Genome-Wide Association Study Based on Multiple Imputation with Low-Depth Sequencing Data: Application to Biofuel Traits in Reed Canarygrass

Ramstein, Guillaume P.; Lipka, Alexander E.; Lu, Fei; Costich, Denise E.; Cherney, Jerome H.; Buckler, Edward S.; Casler, Michael D.

doi:10.1534/g3.115.017533

Title: Genome-Wide Association Study Based on Multiple Imputation with Low-Depth Sequencing Data: Application to Biofuel Traits in Reed Canarygrass

Journal Article · Thu Mar 12 00:00:00 EDT 2015 · G3

DOI:https://doi.org/10.1534/g3.115.017533· OSTI ID:1627953

Ramstein, Guillaume P. ^[1]; Lipka, Alexander E. ^[2]; Lu, Fei ^[2]; Costich, Denise E. ^[3]; Cherney, Jerome H. ^[4]; Buckler, Edward S. ^[5]; Casler, Michael D. ^[1]

Univ. of Wisconsin, Madison, WI (United States). Dept. of Agronomy
Univ. of Wisconsin, Madison, WI (United States). Inst. for Genomic Diversity
Cornell Univ., Ithaca, NY (United States). Dept. of Plant Breeding and Genetics
Cornell Univ., Ithaca, NY (United States). School of Integrative Plant Science. Soil and Crops Section
US Dept. of Agriculture (USDA), Ithaca, NY (United States). Agricultural Research Service (ARS); US Dept. of Agriculture (USDA), Madison, WI (United States). Agricultural Research Service (ARS)

Genotyping by sequencing allows for large-scale genetic analyses in plant species with no reference genome, but sets the challenge of sound inference in presence of uncertain genotypes. We report an imputation-based genome-wide association study (GWAS) in reed canarygrass (Phalaris arundinacea L., Phalaris caesia Nees), a cool-season grass species with potential as a biofuel crop. Our study involved two linkage populations and an association panel of 590 reed canarygrass genotypes. Plants were assayed for up to 5228 single nucleotide polymorphism markers and 35 traits. The genotypic markers were derived from lowdepth sequencing with 78% missing data on average. To soundly infer marker-trait associations, multiple imputation (MI) was used: several imputes of the marker data were generated to reflect imputation uncertainty and association tests were performed on marker effects across imputes. A total of nine significant markers were identified, three of which showed significant homology with the Brachypodium dystachion genome. Because no physical map of the reed canarygrass genome was available, imputation was conducted using classification trees. In general, MI showed good consistency with the complete-case analysis and adequate control over imputation uncertainty. A gain in significance of marker effects was achieved through MI, but only for rare cases when missing data were ,45%. In addition to providing insight into the genetic basis of important traits in reed canarygrass, this study presents one of the first applications of MI to genome-wide analyses and provides useful guidelines for conducting GWAS based on genotyping-by-sequencing data.

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Research Organization:: US Dept. of Agriculture (USDA), Washington, DC (United States). Agricultural Research Service (ARS)

Sponsoring Organization:: USDOE Office of Science (SC)

Grant/Contract Number:: AI02-07ER64454

OSTI ID:: 1627953

Journal Information:: G3, Vol. 5, Issue 5; ISSN 2160-1836

Publisher:: Genetics Society of AmericaCopyright Statement

Country of Publication:: United States

Language:: English

References (66)

