The HXB/BXH family of recombinant inbred rat strains is a unique genetic resource that has been extensively phenotyped over 25 years, resulting in a vast dataset of quantitative molecular and physiological phenotypes. We built a pangenome graph from 10x Genomics Linked-Read data for 31 recombinant inbred rats to study genetic variation and association mapping. The pangenome includes 0.2Gb of sequence that is not present the reference mRatBN7.2, confirming the capture of substantial additional variation. We validated variants in challenging regions, including complex structural variants resolving into multiple haplotypes. Phenome-wide association analysis of validated SNPs uncovered variants associated with glucose/insulin levels and hippocampal gene expression. We propose an interaction between Pirl1l1, chromogranin expression, TNF-α levels, and insulin regulation. This study demonstrates the utility of linked-read pangenomes for comprehensive variant detection and mapping phenotypic diversity in a widely used rat genetic reference panel.

• Keywords
• Association analysis, Genomics, Model organism, Quantitative genetics,
• Publication type
• Journal Article MeSH

The HXB/BXH family of recombinant inbred rat strains is a unique genetic resource that has been extensively phenotyped over 25 years, resulting in a vast dataset of quantitative molecular and physiological phenotypes. We built a pangenome graph from 10x Genomics Linked-Read data for 31 recombinant inbred rats to study genetic variation and association mapping. The pangenome includes 0.2Gb of sequence that is not present the reference mRatBN7.2, confirming the capture of substantial additional variation. We validated variants in challenging regions, including complex structural variants resolving into multiple haplotypes. Phenome-wide association analysis of validated SNPs uncovered variants associated with glucose/insulin levels and hippocampal gene expression. We propose an interaction between Pirl1l1, chromogranin expression, TNF-α levels, and insulin regulation. This study demonstrates the utility of linked-read pangenomes for comprehensive variant detection and mapping phenotypic diversity in a widely used rat genetic reference panel.

• Keywords
• Chromogranin expression, Genotype-Phenotype, Glucose, Insulin, Pangenome, Rat, Recombinant Inbred,
• Publication type
• Journal Article MeSH
• Preprint MeSH

BACKGROUND: A statistical pipeline was developed and used for determining candidate genes and candidate gene coexpression networks involved in 2 alcohol (i.e., ethanol [EtOH]) metabolism phenotypes, namely alcohol clearance and acetate area under the curve in a recombinant inbred (RI) (HXB/BXH) rat panel. The approach was also used to provide an indication of how EtOH metabolism can impact the normal function of the identified networks. METHODS: RNA was extracted from alcohol-naïve liver tissue of 30 strains of HXB/BXH RI rats. The reconstructed transcripts were quantitated, and data were used to construct gene coexpression modules and networks. A separate group of rats, comprising the same 30 strains, were injected with EtOH (2 g/kg) for measurement of blood EtOH and acetate levels. These data were used for quantitative trait loci (QTL) analysis of the rate of EtOH disappearance and circulating acetate levels. The analysis pipeline required calculation of the module eigengene values, the correction of these values with EtOH metabolism rates and acetate levels across the rat strains, and the determination of the eigengene QTLs. For a module to be considered a candidate for determining phenotype, the module eigengene values had to have significant correlation with the strain phenotypic values and the module eigengene QTLs had to overlap the phenotypic QTLs. RESULTS: Of the 658 transcript coexpression modules generated from liver RNA sequencing data, a single module satisfied all criteria for being a candidate for determining the alcohol clearance trait. This module contained 2 alcohol dehydrogenase genes, including the gene whose product was previously shown to be responsible for the majority of alcohol elimination in the rat. This module was also the only module identified as a candidate for influencing circulating acetate levels. This module was also linked to the process of generation and utilization of retinoic acid as related to the autonomous immune response. CONCLUSIONS: We propose that our analytical pipeline can successfully identify genetic regions and transcripts which predispose a particular phenotype and our analysis provides functional context for coexpression module components.

