Hostname: page-component-586b7cd67f-t7fkt Total loading time: 0 Render date: 2024-12-01T00:10:56.722Z Has data issue: false hasContentIssue false
  • English
  • Français

Using SSR markers to map genetic diversity and population structure of Solanum pimpinellifolium for development of a core collection

Published online by Cambridge University Press:  12 December 2011

Eguru Sreenivasa Rao ,
Palchamy Kadirvel ,
Rachael C. Symonds ,
Subramaniam Geethanjali  and
Andreas W. Ebert
Eguru Sreenivasa Rao
Affiliation:
AVRDC – The World Vegetable Center, PO Box 42, Shanhua, Tainan74199, Taiwan, Republic of China
Palchamy Kadirvel
Affiliation:
AVRDC – The World Vegetable Center, PO Box 42, Shanhua, Tainan74199, Taiwan, Republic of China
Rachael C. Symonds
Affiliation:
AVRDC – The World Vegetable Center, PO Box 42, Shanhua, Tainan74199, Taiwan, Republic of China
Subramaniam Geethanjali
Affiliation:
AVRDC – The World Vegetable Center, PO Box 42, Shanhua, Tainan74199, Taiwan, Republic of China
Andreas W. Ebert*
Affiliation:
AVRDC – The World Vegetable Center, PO Box 42, Shanhua, Tainan74199, Taiwan, Republic of China
*
*Corresponding author. E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

The present study was undertaken to examine the population structure of the Solanum pimpinellifolium collection maintained by AVRDC – The World Vegetable Center – and to construct a core set of this collection. Out of the entire collection of 322 accessions, a diverse subset of 190 accessions was chosen representing 14 countries of origin. Data on 32 qualitative and 22 quantitative phenotypic traits (IPGRI–AVRDC descriptor traits) and 48 simple sequence repeat markers evenly distributed over the genome were used to develop the core set. A total of 377 alleles were detected with 7.85 alleles per locus, on average. Of these, 52 alleles at 28 loci were extremely rare-frequency alleles. The 190 accessions clustered into two main populations and an admixture group. Population I (PopI) included 99 accessions, 93 of which originated from Peru. Population II (PopII) contained 49 accessions, the majority of which originated from Ecuador and Mexico. The remaining 42 accessions were classified as admixture group. The two main populations were further subdivided into five subgroups. Values of Fst among the five sub-populations were significant (average pairwise Fst of 0.296), suggesting a real difference between these populations. A clear differentiation was observed among and within populations based on geography. Peruvian accessions were genetically more diverse than accessions originating in Ecuador and Mexico. Within the Peruvian group, a gradual increase in genetic diversity was observed from southern to northern Peru. The constructed core collection consists of 75 accessions representing 23.4% of AVRDC's entire S. pimpinellifolium collection and 39.5% of the subset used in this study. It is a well-balanced core with a good representation of the different populations (31 accessions from PopI, 22 from PopII and 22 from the Admixture group) and geographic origins (40 accessions from Peru, 17 from Ecuador, 14 from Mexico and four from other countries).

Keywords

association mappingcentre of origincore collectiongenome-wide SSR markersphenotypic traitspopulation structureSolanum pimpinellifoliumtomato genetic resources
Type
Research Article
Information
Plant Genetic Resources , Volume 10 , Issue 1 , April 2012 , pp. 38 - 48
Copyright
Copyright © NIAB 2011