Lignin Biosynthesis Boerjan, Wout; Ralph, John; Baucher, Marie Annual Review of Plant Biology, Vol. 54, Issue 1, p. 519-546 https://doi.org/10.1146/annurev.arplant.54.031902.134938	journal	June 2003
Imputation methods to improve inference in SNP association studies Dai, James Y.; Ruczinski, Ingo; LeBlanc, Michael Genetic Epidemiology, Vol. 30, Issue 8 https://doi.org/10.1002/gepi.20180	journal	January 2006
Early Trials and Use of Reed Canary Grass as a Forage Plant ¹ Alway, Frederick J. Agronomy Journal, Vol. 23, Issue 1 https://doi.org/10.2134/agronj1931.00021962002300010008x	journal	January 1931
Mixed linear model approach adapted for genome-wide association studies Zhang, Zhiwu; Ersoz, Elhan; Lai, Chao-Qiang Nature Genetics, Vol. 42, Issue 4 https://doi.org/10.1038/ng.546	journal	March 2010
Variance component model to account for sample structure in genome-wide association studies Kang, Hyun Min; Sul, Jae Hoon; Service, Susan K. Nature Genetics, Vol. 42, Issue 4 https://doi.org/10.1038/ng.548	journal	March 2010
Genetic Modification of Herbaceous Plants for Feed and Fuel Vogel, K. Critical Reviews in Plant Sciences, Vol. 20, Issue 1 https://doi.org/10.1016/S0735-2689(01)80011-3	journal	January 2001
Genotype and SNP calling from next-generation sequencing data Nielsen, Rasmus; Paul, Joshua S.; Albrechtsen, Anders Nature Reviews Genetics, Vol. 12, Issue 6 https://doi.org/10.1038/nrg2986	journal	May 2011
Phylogeny of the tribe Aveneae (Pooideae, Poaceae) inferred from plastid trnT-F and nuclear ITS sequences Quintanar, A.; Castroviejo, S.; Catalan, P. American Journal of Botany, Vol. 94, Issue 9 https://doi.org/10.3732/ajb.94.9.1554	journal	September 2007
Large multi-gene phylogenetic trees of the grasses (Poaceae): Progress towards complete tribal and generic level sampling Bouchenak-Khelladi, Yanis; Salamin, Nicolas; Savolainen, Vincent Molecular Phylogenetics and Evolution, Vol. 47, Issue 2 https://doi.org/10.1016/j.ympev.2008.01.035	journal	May 2008
The interacting effects of temperature and plant community type on nutrient removal in wetland microcosms Picard, Christian R.; Fraser, Lauchlan H.; Steer, David Bioresource Technology, Vol. 96, Issue 9 https://doi.org/10.1016/j.biortech.2004.09.007	journal	June 2005
Switchgrass as a sustainable bioenergy crop Sanderson, M. A.; Reed, R. L.; McLaughlin, S. B. Bioresource Technology, Vol. 56, Issue 1, p. 83-93 https://doi.org/10.1016/0960-8524(95)00176-X	journal	April 1996
Biomass Yield of Naturalized Populations and Cultivars of Reed Canary Grass Casler, Michael D.; Cherney, Jerome H.; Brummer, E. Charles BioEnergy Research, Vol. 2, Issue 3 https://doi.org/10.1007/s12155-009-9043-0	journal	August 2009
Switchgrass Genomic Diversity, Ploidy, and Evolution: Novel Insights from a Network-Based SNP Discovery Protocol Lu, Fei; Lipka, Alexander E.; Glaubitz, Jeff PLoS Genetics, Vol. 9, Issue 1 https://doi.org/10.1371/journal.pgen.1003215	journal	January 2013
Gapped BLAST and PSI-BLAST: a new generation of protein database search programs Altschul, Stephen F.; Madden, Thomas L.; Schäffer, Alejandro A. Nucleic Acids Research, Vol. 25, Issue 17, p. 3389-3402 https://doi.org/10.1093/nar/25.17.3389	journal	September 1997
Genetic Variability in Forage Yield, Crude Protein Percentage, and Palatability in Reed Canarygrass, Phalaris arundinacea L. ¹ Asay, K. H.; Carlson, I. T.; Wilsie, C. P. Crop Science, Vol. 8, Issue 5 https://doi.org/10.2135/cropsci1968.0011183X000800050018x	journal	September 1968
Fully conditional specification in multivariate imputation Van Buuren, S.; Brand, J. P. L.; Groothuis-Oudshoorn, C. G. M. Journal of Statistical Computation and Simulation, Vol. 76, Issue 12 https://doi.org/10.1080/10629360600810434	journal	December 2006
