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

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dc.contributor.authorFarkas, C.
dc.contributor.authorFuentes-Villalobos, F.
dc.contributor.authorRebolledo-Jaramillo, Boris
dc.contributor.authorBenavides, F.
dc.contributor.authorCastro, A.F.
dc.contributor.authorPincheira, R.
dc.date.accessioned2020-01-02T19:16:13Z
dc.date.available2020-01-02T19:16:13Z
dc.date.issued2019
dc.description.abstractBackground: 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.
dc.format.extent20 p.
dc.identifier.citationBMC Genomics, 2019, 20:131
dc.identifier.urihttp://hdl.handle.net/11447/2984
dc.language.isoen
dc.subjectSequencing, Congenic mouse
dc.subjectKnockout mouse
dc.subjectGenomic variation
dc.subjectGenetic interactions
dc.subjectModifier genes
dc.subjectGenetic background
dc.subjectRNA-Seq variant calling
dc.subjectqPCR validation
dc.subjectAng
dc.subjectCdkn1a
dc.subjectSall2
dc.titleStreamlined computational pipeline for genetic background characterization of genetically engineered mice based on next generation sequencing data
dc.typeArticle

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