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

Agrama, HA, Eizenga, GC and Yan, W (2007) Association mapping of yield and its components in rice cultivars. Molecular Breeding 19: 341–356.CrossRefGoogle Scholar
Agrama, HA, Yan, WG, Lee, F, Fjellstrom, R, Chen, MH, Jia, M and McClung, A (2009) Genetic assessment of a mini-core subset developed from the USDA Rice Genebank. Crop Science 49: 1336–1346.CrossRefGoogle Scholar
AVRDC Vegetable Genetic Resources Information System (AVGRIS)(2011) Available at http://203.64.245.173/avgris/search_result.asp?VINO = &ACCNO = &TEMPNO = &SPECIE = TM%3A+SOLANUMPIMPINELLIFOLIUM&PEDCUL = &SUBTAX = &COUNTR = &NOTES = 2011.Google Scholar
Balfourier, F, Charmet, G, Prosperi, JM, Goulard, M and Monestiez, P (1998) Comparison of different spatial strategies for sampling a core collection of natural populations of fodder crops. Genetics Selection Evolution 30: 215–235.CrossRefGoogle Scholar
Caicedo, AL and Schaal, BA (2004) Population structure and phylogeography of Solanum pimpinellifolium inferred from a nuclear gene. Molecular Ecology 13: 1871–1882.CrossRefGoogle ScholarPubMed
Chandra, S, Huaman, Z, Hari Krishna, S and Ortiz, R (2002) Optimal sampling strategy and core collection size of Andean tetraploid potato based on isozyme data – a simulation study. Theoretical and Applied Genetics 104: 1325–1334.CrossRefGoogle ScholarPubMed
Chunwongse, J, Chunwongse, C, Black, L and Hanson, P (2002) Molecular mapping of the Ph-3 gene for late blight resistance in tomato. Journal of Horticultural Science Biotechnology 77: 281–286.CrossRefGoogle Scholar
Evanno, GG, 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.CrossRefGoogle ScholarPubMed
Fernie, AR, Tadmor, Y and Zamir, D (2006) Natural genetic variation for improving crop quality. Current Opinion in Plant Biology 9: 196–202.CrossRefGoogle ScholarPubMed
Flint-Garcia, SA, Thornsberry, JM and Buckler, ES (2003) Structure of linkage disequilibrium in plants. Annual Review of Plant Biology 54: 357–374.CrossRefGoogle ScholarPubMed
Flint-Garcia, SA, Thuillet, AC, Yu, J, Pressoir, G, Romero, SM, Mitchell, S, Doebley, J, Kresovich, S, Goodman, MM and Buckler, ES (2005) Maize association population: a high-resolution platform for quantitative trait locus dissection. Plant Journal 44: 1054–1064.CrossRefGoogle ScholarPubMed
Foolad, MJ (2007) Genome mapping and molecular breeding of tomato. International Journal of Plant Genomics Vol. 2007, 52 pages. Doi: 10.1155/2007/64358.CrossRefGoogle ScholarPubMed
Franco, J, Crossa, J, Warburton, ML and Taba, S (2006) Sampling strategies for conserving maize diversity when forming core subsets using genetic markers. Crop Science 46: 854–864.CrossRefGoogle 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 & Unwin Ltd, pp. 249–257.Google Scholar
Frary, A, Xu, Y, Liu, J, Mitchell, S, Tedeschi, E and Tanksley, SD (2005) Development of a set of PCR-based anchor markers encompassing the tomato genome and evaluation of their usefulness for genetics and breeding experiments. Theoretical and Applied Genetics 111: 291–312.CrossRefGoogle ScholarPubMed
Geethanjali, S, Kadirvel, P, de la Peña, R, Rao, ES and Wang, JF (2011) Development of tomato SSR markers from anchored BAC clones of chromosome 12 and their application for genetic diversity analysis and linkage mapping. Euphytica 178: 283–295.CrossRefGoogle 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
Hu, J, Zhu, J and Xu, HM (2000) Methods of constructing core collections by stepwise clustering with three sampling strategies based on the genotypic values of crops. Theoretical and Applied Genetics 101: 264–268.CrossRefGoogle Scholar
International Plant Genetic Resources Institute (IPGRI) (1996) Descriptors for Tomato (Lycopersicon spp.). Rome: IPGRI.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.CrossRefGoogle ScholarPubMed
Kim, KW, Chung, HK, Cho, GT, Ma, KH, Chandrabalan, D, Gwag, JG, Kim, TS, Cho, EG and Park, YJ (2007) PowerCore: a program applying the advanced M strategy with a heuristic search for establishing allele mining sets. Bioinformatics 23: 2155–2162.CrossRefGoogle Scholar
Li, J, Schulz, B and Stich, B (2010) Population structure and genetic diversity in elite sugar beet germplasm investigated with SSR markers. Euphytica 175: 35–42.CrossRefGoogle Scholar
Liu, KJ and Muse, SV (2005) PowerMarker: an integrated analysis environment for genetic marker analysis. Bioinformatics 21: 2128–2129.CrossRefGoogle ScholarPubMed
