Seasonal acclimation in resting metabolism of the skink, Mabuya brevicollis (Reptilia: Scincidae) from southwestern Saudi Arabia

The resting metabolic rate (RMR) of seasonally-acclimated Mabuya brevicollis of various body masses was determined at 20, 25, 30, 35 and 40 °C, using open-flow respirometry. RMR (ml g⁻¹ h⁻¹) decreased with increasing mass at each temperature. RMRs increaProd. Type: FTPsed as temperature increased. The highest and lowest Q₁₀ values were obtained for the temperature ranges 20–25 °C and 30–35 °C for the summer-acclimated lizards. The exponent of mass “b” in the metabolism-body mass relation ranged from 0.41 to 0.61. b values were lower in the autumn and winter-acclimated lizards than in spring and summer-acclimated lizards. Seasonal acclimation effects were evident at all temperatures (20–40 °C) for M. brevicollis. Winter-acclimated skinks had the lowest metabolic rates at different temperatures. The pattern of acclimation exhibited by M. brevicollis may represent a useful adaptation for lizards inhabiting subtropical deserts to promote activity during their active seasons.     

Protein subunit interfaces: a statistical analysis of hot spots in Sm proteins

The distinguishing property of Sm protein associations is very high stability. In order to understand this property, we analyzed the interfaces and compared the properties of Sm protein interfaces with those of a test set, the Binding Interface Database (BID). The comparison revealed that the main differences between the interfaces of Sm proteins and those of the BID set are the content of charged residues, the coordination numbers of the residues, knowledge-based pair potentials, and the conservation scores of hot spots. In Sm proteins, the interfaces have more hydrophobic and fewer charged residues than the surfaces, which is also the case for the BID test set and other proteins. However, in the interfaces, the content of charged residues in Sm proteins (26%) is substantially larger than that in the BID set (22%). Hot spots are residues that make up a small fraction of the interfaces, but they contribute most of the binding energy. These residues are critical to protein–protein interactions. Analyses of knowledge-based pair potentials of hot spot and non-hot spot residues in Sm proteins show that they are significantly different; their mean values are 31.5 and 11.3, respectively. In the BID set, this difference is smaller; in this case, the mean values for hot spot and non-hot spot residues are 20.7 and 12.4, respectively. Hence, the pair potentials of hot spots differ significantly for the Sm and BID data sets. In the interfaces of Sm proteins, the amino acids are tightly packed, and the coordination numbers are larger in Sm proteins than in the BID set for both hot spots and non-hot spots. At the same time, the coordination numbers are higher for hot spots; the average coordination number of the hot spot residues in Sm proteins is 7.7, while it is 6.1 for the non-hot spot residues. The difference in the calculated average conservation score for hot spots and non-hot spots in Sm proteins is significantly larger than it is in the BID set. In Sm proteins, the average conservation score for the hot spots is 7.4. Hot spots are surrounded by residues that are moderately conserved (5.9). The average conservation score for the other interface residues is 5.6. The conservation scores in the BID set do not show a significant distinction between hot and non-hot spots: the mean values for hot and non-hot spot residues are 5.5 and 5.2, respectively. These data show that structurally conserved residues and hot spots are significantly correlated in Sm proteins.     

2q35-rs13387042 variant and the risk of breast cancer: a case–control study

Molecular Biology Reports - Breast Cancer is the most frequent neoplasm diagnosed among women worldwide. Genetic background and lifestyle/environment play a significant role in the disease...     

The ratio of acetate‐to‐glucose oxidation in astrocytes from a single 13C NMR spectrum of cerebral cortex

The ¹³C‐labeling patterns in glutamate and glutamine from brain tissue are quite different after infusion of a mixture of ¹³C‐enriched glucose and acetate. Two processes contribute to this observation, oxidation of acetate by astrocytes but not neurons, and preferential incorporation of α‐ketoglutarate into glutamate in neurons, and incorporation of α‐ketoglutarate into glutamine in astrocytes. The acetate:glucose ratio, introduced previously for analysis of a single ¹³C NMR spectrum, provides a useful index of acetate and glucose oxidation in the brain tissue. However, quantitation of relative substrate oxidation at the cell compartment level has not been reported. A simple mathematical method is presented to quantify the ratio of acetate‐to‐glucose oxidation in astrocytes, based on the standard assumption that neurons do not oxidize acetate. Mice were infused with [1,2‐¹³C]acetate and [1,6‐¹³C]glucose, and proton decoupled ¹³C NMR spectra of cortex extracts were acquired. A fit of those spectra to the model indicated that ¹³C‐labeled acetate and glucose contributed approximately equally to acetyl‐CoA (0.96) in astrocytes. As this method relies on a single ¹³C NMR spectrum, it can be readily applied to multiple physiologic and pathologic conditions.

