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Current Genomics

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ISSN (Print): 1389-2029
ISSN (Online): 1875-5488

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Research Article

A Pipeline for the Development of Microsatellite Markers using Next Generation Sequencing Data

Author(s): Adriana Maria Antunes*, Júlio Gabriel Nunes Stival, Cíntia Pelegrineti Targueta, Mariana Pires de Campos Telles and Thannya Nascimento Soares

Volume 23, Issue 3, 2022

Published on: 02 June, 2022

Page: [175 - 181] Pages: 7

DOI: 10.2174/1389202923666220428101350

Price: $65

Abstract

Background: Also known as Simple Sequence Repetitions (SSRs), microsatellites are profoundly informative molecular markers and powerful tools in genetics and ecology studies on plants.

Objective: This research presents a workflow for developing microsatellite markers using genome skimming.

Methods: The pipeline was proposed in several stages that must be performed sequentially: obtaining DNA sequences, identifying microsatellite regions, designing primers, and selecting candidate microsatellite regions to develop the markers. Our pipeline efficiency was analyzed using Illumina sequencing data from the non-model tree species Pterodon emarginatus Vog.

Results: The pipeline revealed 4,382 microsatellite regions and drew 7,411 pairs of primers for P. emarginatus. However, a much larger number of microsatellite regions with the potential to develop markers were discovered from our pipeline. We selected 50 microsatellite regions with high potential for developing markers and organized 29 microsatellite regions in sets for multiplex PCR.

Conclusion: The proposed pipeline is a powerful tool for fast and efficient development of microsatellite markers on a large scale in several species, especially nonmodel plant species.

Keywords: Bioinformatics, genome skimming, PCR multiplex, primer design, Pterodon emarginatus, microsatellite markers.

