Streamlined computational pipeline for genetic background characterization of genetically engineered mice based on next generation sequencing data
Streamlined computational pipeline for genetic background characterization of genetically engineered mice based on next generation sequencing data
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DOI：
10.1186/s12864-019-5504-9
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发表时间：
2019-02-12
期刊：
影响因子：
4.4
通讯作者：
Pincheira, R.
中科院分区：
文献类型：
--
作者：
Farkas, C.;Fuentes-Villalobos, F.;Pincheira, R.
背景：基因工程小鼠（GEM）是了解基因功能和疾病模型的重要工具。从历史上看，基因靶向首先在来自129家族近交系的胚胎干细胞（ESC）中进行，当与C57 BL/6小鼠杂交时，导致混合背景或同源小鼠。根据回交的数量和育种策略，来自129个来源的ESC的基因组片段可以渗入C57 BL/6基因组中，建立需要表征的独特遗传组成，以便从使用GEM系的实验中获得有效的结论。目前，SNP基因分型用于检测129来源的ESC基因组渗入C57 BL/6受体的程度;然而，它未能检测到新的/罕见的变异。在这里，我们提出了在Galaxy平台和BASH/R脚本中实现的计算管道，以使用下一代测序数据（NGS）（例如全基因组测序（WGS））来确定GEM的遗传渗入，全外显子组测序（WES）和RNA-Seq.该管道包括揭示与靶基因座相关的变异的策略，全基因组变异可视化以及潜在修饰基因的识别。虽然这些方法适用于同类小鼠，但它们也可用于描述通过遗传漂变固定的变异。作为原理的证明，我们分析了来自五个同源基因敲除（KO）系的公开可用的RNA-Seq数据和我们自己的来自Sall 2 KO系的RNA-Seq数据。此外，我们进行了目标验证使用几种遗传学approaches.Conclusions：我们揭示了129衍生的ESC基因组渗入对基因表达的影响，预测潜在的修饰基因，并确定潜在的表型干扰KO线。我们的研究结果表明，我们的新方法是一种有效的方法来确定遗传渐渗的GEM。
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.