Comparative Analysis of SSR Markers Developed in Exon, Intron, and Intergenic Regions and Distributed in Regions Controlling Fruit Quality Traits in Prunus Species: Genetic Diversity and Association Studies

  • Beatriz García-Gómez
  • Mitra Razi
  • Juan A. Salazar
  • Angela S. Prudencio
  • David Ruiz
  • Luca Dondini
  • Pedro Martínez-Gómez
Original Paper

Abstract

Simple sequence repeats (SSRs) are genome domains located in both coding and non-coding regions in eukaryotic genomes. Although SSRs are often characterized by low polymorphism, their DNA-flanking sequences could be a useful source of DNA markers, which could help in genetic studies and breeding because they are associated with genes that control traits of interest. In this study, 56 genotypes from different Prunus species were used, including peach, apricot, plum, and almond (already phenotyped for several agronomical traits, including self-compatibility, flowering and ripening time, fruit type, skin and flesh color, and shell hardness). These Prunus genotypes were molecularly characterized using 28 SSR markers developed in exons, introns, and intergenic regions. All these genes were located in specific regions where quantitative trait loci (QTLs) for certain fruit quality traits were also located, including flowering and ripening times and fruit flesh and skin color. A sum of 309 SSR alleles were identified in the whole panel of analyzed cultivars, with expected heterozygosity values of 0.61 (upstream SSRs), 0.17 (exonic SSRs), 0.65 (intronic SSRs), and 0.58 (downstream SSRs). These values prove the low level of polymorphism of the exonic (gene-coding regions) markers. Cluster and structural analysis based on SSR data clearly differentiated the genotypes according to either specie (for the four species) and pedigree (apricot) or geographic origin (Japanese plum). In addition, some SSR markers mainly developed in intergenic regions could be associated with genes that control traits of interest in breeding and could therefore help in marker-assisted breeding. These findings highlight the importance of using molecular markers able to discriminate between the functional roles of the gene allelic variants.

Keywords

SSR mining Genome structure Prunus Agronomical traits Breeding 

Notes

Acknowledgements

The authors offer grateful thanks to the University of Zajan and the Chilean government (FONDECYT Postdoctoral fellowship No. 3160080) for financial assistance in the stay of Mitra Razi and Juan A. Salazar in Murcia. This study was also supported by the “Apricot breeding” project of the Spanish Ministry of Economy and Competiveness (AGL2013-41452-R) and the project “Breeding stone fruit species assisted by molecular tools” of the Seneca Foundation of the Region of Murcia (19879/GERM/15).

Supplementary material

11105_2017_1058_MOESM1_ESM.xls (56 kb)
Table S1 Details of the 28 SSRs assayed, including nature, repeat motif, primer sequences, product size, and annealing temperature. In addition, the position and associated genes with respect to the reference peach genome have been added. (XLS 55 kb)
11105_2017_1058_MOESM2_ESM.xls (78 kb)
Table S2 Allele sizes of the 28 SSRs obtained in the analysis of the 56 peach, almond, Japanese plum and apricot genotypes. NA = no amplification. (XLS 77 kb)
11105_2017_1058_MOESM3_ESM.xls (68 kb)
Table S3 Pairwise genetic distances and estimation of evolutionary divergence between the 56 peach, almond, plum and apricot genotypes studied, obtained with the application of the 28 SSR markers assayed using the MCL method. (XLS 68 kb)

