Streamlined computational pipeline for genetic background characterization of genetically engineered mice based on next generation sequencing data

Abstract 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 whe...

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Main Authors: C. Farkas, F. Fuentes-Villalobos, B. Rebolledo-Jaramillo, F. Benavides, A. F. Castro, R. Pincheira
Format: Article
Language:English
Published: BMC 2019-02-01
Series:BMC Genomics
Subjects:
Online Access:http://link.springer.com/article/10.1186/s12864-019-5504-9
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spelling doaj-57e710545db14bdbbc54e23a095400fd2020-11-25T01:21:50ZengBMCBMC Genomics1471-21642019-02-0120112010.1186/s12864-019-5504-9Streamlined computational pipeline for genetic background characterization of genetically engineered mice based on next generation sequencing dataC. Farkas0F. Fuentes-Villalobos1B. Rebolledo-Jaramillo2F. Benavides3A. F. Castro4R. Pincheira5Laboratorio de Transducción de Señales y Cáncer. Departamento de Bioquímica y Biología Molecular. Facultad Cs. Biológicas, Universidad de ConcepciónLaboratorio de Transducción de Señales y Cáncer. Departamento de Bioquímica y Biología Molecular. Facultad Cs. Biológicas, Universidad de ConcepciónFacultad de Medicina Clínica Alemana, Universidad del DesarrolloDepartment of Epigenetics and Molecular Carcinogenesis, M.D. Anderson Cancer CenterLaboratorio de Transducción de Señales y Cáncer. Departamento de Bioquímica y Biología Molecular. Facultad Cs. Biológicas, Universidad de ConcepciónLaboratorio de Transducción de Señales y Cáncer. Departamento de Bioquímica y Biología Molecular. Facultad Cs. Biológicas, Universidad de ConcepciónAbstract 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.http://link.springer.com/article/10.1186/s12864-019-5504-9SequencingCongenic mouseKnockout mouseGenomic variationGenetic interactionsModifier genes
collection DOAJ
language English
format Article
sources DOAJ
author C. Farkas
F. Fuentes-Villalobos
B. Rebolledo-Jaramillo
F. Benavides
A. F. Castro
R. Pincheira
spellingShingle C. Farkas
F. Fuentes-Villalobos
B. Rebolledo-Jaramillo
F. Benavides
A. F. Castro
R. Pincheira
Streamlined computational pipeline for genetic background characterization of genetically engineered mice based on next generation sequencing data
BMC Genomics
Sequencing
Congenic mouse
Knockout mouse
Genomic variation
Genetic interactions
Modifier genes
author_facet C. Farkas
F. Fuentes-Villalobos
B. Rebolledo-Jaramillo
F. Benavides
A. F. Castro
R. Pincheira
author_sort C. Farkas
title 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_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_sort streamlined computational pipeline for genetic background characterization of genetically engineered mice based on next generation sequencing data
publisher BMC
series BMC Genomics
issn 1471-2164
publishDate 2019-02-01
description Abstract 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.
topic Sequencing
Congenic mouse
Knockout mouse
Genomic variation
Genetic interactions
Modifier genes
url http://link.springer.com/article/10.1186/s12864-019-5504-9
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