The insulin polymorphism -23Hph increases the risk for type 1 diabetes mellitus in the Romanian population

The insulin -23Hph and IGF2 Apa polymorphisms were genotyped in Romanian patients with T1DM (n = 204), T2DM (n = 215) or obesity (n = 200) and normoponderal healthy subjects (n = 750). The genotypes of both polymorphisms were distributed in concordance with Hardy-Weinberg equilibrium in all groups. The -23Hph AA genotype increased the risk for T1DM (OR: 3.22, 95%CI: 2.09-4.98, p < 0,0001), especially in patients without macroalbuminuria (OR: 4.32, 95%CI: 2.54-7.45, p < 0,0001). No other significant association between the alleles or genotypes of insulin -23Hph and IGF2 Apa and diabetes or obesity was identified

Features generated for computational splice-site prediction correspond to functional elements

<p>Abstract</p> <p>Background</p> <p>Accurate selection of splice sites during the splicing of precursors to messenger RNA requires both relatively well-characterized signals at the splice sites and auxiliary signals in the adjacent exons and introns. We previously described a feature generation algorithm (FGA) that is capable of achieving high classification accuracy on human 3' splice sites. In this paper, we extend the splice-site prediction to 5' splice sites and explore the generated features for biologically meaningful splicing signals.</p> <p>Results</p> <p>We present examples from the observed features that correspond to known signals, both core signals (including the branch site and pyrimidine tract) and auxiliary signals (including GGG triplets and exon splicing enhancers). We present evidence that features identified by FGA include splicing signals not found by other methods.</p> <p>Conclusion</p> <p>Our generated features capture known biological signals in the expected sequence interval flanking splice sites. The method can be easily applied to other species and to similar classification problems, such as tissue-specific regulatory elements, polyadenylation sites, promoters, etc.</p

Genome-Wide Data-Mining of Candidate Human Splice Translational Efficiency Polymorphisms (STEPs) and an Online Database

Variation in pre-mRNA splicing is common and in some cases caused by genetic variants in intronic splicing motifs. Recent studies into the insulin gene (INS) discovered a polymorphism in a 5' non-coding intron that influences the likelihood of intron retention in the final mRNA, extending the 5' untranslated region and maintaining protein quality. Retention was also associated with increased insulin levels, suggesting that such variants--splice translational efficiency polymorphisms (STEPs)--may relate to disease phenotypes through differential protein expression. We set out to explore the prevalence of STEPs in the human genome and validate this new category of protein quantitative trait loci (pQTL) using publicly available data.Gene transcript and variant data were collected and mined for candidate STEPs in motif regions. Sequences from transcripts containing potential STEPs were analysed for evidence of splice site recognition and an effect in expressed sequence tags (ESTs). 16 publicly released genome-wide association data sets of common diseases were searched for association to candidate polymorphisms with HapMap frequency data. Our study found 3324 candidate STEPs lying in motif sequences of 5' non-coding introns and further mining revealed 170 with transcript evidence of intron retention. 21 potential STEPs had EST evidence of intron retention or exon extension, as well as population frequency data for comparison.Results suggest that the insulin STEP was not a unique example and that many STEPs may occur genome-wide with potentially causal effects in complex disease. An online database of STEPs is freely accessible at http://dbstep.genes.org.uk/

Why boys will be boys: two pathways of fetal testicular androgen biosynthesis are needed for male sexual differentiation

Human sexual determination is initiated by a cascade of genes that lead to the development of the fetal gonad. Whereas development of the female external genitalia does not require fetal ovarian hormones, male genital development requires the action of testicular testosterone and its more potent derivative dihydrotestosterone (DHT). The "classic" biosynthetic pathway from cholesterol to testosterone in the testis and the subsequent conversion of testosterone to DHT in genital skin is well established. Recently, an alternative pathway leading to DHT has been described in marsupials, but its potential importance to human development is unclear. AKR1C2 is an enzyme that participates in the alternative but not the classic pathway. Using a candidate gene approach, we identified AKR1C2 mutations with sex-limited recessive inheritance in four 46,XY individuals with disordered sexual development (DSD). Analysis of the inheritance of microsatellite markers excluded other candidate loci. Affected individuals had moderate to severe undervirilization at birth; when recreated by site-directed mutagenesis and expressed in bacteria, the mutant AKR1C2 had diminished but not absent catalytic activities. The 46,XY DSD individuals also carry a mutation causing aberrant splicing in AKR1C4, which encodes an enzyme with similar activity. This suggests a mode of inheritance where the severity of the developmental defect depends on the number of mutations in the two genes. An unrelated 46,XY DSD patient carried AKR1C2 mutations on both alleles, confirming the essential role of AKR1C2 and corroborating the hypothesis that both the classic and alternative pathways of testicular androgen biosynthesis are needed for normal human male sexual differentiation