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Hierarchical Analysis of Multi-mapping RNA-Seq Reads Improves the Accuracy of Allele-specific Expression

ABSTRACT: RNA-seq experiment on reciprocal F1 hybrid cross between two diverse mouse strains NOD/ShiLtJ and PWK/PhJ to study the extent of Allele-specific expression (ASE) and the cause of ASE.

ORGANISM(S): Mus musculus

PROVIDER: GSE101815 | GEO | 2017/07/30

SECONDARY ACCESSION(S): PRJNA395581

REPOSITORIES: GEO

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Project description:The collaborative cross (CC) founder strains include five classical inbred laboratory strains (129S1/SvlmJ, A/J, C57BL/6J (B6), NOD/ShiLtJ, and NZO/HILtJ) and three wild-derived strains (CAST/EiJ, PWK/PhJ (PWK) and WSB/EiJ) The strains encompass 89% of the genetic diversity available in Mus musculus and about 10 to 20 times more genetic diversity than found in Homo sapiens. For more than 60 years the B6 strain has been used as the model strain for high ethanol preference/high consumption. However, another one of the CC founder strains, PWK, was identified as a high ethanol preference/high consumption strain. The current study determined how the transcriptomes of the B6 and PWK strains differed from the 6 low preference CC strains across 3 nodes of the brain addiction circuit. RNA-Seq data were collected from the central nucleus of the amygdala, the nucleus accumbens core and the prelimbic cortex. Differential expression (DE) analysis was performed in each of these brain regions for all 28 possible pairwise comparisons of the CC founder strains. Unique genes for each strain were identified by selecting for genes that differed significantly (false discovery rate (FDR) < 0.05) from all other strains in the same direction. B6 was identified as the most distinct inbred laboratory strain, having the highest number of total differently expressed genes (DEGs) and DEGs with high log fold change, and unique genes compared to other CC strains. Less than 50 unique DEGs were identified in common between B6 and PWK within all three brain regions, indicating the strains potentially represent two distinct genetic signatures for risk for high ethanol-preference. 238 DEGs were found to be commonly different between B6, PWK and the average expression of the remaining CC strains within all three regions. The commonly different up-expressed genes were significantly enriched (FDR < 0.001) among genes associated with neuroimmune function. These data compliment the observation that neuroimmune signaling is key to understanding alcohol use disorder and and support use of these 8 strains and the highly heterogeneous mouse populations derived from them to identify alcohol-related brain mechanisms and treatment targets.

Project description:Purpose: To investigate the diet- or strain-dependence of liver transcriptome in eight Diversity Outbred (DO) founder strains [A/J, C57BL/6J (B6), 129S1/SvImJ (129), NOD/ShiLtJ (NOD), NZO/HILtJ (NZO), and three wild-derived strains CAST/EiJ (CAST), PWK/PhJ (PWK), and WSB/EiJ (WSB)] Methods: Total RNA from eight DO founder strains was extracted from snap frozen liver using Maxwell® 16 LEV simplyRNA Tissue Kit (Promega) according to the manufacturer’s protocol. The quality and amount of liver RNA was evaluated using a qubit RNA assay (Invitrogen R11490) and run on an Biorad Bioanalyzer Chip to verify RNA integrity. RNASeq library was prepared by using Illumina TruSeq RNA library construction protocol. RNA samples from 24 mice-fed AIN-93 M diet and 24 mice-fed HFCA diet were submitted to the David H. Murdock Research Institute (DHMRI) for sequencing. The RNA-seq libraries were constructed from 1 µg total RNA after poly-A library preparation. The pooled libraries were sequenced on two lanes of the Illumina HiSeq2500 Instrument. Results: Our liver transcriptomic analysis of eight mouse strains shows that diet and genetic background have a strong effect on the liver transcriptome, which may be related to differences in cardo-metabolic traits. We calculated a gene module consisting of highly correlated transcripts that enriched the biological pathway and provided a searchable database of liver transcript profiles. To further investigate the association of hepatic gene modules with cardio-metabolic traits, Fmo3, a key enzyme in the production of trimethylamine N-oxide (TMAO), and Nox4, which showed strong association with plasma TMAO and liver triglyceride, were identified as the highest expressed in the laboratory-like inbred strains (B6, 129 and NZO) and the lowest expressed transcripts in the CAST strain. We found differences in the production of TMAO and liver triglyceride, which contributes to metabolic syndrome, depending on genetic backgrounds. Conclusions: Our study provide a valuable data resource to the research community and show that liver transcriptomic analysis identified diet- or strain-specific pathways to pathogenesis of metabolic syndrome.

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Hierarchical Analysis of Multi-mapping RNA-Seq Reads Improves the Accuracy of Allele-specific Expression

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