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Molecular Breeding

, Volume 30, Issue 2, pp 731–744 | Cite as

Abundance, marker development and genetic mapping of microsatellites from unigenes in Brassica napus

  • Fang Wang
  • Xiaofeng Wang
  • Xun Chen
  • Yingjie Xiao
  • Haitao Li
  • Shunchang Zhang
  • Jinsong Xu
  • Jie Fu
  • Lei Huang
  • Chao Liu
  • Jiangsheng Wu
  • Kede Liu
Article

Abstract

Rapeseed (Brassica napus) is the second most important oil crop in the world after soybean. The repertoire of simple sequence repeat (SSR) markers for rapeseed is limited and warrants a search for a larger number of polymorphic SSRs for germplasm characterization and breeding applications. In this study, a total of 5,310 SSR-containing unigenes were identified from a set of 46,038 B. napus unigenes with an average density of one SSR every 5.75 kb. A set of 1,000 expressed sequence tag (EST)-SSR markers with repeat length ≥18 bp were developed and tested for their ability to detect polymorphism among a panel of six rapeseed varieties. Of these SSR markers, 776 markers detected clear amplification products, and 511 displayed polymorphisms among the six varieties. Of these polymorphic markers, 195 EST-SSR markers, corresponding to 233 loci, were integrated into an existing B. napus linkage map. These EST-SSRs were randomly distributed on the 19 linkage groups of B. napus. Of the mapped loci, 166 showed significant homology to Arabidopsis genes. Based on the homology, 44 conserved syntenic blocks were identified between B. napus and Arabidopsis genomes. Most of the syntenic blocks were consistent with the duplication and rearrangement events identified previously. In addition, we also identified three previously unreported blocks in B. napus. A subset of 40 SSRs was used to assess genetic diversity in a collection of 192 rapeseed accessions. The polymorphism information content of these markers ranged from 0.0357 to 0.6753 with an average value of 0.3373. These results indicated that the EST-SSR markers developed in this study are useful for genetic mapping, molecular marker-assisted selection and comparative genomics.

Keywords

Brassica napus EST-SSR Linkage map Syntenic blocks 

Notes

Acknowledgments

The research was supported by the National Natural Science Foundation of China (No. 31071452) and the Doctoral Fund of Ministry of Education of China (No. 20100146110019).

Supplementary material

11032_2011_9658_MOESM1_ESM.xls (316 kb)
Supplementary material 1 (XLS 315 kb)

