Dataset Information

Expression quantitative trait Loci for extreme host response to influenza a in pre-collaborative cross mice.

ABSTRACT: Outbreaks of influenza occur on a yearly basis, causing a wide range of symptoms across the human population. Although evidence exists that the host response to influenza infection is influenced by genetic differences in the host, this has not been studied in a system with genetic diversity mirroring that of the human population. Here we used mice from 44 influenza-infected pre-Collaborative Cross lines determined to have extreme phenotypes with regard to the host response to influenza A virus infection. Global transcriptome profiling identified 2671 transcripts that were significantly differentially expressed between mice that showed a severe ("high") and mild ("low") response to infection. Expression quantitative trait loci mapping was performed on those transcripts that were differentially expressed because of differences in host response phenotype to identify putative regulatory regions potentially controlling their expression. Twenty-one significant expression quantitative trait loci were identified, which allowed direct examination of genes associated with regulation of host response to infection. To perform initial validation of our findings, quantitative polymerase chain reaction was performed in the infected founder strains, and we were able to confirm or partially confirm more than 70% of those tested. In addition, we explored putative causal and reactive (downstream) relationships between the significantly regulated genes and others in the high or low response groups using structural equation modeling. By using systems approaches and a genetically diverse population, we were able to develop a novel framework for identifying the underlying biological subnetworks under host genetic control during influenza virus infection.

SUBMITTER: Bottomly D

PROVIDER: S-EPMC3284329 | biostudies-literature | 2012 Feb

REPOSITORIES: biostudies-literature

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Expression quantitative trait Loci for extreme host response to influenza a in pre-collaborative cross mice.

Bottomly Daniel D Ferris Martin T MT Aicher Lauri D LD Rosenzweig Elizabeth E Whitmore Alan A Aylor David L DL Haagmans Bart L BL Gralinski Lisa E LE Bradel-Tretheway Birgit G BG Bryan Janine T JT Threadgill David W DW de Villena Fernando Pardo-Manuel FP Baric Ralph S RS Katze Michael G MG Heise Mark M McWeeney Shannon K SK

G3 (Bethesda, Md.) 20120201 2

Outbreaks of influenza occur on a yearly basis, causing a wide range of symptoms across the human population. Although evidence exists that the host response to influenza infection is influenced by genetic differences in the host, this has not been studied in a system with genetic diversity mirroring that of the human population. Here we used mice from 44 influenza-infected pre-Collaborative Cross lines determined to have extreme phenotypes with regard to the host response to influenza A virus i ...[more]

PMID: 22384400

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Project description:ObjectiveAnimal studies remain essential for understanding mechanisms of epilepsy and identifying new therapeutic targets. However, existing animal models of epilepsy do not reflect the high level of genetic diversity found in the human population. The Collaborative Cross (CC) population is a genetically diverse recombinant inbred panel of mice. The CC offers large genotypic and phenotypic diversity, inbred strains with stable genomes that allow for repeated phenotypic measurements, and genomic tools including whole genome sequence to identify candidate genes and candidate variants.MethodsWe evaluated multiple complex epileptic traits in a sampling of 35 CC inbred strains using the flurothyl-induced seizure and kindling paradigm. We created an F2 population of 297 mice with extreme seizure susceptibility and performed quantitative trait loci (QTL) mapping to identify genomic regions associated with seizure sensitivity. We used quantitative RNA sequencing from CC hippocampal tissue to identify candidate genes and whole genome sequence to identify genetic variants likely affecting gene expression.ResultsWe identified new mouse models with extreme seizure susceptibility, seizure propagation, epileptogenesis, and SUDEP (sudden unexpected death in epilepsy). We performed QTL mapping and identified one known and seven novel loci associated with seizure sensitivity. We combined whole genome sequencing and hippocampal gene expression to pinpoint biologically plausible candidate genes (eg, Gabra2) and variants associated with seizure sensitivity.SignificanceNew mouse models of epilepsy are needed to better understand the complex genetic architecture of seizures and to identify therapeutics. We performed a phenotypic screen utilizing a novel genetic reference population of CC mice. The data we provide enable the identification of protective/risk genes and novel molecular mechanisms linked to complex seizure traits that are currently challenging to study and treat.

Project description:Genetic dissection of the S rat genome has provided strong evidence for the presence of two interacting blood pressure (BP) quantitative trait loci (QTLs), termed QTL1 and QTL2, on rat chromosome 5. However, the identities of the underlying interacting genetic factors remain unknown. Further experiments targeted to identify the interacting genetic factors by the substitution mapping approach alone are difficult because of the interdependency of natural recombinations to occur at the two QTLs. We hypothesized that the interacting genetic factors underlying these two QTLs may interact at the level of gene transcription and thereby represent expression QTLs (eQTLs). To detect these interacting eQTLs, a custom QTL chip containing the annotated genes within QTL1 and QTL2 was developed and used to conduct a transcriptional profiling study of S and two congenic strains that retain either one or both the QTLs. The results uncovered an interaction between two transcription factors, DMRTA2 and NFIA. Further, the âbiological signatureâ elicited by these two transcription factors was differential between the congenic strain that retained LEW alleles at both QTL1 and 2 compared to the congenic strain that retained LEW alleles at QTL1 alone. A network of transcription factors potentially affecting BP could be traced, lending support to our hypothesis. Pairs of Cy5 and Cy3 labeled targets were co-hybridized onto either a custom long oligonucleotide microarray for the interrogation of 231 genes encompassed by QTL1 and QTL2, or a TIGR rat cDNA array consisting of 26,401 probe elements representing 20,465 unique non-QTL genes. A âflip-dyeâ or âbalanced blockâ design was used as the experimental method of choice to account for potential dye-bias labeling effects. Six âbalanced blockâ normalized files are submitted for the long oligonucleotide array interrogating the hearts from S versus S.LEW(5)x6x9 animals, fourteen âflip-dyeâ hybridizations are submitted for the cDNA array interrogating the hearts from S versus S.LEW(5)x6x9 animals, and twelve âflip-dyeâ hybridizations are submitted for the cDNA array interrogating the hearts from S versus S.LEW(5)x6x11 animals. GPR and MEV files cannot be located.

Dataset Information

Expression quantitative trait Loci for extreme host response to influenza a in pre-collaborative cross mice.

Publications

Expression quantitative trait Loci for extreme host response to influenza a in pre-collaborative cross mice.

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