In silico analysis of the genomes within the Rosaceae Juss. family to develop ISAP markers

Background. The rose family (Rosaceae Juss.) is an economically important taxon that includes a number of cultivated species. Studying the genetic diversity of crop wild relatives within this family is important to include new genetic material into genetic collections and utilize it in breeding practice. Markers based on retrotransposon polymorphism, including ISAP markers that detect differences in the location of SINE transposons, can be a useful tool for rapid and informative analysis of natural Rosaceae populations. Since SINE elements are highly heterogeneous, ISAP markers developed for one species may be unsuitable for the others.

Materials and methods. Genomes representing five species of the genera Rubus L., Rosa L. and Fragaria L. were analyzed in silico. An original bioinformatics program was developed to align and cluster the SINE sequences. The primers designed for raspberry and rose were tested on limited subsets (28 and 21 accessions, respectively).

Results. From 857 to 3477 SINEs were identified in the haploid genomes of the studied genera; an uneven distribution of elements across chromosomes was observed in all genomes. Bioinformatics methods applied to analyze the obtained SINE sequences made it possible to develop specific primers for each crop. The designed ISAP marker system revealed a high degree of generated polymorphism in the samples (PIC > 0.90). The primers developed for the genus Rosa were also capable of generating PCR products in other crops from the Rosaceae family, including cherry, pear, and strawberry, although the observed polymorphism was significantly lower.

Conclusion. The developed ISAP marker system can generate large amounts of polymorphic fragments. Therefore, it may be used for genotyping and molecular certification of cultivars as well as for studying the genetic diversity of wild populations.

1. Antonius-Klemola K., Kalendar R., Schulman A.H. TRIM retrotransposons occur in apple and are polymorphic between varieties but not sports. Theoretical and Applied Genetics. 2006;112(6):999-1008. DOI: 10.1007/s00122-005-0203-0

2. Aristya G.R., Kasiamdari R.S., Setyoningrum R., Larasati B. Genetic variations of strawberry cultivars of Fragaria × ananassa and Fragaria vesca based on RAPD. Biodiversitas. 2019;20(3):770-775. DOI: 10.13057/biodiv/d200322

3. Badakhshan H., Kamangar M.S., Mozafari A.A. Characterization of strawberry (Fragaria × ananassa Duch.) cultivars using SCoT, ISSR and IRAP markers. Crop Breeding Journal. 2018;8(2):61-72. DOI: 10.22092/CBJ.2018.123510.1028

4. Borodulina O.R., Kramerov D.A. PCR-based approach to SINE isolation: Simple and complex SINEs. Gene. 2005;349:197-205. DOI: 10.1016/j.gene.2004.12.035

5. Brozynska M., Furtado A., Henry R.J. Genomics of crop wild relatives: expanding the gene pool for crop improvement. Plant Biotechnology Journal. 2016;14(4):1070-1085. DOI: 10.1111/pbi.12454

6. Clustal Omega. Multiple Sequence Alignment (MSA): [website]. Available from: https://www.ebi.ac.uk/jdispatcher/msa/clustalo [accessed Oct. 01, 2025].

7. Dossett M., Bassil N.V., Lewers K.S., Finn C.E. Genetic diversity in wild and cultivated black raspberry (Rubus occidentalis L.) evaluated by simple sequence repeat markers. Genetic Resources and Crop Evolution. 2012;59(8):1849-1865. DOI: 10.1007/s10722-012-9808-8

8. Folta K.M., Gardiner S.E. (eds). Genetics and genomics of Rosaceae. New York, NY: Springer; 2009. DOI: 10.1007/978-0-387-77491-6

9. GDR. Genome Database of Rosaceae: [website]. Available from: https://www.rosaceae.org [accessed Oct. 01, 2025].

10. Girichev G., Hanke M.V., Peil A., Flachowsky H. SSR fingerprinting of a German Rubus collection and pedigree based evaluation on trueness-to-type. Genetic Resources and Crop Evolution. 2015;64(1):89-103. DOI: 10.1007/s10722-015-0345-0