References

  1. Batley J, Hopkins CJ, Cogan NOI, Hand M, Jewell E, Kaur J, Kaur S, Li XI, Ling AE, Love C, Mountford H, Todorovic M, Vardy M, Walkiewicz M, Spangenberg GC, Edwards D (2007) Identification and characterization of simple sequence repeat markers from Brassica napus expressed sequences. Mol Ecol Notes 7:886–889CrossRefGoogle Scholar
  2. 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 32:314–331PubMedGoogle Scholar
  3. Chen G, Geng J, Rahman M, Liu X, Tu J, Fu T, Li G, McVetty P, Tahir M (2010) Identification of QTL for oil content, seed yield, and flowering time in oilseed rape Brassica napus. Euphytica 175:161–174CrossRefGoogle Scholar
  4. Cheng X, Xu J, Xia S, Gu J, Yang Y, Fu J, Qian X, Zhang S, Wu J, Liu K (2009) Development and genetic mapping of microsatellite markers from genome survey sequences in Brassica napus. Theor Appl Genet 118:1121–1131PubMedCrossRefGoogle Scholar
  5. Cheung F, Trick M, Drou N, Lim YP, Park J-Y, Kwon SJ, Kim JA, Scott R, Pires JC, Paterson AH, Town C, Bancroft I (2009) Comparative analysis between homoeologous genome segments of Brassica napus and its progenitor species reveals extensive sequence-level divergence. Plant Cell 21:1912–1928PubMedCrossRefGoogle Scholar
  6. Childs KL, Hamilton JP, Zhu W, Ly E, Cheung F, Wu H, Rabinowicz PD, Town CD, Buell CR, Chan AP (2007) The TIGR plant transcript assemblies database. Nucleic Acids Res 35:D846–851PubMedCrossRefGoogle Scholar
  7. Choi SR, Teakle GR, Plaha P, Kim JH, Allender CJ, Beynon E, Piao ZY, Soengas P, Han TH, King GJ, Barker GC, Hand P, Lydiate DJ, Batley J, Edwards D, Koo DH, Bang JW, Park BS, Lim YP (2007) The reference genetic linkage map for the multinational Brassica rapa genome sequencing project. Theor Appl Genet 115:777–792PubMedCrossRefGoogle Scholar
  8. Fujimori S, Washio T, Higo K, Ohtomo Y, Murakami K, Matsubara K, Kawai J, Carninci P, Hayashizaki Y, Kikuchi S, Tomita M (2003) A novel feature of microsatellites in plants: a distribution gradient along the direction of transcription. FEBS Lett 554:17–22PubMedCrossRefGoogle Scholar
  9. Gao L, Tang J, Li H, Jia J (2003) Analysis of microsatellites in major crops assessed by computational and experimental approaches. Mol Breeding 12:245–261 Google Scholar
  10. Ge Y, Ramchiary N, Wang T, Liang C, Wang N, Wang Z, Choi S, Lim Y, Piao Z (2011) Development and linkage mapping of unigene-derived microsatellite markers in Brassica rapa L. Breed Sci 61:160–167CrossRefGoogle Scholar
  11. Grover A, Aishwarya V, Sharma PC (2007) Biased distribution of microsatellite motifs in the rice genome. Mol Genet Genomics 277:469–480PubMedCrossRefGoogle Scholar
  12. Hong CP, Plaha P, Koo DH, Yang TJ, Choi SR, Lee YK, Uhm T, Bang JW, Edwards D, Bancroft I, Park BS, Lee J, Lim YP (2006) A Survey of the Brassica rapa genome by BAC-end sequence analysis and comparison with Arabidopsis thaliana. Mol Cells 22:300–307PubMedGoogle Scholar
  13. Iniguez-Luy FL, Voort AV, Osborn TC (2008) Development of a set of public SSR markers derived from genomic sequence of a rapid cycling Brassica oleracea L. genotype. Theor Appl Genet 117:977–985PubMedCrossRefGoogle Scholar
  14. Kim H, Choi SR, Bae J, Hong CP, Lee SY, Hossain MJ, Van Nguyen D, Jin M, Park BS, Bang JW, Bancroft I, Lim YP (2009) Sequenced BAC anchored reference genetic map that reconciles the ten individual chromosomes of Brassica rapa. BMC Genomics 10:432PubMedCrossRefGoogle Scholar
  15. Kosambi D (1944) The estimation of map distances from recombination values. Ann Eugen 12:172–175CrossRefGoogle Scholar
  16. Kumpatla SP, Mukhopadhyay S (2005) Mining and survey of simple sequence repeats in expressed sequence tags of dicotyledonous species. Genome 48:985–998PubMedCrossRefGoogle Scholar
  17. Lan TH, DelMonte TA, Reischmann KP, Hyman J, Kowalski SP, McFerson J, Kresovich S, Paterson AH (2000) An EST-enriched comparative map of Brassica oleracea and Arabidopsis thaliana. Genome Res 10:776–788PubMedCrossRefGoogle Scholar
