Genome-wide association study (GWAS) of carbon isotope ratio (δ13C) in diverse soybean [Glycine max (L.) Merr.] genotypes

Theoretical and Applied Genetics

Volumn 128, Issue 1, 2014, Pages 73-91

  Dhanapal, Arun Prabhu ^a   Ray, Jeffery D ^b   Singh, Shardendu K ^c   Hoyos Villegas, Valerio ^d   Smith, James R ^b   Purcell, Larry C ^e   Andy King, C ^e   Cregan, Perry B ^c   Song, Qijian ^c   Fritschi, Felix B ^a  

^a UNIVERSITY OF MISSOURI   (United States)

^b AGRICULTURAL RESEARCH SERVICE   (United States)

^c AGRICULTURAL RESEARCH SERVICE   (United States)

^d MICHIGAN STATE UNIVERSITY   (United States)

^e UNIVERSITY OF ARKANSAS   (United States)

Author keywords

Carbon isotope ratio; Genome wide association studies (GWAS); SNPs; Water use efficiency (WUE)

Indexed keywords

AMINO ACIDS; EFFICIENCY; GENES; ISOTOPES; LOCATION; PLANTS (BOTANY);

CARBON ISOTOPE RATIO; GENOME-WIDE ASSOCIATION STUDIES; POPULATION STRUCTURES; SINGLE NUCLEOTIDE POLYMORPHISMS; SNPS; SOYBEAN [GLYCINE MAX (L.) MERR.]; WATER DEFICIT STRESS; WATER-USE EFFICIENCY;

NITROGEN FIXATION;

CARBON;

BIOLOGICAL MODEL; DROUGHT; GENE LINKAGE DISEQUILIBRIUM; GENETIC ASSOCIATION; GENETICS; GENOTYPE; PHYSIOLOGICAL STRESS; POPULATION GENETICS; SINGLE NUCLEOTIDE POLYMORPHISM; SOYBEAN;

CARBON ISOTOPES; DROUGHTS; GENETIC ASSOCIATION STUDIES; GENETICS, POPULATION; GENOTYPE; LINKAGE DISEQUILIBRIUM; MODELS, GENETIC; POLYMORPHISM, SINGLE NUCLEOTIDE; SOYBEANS; STRESS, PHYSIOLOGICAL;

EID: 84928108863     PISSN: 00405752     EISSN: None     Source Type: Journal    
DOI: 10.1007/s00122-014-2413-9     Document Type: Article

References (98)