Martin, GB, Williams, JGK and Tanksley, SD (1991) Rapid identification of markers linked to a Pseudomonas resistance gene in tomato by using random primers and near-isogenic lines. Proceedings of the National Academy of Sciences of the United States of America 88: 2336–2340.CrossRefGoogle ScholarPubMed
Moe, KT, Gwag, JG and Park, YJ (2011) Efficiency of PowerCore in core set development using amplified fragment length polymorphic markers in mungbean. Plant Breeding. Published online on 6 September 2011. Doi: 10.1111/j.1439-0523.2011.01896.x.Google Scholar
Nei, M (1973) Analysis of gene diversity in subdivided populations. Proceedings of the National Academy of Sciences of the United States of America 70: 3321–3323.CrossRefGoogle ScholarPubMed
Pritchard, JK and Wen, W (2004) Documentation of STRUCTURE Software. Chicago, IL: The University of Chicago Press.Google Scholar
Pritchard, JK, Stephens, M and Donnelly, P (2000) Inference of population structure using multilocus genotype data. Genetics 155: 945–959.CrossRefGoogle ScholarPubMed
Ranc, N, Muños, S, Santoni, S and Mathilde, C (2008) A clarified position for Solanum lycopersicum var. cerasiforme in the evolutionary history of tomatoes (solanaceae). BMC Plant Biology 8: 130.CrossRefGoogle ScholarPubMed
Remington, DL, Thornsberry, JM, Matsuola, Y, Wilson, LM, Whitt, SR, Doebley, J, Kresovich, S, Goodman, MM and Buckler, ES IV (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.CrossRefGoogle ScholarPubMed
Rick, CM and Fobes, JF (1975) Allozyme variation in the cultivated tomato and closely related species. Bulletin of the Torrey Botanical Club 102: 376–384.CrossRefGoogle Scholar
Rick, CM, Fobes, JF and Holle, M (1977) Genetic variation in Lycopersicon pimpinellifolium: evidence of evolutionary change in mating systems. Plant Systematics and Evolution 127: 139–170.CrossRefGoogle Scholar
Segal, G, Sarfatti, M, Schaffer, MA, Ori, N, Zamir, D and Fluhr, R (1992) Correlation of genetic and physical structure in the region surrounding the I2 Fusarium oxysporum resistance locus in tomato. Molecular and General Genetics 231: 179–185.CrossRefGoogle ScholarPubMed
Shannon, CE and Weaver, W (1963) The Mathematical Theory of Communication. Urbana: University of Illinois Press. (first published in 1949).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.CrossRefGoogle ScholarPubMed
Thornsberry, JM, Goodman, MM, Doebley, J, Kresovich, S, Nielsen, D and Buckler, ES (2001) Dwarf8 polymorphisms associate with variation in flowering time. Nature Genetics 28: 286–289.CrossRefGoogle ScholarPubMed
USDA, ARS, National Genetic Resources Program (USDA-ARS) (2011) Taxon: Solanum pimpinellifolium L. Germplasm Resources Information Network - (GRIN) [Online Database]. National Germplasm Resources Laboratory, Beltsville, Maryland. Available at http://www.ars-grin.gov/cgi-bin/npgs/html/tax_search.pl (accessed 3 June 2011).Google Scholar
van der Knaap, E, Sanyal, A, Jackson, SA and Tanksley, SD (2004) High-resolution fine mapping and fluorescence in situ hybridization analysis of sun, a locus controlling tomato fruit shape, reveals a region of the tomato genome prone to DNA rearrangements. Genetics 168: 2127–2140.CrossRefGoogle Scholar
Wiersema, JH and León, B (1999) World Economic Plants. A Standard Reference. Boca Raton, FL: CRC Press.CrossRefGoogle Scholar
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 and Li, J (2010) Genetic analysis and characterization of a new maize association mapping panel for quantitative trait loci dissection. Theoretical and Applied Genetics 121: 417–431.CrossRefGoogle ScholarPubMed
Yu, J and Buckler, ES (2006) Genetic association mapping and genome organization of maize. Current Opinion in Biotechnology 17: 155–160.CrossRefGoogle ScholarPubMed
Zhao, W, Cho, GT, Ma, KH, Chung, JW, Gwag, JG and Park, YJ (2010) Development of an allele mining set in rice using a heuristic algorithm and SSR genotype data with least redundancy for the post-genomic era. Molecular Breeding 26: 639–651.CrossRefGoogle Scholar
Zhu, CS, Gore, M, Buckler, ES and Yu, JM (2008) Status and prospects of association mapping in plants. Plant Genome 1: 5–20.CrossRefGoogle Scholar
Zuriaga, E, Blanca, JM, Cordero, L, Sifres, A, Blas-Cerdán, WG, Morales, R and Nuez, F (2009) Genetic and bioclimatic variation in Solanum pimpinellifolium. Genetic Resources and Crop Evolution 56: 39–51.CrossRefGoogle Scholar
Supplementary material: File

Ebert Supplementary Material

Ebert Supplementary Material

Download Ebert Supplementary Material(File)
File 337.9 KB