Hostname: page-component-586b7cd67f-dlnhk Total loading time: 0 Render date: 2024-11-24T18:47:50.642Z Has data issue: false hasContentIssue false
  • English
  • Français

Genetic diversity and linkage disequilibrium in the Argentine public maize inbred line collection

Published online by Cambridge University Press:  10 June 2016

Sofía E. Olmos ,
Verónica V. Lia  and
Guillermo H. Eyhérabide
Sofía E. Olmos*
Affiliation:
Instituto Nacional de Tecnología Agropecuaria EEA Pergamino, Ruta 32 Km.4,5 CP 2700. Pergamino Buenos Aires, Argentina
Verónica V. Lia
Affiliation:
Instituto de Biotecnología, CICVyA, INTA, Castelar, Los Reseros y Las Cabañas s/n, B1686ICG Hurlingham, Buenos Aires, Argentina
Guillermo H. Eyhérabide
Affiliation:
Instituto Nacional de Tecnología Agropecuaria EEA Pergamino, Ruta 32 Km.4,5 CP 2700. Pergamino Buenos Aires, Argentina
*
*Corresponding author. E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Knowledge of linkage disequilibrium (LD) patterns is considered a prerequisite for effective association mapping studies. However, no LD analysis in the Argentine public temperate maize collection has been reported to date. In this study, a panel of 111 temperate maize inbreds genotyped at 74 single sequence repeats (SSRs) loci was used to assess LD, genetic diversity and population structure to evaluate the suitability of the panel for association mapping. Mini-core sets were also designed for in-depth phenotyping and allele mining purposes. The panel consisted of: (1) locally developed orange flint germplasm; (2) temperate inbred lines with Iowa Stiff Stalk Synthetic background; and (3) eight historic flint lines, some of them from the Cuarentín race. As a result, four subpopulations were defined. Joint analysis of population structure and combining ability allowed identifying two main heterotic patterns. High molecular diversity, a low extent of LD and a high ratio of linked to unlinked SSR loci pairs in significant LD were detected indicating the suitability of the entire collection for association mapping. The fact that the LD extent in the mini-core sets was similar to that observed in the entire collection and that only a small percentage of allelic richness was reduced suggests that these mini-core sets are suitable to capture diversity, exploit phenotypic variance and discover useful variants representative of the entire collection.

Keywords

allelic richnessgenetic structureHardy–Weinberg disequilibriumheterotic patternsmicrosatellites
Type
Research Article
Information
Plant Genetic Resources , Volume 15 , Issue 6 , December 2017 , pp. 515 - 526
Copyright
Copyright © NIAB 2016 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Abdurakhmonov, IY, Saha, S, Jenkins, JN, Buriev, ZT, Shermatov, SE, Scheffler, BE, Pepper, AE, Yu, JZ, Kohel, RJ and Abdukarimov, A (2009) Linkage disequilibrium based association mapping of fiber quality traits in G. hirsutum L. variety germplasm. Genetica 136: 401–417.Google Scholar
Altschul, SF, Gish, W, Miller, W, Myers, EW and Lipman, DJ (1990) Basic local alignment search tool. Journal of Molecular Biology 215: 403–410.Google Scholar
Andrade, FH, Sala, RG, Pontaroli, AC and León, A (2015) Chapter 19 – integration of biotechnology, plant breeding and crop physiology: dealing with complex interactions from a physiological perspective. In: Sadras, VO and Calderini, D (eds) Crop Physiology Applications for Genetic Improvement and Agronomy, 2nd edn, Oxford, UK: Elsevier Inc, pp. 487–503.Google Scholar