References

  1. Abbott AG, Rajapakse S, Sosinski B, Lu ZX, Sossey-Alaoui K, Gannavarapu M, Reighard G, Ballard RE, Baird WV, Callahan A (1998) Construction of saturated linkage maps of peach crosses segregating for characters controlling fruit quality, tree architecture and pest resistance. Acta Hortic 465:41–49CrossRefGoogle Scholar
  2. Bianchi V, Rubio M, Trainotti L, Verde I, Bonghi C, Martínez-Gómez P (2015) Prunus transcription factors: breeding perspectives. Front Plant Sci 6:443.  https://doi.org/10.3389/fpls.2015.00443 CrossRefPubMedPubMedCentralGoogle Scholar
  3. Bielenberg DG, Wang Y, Li ZG, Zhebentyayeva T, Fan SH, Reighard GL, Scorza R, Abbott AG (2008) Sequencing and annotation of the evergrowing locus in peach [Prunus persica (L.) Batsch] reveals a cluster of six MADS-BOX transcription factors as candidate genes for regulation of terminal bud formation. Tree Genet Genomes 4(3):495–507.  https://doi.org/10.1007/s11295-007-0126-9 CrossRefGoogle Scholar
  4. Bradbury PJ, Zhang Z, Kroon DE, Casstevens TM, Ramdoss Y, Buckler ES (2007) TASSEL: software for association mapping of complex traits in diverse samples. Bioinformatics 23(19):2633–2665.  https://doi.org/10.1093/bioinformatics/btm308 CrossRefPubMedGoogle Scholar
  5. Campoy JA, Martínez-Gómez P, Ruiz D, Rees J, Celton JM (2010) Developing microsatellite multiplex and megaplex PCR systems for high throughput characterization of breeding progenies and linkage maps spanning the apricot genome. Plant Mol Biol Report 28(4):560–568.  https://doi.org/10.1007/s11105-010-0186-0 CrossRefGoogle Scholar
  6. Doyle JJ, Doyle JL (1987) A rapid DNA isolation procedure for small quantities of fresh leaf tissue. Phytochem Bull 19:11–15Google Scholar
  7. Eduardo I, Pacheco I, Chietera G, Bassi D, Pozzi C, Vecchietti A, Rossini L (2011) QTL analysis of fruit quality traits in two peach intraspecific populations and importance of maturity date pleiotropic effect. Tree Genet Genomes 7(2):323–335.  https://doi.org/10.1007/s11295-010-0334-6 CrossRefGoogle Scholar
  8. Flachowsky H, Peil A, Sopanen T, Elo A, Hanke V (2007) Overexpression of BpMADS4 from silver birch (Betula pendula Roth.) induces early-flowering in apple (Malus domestica Borkh.) Plant Breed 126(2):137–145.  https://doi.org/10.1111/j.1439-0523.2007.01344.x CrossRefGoogle Scholar
  9. Fresnedo-Ramírez J, Bink MC, van de Weg E, Famula TR, Crisosto CH, Frett TJ, Gradziel TM (2015) QTL mapping of pomological traits in peach and related species breeding germplasm. Mol Breed 35:1–19CrossRefGoogle Scholar
  10. Gupta PK, Balyan HS, Sharma PC, Ramesh B (1996) Microsatellites in plants: a new class of molecular markers. Curr Sci 70:45–54Google Scholar
  11. Gupta S, Kumari K, Muthamilarasan M, Parida SK, Prasad M (2014) Population structure 586 and association mapping of yield contributing agronomic traits in foxtail millet. Plant Cell Rep 33(6):881–893.  https://doi.org/10.1007/s00299-014-1564-0 CrossRefPubMedGoogle Scholar
  12. Hodel RG, Gitzendanner MA, Germain-Aubrey CC, Liu X, Crowl AA, Sun M, Soltis DE (2016) A new resource for the development of SSR markers: millions of loci from a thousand plant transcriptomes. Appl Plant Sci 4(6):1600024.  https://doi.org/10.3732/apps.1600024 CrossRefGoogle Scholar
  13. Holland JB, Helland SJ, Sharopova N, Rhyne DC (2001) Polymorphism of PCR-based markers targeting exons, introns, promoter regions, and SSRs in maize and introns and repeat sequences in oat. Genome 44(6):1065–1076.  https://doi.org/10.1139/g01-110 CrossRefPubMedGoogle Scholar
