Transferability of Marker Trait Associations in Wheat Is Disturbed Mainly by Genotype × Year Interaction-Crop Breeding, Genetics and Genomics-CSCIED科技核心评价数据库-手机版

Transferability of Marker Trait Associations in Wheat Is Disturbed Mainly by Genotype × Year Interaction

Transferability of Marker Trait Associations in Wheat Is Disturbed Mainly by Genotype × Year Interaction

ES评分 0 浏览量：738 下载量：0

DOI	10.20900/cbgg20200013
刊名	Crop Breeding, Genetics and Genomics CBGG
年，卷(期)	2020, 2(3)
作者	Blake Russell,Gina Brown-Guedira,Clay H. Sneller,Mohsen Mohammadi*,
作者单位	Department of Agronomy, Purdue University, 915 West State Street, West Lafayette, IN 47907, USA ; US Department of Agriculture, Agricultural Research Services, Small Grains Genotyping Laboratory, Raleigh, NC 27695, USA ; Ohio Agricultural Research and Development Center, The Ohio State University, Wooster, Ohio 446931, USA ;
Abstract	Grain yield is the primary target for increasing soft red winter wheat production in the United States. Genome wide association studies were performed for yield-related traits using field-based evaluation of 270 elite breeding lines. Yield ranged from 3.9 to 7.5 tons·ha−1. The effect of genotype by year interaction was significant for most traits. Heritability estimates ranged from 0.21 for biomass to 0.84 for plant height. Biomass, kernel weight, and grain weight per spike were positively correlated with grain yield while days to heading and maturity were negatively correlated with grain yield. We used FarmCPU method and 45K markers to identify marker-trait associations. Fifty-nine MTAs were identified based on two-year phenotypic estimates. An association for grain yield on chromosome 7D showed a −logP value of 16.35 and explained 18% of the phenotypic variation. Associations were identified at −logP values of 6.30 and 4.08 on chromosomes 5A for thousand kernel weight and grain per spike that explained 10% and 6% of phenotypic variations, respectively. Grain yield and days to heading data from previous trials in other states were used to validate and evaluate the transferability of associations. We observed that for grain yield, only 7 out of 28 associations and for days to heading, only 8 out of 47 associations were validated across seemingly homogenous environments, indicating the majority of associations are not stable QTL across environments. This study suggests that achieving genetic gains appears to require utilizing genotype by environment interaction and local field based germplasm testing.
KeyWord	wheat; genome wide association studies; marker trait associations; yield components; grain yield; days to heading
基金项目
页码	-

参考文献
相关文献

1.Bushuk W. Wheat breeding for end-product use. In: Braun H-J, Altay F, Kronstad WE, Beniwal SPS, McNab A, editors. Wheat: Prospects for global improvement. Dordrecht (The Netherlands): Springer; 1997. p. 203-11.

2.USDA. Economics, Statistics, and Market Information System. 2019. Available from: Accessed 2019 Jun 28.

3.Leff B, Ramankutty N, Foley JA. Geographic distribution of major crops across the world. Global Bbiogeochem Cycles. 2004 Mar;18(1):GB1009.

4.Bacon RK. US Soft Winter Wheat Pool. In: Bonjean AP, Angus WJ, editors. The World Wheat Book: A History of Wheat Breeding. New York (US): Intercept; 2001. p. 469-78.

5.Kiszonas AM, Fuerst EP, Morris CF. A comprehensive survey of soft wheat grain quality in US germplasm. Cereal Chem. 2013 Jan;90(1):47-57.

6.Reynolds M, Foulkes J, Furbank R, Griffiths S, King J, Murchie E, et al. Achieving yield gains in wheat. Plant Cell Environ. 2012 Oct;35(10):1799-823.

7.Hawkesford MJ, Araus JL, Park R, Calderini D, Miralles D, Shen T, et al. Prospects of doubling global wheat yields. Food Energy Secur. 2013 May;2(1):34-48.

8.Ray DK, Mueller ND, West PC, Foley JA. Yield trends are insufficient to double global crop production by 2050. PLoS One. 2013 Jun 19;8(6):e66428.

9.Reynolds MP, Rajaram S, Sayre KD. Physiological and genetic changes of irrigated wheat in the post–green revolution period and approaches for meeting projected global demand. Crop Sci. 1999 Nov;39(6):1611-21.

