Regulation of gene expression in the mammalian eye and its relevance to eye disease

Abstract

We used expression quantitative trait locus mapping in the laboratory rat (Rattus norvegicus) to gain a broad perspective of gene regulation in the mammalian eye and to identify genetic variation relevant to human eye disease. Of >31,000 gene probes represented on an Affymetrix expression microarray, 18,976 exhibited sufficient signal for reliable analysis and at least 2-fold variation in expression among 120 F2 rats generated from an SR͞JrHsd ؋ SHRSP intercross. Genome-wide linkage analysis with 399 genetic markers revealed significant linkage with at least one marker for 1,300 probes (␣ ‫؍‬ 0.001; estimated empirical false discovery rate ‫؍‬ 2%). Both contiguous and noncontiguous loci were found to be important in regulating mammalian eye gene expression. We investigated one locus of each type in greater detail and identified putative transcription-altering variations in both cases. We found an inserted cREL binding sequence in the 5 flanking sequence of the Abca4 gene associated with an increased expression level of that gene, and we found a mutation of the gene encoding thyroid hormone receptor ␤2 associated with a decreased expression level of the gene encoding short-wavelength sensitive opsin (Opn1sw). In addition to these positional studies, we performed a pairwise analysis of gene expression to identify genes that are regulated in a coordinated manner and used this approach to validate two previously undescribed genes involved in the human disease Bardet-Biedl syndrome. These data and analytical approaches can be used to facilitate the discovery of additional genes and regulatory elements involved in human eye disease.bioinformatics ͉ expression quantitative trait locus analysis ͉ gene regulation ͉ ophthalmology

Regulation of photoreceptor gene expression by Crx-associated transcription factor network

“…Findings from a study designed to map expression quantitative trait loci (eQTL) in the rat showed that point mutations affecting a conserved serine and another residue in the N-terminal domain of Trβ2 (Ser56Asn and His58Arg) correlated with decreases in S-opsin expression levels of as much as 30% in homozygotes (Scheetz et al, 2006). The affected residues fall within a poorly characterized ligand-independent transactivation domain that can interact with cofactors and is the target of post-translational modification in some nuclear receptors (Germain et al, 2006).…”

“…Trβ2 binds directly to the S-opsin promoter (Figure 3) and has been reported to interact with the basal transcription machinery as well as co-activators and co-repressors to exert complex regulatory effects on target genes (Eckey et al, 2003). The mutations identified by Scheetz et al (2006) might therefore alter one or more of these interactions, making activation of the S-opsin gene less efficient in the presence of the mutated receptor.…”

Model-Free Feature Screening for Ultrahigh Dimensional Data through a Modified Blum-Kiefer-Rosenblatt Correlation

“…In this section we illustrate the performance of MBKR-SIS through an empirical analysis of rat eye microarray expression dataset collected by Scheetz et al (2006). They experimented on 120 twelve-week-old male rats, obtained 31,042 different probe sets, and conducted genome-wide linkage analysis with 399 genetic markers.…”

“…The dataset is available at Gene Expression Omnibus (http://www.ncbi.nlm.nih.gov/geo) with GEO accession number GSE5680. In order to gain insight into genetic variation involved in human eye disease, Scheetz et al (2006) applied expression quantitative trait locus (eQTL) mapping method to 18,976 probes that are considered Chiang et al (2006) found that the gene TRIM32 at probe 1389163 at is a critical gene to the Bardet-Biedl syndrome, which is a genetic human disease concerning about retina. Our goal is to find out which gene expression levels and genetic markers are the most predictive for the expression level of the gene TRIM32.…”

A note on standardization in penalized regressions

“…These results suggest that the standardized methods are more useful than the original methods, especially when variances of predictors are substantially different. Second, we analyze the gene expression data set used by Scheetz et al (2006) to compare the prediction accuracy of the original and standardized estimators in a high-dimensional setting. This data set consists of the gene expression levels of 31,042 probe sets on 120 twelveweek-old male rats.…”