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Streamlined computational pipeline for genetic background characterization of genetically engineered mice based on next generation sequencing data
BACKGROUND: Genetically engineered mice (GEM) are essential tools for understanding gene function and disease modeling. Historically, gene targeting was first done in embryonic stem cells (ESCs) derived from the 129 family of inbred strains, leading to a mixed background or congenic mice when crosse...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6373082/ https://www.ncbi.nlm.nih.gov/pubmed/30755158 http://dx.doi.org/10.1186/s12864-019-5504-9 |
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author | Farkas, C. Fuentes-Villalobos, F. Rebolledo-Jaramillo, B. Benavides, F. Castro, A. F. Pincheira, R. |
author_facet | Farkas, C. Fuentes-Villalobos, F. Rebolledo-Jaramillo, B. Benavides, F. Castro, A. F. Pincheira, R. |
author_sort | Farkas, C. |
collection | PubMed |
description | BACKGROUND: Genetically engineered mice (GEM) are essential tools for understanding gene function and disease modeling. Historically, gene targeting was first done in embryonic stem cells (ESCs) derived from the 129 family of inbred strains, leading to a mixed background or congenic mice when crossed with C57BL/6 mice. Depending on the number of backcrosses and breeding strategies, genomic segments from 129-derived ESCs can be introgressed into the C57BL/6 genome, establishing a unique genetic makeup that needs characterization in order to obtain valid conclusions from experiments using GEM lines. Currently, SNP genotyping is used to detect the extent of 129-derived ESC genome introgression into C57BL/6 recipients; however, it fails to detect novel/rare variants. RESULTS: Here, we present a computational pipeline implemented in the Galaxy platform and in BASH/R script to determine genetic introgression of GEM using next generation sequencing data (NGS), such as whole genome sequencing (WGS), whole exome sequencing (WES) and RNA-Seq. The pipeline includes strategies to uncover variants linked to a targeted locus, genome-wide variant visualization, and the identification of potential modifier genes. Although these methods apply to congenic mice, they can also be used to describe variants fixed by genetic drift. As a proof of principle, we analyzed publicly available RNA-Seq data from five congenic knockout (KO) lines and our own RNA-Seq data from the Sall2 KO line. Additionally, we performed target validation using several genetics approaches. CONCLUSIONS: We revealed the impact of the 129-derived ESC genome introgression on gene expression, predicted potential modifier genes, and identified potential phenotypic interference in KO lines. Our results demonstrate that our new approach is an effective method to determine genetic introgression of GEM. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12864-019-5504-9) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6373082 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-63730822019-02-25 Streamlined computational pipeline for genetic background characterization of genetically engineered mice based on next generation sequencing data Farkas, C. Fuentes-Villalobos, F. Rebolledo-Jaramillo, B. Benavides, F. Castro, A. F. Pincheira, R. BMC Genomics Research Article BACKGROUND: Genetically engineered mice (GEM) are essential tools for understanding gene function and disease modeling. Historically, gene targeting was first done in embryonic stem cells (ESCs) derived from the 129 family of inbred strains, leading to a mixed background or congenic mice when crossed with C57BL/6 mice. Depending on the number of backcrosses and breeding strategies, genomic segments from 129-derived ESCs can be introgressed into the C57BL/6 genome, establishing a unique genetic makeup that needs characterization in order to obtain valid conclusions from experiments using GEM lines. Currently, SNP genotyping is used to detect the extent of 129-derived ESC genome introgression into C57BL/6 recipients; however, it fails to detect novel/rare variants. RESULTS: Here, we present a computational pipeline implemented in the Galaxy platform and in BASH/R script to determine genetic introgression of GEM using next generation sequencing data (NGS), such as whole genome sequencing (WGS), whole exome sequencing (WES) and RNA-Seq. The pipeline includes strategies to uncover variants linked to a targeted locus, genome-wide variant visualization, and the identification of potential modifier genes. Although these methods apply to congenic mice, they can also be used to describe variants fixed by genetic drift. As a proof of principle, we analyzed publicly available RNA-Seq data from five congenic knockout (KO) lines and our own RNA-Seq data from the Sall2 KO line. Additionally, we performed target validation using several genetics approaches. CONCLUSIONS: We revealed the impact of the 129-derived ESC genome introgression on gene expression, predicted potential modifier genes, and identified potential phenotypic interference in KO lines. Our results demonstrate that our new approach is an effective method to determine genetic introgression of GEM. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12864-019-5504-9) contains supplementary material, which is available to authorized users. BioMed Central 2019-02-12 /pmc/articles/PMC6373082/ /pubmed/30755158 http://dx.doi.org/10.1186/s12864-019-5504-9 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Farkas, C. Fuentes-Villalobos, F. Rebolledo-Jaramillo, B. Benavides, F. Castro, A. F. Pincheira, R. Streamlined computational pipeline for genetic background characterization of genetically engineered mice based on next generation sequencing data |
title | Streamlined computational pipeline for genetic background characterization of genetically engineered mice based on next generation sequencing data |
title_full | Streamlined computational pipeline for genetic background characterization of genetically engineered mice based on next generation sequencing data |
title_fullStr | Streamlined computational pipeline for genetic background characterization of genetically engineered mice based on next generation sequencing data |
title_full_unstemmed | Streamlined computational pipeline for genetic background characterization of genetically engineered mice based on next generation sequencing data |
title_short | Streamlined computational pipeline for genetic background characterization of genetically engineered mice based on next generation sequencing data |
title_sort | streamlined computational pipeline for genetic background characterization of genetically engineered mice based on next generation sequencing data |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6373082/ https://www.ncbi.nlm.nih.gov/pubmed/30755158 http://dx.doi.org/10.1186/s12864-019-5504-9 |
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