Genomics & Informatics

Korea Genome Organization (한국유전체학회)
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Chromosome-specific polymorphic SSR markers in tropical eucalypt species using low coverage whole genome sequences: systematic characterization and validation

  • Received : 2021.05.21
  • Accepted : 2021.06.29
  • Published : 2021.09.30
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Abstract

Eucalyptus is one of the major plantation species with wide variety of industrial uses. Polymorphic and informative simple sequence repeats (SSRs) have broad range of applications in genetic analysis. In this study, two individuals of Eucalyptus tereticornis (ET217 and ET86), one individual each from E. camaldulensis (EC17) and E. grandis (EG9) were subjected to whole genome resequencing. Low coverage (10×) genome sequencing was used to find polymorphic SSRs between the individuals. Average number of SSR loci identified was 95,513 and the density of SSRs per Mb was from 157.39 in EG9 to 155.08 in EC17. Among all the SSRs detected, the most abundant repeat motifs were di-nucleotide (59.6%-62.5%), followed by tri- (23.7%-27.2%), tetra- (5.2%-5.6%), penta- (5.0%-5.3%), and hexa-nucleotide (2.7%-2.9%). The predominant SSR motif units were AG/CT and AAG/TTC. Computational genome analysis predicted the SSR length variations between the individuals and identified the gene functions of SSR containing sequences. Selected subset of polymorphic markers was validated in a full-sib family of eucalypts. Additionally, genome-wide characterization of single nucleotide polymorphisms, InDels and transcriptional regulators were carried out. These variations will find their utility in genome-wide association studies as well as understanding of molecular mechanisms involved in key economic traits. The genomic resources generated in this study would provide an impetus to integrate genomics in marker-trait associations and breeding of tropical eucalypts.

Keywords

Acknowledgement

The authors acknowledge the funding support from the Department of Biotechnology, Government of India.