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Graphical Abstract

[1]
Taheri, S.; Lee Abdullah, T.; Yusop, M.R.; Hanafi, M.M.; Sahebi, M.; Azizi, P.; Shamshiri, R.R. Mining and development of novel SSR markers using Next Generation Sequencing (NGS) data in plants. Molecules, 2018, 23(2), 1-20.
[http://dx.doi.org/10.3390/molecules23020399] [PMID: 29438290]
[2]
Vieira, M.L.C.; Santini, L.; Diniz, A.L.; Munhoz, C.F. Microsatellite markers: What they mean and why they are so useful. Genet. Mol. Biol., 2016, 39(3), 312-328.
[http://dx.doi.org/10.1590/1678-4685-GMB-2016-0027] [PMID: 27561112]
[3]
Deng, P.; Wang, M.; Feng, K.; Cui, L.; Tong, W.; Song, W.; Nie, X. Genome-wide characterization of microsatellites in Triticeae species: Abundance, distribution and evolution. Sci. Rep., 2016, 6(1), 32224.
[http://dx.doi.org/10.1038/srep32224] [PMID: 27561724]
[4]
Teshome, Z.; Terfa, M.T.; Tesfaye, B.; Shiferaw, E.; Olango, T.M. Genetic diversity in anchote (Coccinia abyssinica (Lam.) Cogn) using microsatellite markers. Curr. Plant Biol., 2020, 24, 100167.
[http://dx.doi.org/10.1016/j.cpb.2020.100167]
[5]
Kumar, C.; Kumar, R.; Singh, S.K.; Goswami, A.K.; Nagaraja, A.; Paliwal, R.; Singh, R. Development of novel g-SSR markers in guava (Psidium guajava L.) cv. Allahabad Safeda and their application in genetic diversity, population structure and cross species transferability studies. PLoS One, 2020, 15(8), e0237538.
[http://dx.doi.org/10.1371/journal.pone.0237538] [PMID: 32804981]
[6]
Kristamtinila, T.; Basunanda, P.; Murti, R.H. Application of microsatellite markers as marker assisted selection (mas) in the f3 generation results crosses of black rice and white rice. AIP Conf. Proc., 2020, 2260, 0-9.
[7]
Miah, G.; Rafii, M.Y.; Ismail, M.R.; Puteh, A.B.; Rahim, H.A.; Islam, KhN.; Latif, M.A. A review of microsatellite markers and their applications in rice breeding programs to improve blast disease resistance. Int. J. Mol. Sci., 2013, 14(11), 22499-22528.
[http://dx.doi.org/10.3390/ijms141122499] [PMID: 24240810]
[8]
Bastías, A.; Correa, F.; Rojas, P.; Almada, R.; Muñoz, C.; Sagredo, B. Identification and characterization of microsatellite loci in maqui (Aristotelia chilensis [molina] stunz) using Next-Generation Sequencing (NGS). PLoS One, 2016, 11(7), e0159825.
[http://dx.doi.org/10.1371/journal.pone.0159825] [PMID: 27459734]
[9]
Guimarães, R.A.; Telles, M.P.C.; Antunes, A.M.; Corrêa, K.M.; Ribeiro, C.V.G.; Coelho, A.S.G.; Soares, T.N. Discovery and characterization of new microsatellite loci in Dipteryx alata Vogel (Fabaceae) using next-generation sequencing data. Genet. Mol. Res., 2017, 16(2), 16.
[http://dx.doi.org/10.4238/gmr16029639] [PMID: 28453176]
[10]
Mardis, E.R. Next-generation DNA sequencing methods. Annu. Rev. Genomics Hum. Genet., 2008, 9(1), 387-402.
[http://dx.doi.org/10.1146/annurev.genom.9.081307.164359] [PMID: 18576944]
[11]
Metzker, M.L. Sequencing technologies - the next generation. Nat. Rev. Genet., 2010, 11(1), 31-46.
[http://dx.doi.org/10.1038/nrg2626] [PMID: 19997069]
[12]
Mehrotra, S.; Goyal, V. Repetitive sequences in plant nuclear DNA: Types, distribution, evolution and function. Proteom. Bioinform., 2014, 12(4), 164-171.
[http://dx.doi.org/10.1016/j.gpb.2014.07.003] [PMID: 25132181]
[13]
Pandey, M.; Sharma, J. Efficiency of microsatellite isolation from orchids via next generation sequencing. Open J. Genet., 2012, 2(4), 167-172.
[http://dx.doi.org/10.4236/ojgen.2012.24022]
[14]
Lima, H.C.; Lima, I.B. Pterodon in Lista de Espécies da Flora do Brasil. In: Jard Botânico do Rio Janeiro. 2015. Available from: http://floradobrasil.jbrj.gov.br/jabot/floradobrasil/FB29840
[15]
Pascoa, H.; Diniz, D.G.A.; Florentino, I.F.; Costa, E.A.; Bara, M.T.F. Microemulsion based on Pterodon emarginatus oil and its anti-infammatory potential. Braz. J. Pharm. Sci., 2015, 51(1), 117-126.