1. Abdurakhmonov I, Abdukarimov A (2008) Application of Association Mapping to Understanding the Genetic Diversity of Plant Germplasm Resources. Int J Plant Genomics. doi: 10.1155/2008/574927
2. Ahmed IM, Dai H, Zheng W, Cao F, Zhang G, Sun D, Wu F (2013) Genotypic differences in physiological characteristics in the tolerance to drought and salinity combined stress between Tibetan wild and cultivated barley. Plant Physiol Biochem 63: 49-60
3. Anderson MJ, Ter Braak CJF (2003) Permutations tests for multifactorial analysis of variance. J Stat Comput Simul 73: 85-113
4. Angus J, van Herwarden AF (2001) Increasing water use and water use efficiency in dryland wheat. Agron J 93: 290-298
5. Aranzana MJ, Abbassi EK, Howad W, Arus P (2010) Genetic variation, population structure and linkage disequilibrium in peachcommercial varieties. Genetics 11: 69
6. Araus JL, Slafer GA, Reynolds MP, Royo C (2002) Plant breeding and drought in C3 cereals: what should we breed for? Ann Bot 89: 925-940
7. Barrett JC, Fry B, Maller J, Daly MJ (2005) Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics 21(2): 263-265
8. Baum M, Von Korff M, Guo P, Lakew B, Hamwieh A, Lababidi S, Udupa SM, Sayed H, Choumane W, Grando S, Ceccarelli S (2007) Molecular approaches and breeding strategies for drought tolerance in barley. In: Varshney R, Tuberosa R Genomics-Assisted Crop Improvement, Volume 2: Genomics Applications in Crops. Springer, Dordrecht, pp 51-79
9. Belamkar V, Selvaraj MG, Ayers JL, Payton PR, Puppala N, Burow MD (2011) A first insight into population structure and linkage disequilibrium in the US peanut minicore collection. Genetica 139: 411-429
10. Benjamini Y, Hochberg Y (1995) Controlling the false discovery rate: a practical and powerful approach to multiple testing. J Roy Stat Soc Ser B (Methodol) 57(1): 289-300
11. Blum A (2005) Drought resistance, water-use efficiency, and yield potential-are they compatible, dissonant, or mutually exclusive? Aust J Agric Res 56: 1159-1168
12. Bondari K (2003) Statistical analysis of genotype x environment interaction in agricultural research. Paper SD15, SESUG: The Proceedings of the SouthEast SAS Users Group, St Pete Beach
13. Botstein D, White RL, Skolnick M, Davis RW (1980) Construction of a genetic linkage map in man using restriction fragment length polymorphisms. Am J Hum Genet 32: 314-331
14. Bradbury PJ, Zhang Z, Kroon DE, Casstevens TM, Ramdoss Y, Buckler ES (2007) TASSEL: software for association mapping of complex traits in diverse samples. Bioinformatics 23: 2633-2635
15. Breseghello F, Sorrells ME (2006) Association mapping of kernel size and milling quality in wheat (Triticum aestivum L.) cultivars. Genetics 172: 1165-1177
16. Brüggemann N, Gessler A, Kayler Z, Keel SG, Badeck F, Barthel M, Boeckx P, Buchmann N, Brugnoli E, Esperschütz J, Gavrichkova O, Ghashghaie J, Gomez-Casanovas N, Keitel C, Knohl A, Kuptz D, Palacio S, Salmon Y, Uchida Y, Bahn M (2011) Carbon allocation and carbon isotope fluxes in the plant-soil-atmosphere continuum a review. Biogeosciences 8: 3457-3489
17. Buckler E, Casstevens T, Bradbury P, Zhang Z (2009) Analysis byaSSociation, evolution and linkage (TASSEL) version 2.1. user manual. Cornell University, Ithaca
18. Bush WS, Moore JH (2012) Chapter 11: Genome-wide association studies. PLoS Computional Biol 8: e1002822
19. Cao K, Wang L, Zhu G, Fang W, Chen C, Luo J (2012) Genetic diversity, linkage disequilibrium, and association mappinganalyses of peach (Prunus persica) landraces in China. Tree Genetics Genomes 8: 975-990