  14. Huang J, Li W, Jian Z, Yue B, Yan YF (2016) Genome-wide distribution and organization of microsatellites in six species of birds. Biochem Syst Ecol 67:95–102.  https://doi.org/10.1016/j.bse.2016.05.023 CrossRefGoogle Scholar
  15. Illa I, Eduardo I, Audergon JM, Barale F, Dirlewanger E, Li X, Moing A, Lambert P, Le Dantec L, Gao Z, Poëssel JL, Pozzi C, Rossini L, Vecchietti A, Arús P, Howad W (2011) Saturating the Prunus (stone fruits) genome with candidate genes for fruit quality. Mol Breed 28(4):667–682.  https://doi.org/10.1007/s11032-010-9518-x CrossRefGoogle Scholar
  16. Infante R, Martínez-Gómez P, Predieri S (2008) Quality oriented fruit breeding: peach [Prunus persica (L.) Batsch]. J Food Agric Environ 6:342–356Google Scholar
  17. Infante R, Martínez-Gómez P, Predieri S (2011) Breeding for fruit quality in Prunus. In: Jenks MA, Bebeli PJ (eds) Breeding for fruit quality. Editorial Wiley & Blackwel, New York (EEUU), pp 201–229CrossRefGoogle Scholar
  18. Jiménez S, Lawton-Rauh AL, Reighard GL, Abbott AG, Bielenberg DG (2009) Phylogenetic analysis and molecular evolution of the dormancy associated MADS-BOX genes from peach. BMC Plant Biol 9(1):81.  https://doi.org/10.1186/1471-2229-9-81 CrossRefPubMedPubMedCentralGoogle Scholar
  19. Jiménez S, Reighard GL, Bielenberg DG (2010) Gene expression of DAM5 and DAM6 is suppressed by chilling temperatures and inversely correlated with bud break rate. Plant Mol Biol 73(1-2):157–167.  https://doi.org/10.1007/s11103-010-9608-5 CrossRefPubMedGoogle Scholar
  20. Kantety RV, La Rota M, Matthews DE, Sorrells ME (2002) Data mining for simple sequence repeats in expressed sequence tags from barley, maize, rice, sorghum and wheat. Plant Mol Biol 48(5/6):501–510.  https://doi.org/10.1023/A:1014875206165 CrossRefPubMedGoogle Scholar
  21. Kumar S, Stecher G, Tamura K (2016) MEGA7: molecular evolutionary genetics analysis version 7.0 bigger datasets. Mol Biol Evol 33(7):1870–1874.  https://doi.org/10.1093/molbev/msw054 CrossRefPubMedGoogle Scholar
  22. Lal S, Singh AK, Sing SK, Srivastav M, Sing BP, Sharma N, Sing NM (2017) Association analysis for pomological traits in mango (Mangifera indica L.) by genic-SSR markers. Trees 31:1391–1409CrossRefGoogle Scholar
  23. Martínez-Gómez P, Arulsekar S, Potter D, Gradziel TM (2003) An extended interspecific gene pool available to peach and almond breeding as characterized using simple sequence repeat (SSR) markers. Euphytica 131(3):313–322.  https://doi.org/10.1023/A:1024028518263 CrossRefGoogle Scholar
  24. Martínez-Gómez P, Crisosto CH, Bonghi C, Rubio M (2011) New approaches to Prunus transcriptome analysis. Genetica 139(6):755–769.  https://doi.org/10.1007/s10709-011-9580-2 CrossRefPubMedGoogle Scholar
  25. Martínez-Gómez P, Sánchez-Pérez R, Rubio M (2012) Clarifying omics concepts, challenges, and opportunities for Prunus breeding in the postgenomic era. OMICS 16(5):268–283.  https://doi.org/10.1089/omi.2011.0133 CrossRefPubMedGoogle Scholar
  26. Milne I, Stephen G, Bayer M, Cock PJ, Pritchard L et al (2013) Using tablet for visual exploration of second-generation sequencing data. Brief Bioinform 14(2):193–202.  https://doi.org/10.1093/bib/bbs012 CrossRefPubMedGoogle Scholar
  27. Morgante M, Hanafey M, Powell W (2002) Microsatellites are preferentially associated with nonrepetitive DNA in plant genomes. Nature Genet 30:194–200Google Scholar