[http://dx.doi.org/10.1590/S1984-82502015000100013]
[16]
Bavaresco, O.S.A.; Pereira, I.C.P.; Melo, C.D.; Lobato, F.; Falcai, A.; Bomfim, M.R.Q. Popular use of Pterodon spp. in the treatment of rheumatic diseases. Rev. Investig. Biomed., 2016, 8(1), 81-91.
[http://dx.doi.org/10.24863/rib.v8i1.32]
[17]
Lorenzi, H. Brazilian Trees: Manual for the identification and cultivation of native tree plants in Brazil. nhbs, 2008, 2, 384.
[18]
Hansen, D.; Haraguchi, M.; Alonso, A. Pharmaceutical properties of “sucupira” (Pterodon spp.). Braz. J. Pharm. Sci., 2010, 46(4), 607-616.
[http://dx.doi.org/10.1590/S1984-82502010000400002]
[19]
Dutra, R.C.; Silva, P.S.; Pittella, F.; Viccini, L.F.; Leite, M.N.; Raposo, N.R.B. Phytochemical and cytogenetic characterization of Pterodon emarginatus Vogel seeds. IFSC Tech. Sci. J., 2012, 3(1), 99-109.
[20]
Andrews, S. FastQC: a quality control tool for high throughput sequence data., 2010. Available from: http://www.bioinformatics. babraham.ac.uk/projects/fastqc/ (Accessed on: March 16, 2022).
[21]
Bolger, A.M.; Lohse, M.; Usadel, B. Trimmomatic: A flexible trimmer for Illumina sequence data. Bioinformatics, 2014, 30(15), 2114-2120.
[http://dx.doi.org/10.1093/bioinformatics/btu170] [PMID: 24695404]
[22]
Langmead, B.; Trapnell, C.; Pop, M.; Salzberg, S.L. Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol., 2009, 10(3), R25.
[http://dx.doi.org/10.1186/gb-2009-10-3-r25] [PMID: 19261174]
[23]
Zimin, A.V.; Marçais, G.; Puiu, D.; Roberts, M.; Salzberg, S.L.; Yorke, J.A. The MaSuRCA genome assembler. Bioinformatics, 2013, 29(21), 2669-2677.
[http://dx.doi.org/10.1093/bioinformatics/btt476] [PMID: 23990416]
[24]
Altschul, S.F.; Gish, W.; Miller, W.; Myers, E.W.; Lipman, D.J. Basic local alignment search tool. J. Mol. Biol., 1990, 215(3), 403-410.
[http://dx.doi.org/10.1016/S0022-2836(05)80360-2] [PMID: 2231712]
[25]
Meglécz, E.; Costedoat, C.; Dubut, V.; Gilles, A.; Malausa, T.; Pech, N.; Martin, J.F. QDD: A user-friendly program to select microsatellite markers and design primers from large sequencing projects. Bioinformatics, 2010, 26(3), 403-404.
[http://dx.doi.org/10.1093/bioinformatics/btp670] [PMID: 20007741]
[26]
Kalendar, R.; Khassenov, B.; Ramankulov, Y.; Samuilova, O.; Ivanov, K.I. FastPCR: An in silico tool for fast primer and probe design and advanced sequence analysis. Genomics, 2017, 109(3-4), 312-319.
[http://dx.doi.org/10.1016/j.ygeno.2017.05.005] [PMID: 28502701]
[27]
Antunes, A.M.; Nunes, R.; Novaes, E.; Coelho, A.S.G.; Soares, T.N.; Telles, M.P.C. Large number of repetitive elements in the draft genome assembly of Dipteryx alata (Fabaceae). Genet. Mol. Res., 2020, 19(2), 1-9.
[http://dx.doi.org/10.4238/gmr18463]
[28]
Araya, S.; Martins, A.M.; Junqueira, N.T.V.; Costa, A.M.; Faleiro, F.G.; Ferreira, M.E. Microsatellite marker development by partial sequencing of the sour passion fruit genome (Passiflora edulis Sims). BMC Genomics, 2017, 18(1), 549.
[http://dx.doi.org/10.1186/s12864-017-3881-5] [PMID: 28732469]
[29]
Merritt, A.B.J.; Culley, T.M.; Avanesyan, A.; Stokes, R. An empirical review: Characteristics of plant microsatellite markers that confer higher levels of genetic variation. Appl. Plant Sci., 2015, 3(8), 1-12.
[http://dx.doi.org/10.3732/apps.1500025] [PMID: 26312192]
[30]
Han, Z.; Ma, X.; Wei, M.; Zhao, T.; Zhan, R.; Chen, W. SSR marker development and intraspecific genetic divergence exploration of Chrysanthemum indicum based on transcriptome analysis. BMC Genomics, 2018, 19(1), 291.
[http://dx.doi.org/10.1186/s12864-018-4702-1] [PMID: 29695227]
[31]
Mason, A. SSR Genotyping., In: Batley J. Ed., Plant Genotyping; Springer: New York, NY. 2015. pp. 77-89.
[32]
Lepais, O.; Chancerel, E.; Boury, C. Fast sequence-based microsatellite genotyping development workflow. Prepr. bioRxiv, 2019, 2019, 1-30.

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