20. Cattivelli L, Rizza F, Badeck FW, Mazzucotelli E, Mastrangelo AM, Francia E, Marè C, Tondelli A, Stanca AM (2008) Drought tolerance improvement in crop plants: an integrated view from breeding to genomics. Field Crops Res 105: 1-14
21. Chen H, He H, Zou Y, Chen W, Yu R, Liu X, Yang Y, Gao YM, Xu JL, Fan LM, Li Y, Li ZK, Deng XW (2011) Development and application of a set of breeder-friendly SNP markers for genetic analyses and molecular breeding of rice (Oryza sativa L.). Theori App Genet 123: 869-879
22. Chen J, Chang SX, Anyia AO (2012) Quantitative trait loci for wateruse efficiency in barley (Hordeum vulgare L.) measured by carbon isotope discrimination under rain-fed conditions on the Canadian Prairies. Theor Appl Genet 125: 71-90
23. Chevenet F, Brun C, Banuls AL, Jacq B, Christen R (2006) TreeDyn: towards dynamic graphics and annotations for analyses of trees. BMC Bioinformatics 7: 439
24. Condon AG, Richards RA (1992) Broad sense heritability and genotype environment interaction for carbon isotope discrimination in field-grown wheat. Aust J Agric Res 43: 921-934
25. Condon AG, Farquhar GD, Richards RA (1990) Genotypic variation in carbon isotope discrimination and transpiration efficiency in wheat leaf gas exchange and whole plant studies. Aust J Plant Physiol 17: 9-22
26. Condon AG, Richards RA, Farquhar GD (2002) Improving intrinsic water-use efficiency and crop yield. Crop Sci 42: 122-131
27. Condon AG, Farquhar GD, Rebetzke GJ, Richards RA (2004) Breeding for high water-use efficiency. J Exp Bot 55: 2447-2460
28. Dhanapal AP, Crisosto CH (2013) Association genetics of chilling injury susceptibility in peach (Prunus persica (L.) Batsch) across multiple years. 3 Biotech 3: 481-490
29. Edae EA, Byrne PF, Haley SD, Lopes MS, Reynolds MP (2014) Genome-wide association mapping of yield and yield components of spring wheat under contrasting moisture regimes. Theor Appl Genetics 127(4): 791-807
30. Ehdaie B, Hall AE, Farquhar GD, Nguyen HT, Waines JG (1991) Water-use efficiency and carbon isotope discrimination in wheat. Crop Sci 31: 1282-1288
31. Ehleringer JR, Klassen S, Clayton C, Sherrill D, Fuller-Holbrook M, Fu Q, Cooper T (1991) Carbon isotope discrimination and transpiration efficiency in common bean. Crop Sci 31: 1611-1615
32. Evanno G, Regnaut S, Goudet J (2005) Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Mol Ecol 14: 2611-2620
33. Farquhar GD, Richards RA (1984) Isotopic composition of plant carbon correlates with water-use efficiency of wheat genotypes. Aust J Plant Physiol 11: 539-552
34. Farquhar GD, O’Leary MH, Berry JA (1982) On the relationship between carbon isotope discrimination and the inter-cellular carbon-dioxide concentration in leaves. Aus J Plant Physiol 9: 121-137
35. Farquhar GD, Ehleringer JR, Hubick KT (1989) Carbon isotope discrimination and photosynthesis. Ann Rev Plant Physiol 40: 503-538
36. Fehr WR, Caviness CE, Burmood DT, Pennington JS (1971) Stage of development descriptions for soybeans, Glycine max (L.) Merr. Crop Sci 11: 929-931
37. Geber MA, Dawson TE (1997) Genetic variation in stomatal and biochemical limitations to photosynthesis in the annual plant Polygonum arenastrum. Oecologia 109: 535-546
38. Gilbert ME, Zwieniecki MA, Holbrook NM (2011) Independent variation in photosynthetic capacity and stomatal conductance leads to differences in intrinsic water use efficiency in 11 soybean genotypes before and during mild drought. J Exp Bot 62: 2875-2887
39. Grant D, Nelson RT, Cannon SC (2013) SoyBase, the USDA-ARS genetics and genomics database. [WWW document] http://soyb ase.org
