Innovations in double digest restriction-site associated DNA sequencing (ddRAD-Seq) method for more efficient SNP identification.

Genotyping by sequencing Next generation sequencing Reduced genome representation Restriction enzyme digestion SNPs identification

Journal

Analytical biochemistry
ISSN: 1096-0309
Titre abrégé: Anal Biochem
Pays: United States
ID NLM: 0370535

Informations de publication

Date de publication:
01 02 2023
Historique:
received: 30 08 2022
revised: 23 11 2022
accepted: 28 11 2022
pubmed: 9 12 2022
medline: 27 12 2022
entrez: 8 12 2022
Statut: ppublish

Résumé

We present an improved ddRAD-Seq protocol for identifying single nucleotide polymorphisms (SNPs). It utilizes selected restriction enzyme digestion fragments, quick acting ligases that are neutral with the restriction enzyme buffer eliminating buffer exchange steps, and adapters designed to be compatible with Illumina index primers. Library amplification and barcoding are completed in one PCR step, and magnetic beads are used to purify the genomic fragments from the ligation and library generation steps. Our protocol increases the efficiency and decreases the time to complete a ddRAD-Seq experiment. To demonstrate its utility, we compared SNPs from our protocol with those from whole genome resequencing data from Gossypium herbaceum and Gossypium arboreum. Principal component analysis demonstrated that the variability of the combined data was explained by the genotype (PC1) and methodology applied (PC2). Phylogenetic analysis showed that the SNPs from our method clustered with SNPs from the resequencing data of the corresponding genotype. Sequence alignments illustrated that for homozygous loci, more than 90% of the SNPs from the resequencing data were discovered by our method. Our analyses suggest that our ddRAD-Seq method is reliable in identifying SNPs suitable for phylogenetic and association genetic studies while reducing cost and time over known methods.

Identifiants

pubmed: 36481242
pii: S0003-2697(22)00461-4
doi: 10.1016/j.ab.2022.115001
pii:
doi:

Types de publication

Journal Article Research Support, U.S. Gov't, Non-P.H.S.

Langues

eng

Sous-ensembles de citation

IM

Pagination

115001

Informations de copyright

Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of competing interest The authors declare no conflict of interest regarding the research, authorship, funding, and publication of this work.

Auteurs

Zenaida V Magbanua (ZV)

Institute for Genomics, Biocomputing and Biotechnology, Mississippi State University, Mississippi State, USA. Electronic address: zenaida@igbb.msstate.edu.

Chuan-Yu Hsu (CY)

Institute for Genomics, Biocomputing and Biotechnology, Mississippi State University, Mississippi State, USA.

Olga Pechanova (O)

Institute for Genomics, Biocomputing and Biotechnology, Mississippi State University, Mississippi State, USA.

Mark Arick (M)

Institute for Genomics, Biocomputing and Biotechnology, Mississippi State University, Mississippi State, USA.

Corrinne E Grover (CE)

Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, USA.

Daniel G Peterson (DG)

Institute for Genomics, Biocomputing and Biotechnology, Mississippi State University, Mississippi State, USA.

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Classifications MeSH