References

  1. Gullon B, Muniz-Mouro A, Lu-Chau TA, Moreira MT, Lema JM, Eibes G. Green approaches for the extraction of antioxidants from eucalyptus leaves. Ind Crops Prod 2019;138:111473. https://doi.org/10.1016/j.indcrop.2019.111473
  2. Salehi B, Sharifi-Rad J, Quispe C, Llaique H, Villalobos M, Smeriglio A, et al. Insights into Eucalyptus genus chemical constituents, biological activities and health-promoting effects. Trends Food Sci Technol 2019;91:609-624. https://doi.org/10.1016/j.tifs.2019.08.003
  3. Vena PF, Garcia-Aparicio MP, Brienzo M, Gorgens JF, Rypstra T. Effect of alkaline hemicellulose extraction on kraft pulp fibers from Eucalyptus grandis. J Wood Chem Technol 2013;33:157-173. https://doi.org/10.1080/02773813.2013.773040
  4. Booth TH. Assessing the thermal adaptability of tree provenances: an example using Eucalyptus tereticornis. Aust For 2019;82:176-180. https://doi.org/10.1080/00049158.2019.1680594
  5. Chen S, Weng Q, Li F, Li M, Zhou C, Gan S. Genetic parameters for growth and wood chemical properties in Eucalyptus urophylla × E. tereticornis hybrids. Ann For Sci 2018;75:16. https://doi.org/10.1007/s13595-018-0694-x
  6. Grattapaglia D, Vaillancourt RE, Shepherd M, Thumma BR, Foley W, Kulheim C, et al. Progress in Myrtaceae genetics and genomics: Eucalyptus as the pivotal genus. Tree Genet Genomes 2012;8:463-508. https://doi.org/10.1007/s11295-012-0491-x
  7. Vieira ML, Santini L, Diniz AL, Munhoz Cde F. Microsatellite markers: what they mean and why they are so useful. Genet Mol Biol 2016;39:312-328. https://doi.org/10.1590/1678-4685-GMB-2016-0027
  8. Brondani RP, Brondani C, Grattapaglia D. Towards a genus-wide reference linkage map for Eucalyptus based exclusively on highly informative microsatellite markers. Mol Genet Genomics 2002;267:338-347. https://doi.org/10.1007/s00438-002-0665-6
  9. Grattapaglia D, Mamani EM, Silva-Junior OB, Faria DA. A novel genome-wide microsatellite resource for species of Eucalyptus with linkage-to-physical correspondence on the reference genome sequence. Mol Ecol Resour 2015;15:437-448. https://doi.org/10.1111/1755-0998.12317
  10. Zhou C, He X, Li F, Weng Q, Yu X, Wang Y, et al. Development of 240 novel EST-SSRs in Eucalyptus L'Herit. Mol Breed 2014;33:221-225. https://doi.org/10.1007/s11032-013-9923-z
  11. Gion JM, Hudson CJ, Lesur I, Vaillancourt RE, Potts BM, Freeman JS. Genome-wide variation in recombination rate in Eucalyptus. BMC Genomics 2016;17:590. https://doi.org/10.1186/s12864-016-2884-y
  12. Srivastava S, Kushwaha B, Prakash J, Kumar R, Nagpure NS, Agarwal S, et al. Development and characterization of genic SSR markers from low depth genome sequence of Clarias batrachus (magur). J Genet 2016;95:603-609. https://doi.org/10.1007/s12041-016-0672-8
  13. Taheri S, Lee Abdullah T, Yusop MR, Hanafi MM, Sahebi M, Azizi P, et al. Mining and development of novel SSR markers using next generation sequencing (NGS) data in plants. Molecules 2018;23:399. https://doi.org/10.3390/molecules23020399
  14. Yang J, Zhang J, Han R, Zhang F, Mao A, Luo J, et al. Target SSR-Seq: a novel SSR genotyping technology associate with perfect SSRs in genetic analysis of cucumber varieties. Front Plant Sci 2019;10:531. https://doi.org/10.3389/fpls.2019.00531
  15. Mun JH, Chung H, Chung WH, Oh M, Jeong YM, Kim N, et al. Construction of a reference genetic map of Raphanus sativus based on genotyping by whole-genome resequencing. Theor Appl Genet 2015;128:259-272. https://doi.org/10.1007/s00122-014-2426-4
  16. Song WH, Chung SM. Whole genome re-sequencing and development of SSR markers in oriental melon. J Plant Biotechnol 2019;46:71-78. https://doi.org/10.5010/jpb.2019.46.2.071
  17. Yang H, Geng X, Zhao S, Shi H. Genomic diversity analysis and identification of novel SSR markers in four tobacco varieties by high-throughput resequencing. Plant Physiol Biochem 2020;150:80-89. https://doi.org/10.1016/j.plaphy.2020.02.023
  18. Li B, Lin F, Huang P, Guo W, Zheng Y. Development of nuclear SSR and chloroplast genome markers in diverse Liriodendron chinense germplasm based on low-coverage whole genome sequencing. Biol Res 2020;53:21. https://doi.org/10.1186/s40659-020-00289-0
  19. Biswas MK, Darbar JN, Borrell JS, Bagchi M, Biswas D, Nuraga GW, et al. The landscape of microsatellites in the enset (Ensete ventricosum) genome and web-based marker resource development. Sci Rep 2020;10:15312. https://doi.org/10.1038/s41598-020-71984-x
  20. Wang X, Wang L. GMATA: an integrated software package for genome-scale SSR mining, marker development and viewing. Front Plant Sci 2016;7:1350.
  21. Wang W, Das A, Kainer D, Schalamun M, Morales-Suarez A, Schwessinger B, et al. The draft nuclear genome assembly of Eucalyptus pauciflora: a pipeline for comparing de novo assemblies. Gigascience 2020;9:giz160. https://doi.org/10.1093/gigascience/giz160