40. Gu J, Yin X, Struik PC, Stomph TJ, Wang H (2012) Using chromosome introgression lines to map quantitative trait loci for photosynthesis parameters in rice (Oryza sativa L.) leaves under drought and well-watered field conditions. J Exp Bot 63: 455-469
41. Guo J, Liu Y, Wang Y, Chen J, Li Y, Huang H, Qiu L, Wang Y (2012) Population structure of the wild soybean (Glycine soja) in China: implications from microsatellite analyses. Ann Bot 110: 777-785
42. Hall AE, Mutters RG, Hubick KT, Farquhar GD (1990) Genotypic differences in carbon isotope discrimination by cowpea under wet and dry field conditions. Crop Sci 30: 300-305
43. Hao D, Cheng H, Yin Z, Cui S, Zhang D, Wang H, Yu D (2012) Identification of single nucleotide polymorphisms and haplotypes associated with yield and yield components in soybean (Glycine max) landraces across multiple environments. Theor Appl Genet 124: 447-458
44. Hervé D, Fabre F, Berrios EF, Leroux N, Al Chaarani G, Planchon C, Sarrafi A, Gentzbittel L (2001) QTL analysis of photosynthesis and water status traits in sunflower (Helianthus annuus L.) under greenhouse conditions. J Exp Bot 52: 1857-1864
45. Holland JB, Nyquist WE, Cervantes-Martinez CT (2003) Estimating and interpreting heritability for plant breeding: an update. Plant Breed Rev 22: 9-112
46. Hwang EY, Song Q, Jia G, Specht JE, Hyten DL, Costa J, Cregan PB (2014) A genome-wide association study of seed protein and oil content in soybean. BMC Genomics 15(1)
47. Hyten DL, Choi IY, Song Q, Shoemaker RC, Nelson RL, Costa JM, Specht JE, Cregan PB (2007) Highly variable patterns of linkage disequilibrium in multiple soybean populations. Genetics 175: 1937-1944
48. Ismail A, Hall A (1992) Correlation between water-use efficiency and carbon isotope discrimination in diverse cowpea genotypes and isogenic lines. Crop Sci 32: 7-12
49. Johnson RC (1993) Carbon isotope discrimination, water relations, and photosynthesis in Tall Fescues. Crop Sci 33: 169-174
50. Juenger TE, McKay JK, Hausmann N, Keurentjes J, Sen S, Stowe KA, Dawson TE, Simms EL, Richards JH (2005) Identification and characterization of QTL underlying whole-plant physiology in Arabidopsis thaliana: delta C-13, stomatal conductance and transpiration efficiency. Plant Cell Environ 28: 697-708
51. Kump KL, Bradbury PJ, Wisser RJ, Buckler ES, Belcher AR, Oropeza-Rosas MA, Zwonitzer JC, Kresovich S, McMullen MD, Ware D (2011) Genome-wide association study of quantitative resistance to southern leaf blight in the maize nested association mapping population. Nat Genet 43(2): 163-168
52. 13C and productivity in irrigated lowland rice. Crop Sci 46: 763-773
53. Li Y, Li W, Zhang C, Yang L, Chang R, Gaut B, Qiu L (2010) Genetic diversity in domesticated soybean (Glycine max) and its wild progenitor (Glycine soja) for simple sequence repeat and single nucleotide polymorphism loci. New Phytol 188: 242-253
54. Littell RC, Milliken GA, Stroup WW, Wolfinger RD (1996) SAS system for mixed models. SAS Institute Inc, Cary
55. Liu K, Muse SV (2005) Power Marker: integrated analysis environment for genetic marker data. Bioinformatics 21: 2128-2129
56. Louette D, Charrier A, Berthaud J (1997) In situ conservation of maize in Mexico: genetic diversity and maize seed management in a traditional community. Econ Bot 51: 20-38
57. Lu Y, Yan J, Guimaraes CT, Taba S, Hao Z, Gao S, Chen S, Li J, Zhang S, Vivek BS, Magorokosho C, Mugo S, Makumbi D, Parentoni SN, Shah T, Rong T, Crouch JH, Xu Y (2009) Molecular characterization of global maize breeding germplasm based on genome-wide single nucleotide polymorphisms. Theor App Genetics 120: 93-115