Ashkani, S, Yusop, MR, Shabanimofrad, M, Azadi, A, Ghasemzadeh, A, Azizi, P and Latif, MA (2015) Allele mining strategies: principles and utilisation for blast resistance genes in rice (Oryza sativa L.). Current Issues in Molecular Biology 17: 57–74.Google ScholarPubMed
Ball, RD (2007) Statistical analysis and experimental design. In: Oraguzie, NC, Rikkerink, EHA, De Silva, HN and Gardiner, SE (eds) Association Mapping in Plants. New York: Springer, pp. 133–196.Google Scholar
Blumenschein, A (1973) Chromosome knob patterns in Latin American maize. Basic Life Science 2: 271–277.Google Scholar
Brown, AHD (1989) Core collections: a practical approach to genetic resources management. Genome 31: 818–824.Google Scholar
Brown, AHD and Schoen, DJ (1994) Optimal sampling strategies for core collections of plant genetic resources. In: Loeschcke, V, Tomiuk, J, Jain, SK (eds) Conservation Genetics. Basel, Switzerland: Birkhäuser Verlag, pp. 357–370.CrossRefGoogle Scholar
Campos-Bermudez, VA, Fauguel, CM, Tronconi, MA, Casati, P, Presello, DA and Andreo, CS (2013) Transcriptional and metabolic changes associated to the infection by Fusarium verticillioides in maize inbreds with contrasting ear rot resistance. PLoS ONE 8: e61580.Google Scholar
Camus-Kulandaivelu, L, Veyrieras, JB, Madur, D, Combes, V, Fourmann, M, Nordborg, M, Bergelson, J, Cuguen, J, and Roux, F (2006) Maize adaptation to temperate climate: relationship between population structure and polymorphism in the Dwarf8 gene. Genetics 172: 2449–2463.Google Scholar
Cockram, J, White, J, Leigh, FJ, Lea, VJ, Chiapparino, E, Laurie, DA, Mackay, IJ, Powell, W and O'Sullivan, DM (2008) Association mapping of partitioning loci in barley. BMC Genetics 9: 16.Google Scholar
D'Andrea, KE, Piedra, CV, Mandolino, CI, Bender, R, Cerri, AM, Cirilo, AG and Otegui, ME (2016) Contribution of reserves to kernel weight and grain yield determination in maize: phenotypic and genotypic variation. Crop Science 56: 697–706.Google Scholar
Delucchi, C, Eyhérabide, GH, Lorea, RD, Presello, DA, Otegui, ME and López, CG (2012) Classification of argentine maize landraces in heterotic groups. Maydica 57: 26–33.Google Scholar
Earl, DA and vonHoldt, BM (2012) STRUCTURE HARVESTER: a website and program for visualizing STRUCTURE output and implementing the Evanno method. Conservation Genetics Resources 4: 359–361.CrossRefGoogle Scholar
Evanno, G, Regnaut, S and Goudet, J (2005) Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Molecular Ecology 14: 2611–2620.Google Scholar
Frankel, OH and Brown, AHD (1984) Plant genetic resources today: a critical appraisal. In: Holden, JHW and Williams, JT (eds) Crop Genetic Resources: Conservation and Evaluation. London: Allen and Unwin, pp. 249–257.Google Scholar
Gaut, BS and Long, AD (2003) The lowdown on linkage disequilibrium. Plant Cell 15: 1502–1506.Google Scholar
Goodman, MM (1999) Broadening the genetic diversity in maize breeding by use of exotic germplasm. In: Coors, JG and Pandey, S (eds) The Genetics and Exploitation of Heterosis in Crops. Madison, WI, USA: ASA-CSSA-SSSA, 524 p.Google Scholar
Gouesnard, B, Dallard, J, Bertin, P, Boyat, A and Charcosset, A (2005) European maize landraces: genetic diversity, core collection definition and methodology of use. Maydica 50: 225–234.Google Scholar
