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A protocol for applying low-coverage whole-genome sequencing data in structural variation studies

Structural variations (SVs) have a great impact on various biological processes and influence physical traits in many species. Here, we present a protocol for applying the low-coverage next-generation sequencing data of Rhipicephalus microplus to detect high-differentiated SVs accurately. We also ou...

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Detalles Bibliográficos
Autores principales: Liu, Qi, Xie, Bo, Gao, Yang, Xu, Shuhua, Lu, Yan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10362160/
https://www.ncbi.nlm.nih.gov/pubmed/37432854
http://dx.doi.org/10.1016/j.xpro.2023.102433
Descripción
Sumario:Structural variations (SVs) have a great impact on various biological processes and influence physical traits in many species. Here, we present a protocol for applying the low-coverage next-generation sequencing data of Rhipicephalus microplus to detect high-differentiated SVs accurately. We also outline its use to investigate population/species-specific genetic structures, local adaptation, and transcriptional function. We describe steps for constructing variation maps and SV annotation. We then detail population genetic analysis and differential gene expression analysis. For complete details on the usage and execution of this protocol, please refer to Liu et al. (2023).