10.Donmez E, Sears RG, Shroyer JP, Paulsen GM. Genetic gain in yield attributes of winter wheat in the Great Plains. Crop Sci. 2001 Sep;41(5):1412-9.

11.Green AJ, Berger G, Griffey CA, Pitman R, Thomason W, Balota M, et al. Genetic yield improvement in soft red winter wheat in the Eastern United States from 1919 to 2009. Crop Sci. 2012 Sep;52(5):2097-108.

12.Austin RB, Bingham J, Blackwell RD, Evans LT, Ford MA, Morgan CL, et al. Genetic improvements in winter wheat yields since 1900 and associated physiological changes. Journal Agric Sci. 1980 Jun;94(3):675-89.

13.Reynolds MP, Pellegrineschi A, Skovmand B. Sink‐limitation to yield and biomass: a summary of some investigations in spring wheat. Ann Appl Biol. 2005 Jan;146(1):39-49.

14.Devos KM, Atkinson MD, Chinoy CN, Liu CJ, Gale MD. RFLP-based genetic map of the homoeologous group 3 chromosomes of wheat and rye. Theor Appl Genet. 1992 May 1;83(8):931-9.

15.Helentjaris T, Slocum M, Wright S, Schaefer A, Nienhuis J. Construction of genetic linkage maps in maize and tomato using restriction fragment length polymorphisms. Theor Appl Genet. 1986 Sep 1;72(6):761-9.

16.Doerge RW. Mapping and analysis of quantitative trait loci in experimental populations. Nat Rev Genet. 2002 Jan;3(1):43-52.

17.Kumar N, Kulwal PL, Balyan HS, Gupta PK. QTL mapping for yield and yield contributing traits in two mapping populations of bread wheat. Mol Breed. 2007 Feb 1;19(2):163-77.

18.Cui F, Li J, Ding A, Zhao C, Wang L, Wang X, et al. Conditional QTL mapping for plant height with respect to the length of the spike and internode in two mapping populations of wheat. Theor Appl Genet. 2011 May 1;122(8):1517-36.

19.Paliwal R, Röder MS, Kumar U, Srivastava JP, Joshi AK. QTL mapping of terminal heat tolerance in hexaploid wheat (T. aestivum L.). Theor Appl Genet. 2012 Aug 1;125(3):561-75.

20.Olmos S, Distelfeld A, Chicaiza O, Schlatter AR, Fahima T, Echenique V, et al. Precise mapping of a locus affecting grain protein content in durum wheat. Theor Appl Genet. 2003 Nov 1;107(7):1243-51.

21.Löffler M, Schön CC, Miedaner T. Revealing the genetic architecture of FHB resistance in hexaploid wheat (Triticum aestivum L.) by QTL meta-analysis. Mol Breed. 2009 Apr 1;23(3):473-88.

22.Shen X, Zhou M, Lu W, Ohm H. Detection of Fusarium head blight resistance QTL in a wheat population using bulked segregant analysis. Theor Appl Genet. 2003 Apr 1;106(6):1041-7.

23.Zwart RS, Thompson JP, Milgate AW, Bansal UK, Williamson PM, Raman H, et al. QTL mapping of multiple foliar disease and root-lesion nematode resistances in wheat. Mol Breed. 2010 Jun 1;26(1):107-24.

24.Anderson JA, Stack RW, Liu S, Waldron BL, Fjeld AD, Coyne C, et al. DNA markers for Fusarium head blight resistance QTLs in two wheat populations. Theor Appl Genet. 2001 Jun 1;102(8):1164-8.

25.Kirigwi FM, Van Ginkel M, Brown-Guedira G, Gill BS, Paulsen GM, Fritz AK. Markers associated with a QTL for grain yield in wheat under drought. Mol Breed. 2007 Nov 1;20(4):401-13.

26.Myles S, Peiffer J, Brown PJ, Ersoz ES, Zhang Z, Costich DE, et al. Association mapping: critical considerations shift from genotyping to experimental design. Plant Cell. 2009 Aug 1;21(8):2194-202.

27.Zhu C, Gore M, Buckler ES, Yu J. Status and prospects of association mapping in plants. Plant Genom. 2008 Jul;1(1):5-20.

