Erik J MacLaren1, James M Sikela. 1. Department of Pharmacology, University of Colorado at Denver and Health Sciences Center, Aurora, CO 80045-0508, USA.
Abstract
BACKGROUND: Inbred Long-Sleep (ILS) and Inbred Short-Sleep (ISS) mice exhibit striking differences in a number of alcohol and drug related behaviors. This study examined the expression levels of more than 39,000 transcripts in these strains in the cerebellum, a major target of ethanol's actions in the CNS, to find differentially expressed (DE) candidate genes for these phenotypes. METHODS: Genes that were differentially expressed between the strains were identified using oligonucleotide arrays as well as complimentary DNA arrays. Sequence alignment was used to locate DE genes in the mouse genome assembly. In silico expression QTL (eQTL) mapping was used to identify chromosomal regions likely to control the transcription level of DE genes, and the EASE program identified overrepresented functional themes. The genomic region immediately upstream of the cyclase associated protein homolog 1 (Cap1) gene was directly sequenced from PCR products. RESULTS: Nearly 300 genes were identified as differentially expressed between the cerebella of ILS and ISS. These genes and their corresponding eQTLs map to genomic regions linked to several phenotypes that differ between the ILS and ISS strains, including ethanol preference and cocaine-induced locomotor activation on Chromosomes 4 and 7 respectively. Eight genes were cross-platform validated, four of which are more highly expressed in ILS cerebellum. Three SNPs, one of which disrupts a predicted Sp1 binding site, were found in the upstream region of Cap1, a strong candidate for influencing ethanol phenotypes. CONCLUSIONS: Many of these DE genes are candidates to influence ethanol and drug regulated phenotypes because they either map to ethanol related QTLs in the genome or are linked to them through eQTL mapping. Genes involved in calcium ion binding and transcriptional regulation are overrepresented and therefore these gene classes may influence ethanol behaviors in mice and humans.
BACKGROUND: Inbred Long-Sleep (ILS) and Inbred Short-Sleep (ISS) mice exhibit striking differences in a number of alcohol and drug related behaviors. This study examined the expression levels of more than 39,000 transcripts in these strains in the cerebellum, a major target of ethanol's actions in the CNS, to find differentially expressed (DE) candidate genes for these phenotypes. METHODS: Genes that were differentially expressed between the strains were identified using oligonucleotide arrays as well as complimentary DNA arrays. Sequence alignment was used to locate DE genes in the mouse genome assembly. In silico expression QTL (eQTL) mapping was used to identify chromosomal regions likely to control the transcription level of DE genes, and the EASE program identified overrepresented functional themes. The genomic region immediately upstream of the cyclase associated protein homolog 1 (Cap1) gene was directly sequenced from PCR products. RESULTS: Nearly 300 genes were identified as differentially expressed between the cerebella of ILS and ISS. These genes and their corresponding eQTLs map to genomic regions linked to several phenotypes that differ between the ILS and ISS strains, including ethanol preference and cocaine-induced locomotor activation on Chromosomes 4 and 7 respectively. Eight genes were cross-platform validated, four of which are more highly expressed in ILS cerebellum. Three SNPs, one of which disrupts a predicted Sp1 binding site, were found in the upstream region of Cap1, a strong candidate for influencing ethanol phenotypes. CONCLUSIONS: Many of these DE genes are candidates to influence ethanol and drug regulated phenotypes because they either map to ethanol related QTLs in the genome or are linked to them through eQTL mapping. Genes involved in calcium ion binding and transcriptional regulation are overrepresented and therefore these gene classes may influence ethanol behaviors in mice and humans.
Authors: Laura Dumas; C Michael Dickens; Nathan Anderson; Jonathan Davis; Beth Bennett; Richard A Radcliffe; James M Sikela Journal: Mamm Genome Date: 2014-02-20 Impact factor: 2.957