  18. Lawson M, Zhang L (2006) Distinct patterns of SSR distribution in the Arabidopsis thaliana and rice genomes. Genome Biol 7:1–11CrossRefGoogle Scholar
  19. Li H, Chen X, Yang Y, Xu J, Gu J, Fu J, Qian X, Zhang S, Wu J, Liu K (2010) Development and genetic mapping of microsatellite markers from whole genome shotgun sequences in Brassica oleracea. Mol Breed doi: 10.1007/s11032-010-9509-y
  20. Ling AE, Kaur J, Burgess B, Hand M, Hopkins CJ, Li XI, Love CG, Vardy M, Walkiewicz M, Spangenberg G, Edwards D, Batley J (2007) Characterization of simple sequence repeat markers derived in silico from Brassica rapa bacterial artificial chromosome sequences and their application in Brassica napus. Mol Ecol Notes 7:273–277CrossRefGoogle Scholar
  21. Liu C, Wang J, Huang T, Wang F, Yuan F, Cheng X, Zhang Y, Shi S, Wu J, Liu K (2010) A missense mutation in the VHYNP motif of a DELLA protein causes a semi-dwarf mutant phenotype in Brassica napus. Theor Appl Genet 121:249–258PubMedCrossRefGoogle Scholar
  22. Lombard V, Delourme R (2001) A consensus linkage map for rapeseed (Brassica napus L.): construction and integration of three individual maps from DH populations. Theor Appl Genet 103:491–507CrossRefGoogle Scholar
  23. Lowe AJ, Moule C, Trick M, Edwards KJ (2004) Efficient large-scale development of microsatellites for marker and mapping applications in Brassica crop species. Theor Appl Genet 108:1103–1112PubMedCrossRefGoogle Scholar
  24. Morgante M, Olivieri AM (1993) PCR-amplified microsatellites as markers in plant genetics. Plant J 3:175–182PubMedCrossRefGoogle Scholar
  25. Morgante M, Hanafey M, Powell W (2002) Microsatellites are preferentially associated with nonrepetitive DNA in plant genomes. Nat Genet 30:194–200PubMedCrossRefGoogle Scholar
  26. Mun JH, Kwon SJ, Yang TJ, Seol YJ, Jin M, Kim JA, Lim MH, Kim JS, Baek S, Choi BS, Yu HJ, Kim DS, Kim N, Lim KB, Lee SI, Hahn JH, Lim YP, Bancroft I, Park BS (2009) Genome-wide comparative analysis of the Brassica rapa gene space reveals genome shrinkage and differential loss of duplicated genes after whole genome triplication. Genome Biol 10:R111PubMedCrossRefGoogle Scholar
  27. Parida SK, Anand Raj Kumar K, Dalal V, Singh NK, Mohapatra T (2006) Unigene derived microsatellite markers for the cereal genomes. Theor Appl Genet 112:808–817PubMedCrossRefGoogle Scholar
  28. Parida SK, Yadava DK, Mohapatra T (2010) Microsatellites in Brassica unigenes: relative abundance, marker design, and use in comparative physical mapping and genome analysis. Genome 53:55–67PubMedCrossRefGoogle Scholar
  29. Parkin IA, Sharpe AG, Keith DJ, Lydiate DJ (1995) Identification of the A and C genomes of amphidiploid Brassica napus (oilseed rape). Genome 38:1122–1131PubMedCrossRefGoogle Scholar
  30. Parkin IA, Gulden SM, Sharpe AG, Lukens L, Trick M, Osborn TC, Lydiate DJ (2005) Segmental structure of the Brassica napus genome based on comparative analysis with Arabidopsis thaliana. Genetics 171:765–781PubMedCrossRefGoogle Scholar
  31. Peng J, Richards DE, Hartley NM, Murphy GP, Devos KM, Flintham JE, Beales J, Fish LJ, Worland AJ, Pelica F, Sudhakar D, Christou P, Snape JW, Gale MD, Harberd NP (1999) ‘Green revolution’ genes encode mutant gibberellin response modulators. Nature 400:256–261PubMedCrossRefGoogle Scholar
  32. Piquemal J, Cinquin E, Couton F, Rondeau C, Seignoret E, Doucet I, Perret D, Villeger MJ, Vincourt P, Blanchard P (2005) Construction of an oilseed rape (Brassica napus L.) genetic map with SSR markers. Theor Appl Genet 111:1514–1523PubMedCrossRefGoogle Scholar
  33. Plieske J, Struss D (2001) Microsatellite markers for genome analysis in Brassica. I. Development in Brassica napus and abundance in Brassicaceae species. Theor Appl Genet 102:689–694CrossRefGoogle Scholar
