A cost effective alternative method to ddRADseq library construction during size selection

Münevver Oral

doi:10.12714/egejfas.40.1.03

TR EN

ddRADseq kütüphanesi oluşturma işlemi fragman seçiminde uygun fiyatlı bir alternatif yöntem

Öz

Yeni nesil dizileme (YND) teknolojileri, biyolojide hızlı ve uygun maliyetli veri üretimi vaadi ile 21. yüzyılın en güçlü bilimsel ilerlemesini oluşturmaktadır. Yine de, güncel YND çalışmaları genellikle yerleşik kaynaklara sahip laboratuvarlarla sınırlı kalmaktadır. Bu çalışmada, kütüphane fragman seçimi sırasında yüksek teknoloji ürünü YND sarf malzemelerine (paramanyetik boncuklar) kıyasla rutin laboratuvar sarf malzemelerinden (agaroz jel elektroforezi: buradan itibaren AGE) kullanarak ddRADseq kütüphaneleri oluşturuldu. Standart ddRADseq kütüphanesi, evrensel olarak kullanılan paramanyetik boncuklara dayalı olarak seçilen fragmanlarla oluşturulurken, kalan kısım, sınırlı kaynaklara sahip laboratuvarlar için AGE kullanılarak aynı fragman büyüklüğünde ddRADseq kütüphanesi yapılabilirliğini değerlendirmek için bir şablon olarak kullanıldı. Her iki kütüphane de kalıp DNA yoğunluğunda benzerlik gösteren 15 PCR döngüsü için optimize edilmiştir. Kütüphanelerin PCR sonrası yoğunlukları benzerlik gösterdi (~10 ng.µL^-1). Boyut dağılımı değerlendirmesi, AGE ile manuel olarak seçilen ddRADseq kütüphane boyutunda daha temiz bir seçim olduğunu ortaya çıkardı. Benzer şekilde, Qubit ölçümleri de kütüphane DNA miktarının yakın olduğunu ortaya koydu (>3 ng.µL^-1). Elektroforez öncesi hazırlıklar, seri yıkama ve boyama adımları nedeniyle daha fazla zaman almasına rağmen, ddRADseq kütüphane kurulum işlemi başlangıç için gerekli adaptör ve PCR primerlerinin sağlanması kaydıyla rutin laboratuvar sarf malzemeleri kullanılarak gerçekleştirilebilir. Bu sonuçlar, sınırlı kaynaklara sahip laboratuvarlar için ddRADseq kütüphanesi oluşturmanın uygulanabilirliğini ortaya koymaktadır.

Anahtar Kelimeler

A cost effective alternative method to ddRADseq library construction during size selection

Abstract

Next generation sequencing (NGS) technologies constitute the most powerful scientific advance of 21^st century with a promise of fast and cost effective data generation in biology. Yet, up to date NGS studies remain often limited to laboratories with established resources. In the present study, we employed construction of ddRADseq library by using routine lab consumables (agarose gel electrophoresis: AGE thereafter) compared to high-tech NGS consumables (paramagnetic beads) during size selection. The ddRADseq library was constructed for sequencing size selected based on universally used paramagnetic beads, while remaining aliquot was used as a template to assess the feasibility of ddRADseq library construction using AGE for labs with limited resources. Both libraries were optimised for 15 PCR cycles indicating similarity in template intensity. Post-PCR quantification of the libraries was comparable (~10 ng.µL^-1). Size distribution assessment revealed a cleaner pick at the ddRADseq library size selected manually based on AGE. Similarly, intercalating agent of Qubit confirmed the quantity of libraries was similar (>3 ng.µL^-1). Although being more time consuming due to pre-electrophoresis preparations, serial wash and staining steps, ddRADseq library construction is achievable using routine lab consumables provided to supply the adaptors and PCR primers for the initial wet-lab work. These results manifest the feasibility of ddRADseq library generation for labs with limited resources.

Keywords

Destekleyen Kurum

ISEM, University of Montpellier

Teşekkür

Münevver Oral has received funding from Montpellier University of Excellence (MUSE) an Initiative for Science, Innovation, Territories, and Economy (I-SITE) of the French Investment for the Future Program under Explore#2 international mobility grant. Entire wet-lab work involved in the manuscript was performed at the genomics facility of ISEM the LabEx CeMEB (Centre Méditerranéen pour l’Environnement et la Biodiversité, Montpellier). This study was designed based on the experience of the author gathered working under guidelines of John B. Taggart, Stirling, Scotland during her PhD thesis. Author would like to thank Prof. Dr. Davut Turan for his help and guideline during fieldwork.