  28. Olukolu B, Trainin T, Fan S, Kole C, Bielenberg D, Reighard G, Abbott A, Holland D (2009) Genetic linkage mapping for molecular dissection of chilling requirement and budbreak in apricot (Prunus armeniaca L.) Genome 52(10):819–828.  https://doi.org/10.1139/G09-050 CrossRefPubMedGoogle Scholar
  29. Potter D (2012) Basic information on the stone fruit crops. In: Kole C, Abbott AG (eds) Genetics, genomics and breeding of stone fruits. CRC Press, New York, pp 1–21.  https://doi.org/10.1201/b13104-2 Google Scholar
  30. Powell W, Machray GC, Provan J (1996) Polymorphism revealed by simple sequence repeats. Trends Plant Sci 1(7):215–222.  https://doi.org/10.1016/S1360-1385(96)86898-0 CrossRefGoogle Scholar
  31. Quilot B, BH W, Kervella J, Génard M, Foulongne M, Moreau K (2004) QTL analysis of quality traits in an advanced backcross between Prunus persica cultivars and the wild relative species P. davidiana. Theor Appl Genet 109(4):884–897.  https://doi.org/10.1007/s00122-004-1703-z CrossRefPubMedGoogle Scholar
  32. Romeu JF, Monforte AJ, Sánchez G, Granell A, García-Brunton J, Badenes ML, Ríos G (2014) Quantitative trait loci affecting reproductive phenology in peach. BMC Plant Biol 14(1):52.  https://doi.org/10.1186/1471-2229-14-52 CrossRefPubMedPubMedCentralGoogle Scholar
  33. Rubio M, Ruiz D, Egea J, Martínez-Gómez P, Dicenta F (2014) Opportunities of marker assisted selection for plum pox virus resistance in apricot breeding. Tree Genet Genomes 10(3):513–525.  https://doi.org/10.1007/s11295-014-0700-x CrossRefGoogle Scholar
  34. Ruiz D, Lambert P, Audergon JM, Gouble B, Bureau S, Reich M, Dondini L, Tartarini S, Adami M, Bassi D, Testolin R (2010) Identification of QTLs for fruit quality traits in apricot. Acta Hortic 862:587–592CrossRefGoogle Scholar
  35. Salazar JA, Ruiz D, Egea J, Martínez-Gómez P (2013) Transmission of fruit quality traits in apricot (Prunus armeniaca L.) and analysis of linked quantitative trait loci (QTLs) using simple sequence repeat (SSR) markers. Plant Mol Biol Report 31(6):1506–1517.  https://doi.org/10.1007/s11105-013-0625-9 CrossRefGoogle Scholar
  36. Salazar JA, Ruiz D, Campoy JA, Sánchez-Pérez R, Crisosto CH, Martínez-García PJ, Blenda A, Jung S, Main D, Martínez-Gómez P, Rubio M (2014) Quantitative trait loci (QTL) and Mendelian trait loci (MTL) analysis in Prunus a breeding perspective and beyond. Plant Mol Biol Report 32(1):1–18.  https://doi.org/10.1007/s11105-013-0643-7 CrossRefGoogle Scholar
  37. Salazar JA, Rubio M, Ruiz D, Tartarini S, Martínez-Gómez P, Dondini L (2015) SNP development for genetic diversity analysis in apricot. Tree Genet Genomes 11(1):15.  https://doi.org/10.1007/s11295-015-0845-2 CrossRefGoogle Scholar
  38. Salazar JA, Ruiz D, Campoy JA, Tartarini S, Dondini L, Martínez-Gómez P (2016) Inheritance of reproductive phenology traits and related QTL identification in apricot. Tree Genet Genomes 12(4):71.  https://doi.org/10.1007/s11295-016-1027-6 CrossRefGoogle Scholar
  39. Salazar JA, Pacheco I, Shinya P, Zapata P, Silva C, Ruiz D, Martínez-Gómez P, Infante R (2017) Genotyping by sequencing for SNP-based linkage analysis and identification of QTLs linked to fruit quality traits in Japanese plum (Prunus salicina Lindl.) Front Plant Sci 8:476.  https://doi.org/10.3389/fpls.2017.00476 CrossRefPubMedPubMedCentralGoogle Scholar