• Keywords
• Alcohol Metabolism, HXB/BXH Recombinant Inbred Rat Panel, Liver, Quantitative Trait Locus Mapping, RNA Sequencing, Weighted Gene Coexpression Network Analysis,
• MeSH
• Ethanol administration & dosage   metabolism   MeSH
• Liver drug effects   metabolism   MeSH
• Rats MeSH
• Metabolic Clearance Rate drug effects   physiology   MeSH
• Multifactorial Inheritance drug effects   physiology   MeSH
• Alcohol Drinking genetics   metabolism   MeSH
• Rats, Inbred BN MeSH
• Rats, Inbred SHR MeSH
• Rats, Transgenic MeSH
• Unsupervised Machine Learning * MeSH
• Systems Biology methods   MeSH
• Animals MeSH
• Check Tag
• Rats MeSH
• Male MeSH
• Animals MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Research Support, N.I.H., Extramural MeSH
• Names of Substances
• Ethanol MeSH

Brown adipose tissue (BAT) has been suggested to play an important role in lipid and glucose metabolism in rodents and possibly also in humans. In the current study, we used genetic and correlation analyses in the BXH/HXB recombinant inbred (RI) strains, derived from Brown Norway (BN) and spontaneously hypertensive rats (SHR), to identify genetic determinants of BAT function. Linkage analyses revealed a quantitative trait locus (QTL) associated with interscapular BAT mass on chromosome 4 and two closely linked QTLs associated with glucose oxidation and glucose incorporation into BAT lipids on chromosome 2. Using weighted gene coexpression network analysis (WGCNA) we identified 1,147 gene coexpression modules in the BAT from BXH/HXB rats and mapped their module eigengene QTLs. Through an unsupervised analysis, we identified modules related to BAT relative mass and function. The Coral4.1 coexpression module is associated with BAT relative mass (includes Cd36 highly connected gene), and the Darkseagreen coexpression module is associated with glucose incorporation into BAT lipids (includes Hiat1, Fmo5, and Sort1 highly connected transcripts). Because multiple statistical criteria were used to identify candidate modules, significance thresholds for individual tests were not adjusted for multiple comparisons across modules. In summary, a systems genetic analysis using genomic and quantitative transcriptomic and physiological information has produced confirmation of several known genetic factors and significant insight into novel genetic components functioning in BAT and possibly contributing to traits characteristic of the metabolic syndrome.

• Keywords
• brown adipose tissue, coexpression modules, quantitative trait locus, recombinant inbred strains, spontaneously hypertensive rat,
• MeSH
• Genetic Predisposition to Disease genetics   MeSH
• Glucose metabolism   MeSH
• Adipose Tissue, Brown metabolism   MeSH
• Rats MeSH
• Quantitative Trait Loci genetics   MeSH
• Metabolic Syndrome genetics   metabolism   MeSH
• Rats, Inbred BN MeSH
• Rats, Inbred SHR MeSH
• Animals MeSH
• Check Tag
• Rats MeSH
• Male MeSH
• Animals MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Research Support, N.I.H., Extramural MeSH
• Names of Substances
• Glucose MeSH

Gene co-expression analysis has proven to be a powerful tool for ascertaining the organization of gene products into networks that are important for organ function. An organ, such as the liver, engages in a multitude of functions important for the survival of humans, rats, and other animals; these liver functions include energy metabolism, metabolism of xenobiotics, immune system function, and hormonal homeostasis. With the availability of organ-specific transcriptomes, we can now examine the role of RNA transcripts (both protein-coding and non-coding) in these functions. A systems genetic approach for identifying and characterizing liver gene networks within a recombinant inbred panel of rats was used to identify genetically regulated transcriptional networks (modules). For these modules, biological consensus was found between functional enrichment analysis and publicly available phenotypic quantitative trait loci (QTL). In particular, the biological function of two liver modules could be linked to immune response. The eigengene QTLs for these co-expression modules were located at genomic regions coincident with highly significant phenotypic QTLs; these phenotypes were related to rheumatoid arthritis, food preference, and basal corticosterone levels in rats. Our analysis illustrates that genetically and biologically driven RNA-based networks, such as the ones identified as part of this research, provide insight into the genetic influences on organ functions. These networks can pinpoint phenotypes that manifest through the interaction of many organs/tissues and can identify unannotated or under-annotated RNA transcripts that play a role in these phenotypes.

• MeSH
• Gene Ontology MeSH
• Immune System metabolism   MeSH
• Liver immunology   metabolism   MeSH
• Lod Score MeSH
• Quantitative Trait Loci MeSH
• Rats, Inbred SHR MeSH
• RNA genetics   metabolism   MeSH
• Sequence Analysis, RNA MeSH
• Transcriptome MeSH
• Linkage Disequilibrium MeSH
• Animals MeSH
• Check Tag
• Male MeSH
• Female MeSH
• Animals MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Research Support, N.I.H., Extramural MeSH
• Names of Substances
• RNA MeSH