28.Yu J, Buckler ES. Genetic association mapping and genome organization of maize. Curr Opin Biotechnol. 2006 Apr 1;17(2):155-60.

29.Ersoz ES, Yu J, Buckler ES. Applications of linkage disequilibrium and association mapping in crop plants. In: Rajeev K. Varshney RK, Tuberosa R, editors. Genomics-Assisted Crop Improvement. Cham (Switzerland): Springer; 2007. Volume 1, p. 97-119.

30.Liu J, Xu Z, Fan X, Zhou Q, Cao J, Wang F, et al. A genome-wide association study of wheat spike related traits in China. Front Plant Sci. 2018 Oct 31;9:1584.

31.Breseghello F, Sorrells ME. Association mapping of kernel size and milling quality in wheat (Triticum aestivum L.) cultivars. Genetics. 2006 Feb 1;172(2):1165-77.

32.Daba SD, Tyagi P, Brown-Guedira G, Mohammadi M. Genome-wide association studies to identify loci and candidate genes controlling kernel weight and length in a historical United States wheat population. Front Plant Sci. 2018 Aug 3;9:1045.

33.Gaire R, Huang M, Sneller C, Griffey C, Brown-Guedira G, Mohammadi M. Association analysis of baking and milling quality traits in an elite soft red winter wheat population. Crop Sci. 2019 May;59(3):1085-94.

34.Beyer S, Daba S, Tyagi P, Bockelman H, Brown-Guedira G, Mohammadi M. Loci and candidate genes controlling root traits in wheat seedlings—a wheat root GWAS. Funct Integr Genomics. 2019 Jan 1;19(1):91-107.

35.Lozada DN, Mason RE, Sukumaran S, Dreisigacker S. Validation of grain yield QTLs from soft winter wheat using a CIMMYT spring wheat panel. Crop Sci. 2018 Sep;58(5):1964-71.

36.Sukumaran S, Lopes M, Dreisigacker S, Reynolds M. Genetic analysis of multi-environmental spring wheat trials identifies genomic regions for locus-specific trade-offs for grain weight and grain number. Theor Appl Genet. 2018 Apr 1;131(4):985-98.

37.Yu J, Pressoir G, Briggs WH, Bi IV, Yamasaki M, Doebley JF, et al. A unified mixed-model method for association mapping that accounts for multiple levels of relatedness. Nat Genet. 2006 Feb;38(2):203-8.

38.Zhang Z, Ersoz E, Lai CQ, Todhunter RJ, Tiwari HK, Gore MA, et al. Mixed linear model approach adapted for genome-wide association studies. Nat Genet. 2010 Apr;42(4):355-60.

39.Kaler AS, Gillman JD, Beissinger T, Purcell LC. Comparing different statistical models and multiple testing corrections for association mapping in soybean and maize. Front Plant Sci. 2020 Feb 25;10:1794.

40.Wen YJ, Zhang H, Ni YL, Huang B, Zhang J, Feng JY, et al. Methodological implementation of mixed linear models in multi-locus genome-wide association studies. Briefings Bioinf. 2018 Jul;19(4):700-12.

41.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 Feb 1;12(2):e1005767.

42.Huang M, Cabrera A, Hoffstetter A, Griffey C, Van Sanford D, Costa J, et al. Genomic selection for wheat traits and trait stability. Theor Appl Genet. 2016 Sep 1;129(9):1697-710.

43.Wang S, Wong D, Forrest K, Allen A, Chao S, Huang BE, et al. Characterization of polyploid wheat genomic diversity using a high‐density 90000 single nucleotide polymorphism array. Plant Biotechnol J. 2014 Aug;12(6):787-96.

44.Poland JA, Brown PJ, Sorrells ME, Jannink JL. Development of high-density genetic maps for barley and wheat using a novel two-enzyme genotyping-by-sequencing approach. PLoS One. 2012 Feb 28;7(2):e32253.

45.Bradbury PJ, Zhang Z, Kroon DE, Casstevens TM, Ramdoss Y, Buckler ES. TASSEL: software for association mapping of complex traits in diverse samples. Bioinformatics. 2007 Oct 1;23(19):2633-5.

46.Appels R, Eversole K, Stein N, Feuillet C, Keller B, Rogers J, et al. Shifting the limits in wheat research and breeding using a fully annotated reference genome. Science. 2018 Aug 17;361(6403):eaar7191.