58. Mano Y, Muraki M, Fujimori M, Takamizo T, Kindiger B (2005) Identification of QTL controlling adventitious root formation during flooding conditions in teosinte (Zea mays ssp. huehuetenangensis) seedlings. Euphytica 142: 33-42
59. Mian MAR, Bailey MA, Ashley DA, Wells R, Carter TE, Parrott WA, Boerma HR (1996) A Molecular markers associated with water use efficiency and leaf ash in soybean. Crop Sci 36: 1252-1257
60. Mian MAR, Ashley DA, Boerma HR (1998) An additional QTL for water use efficiency in soybean. Crop Sci 38: 390-393
61. O’Leary MH (1981) Carbon isotope fractionation in plants. Phytochemistry 20: 553-567
62. Pasam RK, Sharma R, Malosetti M, van Eeuwijk FA, Haseneyer G, Kilian B, Graner A (2012) Genome-wide association studies for agronomical traits in a world wide spring barley collection. BMC Plant Biol 12: 16
63. Passioura JB (1977) Grain-yield, harvest index, and water-use of wheat. J Aust Inst Agric Sci 43: 117-120
64. Passioura JB (2004) Water-use efficiency in farmers’ fields. In: Bacon M (ed) Water-use efficiency in plant biology. Blackwell, Oxford, pp 302-321
65. Peakall R, Smouse PE, GENALEX (2006) Genetic analyses in Excel. population genetic software for teaching and research. Mol Ecol Notes 6: 288-295
66. Piepho HP, Möhring J (2007) Computing heritability and selection response From unbalanced plant breeding trials. Genetics 177: 1881-1888
67. Piepho HP, Möhring J, Melchinger AE, Büchse A (2008) BLUP for phenotypic selection in plant breeding and variety testing. Euphytica 161: 209-228
68. Pinto RS, Reynolds MP, Mathews KL, McIntyre CL, Olivares- Villegas JJ, Chapman SC (2010) Heat and drought adaptive QTL in a wheat population designed to minimize confounding agronomic effects. Theor Appl Genet 121: 1001-1021
69. Pritchard J, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics 155: 945
70. Rafalski J (2010) Association genetics in crop improvement. Curr Opin Plant Biol 13: 174-180
71. R Development Core Team (2013) R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN: 3-900051-07-0, http://www.R-project.org
72. Ray JD, Kilen TC, Abel C, Paris RL (2003) Soybean natural crosspollination rates under field conditions. Environ Biosaf Res 2: 133-138
73. Rebetzke GJ, Condon AG, Richards RA, Farquhar GD (2002) Selection for reduced carbon isotope discrimination increases aerial biomass and grain yield on rainfed bread wheat. Crop Sci 42: 739-745
74. Rebetzke GJ, Condon AG, Farquhar GD, Appels R, Richards RA (2008) Quantitative trait loci for carbon isotope discrimination are repeatable across environments and wheat mapping populations. Theor Appl Genet 118: 123-137
75. Reynolds M, Tuberosa R (2008) Translational research impacting on crop productivity in drought-prone environments. Curr Opin Plant Biol 11: 171-179
76. Riedelsheimer C, Lisec J, Czedik-Eysenberg A, Sulpice R, Flis A, Grieder C, Altmann T, Stitt M, Willmitzer L, Melchinger AE (2012) Genome-wide association mapping of leaf metabolic profiles for dissecting complex traits in maize. Proc Natl Acad Sci USA 109: 8872-8877
77. Salekdeh GH, Reynolds M, Bennett J, Boyer J (2009) Conceptual framework for drought phenotyping during molecular breeding. Trends Plant Sci 14: 488-496
78. Saranga Y, Flash I, Paterson AH, Yakir D (1999) Carbon isotope ratio in cotton varies with growth stage and plant organ. Plant Sci 142: 47-56
79. Saranga Y, Jiang CX, Wright RJ, Yakir D, Paterson AH (2004) Genetic dissection of cotton physiological responses to arid conditions and their inter-relationships with productivity. Plant Cell Environ 27: 263-277
80. SAS-Institute-Inc (2004) SAS/STAT User’s guide version 9.2 SASInstitute-Inc., Cary, NC
