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Genotype-free individual genome reconstruction of Multiparental Population Models by RNA sequencing data

Choi, K.; He, H.; Gatti, D. M.; Philip, V. M.; Raghupathy, N.; Munger, S. C.; Chesler, E. J.; Churchill, G. A.

2020-10-11 bioinformatics
10.1101/2020.10.11.335323 bioRxiv
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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.

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