, 215:168 | Cite as

Identification of SNP markers linked to the weeping trait in Prunus mume

  • Suzhen Li
  • Tangchun Zheng
  • Xiaokang Zhuo
  • Lulu Li
  • Like Qiu
  • Jia Wang
  • Tangren Cheng
  • Qixiang ZhangEmail author


Prunus mume is a traditional ornamental tree with a graceful architecture that blossoms early in spring and presents beautiful flowers with a pleasant fragrance. Recently, the weeping trait has received increasing attention for its ornamental appeal and potential application to agriculture. In this study, we identified the SNPs tightly linked to the weeping trait using a linkage population based on specific-locus amplified fragment sequencing (SLAF-Seq). Six SLAF-derived SNP markers (Marker446598, Marker353041, Marker315769, Marker334902, Marker301243 and Marker311414) were validated as being tightly associated with the weeping phenotype using Sanger sequencing. The Sanger sequencing results of Marker353041 indicated that 100% of the weeping individuals and 73.3% of the upright individuals were homozygous (AA) and heterozygous (AT), respectively. Two genotypes were identified using Marker301243 with allele-specific polymerase chain reaction. All upright individuals were heterozygous (TA) and only 16.7% of the weeping individuals heterozygous (TA) in the F1 segregated population. Two marker combinations led to 89.13% predictability in the cultivars. The results suggest the application of this approach for marker-assisted breeding of P. mume and lay the foundation for the molecular breeding process of the weeping trait in woody ornamental plants.


Prunus mume Weeping trait SNP marker Genotyping Ornamental plant 



The research was supported by the program for Science and Technology of Beijing (No. Z181100002418006) and Special Fund for Beijing Common Construction Project.

Author contributions

SL and TZ conceived and drafted the manuscript. TZ conceived and designed the experiments. SL and XZ performed the experiments. LL and LQ analysed the data. JW and TC contributed reagents/materials/analysis tools. QZ contributed to the conception of the study and finalized the manuscript. All authors read and approved the final manuscript.

Compliance with ethical standards

Conflict of interest

The authors declare no conflict of interest and this research has been conducted in the absence of any financial or commercial relationships.

Supplementary material

10681_2019_2488_MOESM1_ESM.jpg (802 kb)
Supplementary Figure 1: Heatmap showing the correlation between the markers. (JPG 801 kb)
10681_2019_2488_MOESM2_ESM.jpg (1.3 mb)
Supplementary Figure 2: AS-PCR amplification results of Marker301243 and Marker311414 in the F1 population. 1–6: upright type of F1 population; 7–12: weeping type of F1 population; and M: Marker DL2000. (JPG 1294 kb)
10681_2019_2488_MOESM3_ESM.jpg (433 kb)
Supplementary Figure 3: AS-PCR amplified results of Marker301243 and Marker311414 in cultivars. (JPG 433 kb)
10681_2019_2488_MOESM4_ESM.jpg (375 kb)
Supplementary Figure 4: Accuracy of Marker 301243 and Marker 311414 in the F1 population and cultivars. a Accuracy of Marker 301243 and Marker 311414 for molecular-assisted selection in the F1 population; b accuracy of Marker 301243 and Marker 311414 for molecular-assisted selection in cultivars; c accuracy of marker combination (Marker 301243 and Marker 311414) for molecular-assisted selection in the F1 population and cultivars. (JPG 375 kb)
10681_2019_2488_MOESM5_ESM.docx (20 kb)
Supplementary File 1: Seventeen SLAF marker sequences. (DOCX 19 kb)
10681_2019_2488_MOESM6_ESM.docx (15 kb)
Supplementary File 2: Primers used for Sanger sequencing and AS-PCR. (DOCX 15 kb)
10681_2019_2488_MOESM7_ESM.xlsx (10 kb)
Supplementary Table 1: Information of 13 markers identified by Sanger sequencing. (XLSX 9 kb)