11. Hadonou A.M., Sargent D.J., Wilson F., James C.M., Simpson D.W. Development of microsatellite markers in Fragaria, their use in genetic diversity analysis, and their potential for genetic linkage mapping. Genome. 2004;47(3):429-438. DOI: 10.1139/g03-142

12. Han C., Yang G., Zhang H., Peng H., Yang J., Zhu P. et al. Development and validation of genome-wide SSR molecular markers of Tapes dorsatus. Molecular Biology Reports. 2024;51(1):73. DOI: 10.1007/s11033-023-08949-6

13. Hoban S., Bruford M., D’Urban Jackson J.D., Lopes-Fernandes M., Heuertz M., Hohenlohe P.A. et al. Genetic diversity targets and indicators in the CBD post-2020 Global Biodiversity Framework must be improved. Biological Conservation. 2020;248:108654. DOI: 10.1016/j.biocon.2020.108654

14. Integrated DNA Technologies. OligoAnalyzer™: Primer analysis tool: [website]. Available from: https://www.idtdna.com/pages/tools/oligoanalyzer [accessed Oct. 01, 2025].

15. IPCN Chromosome Reports. Index to Plant Chromosome Numbers (IPCN): [website]. Available from: https://legacy.tropicos.org/Project/IPCN [accessed Oct. 01, 2025].

16. Kalendar R.N., Aizharkyn K.S., Khapilina O.N., Amenov A.A., Tagimanova D.S. Plant diversity and transcriptional variability assessed by retrotransposon-based molecular markers. Vavilov Journal of Genetics and Breeding. 2017;21(1):128-134. DOI: 10.18699/VJ17.231

17. Kalendar R.N., Glazko V.I. Types of molecular genetic markers and their application. Plant Physiology and Genetics. 2002;34(4):141-156. [in Russian]

18. Kamnev А.М., Antonova O.Yu., Dunaeva S.Е., Gavrilenko T.A, Chukhina I.G. Molecular markers in the genetic diversity studies of representatives of the genus Rubus L. and prospects of their application in breeding. Vavilov Journal of Genetics and Breeding. 2020;24(1):20-30. [in Russian]. DOI: 10.18699/VJ20.591

19. Kumar S., Tamura K., Nei M. MEGA: Molecular Evolutionary Genetics Analysis software for microcomputers. Bioinformatics. 1994;10(2):189-191. DOI: 10.1093/bioinformatics/10.2.189

20. Li Y., Jiang N., Sun Y. AnnoSINE: a short interspersed nuclear elements annotation tool for plant genomes. Plant Physiology. 2022;188(2):955-970. DOI: 10.1093/plphys/kiab524

21. Liang Y., Lenz R.R., Dai W. Development of retrotransposon-based molecular markers and their application in genetic mapping in chokecherry (Prunus virginiana L.). Molecular Breeding. 2016;36(8):109. DOI: 10.1007/s11032-016-0535-2

22. Matveeva T.V., Pavlova O.A., Bogomaz D.I., Lutova L.A., Demkovich A.E. Molecular markers for plant species identification and phylogenetics. Ecological Genetics. 2011;9(1):32-43. [in Russian]

23. Melnikova N.V., Kudryavtseva A.V., Speranskaya A.S., Krinitsina A.A., Dmitriev A.A., Belenikin M.S. et al. The FaRE1 LTR-retrotransposon based SSAP markers reveal genetic polymorphism of strawberry (Fragaria × ananassa) cultivars. Journal of Agricultural Science. 2012;4(11):111. DOI: 10.5539/jas.v4n11p111

24. Melnikova N.V., Speranskaya A.S., Darii M.V., Belenikin M.S., Dmitriev A.A., Kudryavtseva A.V. Retrotransposon-based molecular markers and their use for genetic diversity assessment in plants. Bulletin of the Russian State Agrarian Correspondence University. 2013;14(19):32-35. [in Russian]

25. Mezhnina O.A., Urbanovich O.Yu. Identification of strawberry (Fragaria ananassa) using SSR-markers. Molecular and Applied Genetics. 2016;20:37-45. [in Russian]

26. NCBI. National Center for Biotechnology Information: [website]. Available from: https://www.ncbi.nlm.nih.gov [accessed Oct. 01, 2025].