Recursive partitioning for missing data imputation in the presence of interaction effects Doove, L. L.; Van Buuren, S.; Dusseldorp, E. Computational Statistics & Data Analysis, Vol. 72 https://doi.org/10.1016/j.csda.2013.10.025	journal	April 2014
Use of Multiple Imputation in the Epidemiologic Literature Klebanoff, M. A.; Cole, S. R. American Journal of Epidemiology, Vol. 168, Issue 4 https://doi.org/10.1093/aje/kwn071	journal	June 2008
Principal components analysis corrects for stratification in genome-wide association studies Price, Alkes L.; Patterson, Nick J.; Plenge, Robert M. Nature Genetics, Vol. 38, Issue 8 https://doi.org/10.1038/ng1847	journal	July 2006
Evaluation of Acid-Insoluble Ash as a Natural Marker in Ruminant Digestibility Studies Van Keulen, J.; Young, B. A. Journal of Animal Science, Vol. 44, Issue 2 https://doi.org/10.2527/jas1977.442282x	journal	February 1977
Multiple imputation of discrete and continuous data by fully conditional specification van Buuren, Stef Statistical Methods in Medical Research, Vol. 16, Issue 3 https://doi.org/10.1177/0962280206074463	journal	June 2007
Ridge Regression and Other Kernels for Genomic Selection with R Package rrBLUP Endelman, Jeffrey B. The Plant Genome Journal, Vol. 4, Issue 3 https://doi.org/10.3835/plantgenome2011.08.0024	journal	January 2011
Multiple Imputation for Missing Data via Sequential Regression Trees Burgette, L. F.; Reiter, J. P. American Journal of Epidemiology, Vol. 172, Issue 9 https://doi.org/10.1093/aje/kwq260	journal	September 2010
A comparison of approaches to account for uncertainty in analysis of imputed genotypes Zheng, Jin; Li, Yun; Abecasis, Gonçalo R. Genetic Epidemiology, Vol. 35, Issue 2 https://doi.org/10.1002/gepi.20552	journal	January 2011
DNA Polymorphisms Reveal Geographic Races of Reed Canarygrass Casler, M. D.; Phillips, M. M.; Krohn, A. L. Crop Science, Vol. 49, Issue 6 https://doi.org/10.2135/cropsci2009.02.0055	journal	November 2009
Large-Sample Significance Levels from Multiply Imputed Data Using Moment-Based Statistics and an F Reference Distribution Li, K. H.; Raghunathan, T. E.; Rubin, D. B. Journal of the American Statistical Association, Vol. 86, Issue 416 https://doi.org/10.2307/2290525	journal	December 1991
Flexible Imputation of Missing Data van Buuren, Stef https://doi.org/10.1201/b11826	book	March 2012
Divergent Selection for Secondary Traits in Upland Tetraploid Switchgrass and Effects on Sward Biomass Yield Price, David L.; Casler, Michael D. BioEnergy Research, Vol. 7, Issue 1 https://doi.org/10.1007/s12155-013-9374-8	journal	September 2013
Genetic evidence suggests a widespread distribution of native North American populations of reed canarygrass Jakubowski, Andrew R.; Casler, Michael D.; Jackson, Randall D. Biological Invasions, Vol. 15, Issue 2 https://doi.org/10.1007/s10530-012-0300-3	journal	August 2012
Genetic diversity and population structure of Eurasian populations of reed canarygrass: cytotypes, cultivars, and interspecific hybrids Jakubowski, Andrew R.; Jackson, Randall D.; Johnson, R. C. Crop and Pasture Science, Vol. 62, Issue 11 https://doi.org/10.1071/CP11232	journal	January 2011
Quantifying Actual and Theoretical Ethanol Yields for Switchgrass Strains Using NIRS Analyses Vogel, Kenneth P.; Dien, Bruce S.; Jung, Hans G. BioEnergy Research, Vol. 4, Issue 2 https://doi.org/10.1007/s12155-010-9104-4	journal	August 2010
Pyrolysis of energy crops including alfalfa stems, reed canarygrass, and eastern gamagrass☆ Boateng, A.; Jung, H.; Adler, P. Fuel, Vol. 85, Issue 17-18 https://doi.org/10.1016/j.fuel.2006.04.025	journal	December 2006
