Sex differences in heritability of BMI: a comparative study of results from twin studies in eight countries.

Body mass index (BMI), a simple anthropometric measure, is the most frequently used measure of adiposity and has been instrumental in documenting the worldwide increase in the prevalence of obesity witnessed during the last decades. Although this increase in overweight and obesity is thought to be mainly due to environmental changes, i.e., sedentary lifestyles and high caloric diets, consistent evidence from twin studies demonstrates high heritability and the importance of genetic differences for normal variation in BMI. We analysed self-reported data on BMI from approximately 37,000 complete twin pairs (including opposite sex pairs) aged 20-29 and 30-39 from eight different twin registries participating in the GenomEUtwin project. Quantitative genetic analyses were conducted and sex differences were explored. Variation in BMI was greater for women than for men, and in both sexes was primarily explained by additive genetic variance in all countries. Sex differences in the variance components were consistently significant. Results from analyses of opposite sex pairs also showed evidence of sex-specific genetic effects suggesting there may be some differences between men and women in the genetic factors that influence variation in BMI. These results encourage the continued search for genes of importance to the body composition and the development of obesity. Furthermore, they suggest that strategies to identify predisposing genes may benefit from taking into account potential sex specific effects.     

Heritability of adult body height: a comparative study of twin cohorts in eight countries.

A major component of variation in body height is due to genetic differences, but environmental factors have a substantial contributory effect. In this study we aimed to analyse whether the genetic architecture of body height varies between affluent western societies. We analysed twin data from eight countries comprising 30,111 complete twin pairs by using the univariate genetic model of the Mx statistical package. Body height and zygosity were self-reported in seven populations and measured directly in one population. We found that there was substantial variation in mean body height between countries; body height was least in Italy (177 cm in men and 163 cm in women) and greatest in the Netherlands (184 cm and 171 cm, respectively). In men there was no corresponding variation in heritability of body height, heritability estimates ranging from 0.87 to 0.93 in populations under an additive genes/unique environment (AE) model. Among women the heritability estimates were generally lower than among men with greater variation between countries, ranging from 0.68 to 0.84 when an additive genes/shared environment/unique environment (ACE) model was used. In four populations where an AE model fit equally well or better, heritability ranged from 0.89 to 0.93. This difference between the sexes was mainly due to the effect of the shared environmental component of variance, which appears to be more important among women than among men in our study populations. Our results indicate that, in general, there are only minor differences in the genetic architecture of height between affluent Caucasian populations, especially among men.     

Sensitive fluorescence in situ hybridization signal detection in maize using directly labeled probes produced by high concentration DNA polymerase nick translation

The signal produced by fluorescence in situ hybridization (FISH) often is inconsistent among cells and sensitivity is low. Small DNA targets on the chromatin are difficult to detect. We report here an improved nick translation procedure for Texas red and Alexa Fluor 488 direct labeling of FISH probes. Brighter probes can be obtained by adding excess DNA polymerase I. Using such probes, a 30?kb yeast transgene, and the rp1, rp3 and zein multigene clusters were clearly detected.     

Biodeterioration of Mayan buildings at uxmal and tulum,Mexico

Uxmal and Tulum are two important Mayan sites in the Yucatan peninsula. The buildings are mainly composed of limestone and grey/black discoloration is seen on exposed walls and copious greenish biofilms on inner walls. The principal microorganisms detected on interior walls at both Uxmal and Tulum were cyanobacteria; heterotrophic bacteria and filamentous fungi were also present. A dark‐pigmented mitosporic fungus and Bacillus cereus, both isolated from Uxmal, were shown to be acidogenic in laboratory cultures. Cyanobacteria belonging to rock‐degrading genera Synechocystis and Gloeocapsa were identified at both sites. Surface analysis previously showed that calcium ions were present in the biofilms on buildings at Uxmal and Tulum, suggesting the deposition of biosolubilized stone. Apart from their potential to degrade the substrate, the coccoid cyanobacteria supply organic nutrients for bacteria and fungi, which can produce organic acids, further increasing stone degradation.     

Heritability of eleven metabolic phenotypes in Danish and Chinese twins: A cross‐population comparison

Objectives : A twin‐based comparative study on the genetic influences in metabolic endophenotypes in two populations of substantial ethnic, environmental, and cultural differences was performed. Design and Methods : Data on 11 metabolic phenotypes including anthropometric measures, blood glucose, and lipids levels as well as blood pressure were available from 756 pairs of Danish twins (309 monozygotic and 447 dizygotic twin pairs) with a mean age of 38 years (range: 18‐67) and from 325 pairs of Chinese twins (183 monozygotic and 142 dizygotic twin pairs) with a mean age of 40.5 years (range: 18‐69). Twin modeling was performed on full and nested models with the best fitting models selected. Results : Heritability estimates were compared between Danish and Chinese samples to identify differential genetic influences on each of the phenotypes. Except for hip circumference, all other body measures exhibited similar heritability patterns in the two samples with body weight showing only a slight difference. Higher genetic influences were estimated for fasting blood glucose level in Chinese twins, whereas the Danish twins showed more genetic regulation over most lipids phenotypes. Systolic blood pressure was more genetically controlled in Danish than in Chinese twins. Conclusions : Metabolic endophenotypes show disparity in their genetic determinants in populations under distinct environmental conditions.     