Kaynakça

Andrews, K. R., Good, J. M., Miller, M. R., Luikart, G., & Hohenlohe, P.A. (2016). Harnessing the power of RADseq for ecological and evolutionary genomics. Nature Reviews Genetics, 17(2), 81–92. https://doi.org/10.1038/nrg.2015.28
Burns, M., Starrett, J., Derkarabetian, S., Richart, C. H., Cabrero, A., & Hedin, M. (2017). Comparative performance of double-digest RAD sequencing across divergent arachnid lineages. Molecular Ecology Resources, 17(3), 418–430. https://doi.org/10.1111/1755-0998.12575
Capblancq, T., Després, L., Rioux, D., & Mavárez, J. (2015). Hybridization promotes speciation in Coenonympha butterflies. Molecular Ecology, 24(24). https://doi.org/10.1111/mec.13479
Cumer, T., Pouchon, C., Boyer, F., Yannic, G., Rioux, D., and Bonin, A., & Capblancq, T. (2021). Double-digest RAD-sequencing: do pre- and post-sequencing protocol parameters impact biological results? Molecular Genetics and Genomics, 296, 457–471. https://doi.org/10.1007/s00438-020-01756-9
Davey, J. W., Hohenlohe, P. A, Etter, P. D., Boones, J.Q., Catchen, J.M., & Blaxter, M.L. (2011). Genome-wide genetic marker discovery and genotyping using next-generation sequencing. Nature Reviews Genetics, 12(7), 499–510. https://doi.org/10.1038/nrg3012
Fonseca, R.R., Albrechtsen, A., Themudo, G.E., Madriagal, J.R., Sibbesen, J.A., Maretty, L., Mendoza, M.L., Campos, P.F., Heller, R, & Pereira, R.J. (2016). Next-generation biology: Sequencing and data analysis approaches for non-model organisms. Marine Genomics, 30, 3-13. https://doi.org/10.1016/j.margen.2016.04.012
Glasauer, S. M. K. & Neuhauss, S. C. F. (2014). Whole-genome duplication in teleost fishes and its evolutionary consequences. Molecular Genetics and Genomics, 289(6), 1045–60. https://doi.org/10.1007/s00438-014-0889-2
Guo, Y., Ye, F., Sheng, Y., Sheng, Q., Clark, T., & Samuels, D.C. (2014). Three-stage quality control strategies for DNA re-sequencing data. Briefings in Bioinformatics, 15(6), 879–889. https://doi.org/10.1093/bib/bbt069

