Optimizing ddRADseq in non-model species: a case study in Eucalyptus dunnii Maiden
; Filippi, Carla Valeria
; Zaina, Giusi ; Rivas, Juan Gabriel
; Acuña, Cintia Vanesa
; Villalba, Pamela Victoria
; Garcia, Martín Nahuel
; González, Sergio Alberto
; Rivarola, Maximo Lisandro
; Martinez, Maria Carolina ; Puebla, Andrea Fabiana ; Morgante, Michele ; Hopp, Horacio Esteban ; Paniego, Norma Beatriz
; Marcucci Poltri, Susana Noemí Otros responsables
Fecha
08/2019
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Multidisciplinary Digital Publishing Institute
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Agronomy
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2073-4395
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Restriction site-associated DNA sequencing (RADseq) and its derived protocols, such as double digest RADseq (ddRADseq), offer a flexible and highly cost-effective strategy for efficient plant genome sampling. This has become one of the most popular genotyping approaches for breeding, conservation, and evolution studies in model and non-model plant species. However, universal protocols do not always adapt well to non-model species. Herein, this study reports the development of an optimized and detailed ddRADseq protocol in Eucalyptus dunnii, a non-model species, which combines different aspects of published methodologies. The initial protocol was established using only two samples by selecting the best combination of enzymes and through optimal size selection and simplifying lab procedures. Both single nucleotide polymorphisms (SNPs) and simple sequence repeats (SSRs) were determined with high accuracy after applying stringent bioinformatics settings and quality filters, with and without a reference genome. To scale it up to 24 samples, we added barcoded adapters. We also applied automatic size selection, and therefore obtained an optimal number of loci, the expected SNP locus density, and genome-wide distribution. Reliability and cross-sequencing platform compatibility were verified through dissimilarity coefficients of 0.05 between replicates. To our knowledge, this optimized ddRADseq protocol will allow users to go from the DNA sample to genotyping data in a highly accessible and reproducible way.
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