Identification of conformational B-cell Epitopes in an antigen from its primary sequence

Background

One of the major challenges in the field of vaccine design is to predict conformational B-cell epitopes in an antigen. In the past, several methods have been developed for predicting conformational B-cell epitopes in an antigen from its tertiary structure. This is the first attempt in this area to predict conformational B-cell epitope in an antigen from its amino acid sequence.

Results

All Support vector machine (SVM) models were trained and tested on 187 non-redundant protein chains consisting of 2261 antibody interacting residues of B-cell epitopes. Models have been developed using binary profile of pattern (BPP) and physiochemical profile of patterns (PPP) and achieved a maximum MCC of 0.22 and 0.17 respectively. In this study, for the first time SVM model has been developed using composition profile of patterns (CPP) and achieved a maximum MCC of 0.73 with accuracy 86.59%. We compare our CPP based model with existing structure based methods and observed that our sequence based model is as good as structure based methods.

Conclusion

This study demonstrates that prediction of conformational B-cell epitope in an antigen is possible from is primary sequence. This study will be very useful in predicting conformational B-cell epitopes in antigens whose tertiary structures are not available. A web server CBTOPE has been developed for predicting B-cell epitope http://www.imtech.res.in/raghava/cbtope/.     

Support Vector Machine-based method for predicting subcellular localization of mycobacterial proteins using evolutionary information and motifs

Background

Annotations that describe the function of sequences are enormously important to researchers during laboratory investigations and when making computational inferences. However, there has been little investigation into the data quality of sequence function annotations. Here we have developed a new method of estimating the error rate of curated sequence annotations, and applied this to the Gene Ontology (GO) sequence database (GOSeqLite). This method involved artificially adding errors to sequence annotations at known rates, and used regression to model the impact on the precision of annotations based on BLAST matched sequences.

Results

We estimated the error rate of curated GO sequence annotations in the GOSeqLite database (March 2006) at between 28% and 30%. Annotations made without use of sequence similarity based methods (non-ISS) had an estimated error rate of between 13% and 18%. Annotations made with the use of sequence similarity methodology (ISS) had an estimated error rate of 49%.

Conclusion

While the overall error rate is reasonably low, it would be prudent to treat all ISS annotations with caution. Electronic annotators that use ISS annotations as the basis of predictions are likely to have higher false prediction rates, and for this reason designers of these systems should consider avoiding ISS annotations where possible. Electronic annotators that use ISS annotations to make predictions should be viewed sceptically. We recommend that curators thoroughly review ISS annotations before accepting them as valid. Overall, users of curated sequence annotations from the GO database should feel assured that they are using a comparatively high quality source of information.     

Correlation and prediction of gene expression level from amino acid and dipeptide composition of its protein

Background  

A large number of papers have been published on analysis of microarray data with particular emphasis on normalization of data, detection of differentially expressed genes, clustering of genes and regulatory network. On other hand there are only few studies on relation between expression level and composition of nucleotide/protein sequence, using expression data. There is a need to understand why particular genes/proteins express more in particular conditions. In this study, we analyze 3468 genes of Saccharomyces cerevisiae obtained from Holstege et al., (1998) to understand the relationship between expression level and amino acid composition.     

Genetic and environmental influences of surfactant protein D serum levels

The collectin surfactant protein D (SP-D) is an important component of the pulmonary innate immune system, but SP-D is also present on extrapulmonary epithelial surfaces and in serum, where it has been used as a biomarker for pulmonary disease states. In this study, we investigate the mechanisms defining the constitutional serum level of SP-D and determine the magnitude of the genetic contribution to serum SP-D in the adult population. Recent studies have demonstrated that serum SP-D concentrations in children are genetically determined and that a single nucleotide polymorphism (SNP) located in the NH(2)-terminal region (Met11Thr) of the mature protein is significantly associated with the serum SP-D levels. A classic twin study was performed on a twin population including 1,476 self-reported healthy adults. The serum SP-D levels increased with male sex, age, and smoking status. The intraclass correlation was significantly higher for monozygotic (MZ) twin pairs than for dizygotic (DZ) twin pairs. Serum SP-D variance was influenced by nonshared environmental effects and additive genetic effects. Multivariate analysis of MZ and DZ covariance matrixes showed significant genetic correlation among serum SP-D and metabolic variables. The Met11Thr variant explained a significant part of the heritability indicating that serum SP-D variance could be decomposed into non-shared environmental effects (e(2) = 0.19), additive genetic effects (h(2) = 0.42), and the effect of the Met11Thr variations (q(2) = 0.39).