81. Shiferaw E, Pè ME, Porceddu E, Ponnaiah M (2012) Exploring the genetic diversity of Ethiopian grass pea (Lathyrus sativus L.) using EST-SSR markers. Mol Breeding 30: 789-797
82. Sinclair TR (2012) Is transpiration efficiency a viable plant trait in breeding for crop improvement ? Funct Plant Biol 39: 359-365
83. Song Q, Hyten DL, Jia G, Quigley CV, Fickus EW, Nelson RL, Cregan PB (2013) Development and evaluation of SoySNP50K, a high-density genotyping array for soybean. PLoS One 8: e54985
84. Specht JE, Chase K, Macrander M, Graef GL, Chung J, Markwell JP, Germann M, Orf JH, Lark KG (2001) Soybean response to water: a QTL analysis of drought tolerance. Crop Sci 41: 493-509
85. Storey JD, Tibshirani R (2003) Statistical significance for genomewide studies. Proc Natl Acad Sci USA 100(16): 9440-9445
86. Taji T, Seki M, Satou M, Sakurai T, Kobayashi M, Ishiyama K, Narusaka Y, Narusaka M, Zhu J, Shinozaki K et al (2004) Comparative genomics in salt tolerance between Arabidopsis and Arabidopsis- related halophyte salt cress using Arabidopsis microarray. Plant Physiol 135: 1697-1709
87. Takai T, Fukuta Y, Sugimoto A, Shiraiwa T, Horie T (2006) Mapping of QTLs controlling carbon isotope discrimination in the photosynthetic system using recombinant inbred lines derived from a cross between two different rice (Oryza sativa L.) cultivars. Plant Prod Sci 9: 271-280
88. Teulat B, Merah O, Sirault X, Borries C, Waugh R, This D (2002) QTLs for grain carbon isotope discrimination in field-grown barley. Theor Appl Genet 106: 118-126
89. Tuberosa R (2013) Phenotyping for drought tolerance of crops in the genomics era. Front Physiol 3: 347
90. Tuberosa R, Salvi S (2006) Genomics-based approaches to improve drought tolerance of crops. Trends Plant Sci 8: 405-412
91. Tuberosa R, Gill BS, Quarrie SA (2002) Cereal genomics: ushering in a brave new world. Plant Mol Biol 48: 445-449
92. Wang ML, Sukumaran S, Barkley NA, Chen Z, Chen CY, Guo B, Pittman RN, Stalker HT, Holbrook CC, Pederson GA, Yu J (2011) Population structure and marker-trait association analysis of the US peanut (Arachis hypogaea L.) mini-core collection. Theor Appl Genet 123: 1307-1317
93. Wingate L, Og’ee J, Burlett R, Bosc A, Devaux M, Grace J, Loustau D, Gessler A (2010) Photosynthetic carbon isotope discrimination and its relationship to the carbon isotope signals of stem, soil and ecosystem respiration. New Phytol 188: 576-589
94. Yang X, Yan J, Shah T, Warburton ML, Li Q, Li L, Gao Y, Chai Y, Fu Z, Zhou Y, Xu S, Bai G, Meng Y, Zheng Y, Li J (2010) Genetic analysis and characterization of a new maize association mapping panel for quantitative trait loci dissection. Theor Appl Genet 121: 417-431
95. Yoneyama T, Fujiwara H, Engelaar WM (2000) Weather and nodule mediated variations in delta 13C and delta 15N values in fieldgrown soybean (Glycine max L.) with special interest in the analyses of xylem fluids. J Exp Bot 344: 559-566
96. Yu J, Pressoir G, Briggs WH, Vroh Bi I, Yamasaki M, Doebley JF, McMullen MD, Gaut BS, Nielsen DM, Holland JB, Kresovich S, Buckler E (2006) A unified mixed-model method for association mapping that accounts for multiple levels of relatedness. Nat Genet 38: 203-208
97. Zhang Z, Ersoz E, Lai C, Todhunter R, Tiwari H, Gore M, Bradbury P, Yu J, Arnett D, Ordovas J, Buckler E (2010) Mixed linear model approach adapted for genome-wide association studies. Nat Genet 42: 355-360
98. Zhao K, Tung CW, Eizenga GC, Wright MH, Ali ML, Price AH, Norton GJ, Islam MR, Reynolds A, Mezey J, McClung AM, Bustamante CD, McCouch SR (2011) Genome-wide association mapping reveals a rich genetic architecture of complex traits in Oryza sativa. Nature Commun 2: 467