Mapping gene associations in human mitochondria using clinical disease phenotypes

Nuclear genes encode most mitochondrial proteins, and their mutations cause diverse and debilitating clinical disorders. To date, 1,200 of these mitochondrial genes have been recorded, while no standardized catalog exists of the associated clinical phenotypes. Such a catalog would be useful to develop methods to analyze human phenotypic data, to determine genotype-phenotype relations among many genes and diseases, and to support the clinical diagnosis of mitochondrial disorders. Here we establish a clinical phenotype catalog of 174 mitochondrial disease genes and study associations of diseases and genes. Phenotypic features such as clinical signs and symptoms were manually annotated from full-text medical articles and classified based on the hierarchical MeSH ontology. This classification of phenotypic features of each gene allowed for the comparison of diseases between different genes. In turn, we were then able to measure the phenotypic associations of disease genes for which we calculated a quantitative value that is based on their shared phenotypic features. The results showed that genes sharing more similar phenotypes have a stronger tendency for functional interactions, proving the usefulness of phenotype similarity values in disease gene network analysis. We then constructed a functional network of mitochondrial genes and discovered a higher connectivity for non-disease than for disease genes, and a tendency of disease genes to interact with each other. Utilizing these differences, we propose 168 candidate genes that resemble the characteristic interaction patterns of mitochondrial disease genes. Through their network associations, the candidates are further prioritized for the study of specific disorders such as optic neuropathies and Parkinson disease. Most mitochondrial disease phenotypes involve several clinical categories including neurologic, metabolic, and gastrointestinal disorders, which might indicate the effects of gene defects within the mitochondrial system. The accompanying knowledgebase (http://www.mitophenome.org/) supports the study of clinical diseases and associated genes

Measurement of the Bottom-Strange Meson Mixing Phase in the Full CDF Data Set

We report a measurement of the bottom-strange meson mixing phase \beta_s using the time evolution of B0_s -> J/\psi (->\mu+\mu-) \phi (-> K+ K-) decays in which the quark-flavor content of the bottom-strange meson is identified at production. This measurement uses the full data set of proton-antiproton collisions at sqrt(s)= 1.96 TeV collected by the Collider Detector experiment at the Fermilab Tevatron, corresponding to 9.6 fb-1 of integrated luminosity. We report confidence regions in the two-dimensional space of \beta_s and the B0_s decay-width difference \Delta\Gamma_s, and measure \beta_s in [-\pi/2, -1.51] U [-0.06, 0.30] U [1.26, \pi/2] at the 68% confidence level, in agreement with the standard model expectation. Assuming the standard model value of \beta_s, we also determine \Delta\Gamma_s = 0.068 +- 0.026 (stat) +- 0.009 (syst) ps-1 and the mean B0_s lifetime, \tau_s = 1.528 +- 0.019 (stat) +- 0.009 (syst) ps, which are consistent and competitive with determinations by other experiments.Comment: 8 pages, 2 figures, Phys. Rev. Lett 109, 171802 (2012

Cerebral gene expression in response to single or combined gestational exposure to methylmercury and selenium through the maternal diet

Controversy remains regarding the safety of consuming certain types of seafood, particularly during pregnancy. While seafood is rich in vital nutrients, it may also be an important source of environmental contaminants such as methylmercury (MeHg). Selenium (Se) is one essential element present in seafood, hypothesised to ameliorate MeHg toxicity. The aim of the present study was to ascertain the impact of Se on MeHg-induced cerebral gene expression in a mammalian model. Microarray analysis was performed on brain tissue from 15-day-old mice that had been exposed to MeHg throughout development via the maternal diet. The results from the microarray analysis were validated using qPCR. The exposure groups included: MeHg alone (2.6 mg kg−1), Se alone (1.3 mg kg−1), and MeHg + Se. MeHg was presented in a cysteinate form, and Se as Se–methionine, one of the elemental species occurring naturally in seafood. Eight genes responded to Se exposure alone, five were specific to MeHg, and 63 were regulated under the concurrent exposure of MeHg and Se. Significantly enriched functional classes relating to the immune system and cell adhesion were identified, highlighting potential ameliorating mechanisms of Se on MeHg toxicity. Key developmental genes, such as Wnt3 and Sparcl1, were also identified as putative ameliorative targets. This study, utilising environmentally realistic forms of toxicants, delivered through the natural route of exposure, in association with the power of transcriptomics, highlights significant novel information regarding putative pathways of selenium and MeHg interaction in the mammalian brain

Deciduous Trees and the Application of Universal DNA Barcodes: A Case Study on the Circumpolar Fraxinus

The utility of DNA barcoding for identifying representative specimens of the circumpolar tree genus Fraxinus (56 species) was investigated. We examined the genetic variability of several loci suggested in chloroplast DNA barcode protocols such as matK, rpoB, rpoC1 and trnH-psbA in a large worldwide sample of Fraxinus species. The chloroplast intergenic spacer rpl32-trnL was further assessed in search for a potentially variable and useful locus. The results of the study suggest that the proposed cpDNA loci, alone or in combination, cannot fully discriminate among species because of the generally low rates of substitution in the chloroplast genome of Fraxinus. The intergenic spacer trnH-psbA was the best performing locus, but genetic distance-based discrimination was moderately successful and only resulted in the separation of the samples at the subgenus level. Use of the BLAST approach was better than the neighbor-joining tree reconstruction method with pairwise Kimura's two-parameter rates of substitution, but allowed for the correct identification of only less than half of the species sampled. Such rates are substantially lower than the success rate required for a standardised barcoding approach. Consequently, the current cpDNA barcodes are inadequate to fully discriminate Fraxinus species. Given that a low rate of substitution is common among the plastid genomes of trees, the use of the plant cpDNA “universal” barcode may not be suitable for the safe identification of tree species below a generic or sectional level. Supplementary barcoding loci of the nuclear genome and alternative solutions are proposed and discussed

Low-frequency variation in TP53 has large effects on head circumference and intracranial volume.

Cranial growth and development is a complex process which affects the closely related traits of head circumference (HC) and intracranial volume (ICV). The underlying genetic influences shaping these traits during the transition from childhood to adulthood are little understood, but might include both age-specific genetic factors and low-frequency genetic variation. Here, we model the developmental genetic architecture of HC, showing this is genetically stable and correlated with genetic determinants of ICV. Investigating up to 46,000 children and adults of European descent, we identify association with final HC and/or final ICV + HC at 9 novel common and low-frequency loci, illustrating that genetic variation from a wide allele frequency spectrum contributes to cranial growth. The largest effects are reported for low-frequency variants within TP53, with 0.5 cm wider heads in increaser-allele carriers versus non-carriers during mid-childhood, suggesting a previously unrecognized role of TP53 transcripts in human cranial development