Guo, Y, Li, Y, Hong, H and Qiu, Li-Juan (2014) Establishment of the integrated applied core collection and its comparison with mini core collection in soybean (Glycine max). The Crop Journal 2: 38–45.Google Scholar
Guthrie, WD, Russell, WA, Bing, JW and Dicke, FF (1991) Registration of B96 germplasm line of maize. Crop Science 31: 239–240.Google Scholar
Hardy, OJ and Vekemans, X (2002) SPAGeDi: a versatile computer program to analyze spatial genetic structure at the individual or population levels. Molecular Ecology Notes 2: 618–620.Google Scholar
Hatheway, WH (1957) Races of maize in Cuba. In: Races of Maize in Cuba. Washington, DC: NAS-NRC Publication 453, 75 p. Available at http://www.ars.usda.gov/sp2UserFiles/Place/50301000/Races_of_Maize/RoM_Cuba_0_Book.pdf Google Scholar
Ishitani, M, Rao, I, Wenzl, P, Beebe, S and Tohme, J (2004) Integration of genomics approach with traditional breeding towards improving abiotic stress adaptation: drought and aluminum toxicity as case studies. Field Crops Research 90: 35–45.Google Scholar
Jakobsson, M and Rosenberg, NA (2007) CLUMPP: a cluster matching and permutation program for dealing with label switching and multimodality in analysis of population structure. Bioinformatics 23: 1801–1806.Google Scholar
Jiang, H, Huang, L, Ren, X, Chen, Y, Zhou, X, Xia, Y, Huang, J, Lei, Y, Yan, L, Wan, L and Liao, B (2014) Diversity characterization and association analysis of agronomic traits in a Chinese peanut (Arachis hypogaea L.) mini-core collection. Journal of Integrative Plant Biology 56: 159–69.Google Scholar
Kaga, A, Shimizu, T, Watanabe, S, Tsubokura, Y, Katayose, Y, Harada, K, Vaughan, DA and Tomooka, N (2012) Evaluation of soybean germplasm conserved in NIAS genebank and development of mini core collections. Breeding Science 61: 566–592.CrossRefGoogle ScholarPubMed
Li, X, Yan, W, Agrama, H, Hu, B, Jia, L, Jia, M, Jackson, A, Moldenhauer, K, McClung, A and Wu, D (2010) Genotypic and phenotypic characterization of genetic differentiation and diversity in the USDA rice mini-core collection. Genetica 138: 1221–1230.Google Scholar
Lia, VV, Poggio, L and Confalonieri, VA (2009) Microsatellite variation in maize landraces from Northwestern Argentina: genetic diversity, population structure and racial affiliations. Theoretical and Applied Genetics 119: 1053–1067.Google Scholar
Liu, K and Muse, SV (2005) Powermarker: integrated analysis environment for genetic marker data. Bioinformatics 21: 2128–2129.Google Scholar
Liu, K, Goodman, MM, Muse, S, Smith, JSC, Buckler, ES and Doebley, J (2003) Genetic structure and diversity among maize inbred lines as inferred from DNA microsatellites. Genetics 165: 2117–2128.Google Scholar
Liu, Y, Guo, J, Zhang, D, Zhao, Y, Zhu, L, Huang, Y and Chen, J (2014) Genetic diversity and linkage disequilibrium estimation among the maize breeding germplasm for association mapping. International Journal Of Agriculture & Biology 16: 851–861.Google Scholar
Loiselle, BA, Sork, VL, Nason, J and Graham, C (1995) Spatial genetic structure of a tropical understory shrub, Psychotria officinalis (Rubiaceae). American Journal of Botany 82: 1420–1425.CrossRefGoogle Scholar
Mandel, JR, Nambeesan, S, Bowers, JE, Marek, LF, Ebert, D, Rieseberg, LH, Knapp, SJ and Burke, JM (2013) Association mapping and the genomic consequences of selection in sunflower. PLoS Genetics 9: e1003378.Google Scholar
Melchinger, AE and Gumber, RK (1998) Overview of heterosis and heterotic groups in agronomic crops. In: Lamkey, KR and Staub, JE (eds) Concepts and Breeding of Heterosis in Crop Plants. Madison, WI: CSSA, pp. 29–44.Google Scholar