Genetic Variability for Biofuel Traits in a Circumglobal Reed Canarygrass Collection Olmstead, Julia; Casler, Michael D.; Brummer, E. Charles Crop Science, Vol. 53, Issue 2 https://doi.org/10.2135/cropsci2012.01.0003	journal	March 2013
Different plant parts as raw material for fuel and pulp production Pahkala, K.; Pihala, M. Industrial Crops and Products, Vol. 11, Issue 2-3 https://doi.org/10.1016/S0926-6690(99)00050-3	journal	March 2000
Genomic Selection in Wheat Breeding using Genotyping-by-Sequencing Poland, Jesse; Endelman, Jeffrey; Dawson, Julie The Plant Genome Journal, Vol. 5, Issue 3 https://doi.org/10.3835/plantgenome2012.06.0006	journal	January 2012
Multiple Imputation for Interval Estimation From Simple Random Samples With Ignorable Nonresponse Rubin, Donald B.; Schenker, Nathaniel Journal of the American Statistical Association, Vol. 81, Issue 394 https://doi.org/10.2307/2289225	journal	June 1986
Tetraploid and hexaploid chromosome races of Phalaris arundinacea L. McWilliam, Jr; Neal-Smith, Ca Australian Journal of Agricultural Research, Vol. 13, Issue 1 https://doi.org/10.1071/AR9620001	journal	January 1962
Gramene: a bird's eye view of cereal genomes Jaiswal, P. Nucleic Acids Research, Vol. 34, Issue 90001 https://doi.org/10.1093/nar/gkj154	journal	January 2006
Thin plate regression splines Wood, Simon N. Journal of the Royal Statistical Society: Series B (Statistical Methodology), Vol. 65, Issue 1 https://doi.org/10.1111/1467-9868.00374	journal	February 2003
Chemical composition and response to dilute-acid pretreatment and enzymatic saccharification of alfalfa, reed canarygrass, and switchgrass Dien, B.; Jung, H.; Vogel, K. Biomass and Bioenergy, Vol. 30, Issue 10, p. 880-891 https://doi.org/10.1016/j.biombioe.2006.02.004	journal	October 2006
Imputation of Unordered Markers and the Impact on Genomic Selection Accuracy Rutkoski, Jessica E.; Poland, Jesse; Jannink, Jean-Luc G3: Genes\|Genomes\|Genetics, Vol. 3, Issue 3 https://doi.org/10.1534/g3.112.005363	journal	March 2013
Status and Prospects of Association Mapping in Plants Zhu, Chengsong; Gore, Michael; Buckler, Edward S. The Plant Genome Journal, Vol. 1, Issue 1 https://doi.org/10.3835/plantgenome2008.02.0089	journal	January 2008
A new multipoint method for genome-wide association studies by imputation of genotypes Marchini, Jonathan; Howie, Bryan; Myers, Simon Nature Genetics, Vol. 39, Issue 7 https://doi.org/10.1038/ng2088	journal	June 2007
Genotyping-by-Sequencing for Plant Breeding and Genetics Poland, Jesse A.; Rife, Trevor W. The Plant Genome Journal, Vol. 5, Issue 3 https://doi.org/10.3835/plantgenome2012.05.0005	journal	January 2012
Extremely low-coverage sequencing and imputation increases power for genome-wide association studies Pasaniuc, Bogdan; Rohland, Nadin; McLaren, Paul J. Nature Genetics, Vol. 44, Issue 6 https://doi.org/10.1038/ng.2283	journal	May 2012
Imputation-Based Analysis of Association Studies: Candidate Regions and Quantitative Traits Servin, Bertrand; Stephens, Matthew PLoS Genetics, Vol. 3, Issue 7 https://doi.org/10.1371/journal.pgen.0030114	journal	July 2007
A unified mixed-model method for association mapping that accounts for multiple levels of relatedness Yu, Jianming; Pressoir, Gael; Briggs, William H. Nature Genetics, Vol. 38, Issue 2 https://doi.org/10.1038/ng1702	journal	December 2005
Miscellanea. Small-sample degrees of freedom with multiple imputation Barnard, J. Biometrika, Vol. 86, Issue 4 https://doi.org/10.1093/biomet/86.4.948	journal	December 1999
Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls Sterne, J. A. C.; White, I. R.; Carlin, J. B. BMJ, Vol. 338, Issue jun29 1 https://doi.org/10.1136/bmj.b2393	journal	June 2009