  34. Powell W, Morgante M, Andre C, Hanafey M, Vogel J, Tingey S, Rafalski A (1996) The comparison of RFLP, RAPD, AFLP and SSR (microsatellite) markers for germplasm analysis. Mol Breed 2:225–238CrossRefGoogle Scholar
  35. Qiu D, Morgan C, Shi J, Long Y, Liu J, Li R, Zhuang X, Wang Y, Tan X, Dietrich E, Weihmann T, Everett C, Vanstraelen S, Beckett P, Fraser F, Trick M, Barnes S, Wilmer J, Schmidt R, Li J, Li D, Meng J, Bancroft I (2006) A comparative linkage map of oilseed rape and its use for QTL analysis of seed oil and erucic acid content. Theor Appl Genet 114:67–80PubMedCrossRefGoogle Scholar
  36. Rana D, van den Boogaart T, O’Neill CM, Hynes L, Bent E, Macpherson L, Park JY, Lim YP, Bancroft I (2004) Conservation of the microstructure of genome segments in Brassica napus and its diploid relatives. Plant J 40:725–733PubMedCrossRefGoogle Scholar
  37. Robinson AJ, Love CG, Batley J, Barker G, Edwards D (2004) Simple sequence repeat marker loci discovery using SSR primer. Bioinformatics 20:1475–1476PubMedCrossRefGoogle Scholar
  38. Rozen S, Skaletsky H (2000) Primer3 on the WWW for general users and for biologist programmers. Methods Mol Biol 132:365–386PubMedGoogle Scholar
  39. Schranz ME, Lysak MA, Mitchell-Olds T (2006) The ABC’s of comparative genomics in the Brassicaceae: building blocks of crucifer genomes. Trends Plant Sci 11:535–542PubMedCrossRefGoogle Scholar
  40. Scott KD, Eggler P, Seaton G, Rossetto M, Ablett EM, Lee LS, Henry RJ (2000) Analysis of SSRs derived from grape ESTs. Theor Appl Genet 100:723–726CrossRefGoogle Scholar
  41. Suwabe K, Iketani H, Nunome T, Kage T, Hirai M (2002) Isolation and characterization of microsatellites in Brassica rapa L. Theor Appl Genet 104:1092–1098PubMedCrossRefGoogle Scholar
  42. Town CD, Cheung F, Maiti R, Crabtree J, Haas BJ, Wortman JR, Hine EE, Althoff R, Arbogast TS, Tallon LJ, Vigouroux M, Trick M, Bancroft I (2006) Comparative genomics of Brassica oleracea and Arabidopsis thaliana reveal gene loss, fragmentation, and dispersal after polyploidy. Plant Cell 18:1348–1359PubMedCrossRefGoogle Scholar
  43. UN (1935) Genome analysis in Brassica with special reference to the experimental formation of B. napus and peculiar mode of fertilization. Jpn J Bot 7:389–452Google Scholar
  44. Van OJ, Voorrips R (2001) JoinMap 3.0, Software for the calculation of genetic linkage maps. Plant Research International, WageningenGoogle Scholar
  45. Varshney RK, Zhang H, Potokina E, Stein N, Langridge P, Graner A (2004) A simple hybridization-based strategy for the generation of non-redundant EST collections–a case study in barley (Hordeum vulgare L.). Plant Sci 167:629–634CrossRefGoogle Scholar
  46. Yang T-J, Kim JS, Kwon S-J, Lim K-B, Choi B-S, Kim J-A, Jin M, Park JY, Lim M-H, Kim H-I, Lim YP, Kang JJ, Hong J-H, Kim C-B, Bhak J, Bancroft I, Park B-S (2006) Sequence-Level analysis of the diploidization process in the triplicated FLOWERING LOCUS C region of Brassica rapa. Plant Cell 18:1339–1347PubMedCrossRefGoogle Scholar
  47. Yi G, Lee JM, Lee S, Choi D, Kim BD (2006) Exploitation of pepper EST-SSRs and an SSR-based linkage map. Theor Appl Genet 114:113–130PubMedCrossRefGoogle Scholar
  48. Zhao J, Becker HC, Zhang D, Zhang Y, Ecke W (2006) Conditional QTL mapping of oil content in rapeseed with respect to protein content and traits related to plant development and grain yield. Theor Appl Genet 113:33–38PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  • Fang Wang
    • 1
  • Xiaofeng Wang
    • 1
  • Xun Chen
    • 1
  • Yingjie Xiao
    • 1
  • Haitao Li
    • 1
  • Shunchang Zhang
    • 1
  • Jinsong Xu
    • 1
  • Jie Fu
    • 1
  • Lei Huang
    • 1
  • Chao Liu
    • 1
  • Jiangsheng Wu
    • 1
  • Kede Liu
    • 1
  1. 1.National Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research (Wuhan)Huazhong Agricultural UniversityWuhanChina

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