synthesizes the iron chelator nicotianamine also maps to the same QTL region. Disease resistant genes also map to the major QTL, supporting the hypothesis that pathogens compete with the plant for Fe and increase iron deficiency. The markers and the allelic combinations identified here can be further used for marker assisted selection.
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Affiliation(s)
- Sujan Mamidi
- Genomics and Bioinformatics Program, North Dakota State University, Fargo, North Dakota, United States of America
- Department of Plant Sciences, North Dakota State University, Fargo, North Dakota, United States of America
| | - Rian K. Lee
- Genomics and Bioinformatics Program, North Dakota State University, Fargo, North Dakota, United States of America
- Department of Plant Sciences, North Dakota State University, Fargo, North Dakota, United States of America
| | - Jay R. Goos
- Department of Soil Science, North Dakota State University, Fargo, North Dakota, United States of America
| | - Phillip E. McClean
- Genomics and Bioinformatics Program, North Dakota State University, Fargo, North Dakota, United States of America
- Department of Plant Sciences, North Dakota State University, Fargo, North Dakota, United States of America
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199
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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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200
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Nimmakayala P, Levi A, Abburi L, Abburi VL, Tomason YR, Saminathan T, Vajja VG, Malkaram S, Reddy R, Wehner TC, Mitchell SE, Reddy UK. Single nucleotide polymorphisms generated by genotyping by sequencing to characterize genome-wide diversity, linkage disequilibrium, and selective sweeps in cultivated watermelon. BMC Genomics 2014; 15:767. [PMID: 25196513 PMCID: PMC4246513 DOI: 10.1186/1471-2164-15-767] [Citation(s) in RCA: 55] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2014] [Accepted: 08/29/2014] [Indexed: 02/08/2023] Open
Abstract
Background A large single nucleotide polymorphism (SNP) dataset was used to analyze genome-wide diversity in a diverse collection of watermelon cultivars representing globally cultivated, watermelon genetic diversity. The marker density required for conducting successful association mapping depends on the extent of linkage disequilibrium (LD) within a population. Use of genotyping by sequencing reveals large numbers of SNPs that in turn generate opportunities in genome-wide association mapping and marker-assisted selection, even in crops such as watermelon for which few genomic resources are available. In this paper, we used genome-wide genetic diversity to study LD, selective sweeps, and pairwise FST distributions among worldwide cultivated watermelons to track signals of domestication. Results We examined 183 Citrullus lanatus var. lanatus accessions representing domesticated watermelon and generated a set of 11,485 SNP markers using genotyping by sequencing. With a diverse panel of worldwide cultivated watermelons, we identified a set of 5,254 SNPs with a minor allele frequency of ≥ 0.05, distributed across the genome. All ancestries were traced to Africa and an admixture of various ancestries constituted secondary gene pools across various continents. A sliding window analysis using pairwise FST values was used to resolve selective sweeps. We identified strong selection on chromosomes 3 and 9 that might have contributed to the domestication process. Pairwise analysis of adjacent SNPs within a chromosome as well as within a haplotype allowed us to estimate genome-wide LD decay. LD was also detected within individual genes on various chromosomes. Principal component and ancestry analyses were used to account for population structure in a genome-wide association study. We further mapped important genes for soluble solid content using a mixed linear model. Conclusions Information concerning the SNP resources, population structure, and LD developed in this study will help in identifying agronomically important candidate genes from the genomic regions underlying selection and for mapping quantitative trait loci using a genome-wide association study in sweet watermelon. Electronic supplementary material The online version of this article (doi:10.1186/1471-2164-15-767) contains supplementary material, which is available to authorized users.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | - Umesh K Reddy
- Gus R, Douglass Institute, Department of Biology, West Virginia State University, Dunbar, WV 25112-1000, USA.
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