Mikel, MA and Dudley, JW (2006) Evolution of North American Dent Corn from public to proprietary germplasm. Crop Science 46: 1193–1205.Google Scholar
Olmos, SE, Delucchi, C, Ravera, M, Negri, ME, Mandolino, C and Eyhérabide, GH (2014a) Genetic relatedness and population structure within the public Argentine collection of maize inbred lines. Maydica 59: 16–31.Google Scholar
Olmos, SE, Lorea, R and Eyhérabide, GH (2014b) Genetic variability within accessions of the B73 maize inbred line. Maydica 59: 298–305.Google Scholar
Oraguzie, NC, Wilcox, PL and Rikkerink, E (2007) Linkage disequilibrium. In: Oraguzie, NC, Rikkerink, EHA, De Silva, HN and Gardiner, SE (eds) Association Mapping in Plants. New York, Springer, pp. 10–39.Google Scholar
Paterniani, E and Goodman, MM (1977) Races of Maize in Brazil and Adjacent Areas. ed. Mexico: Las Américas, 95 p.Google Scholar
Pritchard, JK, Stephens, M and Donnelly, P (2000) Inference of population structure using multilocus genotype data. Genetics 155: 945–959.Google Scholar
Pritchard, JK, Wen, X and Falush, D (2010) Documentation for STRUCTURE Software: Version 2.3. The University of Chicago Press. Available at http://pritchardlab.stanford.edu/structure_software/release_versions/v2.3.3/structure_doc.pdf Google Scholar
Rafalski, A (2002) Applications of single nucleotide polymorphisms in crop genetics. Current Opinion in Plant Biology 5: 94–100.Google Scholar
Reif, JC, Hallauer, AR and Melchinger, AE (2005) Heterosis and heterotic patterns in maize. Maydica 50: 215–223.Google Scholar
Remington, DL, Thornsberry, JM, Matsuoka, Y, Wilson, LM, Whitt, SR, Doebley, J, Kresovich, S, Goodman, MM and Buckler, ES (2001) Structure of linkage disequilibrium and phenotypic associations in the maize genome. Proceedings of the National Academy of Sciences of the United States of America 98: 11479–11484.Google Scholar
Rincent, R, Nicolas, S, Bouchet, S, Altmann, T, Brunel, D, Revilla, P, Malvar, RA, Moreno-Gonzalez, J, Campo, L, Melchinger, AE, Schipprack, W, Bauer, E, Schoen, CC, Meyer, N, Ouzunova, M, Dubreuil, P, Giauffret, C, Madur, D, Combes, V, Dumas, F, Bauland, C, Jamin, P, Laborde, J, Flament, P, Moreau, L and Charcosset, A (2014) Dent and Flint maize diversity panels reveal important genetic potential for increasing biomass production. Theoretical and Applied Genetics 127: 2313–2331.CrossRefGoogle ScholarPubMed
Roberts, LM, Grant, UJ, Ramirez, ER, Hatheway, WH and Smith, DL (1957) Factors involved in the evolution of maize in Colombia. In: Races of maize in Colombia. Washington, DC: NAS-NRC Publication 510, 153 p. Available at http://www.ars.usda.gov/sp2UserFiles/Place/50301000/Races_of_Maize/RoM_Colombia_0_Book.pdf Google Scholar
Sampietro, DA, Vattuone, MA, Presello, DA, Fauguel, CM and Catalán, CAN (2009) The pericarp and its surface wax layer in maize kernels as resistance factors to fumonisin accumulation by Fusarium verticillioides . Crop Protection 28: 196–200.Google Scholar
Schafleitner, R, Nair, RM, Rathore, A, Wang, YW, Lin, CY, Chu, SH, Lin, PY, Chang, JC and Ebert, AW (2015) The AVRDC – the world vegetable center mungbean (Vigna radiata) core and mini core collections. BMC Genomics 29: 344.Google Scholar
Slatkin, M (2008) Linkage disequilibrium – understanding the evolutionary past and mapping the medical future. Nature Reviews Genetics 9: 477–485.Google Scholar