A Robust, Simple Genotyping-by-Sequencing (GBS) Approach for High Diversity Species Elshire, Robert J.; Glaubitz, Jeffrey C.; Sun, Qi PLoS ONE, Vol. 6, Issue 5, Article No. e19379 https://doi.org/10.1371/journal.pone.0019379	journal	May 2011
Multiple Imputation After 18+ Years Rubin, Donald B. Journal of the American Statistical Association, Vol. 91, Issue 434 https://doi.org/10.2307/2291635	journal	June 1996
Chemical composition of herbaceous grass and legume species grown for maximum biomass production Cherney, J. H.; Johnson, K. D.; Volenec, J. J. Biomass, Vol. 17, Issue 4 https://doi.org/10.1016/0144-4565(88)90105-9	journal	January 1988
Efficient Control of Population Structure in Model Organism Association Mapping Kang, Hyun Min; Zaitlen, Noah A.; Wade, Claire M. Genetics, Vol. 178, Issue 3 https://doi.org/10.1534/genetics.107.080101	journal	March 2008
Revision of the genus Phalaris L. (Gramineae) Baldini, Riccardo M. Webbia, Vol. 49, Issue 2 https://doi.org/10.1080/00837792.1995.10670587	journal	January 1995
Statistical significance for genomewide studies Storey, J. D.; Tibshirani, R. Proceedings of the National Academy of Sciences, Vol. 100, Issue 16, p. 9440-9445 https://doi.org/10.1073/pnas.1530509100	journal	July 2003
Multiple Imputation of Missing Phenotype Data for QTL Mapping Bobb, Jennifer F.; Scharfstein, Daniel O.; Daniels, Michael J. Statistical Applications in Genetics and Molecular Biology, Vol. 10, Issue 1 https://doi.org/10.2202/1544-6115.1676	journal	January 2011
Practical Issues in Imputation-Based Association Mapping Guan, Yongtao; Stephens, Matthew PLoS Genetics, Vol. 4, Issue 12 https://doi.org/10.1371/journal.pgen.1000279	journal	December 2008
Landfill Leachate Recirculation: Effects on Vegetation Vigor and Clay Surface Cover Infiltration Cureton, P. M.; Groenevelt, P. H.; McBride, R. A. Journal of Environmental Quality, Vol. 20, Issue 1 https://doi.org/10.2134/jeq1991.00472425002000010005x	journal	January 1991
Reed Canarygrass and Other Phalaris Species Carlson, Irving T.; Oram, Rex N.; Surprenant, Jacques Cool-Season Forage Grasses https://doi.org/10.2134/agronmonogr34.c18	book	October 2015
Yield Components of Biomass in Switchgrass Boe, Arvid; Beck, Dwayne L. Crop Science, Vol. 48, Issue 4 https://doi.org/10.2135/cropsci2007.08.0482	journal	January 2008
A Two-Stage Technique for the in Vitro Digestion of Forage Crops Tilley, J. M. A.; Terry, R. A. Grass and Forage Science, Vol. 18, Issue 2 https://doi.org/10.1111/j.1365-2494.1963.tb00335.x	journal	June 1963
Multiple Imputation after 18+ Years Rubin, Donald B. Journal of the American Statistical Association, Vol. 91, Issue 434 https://doi.org/10.1080/01621459.1996.10476908	journal	June 1996
Multiple Imputation for Interval Estimation from Simple Random Samples with Ignorable Nonresponse Rubin, Donald B.; Schenker, Nathaniel Journal of the American Statistical Association, Vol. 81, Issue 394 https://doi.org/10.1080/01621459.1986.10478280	journal	June 1986
Genetic Modification of Herbaceous Plants for Feed and Fuel Vogel, Kenneth P.; Jung, Hans-Joachim G. Critical Reviews in Plant Sciences, Vol. 20, Issue 1 https://doi.org/10.1080/20013591099173	journal	January 2001
Imputation-based analysis of association studies: candidate regions and quantitative traits Servin, Bertrand; Stephens, Matthew PLoS Genetics, Vol. preprint, Issue 2007 https://doi.org/10.1371/journal.pgen.0030114.eor	journal	January 2005
Population Definition, Sample Selection, and Calibration Procedures for Near Infrared Reflectance Spectroscopy Shenk, J. S.; Westerhaus, M. O. Crop Science, Vol. 31, Issue 2 https://doi.org/10.2135/cropsci1991.0011183x003100020049x	journal	January 1991

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