  1. Ayalew H, Tsang PW, Chu C, Wang J, Liu S, Chen C, Ma XF (2019) Comparison of TaqMan, KASP and rhAmp SNP genotyping platforms in hexaploid wheat. PLoS ONE 14:e0217222. CrossRefPubMedPubMedCentralGoogle Scholar
  2. Baird NA, Etter PD, Atwood TS, Currey MC, Shiver AL, Lewis ZA, Selker EU, Cresko WA, Johnson EA (2008) Rapid SNP discovery and genetic mapping using sequenced RAD markers. PLoS ONE 3:e3376. CrossRefPubMedPubMedCentralGoogle Scholar
  3. Bakooie M, Pourjam E, Mahmoudi SB, Safaie N, Naderpour M (2018) Development of an SNP marker for sugar beet resistance/susceptible genotyping to root-knot nematode. J Agric Sci Technol 17:443–454Google Scholar
  4. Bali S, Robinson BR, Sathuvalli V, Bamberg J, Goyer A (2018) Single nucleotide polymorphism (SNP) markers associated with high folate content in wild potato species. PLoS ONE 13:e0193415. CrossRefPubMedPubMedCentralGoogle Scholar
  5. Batley J, Barker G, Sullivan H, Edwards KJ, Edwards D (2003) Mining for single nucleotide polymorphisms and insertions/deletions in maize expressed sequence tag data. Plant Physiol 132:84–91CrossRefGoogle Scholar
  6. Bertioli DJ, Cannon SB, Froenicke L, Huang G, Farmer AD, Cannon EK, Liu X, Gao D, Clevenger J, Dash S et al (2016) The genome sequences of Arachis duranensis and Arachis ipaensis, the diploid ancestors of cultivated peanut. Nat Genet 48:438–446. CrossRefPubMedGoogle Scholar
  7. Chen J (1996) Chinese mei flowers. Hainan Publishing House, Haikou, pp 51–52Google Scholar
  8. Chopra R, Burow G, Farmer A, Mudge J, Simpson CE, Wilkins TA, Baring MR, Puppala N, Chamberlin KD, Burow MD (2015) Next-generation transcriptome sequencing, SNP discovery and validation in four market classes of peanut, Arachis hypogaea L.. Mol Genet Genom 290:1169–1180. CrossRefGoogle Scholar
  9. Chopra R, Burow G, Simpson CE, Chagoya J, Mudge J, Burow MD (2016) Transcriptome sequencing of diverse peanut (Arachis) wild species and the cultivated species reveals a wealth of untapped genetic variability. G3 (Bethesda) 6:3825–3836. Scholar
  10. Christian S (2004) The evolution of molecular markers–just a matter of fashion? Nat Rev Genet 5:63–69CrossRefGoogle Scholar
  11. Clevenger J, Chu Y, Chavarro C, Agarwal G, Bertioli DJ, Leal-Bertioli SCM, Pandey MK, Vaughn J, Abernathy B, Barkley NA et al (2017) Genome-wide SNP genotyping resolves signatures of selection and tetrasomic recombination in peanut. Mol Plant 10:309–322. CrossRefPubMedPubMedCentralGoogle Scholar
  12. Cova V, Lasserre-Zuber P, Piazza S, Cestaro A, Velasco R, Durel CE, Malnoy M (2015) High-resolution genetic and physical map of the Rvi1 (Vg) apple scab resistance locus. Mol Breed 35:16CrossRefGoogle Scholar
  13. Dirlewanger E, Bodo C (1994) Molecular genetic mapping of peach. Euphytica 77:101–103. CrossRefGoogle Scholar
  14. Dougherty L, Singh R, Brown S, Dardick C, Xu K (2018) Exploring DNA variant segregation types in pooled genome sequencing enables effective mapping of weeping trait in Malus. J Exp Bot 69:1499–1516. CrossRefPubMedPubMedCentralGoogle Scholar
  15. Ganal MW, Altmann T, Roder MS (2009) SNP identification in crop plants. Curr Opin Plant Biol 12:211–217. CrossRefPubMedGoogle Scholar
  16. Gaudet M, Fara AG, Beritognolo I, Sabatti M (2009) Allele-specific PCR in SNP genotyping. Methods Mol Biol 578:415–424. CrossRefPubMedGoogle Scholar
  17. Guo Y, Su B, Tang J, Zhou F, Qiu LJ (2018) Gene-based SNP identification and validation in soybean using next-generation transcriptome sequencing. Mol Genet Genom 293:623–633CrossRefGoogle Scholar
  18. Hayashi K, Hashimoto N, Daigen M, Ashikawa I (2004) Development of PCR-based SNP markers for rice blast resistance genes at the Piz locus. Theor Appl Genet 108:1212–1220. CrossRefPubMedGoogle Scholar
