Evidence that RNA editing modulates splice site selection in the 5-HT2C receptor gene

Adenosine to inosine editing of mRNA from the human 5-HT2C receptor gene (HTR2C) occurs at five exonic positions (A–E) in a stable stem–loop that includes the normal 5′ splice site of intron 5 and is flanked by two alternative splice sites. Using in vitro editing, we identified a novel editing site (F) located in the intronic part of the stem–loop and demonstrated editing at this site in human brain. We have shown that in cell culture, base substitutions to mimic editing at different combinations of the six sites profoundly affect relative splicing at the normal and the upstream alternative splice site, but splicing at the downstream alternative splice site was consistently rare. Editing combinations in different splice variants from human brain were determined and are consistent with the effects of editing on splicing observed in cell culture. As RNA editing usually occurs close to exon/intron boundaries, this is likely to be a general phenomenon and suggests an important novel role for RNA editing.     

The role of mitochondrial DNA in the development of type 2 diabetes caused by fetal malnutrition

Epidemiological studies have revealed strong and reproducible links between indices of poor fetal growth and susceptibility to the development of glucose intolerance and insulin resistance syndrome in adult life. To explain these associations, the thrifty phenotype hypothesis has been proposed. Mitochondrial DNA abnormalities have been known to cause insulin deficiency, insulin resistance and diabetes mellitus. In this review, we propose that mitochondrial dysfunction is a link between malnutrition during early life and disease in adult life. The potential mechanism for mitochondrial dysfunction will be focused on availability of the taurine and nucleotides, and imprinting on the genes.     

Application of logistic regression to case-control association studies involving two causative loci

Models in which two susceptibility loci jointly influence the risk of developing disease can be explored using logistic regression analysis. Comparison of likelihoods of models incorporating different sets of disease model parameters allows inferences to be drawn regarding the nature of the joint effect of the loci. We have simulated case-control samples generated assuming different two-locus models and then analysed them using logistic regression. We show that this method is practicable and that, for the models we have used, it can be expected to allow useful inferences to be drawn from sample sizes consisting of hundreds of subjects. Interactions between loci can be explored, but interactive effects do not exactly correspond with classical definitions of epistasis. We have particularly examined the issue of the extent to which it is helpful to utilise information from a previously identified locus when investigating a second, unknown locus. We show that for some models conditional analysis can have substantially greater power while for others unconditional analysis can be more powerful. Hence we conclude that in general both conditional and unconditional analyses should be performed when searching for additional loci.     

The future of association studies: gene-based analysis and replication

Historically, association tests were limited to single variants, so that the allele was considered the basic unit for association testing. As marker density increases and indirect approaches are used to assess association through linkage disequilibrium, association is now frequently considered at the haplotypic level. We suggest that there are difficulties in replicating association findings at the single-nucleotide-polymorphism (SNP) or the haplotype level, and we propose a shift toward a gene-based approach in which all common variation within a candidate gene is considered jointly. Inconsistencies arising from population differences are more readily resolved by use of a gene-based approach rather than either a SNP-based or a haplotype-based approach. A gene-based approach captures all of the potential risk-conferring variations; thus, negative findings are subject only to the issue of power. In addition, chance findings due to multiple testing can be readily accounted for by use of a genewide-significance level. Meta-analysis procedures can be formalized for gene-based methods through the combination of P values. It is only a matter of time before all variation within genes is mapped, at which point the gene-based approach will become the natural end point for association analysis and will inform our search for functional variants relevant to disease etiology.     

GADD34 protein levels increase after transient ischemia in the cortex but not in the CA1 subfield: implications for post-ischemic recovery of protein synthesis in ischemia-resistant cells

Transient cerebral ischemia is a pathological process whereby an irreversible suppression of protein synthesis is believed to contribute to the extent of cell death in vulnerable neurons. Endoplasmic reticulum (ER) dysfunction has been identified as being responsible for ischemia-induced shut-down of translation. Recovery from ER dysfunction is facilitated by GADD34, a protein that dephosphorylates eukaryotic initiation factor (eIF)2alpha-P and thus reactivates protein synthesis. We investigated ischemia-induced changes in GADD34 levels in wild-type and Cu2+/Zn2+ SOD (SOD1) over-expressing rats. Transient global cerebral ischemia was induced by common carotid artery occlusion. Tissue samples were taken from the vulnerable hippocampal CA1 subfield and the resistant cerebral cortex of the right and left hemispheres for evaluation of changes in gadd34 mRNA and GADD34 protein levels. In wild-type animals, we found significantly lower GADD34 levels than in SOD1 transgenes but no differences in gadd34 mRNA levels, implying that superoxides regulate gadd34 translation. After ischemia, GADD34 protein levels were significantly increased in the cortex but not in the CA1 subfield, and these changes occurred earlier in SOD1 transgenic than in wild-type animals. The rise in gadd34 mRNA levels did not differ in the cortex and CA1 subfield, implying that gadd34 expression is regulated at the translational level.     

PLINK: a tool set for whole-genome association and population-based linkage analyses

Whole-genome association studies (WGAS) bring new computational, as well as analytic, challenges to researchers. Many existing genetic-analysis tools are not designed to handle such large data sets in a convenient manner and do not necessarily exploit the new opportunities that whole-genome data bring. To address these issues, we developed PLINK, an open-source C/C++ WGAS tool set. With PLINK, large data sets comprising hundreds of thousands of markers genotyped for thousands of individuals can be rapidly manipulated and analyzed in their entirety. As well as providing tools to make the basic analytic steps computationally efficient, PLINK also supports some novel approaches to whole-genome data that take advantage of whole-genome coverage. We introduce PLINK and describe the five main domains of function: data management, summary statistics, population stratification, association analysis, and identity-by-descent estimation. In particular, we focus on the estimation and use of identity-by-state and identity-by-descent information in the context of population-based whole-genome studies. This information can be used to detect and correct for population stratification and to identify extended chromosomal segments that are shared identical by descent between very distantly related individuals. Analysis of the patterns of segmental sharing has the potential to map disease loci that contain multiple rare variants in a population-based linkage analysis.