  40. Sánchez-Pérez R, Martínez-Gómez P, Dicenta F, Egea J, Ruiz D (2006) Level and transmission of genetic heterozygosity in apricot, explored by simple sequence repeat markers. Genet Resour Crop Evol 53(4):763–770.  https://doi.org/10.1007/s10722-004-4636-0 CrossRefGoogle Scholar
  41. Sánchez-Pérez R, Howad D, Dicenta F, Arús P, Martínez-Gómez P (2007) Mapping major genes and quantitative trait loci controlling agronomic traits in almond. Plant Breed 126(3):310–318.  https://doi.org/10.1111/j.1439-0523.2007.01329.x CrossRefGoogle Scholar
  42. Saxena RK, Edwards D, Varshney RK (2014) Structural variations in plant genomes. Brief Funct Genomics 13(4):296–307.  https://doi.org/10.1093/bfgp/elu016 CrossRefPubMedPubMedCentralGoogle Scholar
  43. Shulaev V, Korban SS, Sosinski B, Abbott AG, Aldwinckle HS, Folta KM, Iezzoni A, Main D, Arús P, Dandekar AM, Lewers K, Gardiner SE, Potter D, Veilleux E (2008) Multiple models for Rosaceae genomics. Plant Physiol 147(3):985–1003.  https://doi.org/10.1104/pp.107.115618 CrossRefPubMedPubMedCentralGoogle Scholar
  44. Sooriyapathirana SS, Khan A, Sebolt AM, Wang D, Bushakra JM, Wang KL, Allan AC, Gardiner SE, Chagné H, Iezzoni AF (2010) QTL analysis and candidate gene mapping for skin and flesh color in sweet cherry fruit (Prunus avium L.) Tree Genet Genomes 6(6):821–832.  https://doi.org/10.1007/s11295-010-0294-x CrossRefGoogle Scholar
  45. Sorkheh K, Prudencio AS, Ghebinejad A, Dehkordi MK, Erogul D, Rubio M, Martínez-Gómez P (2016) In silico search, characterization and validation of new EST-SSR markers in the genus Prunus. BMC Res Notes 9(1):336.  https://doi.org/10.1186/s13104-016-2143-y CrossRefPubMedPubMedCentralGoogle Scholar
  46. Tautz D, Renz M (1984) Simple sequences are ubiquitous repetitive components of eukayotic genomes. Nucleic Acid Res 12(10):4127–4138.  https://doi.org/10.1093/nar/12.10.4127 CrossRefPubMedPubMedCentralGoogle Scholar
  47. Varshney RK, Graner A, Sorrells ME (2005) Genic microsatellite markers in plants: features and applications. Trends Biotechnol 23(1):48–55.  https://doi.org/10.1016/j.tibtech.2004.11.005
  48. Verde I, Jenkins J, Dondini L, Micali S, Pagliarani G, Vendramin E, Schmutz J (2017) The peach v2.0 release: high-resolution linkage mapping and deep resequencing improve chromosome-scale assembly and contiguity. BMC Genomics 18(1):225.  https://doi.org/10.1186/s12864-017-3606-9 CrossRefPubMedPubMedCentralGoogle Scholar
  49. Yamamoto T, Shimada T, Imai T, Yaegaki H, Haji T, Matsuta N, Yamaguchi M, Hayashi T (2001) Characterization of morphological traits based on a genetic linkage map in peach. Breed Sci 51(4):271–278.  https://doi.org/10.1270/jsbbs.51.271 CrossRefGoogle Scholar
  50. Yu J, Pressoir G, Briggs WH, Bi IV, Yamasaki M, Doebley JF, McMullen MD, Gaut BS, Nielsen DM, Holland JB, Kresovich S, Buckler ES (2006) A unified mixed model method for association mapping that accounts for multiple levels of relatedness. Nat Genet 38(2):203–208.  https://doi.org/10.1038/ng1702 CrossRefPubMedGoogle Scholar

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Authors and Affiliations

  1. 1.Department of Plant BreedingCEBAS-CSICMurciaSpain
  2. 2.Department of Horticulture, Faculty of AgricultureUniversity of ZajanZajanIran
  3. 3.Departamento de Producción AgrícolaUniversidad de ChileSantiagoChile
  4. 4.Dipartimento di Scienze AgrarieUniversità degli Studi di BolognaBolognaItaly

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