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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
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author Liu, Qi
Xie, Bo
Gao, Yang
Xu, Shuhua
Lu, Yan
author_facet Liu, Qi
Xie, Bo
Gao, Yang
Xu, Shuhua
Lu, Yan
author_sort Liu, Qi
collection PubMed
description 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).
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spelling pubmed-103621602023-07-23 A protocol for applying low-coverage whole-genome sequencing data in structural variation studies Liu, Qi Xie, Bo Gao, Yang Xu, Shuhua Lu, Yan STAR Protoc Protocol 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). Elsevier 2023-07-10 /pmc/articles/PMC10362160/ /pubmed/37432854 http://dx.doi.org/10.1016/j.xpro.2023.102433 Text en © 2023 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Protocol
Liu, Qi
Xie, Bo
Gao, Yang
Xu, Shuhua
Lu, Yan
A protocol for applying low-coverage whole-genome sequencing data in structural variation studies
title A protocol for applying low-coverage whole-genome sequencing data in structural variation studies
title_full A protocol for applying low-coverage whole-genome sequencing data in structural variation studies
title_fullStr A protocol for applying low-coverage whole-genome sequencing data in structural variation studies
title_full_unstemmed A protocol for applying low-coverage whole-genome sequencing data in structural variation studies
title_short A protocol for applying low-coverage whole-genome sequencing data in structural variation studies
title_sort protocol for applying low-coverage whole-genome sequencing data in structural variation studies
topic Protocol
url 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
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