27. Nei M. Analysis of gene diversity in subdivided populations. Proceedings of the National Academy of Sciences of the United States of America. 1973;70(12):3321-3323. DOI: 10.1073/pnas.70.12.3321

28. Omasheva M.E., Aubakirova K.P., Ryabushkina N.A. Molecular markers. Causes and consequences of genotyping errors (Molekulyarnye markery. Prichiny i posledstviya oshibok genotipirovaniya). Biotechnology. Theory and Practice. 2013;(4):20-28. [in Russian]. DOI: 10.11134/btp.4.2013.3

29. Reiche B., Kögler A., Morgenstern K., Brückner M., Weber B., Heitkam T. et al. Application of retrotransposon-based Inter-SINE Amplified Polymorphism (ISAP) markers for the differentiation of common poplar genotypes. Canadian Journal of Forest Research. 2021;51(11):1650-1663. DOI: 10.1139/cjfr-2020-0209

30. Schwichtenberg K., Wenke T., Zakrzewski F., Seibt K.M., Minoche M., Dohm J. et al. Diversification, evolution and methylation of short interspersed nuclear element families in sugar beet and related Amaranthaceae species. The Plant Journal. 2015;85(2):229-244. DOI: 10.1111/tpj.13103

31. Seibt K.M., Wenke T., Wollrab C., Junghans H., Muders K., Dehmer K.J. et al. Development and application of SINE-based markers for genotyping of potato varieties. Theoretical and Applied Genetics. 2012;125(1):185-196. DOI: 10.1007/s00122-012-1825-7

32. Sonneveld T., Tobutt K.R., Robbins T.P. Allele-specific PCR detection of sweet cherry self-incompatibility (S) alleles S1 to S16 using consensus and allele-specific primers. Theoretical and Applied Genetics. 2003;107(6):1059-1070. DOI: 10.1007/s00122-003-1274-4

33. Sormin S.Y.M., Purwantoro A., Setiawan A.B., Teo C.H. Application of inter-SINE amplified polymorphism (ISAP) markers for genotyping of Cucumis melo accessions and its transferability in Coleus spp. Biodiversitas. 2021;22(5):2918-2929. DOI: 10.13057/biodiv/d220557 DOI:10.13057/biodiv/d220557

34. Sun J., Hao Y., Li L., Song Y., Fan L., Zhang S. et al. Evaluation of new IRAP markers of pear and their potential application in differentiating bud sports and other Rosaceae species. Tree Genetics and Genomes. 2015;11(2):25. DOI: 10.1007/s11295-015-0849-y

35. UGENE team; Okonechnikov K., Golosova O., Fursov M. Unipro UGENE: a unified bioinformatics toolkit. Bioinformatics. 2012;28(8):1166-1167. DOI: 10.1093/bioinformatics/bts091

36. Untergasser A., Cutcutache I., Koressaar T., Ye J., Faircloth B.C., Remm M. et al. Primer3 – new capabilities and interfaces. Nucleic Acids Research. 2012;40(15):e115. DOI: 10.1093/nar/gks596

37. Vetchinnikova L.V., Titov A.F., Topchieva L.V., Rendakov N.L. Estimation of genetic diversity of Karelian birch populations in Karelia using microsatellite markers. Ecological Genetics. 2012;10(1):34-37. [in Russian]

38. Wenke T., Döbel T., Sörensen T.R., Junghans H., Weisshaar B., Schmidt T. Targeted identification of short interspersed nuclear element families shows their widespread existence and extreme heterogeneity in plant genomes. The Plant Cell. 2011;23(9):3117-3128. DOI: 10.1105/tpc.111.088682