  22. Lewis DH, Jarvis DE, Maughan PJ. SSRgenotyper: a simple sequence repeat genotyping application for whole-genome resequencing and reduced representational sequencing projects. Appl Plant Sci 2020;8:e11402.
  23. Guo L, Yang Q, Yang JW, Zhang N, Liu BS, Zhu KC, et al. MultiplexSSR: a pipeline for developing multiplex SSR-PCR assays from resequencing data. Ecol Evol 2020;10:3055-3067. https://doi.org/10.1002/ece3.6121
  24. Humann JL, Lee T, Ficklin S, Main D. Structural and functional annotation of eukaryotic genomes with GenSAS. Methods Mol Biol 2019;1962:29-51. https://doi.org/10.1007/978-1-4939-9173-0_3
  25. Bardou P, Mariette J, Escudie F, Djemiel C, Klopp C. jvenn: an interactive Venn diagram viewer. BMC Bioinformatics 2014;15:293. https://doi.org/10.1186/1471-2105-15-293
  26. Zheng Y, Jiao C, Sun H, Rosli HG, Pombo MA, Zhang P, et al. iTAK: a program for genome-wide prediction and classification of plant transcription factors, transcriptional regulators, and protein kinases. Mol Plant 2016;9:1667-1670. https://doi.org/10.1016/j.molp.2016.09.014
  27. Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nat Methods 2012;9:357-359. https://doi.org/10.1038/nmeth.1923
  28. Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics 2009;25:2078-2079. https://doi.org/10.1093/bioinformatics/btp352
  29. Sumathi M, Bachpai VKW, Mayavel A, Dasgupta MG, Nagarajan B, Rajasugunasekar D, et al. Genetic linkage map and QTL identification for adventitious rooting traits in red gum eucalypts. 3 Biotech 2018;8:242. https://doi.org/10.1007/s13205-018-1276-1
  30. Myburg AA, Grattapaglia D, Tuskan GA, Hellsten U, Hayes RD, Grimwood J, et al. The genome of Eucalyptus grandis. Nature 2014;510:356-362. https://doi.org/10.1038/nature13308
  31. Hussey SG, Grima-Pettenati J, Myburg AA, Mizrachi E, Brady SM, Yoshikuni Y, et al. A standardized synthetic Eucalyptus transcription factor and promoter panel for re-engineering secondary cell wall regulation in biomass and bioenergy crops. ACS Synth Biol 2019;8:463-465. https://doi.org/10.1021/acssynbio.8b00440
  32. Santos SA, Vidigal PM, Guimaraes LM, Mafia RG, Templeton MD, Alfenas AC. Transcriptome analysis of Eucalyptus grandis genotypes reveals constitutive overexpression of genes related to rust (Austropuccinia psidii) resistance. Plant Mol Biol 2020;104:339-357. https://doi.org/10.1007/s11103-020-01030-x
  33. Sasaki K, Ida Y, Kitajima S, Kawazu T, Hibino T, Hanba YT. Overexpressing the HD-Zip class II transcription factor EcHB1 from Eucalyptus camaldulensis increased the leaf photosynthesis and drought tolerance of Eucalyptus. Sci Rep 2019;9:14121. https://doi.org/10.1038/s41598-019-50610-5
  34. Zhang J, Wu J, Guo M, Aslam M, Wang Q, Ma H, et al. Genome-wide characterization and expression profiling of Eucalyptus grandis HD-Zip gene family in response to salt and temperature stress. BMC Plant Biol 2020;20:451. https://doi.org/10.1186/s12870-020-02677-w
  35. Supple MA, Bragg JG, Broadhurst LM, Nicotra AB, Byrne M, Andrew RL, et al. Landscape genomic prediction for restoration of a Eucalyptus foundation species under climate change. Elife 2018;7:e31835. https://doi.org/10.7554/elife.31835
  36. Kainer D, Padovan A, Degenhardt J, Krause S, Mondal P, Foley WJ, et al. High marker density GWAS provides novel insights into the genomic architecture of terpene oil yield in Eucalyptus. New Phytol 2019;223:1489-1504. https://doi.org/10.1111/nph.15887
  37. Thavamanikumar S, Arnold RJ, Luo J, Thumma BR. Genomic studies reveal substantial dominant effects and improved genomic predictions in an open-pollinated breeding population of Eucalyptus pellita. G3 (Bethesda) 2020;10:3751-3763. https://doi.org/10.1534/g3.120.401601
  38. Sumathi M, Yasodha R. Microsatellite resources of Eucalyptus: current status and future perspectives. Bot Stud 2014;55:73. https://doi.org/10.1186/s40529-014-0073-3
  39. Cavagnaro PF, Senalik DA, Yang L, Simon PW, Harkins TT, Kodira CD, et al. Genome-wide characterization of simple sequence repeats in cucumber (Cucumis sativus L.). BMC Genomics 2010;11:569. https://doi.org/10.1186/1471-2164-11-569
  40. Liu G, Xie Y, Zhang D, Chen H. Analysis of SSR loci and development of SSR primers in Eucalyptus. J For Res 2018;29:273-282. https://doi.org/10.1007/s11676-017-0434-3
  41. Arumugasundaram S, Ghosh M, Veerasamy S, Ramasamy Y. Species discrimination, population structure and linkage disequilibrium in Eucalyptus camaldulensis and Eucalyptus tereticornis using SSR markers. PLoS One 2011;6:e28252. https://doi.org/10.1371/journal.pone.0028252
  42. Uncu AT. Genome-wide identification of simple sequence repeat (SSR) markers in Capsicum chinense Jacq. with high potential for use in pepper introgression breeding. Biologia 2019;74:119-126. https://doi.org/10.2478/s11756-018-0155-x