Hohenlohe, P. A., Catchen, J., & Cresko, W. A. (2012). Population Genomic Analysis of Model and Nonmodel Organisms Using Sequenced RAD Tags. In Data Production and Analysis in Population Genomics (pp. 235–260). Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-61779-870-2_14
Hu, T., Chitnis, N., Monos, D., & Dinh, A. (2021). Next-generation sequencing technologies: An overview. Human Immunology 82; 801–811.
Illumina.com. (Accession date: 20.05.2022; 9:00). Converting ng/µl to nM when calculating dsDNA library concentration. (https://emea.support.illumina.com/bulletins/2016/11/converting-ngl-to-nm-when-calculating-dsdna-library-concentration-.html?langsel)
Knapp, B., Bardenet, R., Bernabeu, M.O., & Deane, C.M. (2015). Ten simple rules for a successful cross‐disciplinary collaboration. Plos Computational Biology, 11(4), e1004214. https://doi.org/10.1371/journal.pcbi.1004214
Koboldt, D.C., Steinberg, K.M., Larson, D.E., Wilson, R.K., & Mardis, E.R. (2013). The next-generation sequencing revolution and its impact on genomics. Cell, 155:27–38. https://doi.org/10.1016/j.cell.2013.09.006
Leitwein, M., Gagnaire, P. A., Desmarais, E., Guendouz, S., Rohmer, M., Berrebi, P., & Guinand, B. (2016). Genome-wide nucleotide diversity of hatchery-reared Atlantic and Mediterranean strains of brown trout Salmo trutta compared to wild Mediterranean populations. Journal of Fish Biology, 89, 2717–2734. https://doi.org/10.1111/jfb.13131
MacLean, D., Jonathan D.G.J., & Studholme, D. J. (2009). Application of next-generation sequencing technologies to microbial genetics. Nature Reviews Microbiology, 7, 287-296. https://doi.org/10.1038/nrmicro2088
McCombie, W.R., McPherson, J.D., & Mardis, E.R. (2019). Next Generation Sequencing Technologies, Cold Spring Harb Perspect Med 2019;9:a036798. https://doi.org/10.1101/cshperspect.a036798
McCormack, J.E., Hird, S.M., Zellmer, A. J., Carstens, B.C., & Brumfield, R.T. (2013). Applications of next-generation sequencing to phylogeography and phylogenetics. Molecular Phylogenetics and Evolution, 66(2), 526-538. https://doi.org/10.1016/j.ympev.2011.12.007
Oral, M., Colléter, J., Bekaert, M., Taggart, J.B., Palaiokostas, C., McAndrews, B.J., Vandeputte, M., Chatain, B., Kuhl, H., Reinhard, R., Peruzzi, S., & Penman, D.J. (2017). Gene-centromere mapping in meiotic gynogenetic European seabass. BMC Genomics, 18, 449. https://doi.org/10.1186/s12864-017-3826-z
Palaiokostas, C., Bekaert, M., Khan, M. G. Q., Taggart, J.B., Gharbi, K., McAndrew, B.J., & Penman, D.J. (2015). A novel sex-determining QTL in Nile tilapia (Oreochromis niloticus). BMC Genomics, 16(1), 171. https://doi.org/10.1186/s12864-015-1383-x
Paris, J. R., Stevens, J. R., & Catchen, J. M. (2017). Lost in parameter space: A road map for stacks. Methods in Ecology and Evolution, 8(10), 1360-1373. https://doi.org/10.1111/2041-210X.12775
Peterson, B.K., Weber, J., Kay, E.H., Fisher, H.S., & Hoekstra, H.E. (2012). Double Digest RADseq: An Inexpensive Method for De Novo SNP Discovery and Genotyping in Model and Non-Model Species. Plos One, 7(5), e37135. https://doi.org/10.1371/journal.pone.0037135
Shafer, A. B. A., Peart, C. R., Tusso, S., Maayan, I., Brelsford, A., Wheat, C.W., & Wolf, J.B.W. (2016). Bioinformatic processing of RAD‐seq data dramatically impacts downstream population genetic inference. Methods in Ecology and Evolution, 8(8), 907–917. https://doi.org/10.1111/2041-210X.12700
SPRIselect User Guide. (Accession date: 17.06.2022; 14:20). Size selection based of paramagnetic beads. p. 1-8. (https://research.fhcrc.org/content/dam/stripe/hahn/methods/mol_biol/SPRIselect%20User%20Guide.pdf)
Tan, M.P., Wong, L.L., Razali, S.A. Aleng, N.A., Nor, S.A.M., Sung, Y.Y., Peer, Y.V., Sorgeloos, P., & Daniel, M.D. (2019). Applications of Next-Generation Sequencing Technologies and Computational Tools in Molecular Evolution and Aquatic Animals Conservation Studies: A Short Review. Evolutionary Bioinformatics, 15, 1-5. https://doi.org/10.1177/1176934319892284
Turan, D., Kottelat, M., & Bektaş, Y. (2011). Salmo tigridis, a new species of trout from Tigris River, Turkey (Teleostei: Salmonidae). Zootaxa 2993, 23–33. https://doi.org/10.11646/zootaxa.2993.1.2
Turan, D., Kottelat, M., & Engin, S. (2012). The trouts of the Mediterranean drainages of southern Anatolia, Turkey, with description of three new species (Teleostei: Salmonidae). Ichthyological Exploration of Freshwaters, 23, 219–236.
Yang, G.Q., Chen, Y.M., Wang, J.P., Guo, C., Zhao, L., Wang, X.Y., Guo, Y., Li, L., Li, D.Z., & Guo, Z.H. (2016). Development of a universal and simplified ddRAD library preparation approach for SNP discovery and genotyping in angiosperm plants. Plant Methods, 12, 39. https://doi.org/10.1186/s13007-016-0139-1

Ayrıntılar

Birincil Dil

İngilizce

Konular

Yapısal Biyoloji

Bölüm

Araştırma Makalesi

Yazarlar

Münevver Oral ^*
0000-0001-7318-6641
Türkiye

Yayımlanma Tarihi

15 Mart 2023

Gönderilme Tarihi

16 Ağustos 2022

Kabul Tarihi

30 Kasım 2022

Yayımlandığı Sayı

Yıl 2023 Cilt: 40 Sayı: 1

DOI

https://doi.org/10.12714/egejfas.40.1.03

IZ

https://izlik.org/JA42TC48NF

Kaynak Göster

RIS / Bibtex

APA

Oral, M. (2023). A cost effective alternative method to ddRADseq library construction during size selection. Ege Journal of Fisheries and Aquatic Sciences, 40(1), 20-26. https://doi.org/10.12714/egejfas.40.1.03

Cited By

The trouts of the Marmara and Aegean Sea drainages in Türkiye, with the description of a new species (Teleostei, Salmonidae)

Zoosystematics and Evolution

https://doi.org/10.3897/zse.100.112557