47.Li H, Durbin R. Fast and accurate short read alignment with Burrows–Wheeler transform. Bioinformatics. 2009 Jul 15;25(14):1754-60. https://doi.org/10.1093/bioinformatics/btp324

48.Money D, Gardner K, Migicovsky Z, Schwaninger H, Zhong GY, Myles S. LinkImpute: fast and accurate genotype imputation for nonmodel organisms. G3 (Bethesda). 2015 Nov 1;5(11):2383-90.

49.R Core Team. R: A language and environment for statistical computing. Auckland (New Zealand): R Core Team; 2019.

50.Bates D, Mächler M, Bolker B, Walker S. Fitting linear mixed-effects models using lme4. J Stat Software. 2015;67(1).

51.Rosseel Y. Lavaan: An R package for structural equation modeling and more. Version 0.5–12 (BETA). J Stat Software. 2012 Dec 19;48(2):1-36.

52.Nyquist WE, Baker RJ. Estimation of heritability and prediction of selection response in plant populations. Crit Rev Plant Sci. 1991 Jan 1;10(3):235-322.

53.Piepho HP, Möhring J. Computing heritability and selection response from unbalanced plant breeding trials. Genetics. 2007 Nov 1;177(3):1881-8.

54.Hill WG, Weir BS. Variances and covariances of squared linkage disequilibria in finite populations. Theor Popul Biol. 1988 Feb 1;33(1):54-78.

55.Edae EA, Byrne PF, Haley SD, Lopes MS, Reynolds MP. Genome-wide association mapping of yield and yield components of spring wheat under contrasting moisture regimes. Theor Appl Genet. 2014 Apr 1;127(4):791-807.

56.Vos PG, Paulo MJ, Voorrips RE, Visser RG, van Eck HJ, van Eeuwijk FA. Evaluation of LD decay and various LD-decay estimators in simulated and SNP-array data of tetraploid potato. Theor Appl Genet. 2017 Jan 1;130(1):123-35.

57.Lipka AE, Tian F, Wang Q, Peiffer J, Li M, Bradbury PJ, et al. GAPIT: genome association and prediction integrated tool. Bioinformatics. 2012 Sep 15;28(18):2397-9.

58.Price AL, Patterson NJ, Plenge RM, Weinblatt ME, Shadick NA, Reich D. Principal components analysis corrects for stratification in genome-wide association studies. Nat Genet. 2006 Aug;38(8):904-9.

59.Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Ser B Methodol. 1995 Jan;57(1):289-300.

60.Venables WN, Ripley BD. Modern Applied Statistics with S, 4th ed. New York (US): Springer; 2002. ISBN 0-387-95457-0. http://www.stats.ox.ac.uk/pub/MASS4

61.Kotal BD, Arpita D, Choudhury BK. Genetic variability and association of characters in wheat (Triticum aestivum L.). Asian J Crop Sci. 2010;2(3):155-60.

62.Philipp N, Weichert H, Bohra U, Weschke W, Schulthess AW, Weber H. Grain number and grain yield distribution along the spike remain stable despite breeding for high yield in winter wheat. PLoS One. 2018 Oct 10;13(10):e0205452.

63.Addison CK, Mason RE, Brown-Guedira G, Guedira M, Hao Y, Miller RG, et al. QTL and major genes influencing grain yield potential in soft red winter wheat adapted to the southern United States. Euphytica. 2016 Jun 1;209(3):665-77.

64.Dewey DR, Lu K. A Correlation and Path‐Coefficient Analysis of Components of Crested Wheatgrass Seed Production. Agron J. 1959 Sep;51(9):515-8.

65.Arruda MP, Brown P, Brown‐Guedira G, Krill AM, Thurber C, Merrill KR, et al. Genome‐wide association mapping of Fusarium head blight resistance in wheat using genotyping‐by‐sequencing. Plant Genom. 2016 Mar;9(1):1-4.

66.Huang M, Mheni N, Brown-Guedira G, McKendry A, Griffey C, Van Sanford D, et al. Genetic analysis of heading date in winter and spring wheat. Euphytica. 2018 Aug 1;214(8):128.

