bioRxivBioinformaticsPreprint
Genotype-free individual genome reconstruction of Multiparental Population Models by RNA sequencing data
Kwangbom ChoiiD, Michael W. LloydiD, Hao HeiD, Daniel M. GattiiD, Vivek M. PhilipiD, Narayanan RaghupathyiD, Mathew Vincent, Sai Lek, Isabela Gerdes GyuriczaiD, Steven C. MungeriD, Alan D. Attie, Mark Keller, Elissa J. ChesleriD, Karl W. BromaniD, Anuj Srivastava, Gary A. ChurchilliD
Abstract
AbstractMulti-parent populations (MPPs), model organisms derived from two or more inbred founder strains, are widely used in biomedical and agricultural research. Gene expression profiling by direct RNA sequencing (RNA-Seq) is commonly applied to MPPs to investigate gene expression regulation and to identify candidate genes. In genetically diverse populations, including MPPs, quantification of gene expression is improved when the RNA-Seq reads are aligned to individualized transcriptomes that incorporate known polymorphic loci. However, the process of constructing and analyzing individual genomes can be computationally demanding and error prone. We propose a new approach, genome reconstruction by RNA-Seq (GBRS), that relies on simultaneous alignment of RNA-Seq reads to founder strain transcriptomes to reconstruct the diploid genome and quantify total and allele-specific gene expression in MPPs. We demonstrate that GBRS performs as well as methods that rely on high-density genotyping arrays. When used in conjunction with other genotyping methods, GBRS provides quality control for detecting sample mix-ups or contamination. GBRS software is freely available at https://github.com/churchill-lab/gbrs.
- organism: mouse
- assay: bulk RNA-seq
- research focus: variant calling
- research focus: differential expression
- approach: statistical model
- Citations
- 15
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