Stich, B, Melchinger, AE, Frisch, M, Maurer, HP, Heckenberger, M and Reif, JC (2005) Linkage disequilibrium in European elite maize germplasm investigated with SSRs. Theoretical and Applied Genetics 111: 723–730.Google Scholar
Stich, B, Mohring, J, Piepho, HP, Heckenberger, M, Buckler, ES and Melchinger, AE (2008) Comparison of mixed-model approaches for association mapping. Genetics 178: 1745–1754.Google Scholar
Szpiech, ZA, Jakobsson, M and Rosenberg, NA (2008) ADZE: a rarefaction approach for counting alleles private to combinations of populations. Bioinformatics 24: 2498–2504.Google Scholar
Upadhyaya, HD, Wang, YH, Gowda, CL and Sharma, S (2013) Association mapping of maturity and plant height using SNP markers with the sorghum mini core collection. Theoretical and Applied Genetics 126: 2003–2015.CrossRefGoogle ScholarPubMed
Van Inghelandt, D, Reif, JC, Dhillon, BS, Flament, P and Melchinger, AE (2011) Extent and genome-wide distribution of linkage disequilibrium in commercial maize germplasm. Theoretical and Applied Genetics 123: 11–20.CrossRefGoogle ScholarPubMed
Wang, R, Yu, Y, Zhao, J, Shi, Y, Song, Y, Wang, T and Li, Y (2008) Population structure and linkage disequilibrium of a mini core set of maize inbred lines in China. Theoretical and Applied Genetics 117: 1141–1153.Google Scholar
Wang, ML, Sukumaran, S, Barkley, NA, Chen, Z, Chen, CY, Guo, B, Pittman, RN, Stalker, HT, Holbrook, CC, Pederson, GA and Yu, J (2011) Population structure and marker-trait association analysis of the US peanut (Arachis hypogaea L.) mini-core collection. Theoretical and Applied Genetics 123: 1307–1317.CrossRefGoogle ScholarPubMed
Weir, BS (1996) Genetic data analysis II: Methods for discrete population genetic data, 2nd ed. Sunderland, Massachusetts: Sinauer Associates, 445 p.Google Scholar
Wen, W, Franco, J, Chavez-Tovar, VH, Yan, J and Taba, S (2012) Genetic characterization of a core set of a tropical maize race tuxpeño for further use in maize improvement. PLoS ONE 7: e32626.CrossRefGoogle ScholarPubMed
Yan, J, Shah, T, Warburton, ML, Buckler, ES, McMullen, MD and Crouch, J (2009) Genetic characterization and linkage disequilibrium estimation of a global maize collection using SNP markers. PLoS ONE 4: e8451.CrossRefGoogle ScholarPubMed
Yu, J, Pressoir, G, Briggs, WH, Bi, IV, Yamasaki, M, Doebley, JF, McMullen, MD, Gaut, BS, Nielsen, DM, Holland, JB, Kresovich, S and Buckler, ES (2006) A unified mixed-model method for association mapping that accounts for multiple levels of relatedness. Nature Genetics 38: 203–208.Google Scholar
Yu, J, Holland, JB, McMullen, MD and Buckler, ES (2008) Genetic design and statistical power of nested association mapping in maize. Genetics 178: 539–551.Google Scholar
Zhang, H, Zhang, D, Wang, M, Sun, J, Qi, Y, Li, J, Wei, X, Han, L, Qiu, Z, Tang, S and Li, Z (2011) A core collection and mini core collection of Oryza sativa L. in China. Theoretical and Applied Genetics 122: 49–61.CrossRefGoogle ScholarPubMed
Zhang, Y, Zhang, X, Che, Z, Wang, L, Wei, W and Li, D (2012) Genetic diversity assessment of sesame core collection in China by phenotype and molecular markers and extraction of a mini-core collection. BMC Genetics 15: 102.Google Scholar
Zhu, C, Gore, M, Buckler, ES and Yu, J (2008) Status and prospects of association mapping in plants. The Plant Genome 1: 5–20.Google Scholar
Supplementary material: File

Olmos supplementary Material Tables

Supplementary Tables Zip

Download Olmos supplementary Material Tables(File)
File 2 MB