67.Arguello MN, Mason RE, Roberts TL, Subramanian N, Acuna A, Addison CK, et al. Performance of soft red winter wheat subjected to field soil waterlogging: grain yield and yield components. Field Crops Res. 2016 Aug 1;194:57-64.

68.Sharma RC, Tiwary AK, Ortiz‐Ferrara G. Reduction in kernel weight as a potential indirect selection criterion for wheat grain yield under terminal heat stress. Plant Breed. 2008 Jun;127(3):241-8.

69.Godoy J, Gizaw S, Chao S, Blake N, Carter A, Cuthbert R, et al. Genome‐wide Association Study of Agronomic Traits in a Spring‐Planted North American Elite Hard Red Spring Wheat Panel. Crop Sci. 2018 Sep;58(5):1838-52.

70.Lanning SP, Kephart K, Carlson GR, Eckhoff JE, Stougaard RN, Wichman DM, et al. Climatic change and agronomic performance of hard red spring wheat from 1950 to 2007. Crop Sci. 2010 May;50(3):835-41.

71.Tessmann EW, Dong Y, Van Sanford DA. GWAS for Fusarium head blight traits in a soft red winter wheat mapping panel. Crop Sci. 2019 Sep;59(5):1823-37.

72.Bian Y, Yang Q, Balint-Kurti PJ, Wisser RJ, Holland JB. Limits on the reproducibility of marker associations with southern leaf blight resistance in the maize nested association mapping population. BMC Genomics. 2014 Dec 1;15(1):1068.

73.Poland JA, Bradbury PJ, Buckler ES, Nelson RJ. Genome-wide nested association mapping of quantitative resistance to northern leaf blight in maize. Proc Natl Acad Sci U S A. 2011 Apr 26;108(17):6893-8.

74.Xu Y, Yang T, Zhou Y, Yin S, Li P, Liu J, et al. Genome-wide association mapping of starch pasting properties in maize using single-locus and multi-locus models. Front Plant Sci. 2018 Sep 5;9:1311. doi: 10.3389/fpls.2018.01311

75.Vanous A, Gardner C, Blanco M, Martin‐Schwarze A, Wang J, Li X, et al. Stability Analysis of Kernel Quality Traits in Exotic‐Derived Doubled Haploid Maize Lines. Plant Genom. 2019 Mar;12(1):1-4. doi: 10.3835/plantgenome2017.12.0114

76.Ohm HW, Anderson JM, Sharma HC, Ayala L, Thompson N, Uphaus JJ. Registration of Yellow Dwarf Viruses Resistant Wheat Germplasm Line P961341. Crop Sci. 2005 Mar 1;45(2):805-6.

77.Gutiérrez L, Germán S, Pereyra S, Hayes PM, Pérez CA, Capettini F, et al. Multi-environment multi-QTL association mapping identifies disease resistance QTL in barley germplasm from Latin America. Theor Appl Genet. 2015 Mar 1;128(3):501-16.

78.Collard BC, Mackill DJ. Marker-assisted selection: an approach for precision plant breeding in the twenty-first century. Philos Trans R Soc B Biol Sci. 2008 Feb 12;363(1491):557-72.

79.Ribaut JM, Ragot M. Marker-assisted selection to improve drought adaptation in maize: the backcross approach, perspectives, limitations, and alternatives. J Exp Bot. 2007 Jan 1;58(2):351-60.

80.Guan P, Lu L, Jia L, Kabir MR, Zhang J, Lan T, et al. Global QTL analysis identifies genomic regions on chromosomes 4A and 4B harboring stable loci for yield-related traits across different environments in wheat (Triticum aestivum L.). Front Plant Sci. 2018 Apr 25;9:529.

81.Simmonds J, Scott P, Leverington-Waite M, Turner AS, Brinton J, Korzun V, et al. Identification and independent validation of a stable yield and thousand grain weight QTL on chromosome 6A of hexaploid wheat (Triticum aestivum L.). BMC Plant Biol. 2014 Dec 1;14(1):191.

引用本文

Blake Russell,Gina Brown-Guedira,Clay H. Sneller,Mohsen Mohammadi*. Transferability of Marker Trait Associations in Wheat Is Disturbed Mainly by Genotype × Year Interaction, Crop Breeding, Genetics and Genomics. 2020; 2; (3). https://doi.org/10.20900/cbgg20200013.

文献评论

相关学者

相关机构