  19. Hayashi K, Yoshida H, Ashikawa I (2006) Development of PCR-based allele-specific and InDel marker sets for nine rice blast resistance genes. Theor Appl Genet 113:251–260CrossRefGoogle Scholar
  20. Hollender CA, Pascal T, Tabb A, Hadiarto T, Srinivasan C, Wang W, Liu Z, Scorza R, Dardick C (2018) Loss of a highly conserved sterile alpha motif domain gene (WEEP) results in pendulous branch growth in peach trees. Proc Natl Acad Sci USA 115:E4690–E4699. CrossRefPubMedGoogle Scholar
  21. International HapMap Consortium, Frazer KA, Ballinger DG, Cox DR, Hinds DA, Stuve LL, Gibbs RA, Belmont JW, Boudreau A, Hardenbol P et al. (2007) A second generation human haplotype map of over 3.1 million SNPs. Nature 449:851–861. CrossRefGoogle Scholar
  22. Jain M, Moharana KC, Shankar R, Kumari R, Garg R (2014) Genomewide discovery of DNA polymorphisms in rice cultivars with contrasting drought and salinity stress response and their functional relevance. Plant Biotechnol J 12:253–264. CrossRefPubMedGoogle Scholar
  23. Kim B, Hwang IS, Lee HJ, Oh CS (2017) Combination of newly developed SNP and InDel markers for genotyping the Cf-9 locus conferring disease resistance to leaf mold disease in the tomato. Mol Breed 37:59CrossRefGoogle Scholar
  24. Kim B, Hwang IS, Lee HJ, Lee JM, Seo E, Choi D, Oh CS (2018) Identification of a molecular marker tightly linked to bacterial wilt resistance in tomato by genome-wide SNP analysis. Theor Appl Genet 131:1–14CrossRefGoogle Scholar
  25. Kwok S, Kellogg DE, Mckinney N, Spasic D, Goda L, Levenson C, Sninsky JJ (1990) Effects of primer-template mismatches on the polymerase chain reaction: human immunodeficiency virus type 1 model studies. Nucl Acids Res 18:999–1005. CrossRefPubMedGoogle Scholar
  26. Lee YG, Jeong N, Kim JH, Lee K, Kim KH, Pirani A, Ha BK, Kang ST, Park BS, Moon JK, Kim N, Jeong SC (2015) Development, validation and genetic analysis of a large soybean SNP genotyping array. Plant J 81:625–636. CrossRefPubMedGoogle Scholar
  27. Li B, Tian L, Zhang J, Huang L, Han F, Yan S, Wang L, Zheng H, Sun J (2014) Construction of a high-density genetic map based on large-scale markers developed by specific length amplified fragment sequencing (SLAF-seq) and its application to QTL analysis for isoflavone content in Glycine max. BMC Genom 15:1086CrossRefGoogle Scholar
  28. Michelmore RW, Paran I, Kesseli RV (1991) Identification of markers linked to disease-resistance genes by bulked segregant analysis: a rapid method to detect markers in specific genomic regions by using segregating populations. Proc Natl Acad Sci USA 88:9828CrossRefGoogle Scholar
  29. Moriya S, Okada K, Haji T, Yamamoto T, Abe K (2012) Fine mapping of Co, a gene controlling columnar growth habit located on apple (Malus × domestica Borkh.) linkage group 10. Plant Breed 131:641–647CrossRefGoogle Scholar
  30. Mourad AMI, Sallam A, Belamkar V, Wegulo S, Bowden R, Jin Y, Mahdy E, Bakheit B, El-Wafaa AA, Poland J, Baenziger PS (2018) Genome-wide association study for identification and validation of novel SNP markers for Sr6 stem rust resistance gene in bread wheat. Front Plant Sci 9:380. CrossRefPubMedPubMedCentralGoogle Scholar
  31. Qi Z, Huang L, Zhu R, Xin D, Liu C, Han X, Jiang H, Hong W, Hu G, Zheng H, Chen Q (2014) A high-density genetic map for soybean based on specific length amplified fragment sequencing. PLoS ONE 9:e104871. CrossRefPubMedPubMedCentralGoogle Scholar
  32. Rafalski A (2002) Applications of single nucleotide polymorphisms in crop genetics. Curr Opin Plant Biol 5:94–100CrossRefGoogle Scholar
