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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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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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). |
format | Online Article Text |
id | pubmed-10362160 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
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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