  33. Schneider K, Kulosa D, Soerensen TR, Möhring S, Heine M, Durstewitz G, Polley A, Weber E, Jamsari Lein J, Hohmann U, Tahiro E, Weisshaar B, Schulz B, Koch G, Jung C, Ganal M (2007) Analysis of DNA polymorphisms in sugar beet (Beta vulgaris L.) and development of an SNP-based map of expressed genes. Theor Appl Genet 115:601–615. CrossRefPubMedGoogle Scholar
  34. Semagn K, Babu R, Hearne S, Olsen M (2014) Single nucleotide polymorphism genotyping using Kompetitive Allele Specific PCR (KASP): overview of the technology and its application in crop improvement. Mol Breed 33:1–14. CrossRefGoogle Scholar
  35. Sun L, Yang W, Zhang Q, Cheng T, Pan H, Xu Z, Zhang J, Chen C (2013a) Genome-wide characterization and linkage mapping of simple sequence repeats in mei (Prunus mume Sieb. et Zucc.). PLoS ONE 8:e59562. CrossRefPubMedPubMedCentralGoogle Scholar
  36. Sun X, Liu D, Zhang X, Li W, Liu H, Hong W, Jiang C, Guan N, Ma C, Zeng H, Xu C, Song J, Huang L, Wang C, Shi J, Wang R, Zheng X, Lu C, Wang X, Zheng H (2013b) SLAF-seq: An efficient method of large-scale de novo SNP discovery and genotyping using high-throughput sequencing. PLoS ONE 8:e58700. CrossRefPubMedPubMedCentralGoogle Scholar
  37. Wei Q, Wang Y, Qin X, Zhang Y, Zhang Z, Wang J, Li J, Lou Q, Chen J (2014) An SNP-based saturated genetic map and QTL analysis of fruit-related traits in cucumber using specific-length amplified fragment (SLAF) sequencing. BMC Genom 15:1158CrossRefGoogle Scholar
  38. Werner DJ, Chaparro JX (2005) Genetic interactions of pillar and weeping peach Genotypes. HortScience 40:18–20CrossRefGoogle Scholar
  39. Xu Z, Zhang Q, Sun L, Du D, Cheng T, Pan H, Yang W, Wang J (2014) Genome-wide identification, characterisation and expression analysis of the MADS-box gene family in Prunus mume. Mol Genet Genom 289:903–920. CrossRefGoogle Scholar
  40. Yates CM, Sternberg MJ (2013) The effects of non-synonymous single nucleotide polymorphisms (nsSNPs) on protein-protein interactions. J Mol Biol 425:3949–3963. CrossRefPubMedGoogle Scholar
  41. Ye Y, Cai M, Ju Y, Jiao Y, Feng L, Pan H, Cheng T, Zhang Q (2016) Identification and validation of SNP markers linked to dwarf traits using SLAF-seq technology in Lagerstroemia. PLoS ONE 11:e0158970. CrossRefPubMedPubMedCentralGoogle Scholar
  42. Zhang Y, Wang L, Xin H, Li D, Ma C, Ding X, Hong W, Zhang X (2013) Construction of a high-density genetic map for sesame based on large scale marker development by specific length amplified fragment (SLAF) sequencing. BMC Plant Biol 13:141–141CrossRefGoogle Scholar
  43. Zhang J, Zhang Q, Cheng T, Yang W, Pan H, Zhong J, Huang L, Liu E (2015) High-density genetic map construction and identification of a locus controlling weeping trait in an ornamental woody plant (Prunus mume Sieb. et Zucc). DNA Res 22:183–191CrossRefGoogle Scholar
  44. Zhang Y, Qin L, Wang H, Chen X, Wang S (2017) Identification of S genotypes in loquat (Eriobotrya japonica Lindl.) based on allele specific PCR. Sci Hortic 225:736–742. CrossRefGoogle Scholar

Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Beijing Key Laboratory of Ornamental Plants Germplasm Innovation and Molecular Breeding, National Engineering Research Center for Floriculture, Beijing Laboratory of Urban and Rural Ecological Environment, Engineering Research Center of Landscape Environment of Ministry of Education, Key Laboratory of Genetics and Breeding in Forest Trees and Ornamental Plants of Ministry of Education, School of Landscape ArchitectureBeijing Forestry UniversityBeijingPeople’s Republic of China
  2. 2.Beijing Advanced Innovation Center for Tree Breeding By Molecular DesignBeijing Forestry UniversityBeijingPeople’s Republic of China

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