     

Multiple regression methods show great potential for rare variant association tests

The investigation of associations between rare genetic variants and diseases or phenotypes has two goals. Firstly, the identification of which genes or genomic regions are associated, and secondly, discrimination of associated variants from background noise within each region. Over the last few years, many new methods have been developed which associate genomic regions with phenotypes. However, classical methods for high-dimensional data have received little attention. Here we investigate whether several classical statistical methods for high-dimensional data: ridge regression (RR), principal components regression (PCR), partial least squares regression (PLS), a sparse version of PLS (SPLS), and the LASSO are able to detect associations with rare genetic variants. These approaches have been extensively used in statistics to identify the true associations in data sets containing many predictor variables. Using genetic variants identified in three genes that were Sanger sequenced in 1998 individuals, we simulated continuous phenotypes under several different models, and we show that these feature selection and feature extraction methods can substantially outperform several popular methods for rare variant analysis. Furthermore, these approaches can identify which variants are contributing most to the model fit, and therefore both goals of rare variant analysis can be achieved simultaneously with the use of regression regularization methods. These methods are briefly illustrated with an analysis of adiponectin levels and variants in the ADIPOQ gene.     

Linking woodland key habitat inventory and forest inventory data to prioritize districts needing conservation efforts

Woodland key habitat (WKH) inventories have been conducted in northern European countries, with the aim to create networks of minimally disturbed forest stands for protection. The goal of national forest inventory is to provide information relevant to forest management, such as on forest types, trees species composition, age structure and wood volume. The aim of this study was to link these two inventory databases to identify districts of Latvia most deficient in connectivity and habitat quality, in order to prioritize districts needing conservation effort. As an example, the area of deciduous forest with nemoral tree species (oak, ash, lime, maple and elm) and aspen was chosen. These forests provide habitat for a specific community of epiphytes. Using information in the WKH database, habitat quality in different districts of Latvia was estimated by the frequencies of occurrence of structural elements and selected indicator epiphyte species in nemoral tree species and aspen WKHs. Using digital data in the national forest inventory database, fragmentation metrics were determined for forests that, according to age and tree species composition, could potentially be nemoral tree and aspen WKHs. On a regional level, the lowest habitat quality in WKH occurred in districts that had the least fragmentation of potential WKH forest. In the less fragmented areas, the habitat quality of the existing WKH will likely increase in the future, and could be promoted by management to create structural elements typical of natural forests. The districts with the most fragmented nemoral and aspen forests, contained WKHs with the best habitat quality. A focus on protection should be given to these stands as they are the most likely to support source populations, and there is a need to improve spatial continuity of suitable tree substrate in these areas.     

The empirical power of rare variant association methods: results from sanger sequencing in 1,998 individuals

The role of rare genetic variation in the etiology of complex disease remains unclear. However, the development of next-generation sequencing technologies offers the experimental opportunity to address this question. Several novel statistical methodologies have been recently proposed to assess the contribution of rare variation to complex disease etiology. Nevertheless, no empirical estimates comparing their relative power are available. We therefore assessed the parameters that influence their statistical power in 1,998 individuals Sanger-sequenced at seven genes by modeling different distributions of effect, proportions of causal variants, and direction of the associations (deleterious, protective, or both) in simulated continuous trait and case/control phenotypes. Our results demonstrate that the power of recently proposed statistical methods depend strongly on the underlying hypotheses concerning the relationship of phenotypes with each of these three factors. No method demonstrates consistently acceptable power despite this large sample size, and the performance of each method depends upon the underlying assumption of the relationship between rare variants and complex traits. Sensitivity analyses are therefore recommended to compare the stability of the results arising from different methods, and promising results should be replicated using the same method in an independent sample. These findings provide guidance in the analysis and interpretation of the role of rare base-pair variation in the etiology of complex traits and diseases.     

Novel loci for adiponectin levels and their influence on type 2 diabetes and metabolic traits: a multi-ethnic meta-analysis of 45,891 individuals

Circulating levels of adiponectin, a hormone produced predominantly by adipocytes, are highly heritable and are inversely associated with type 2 diabetes mellitus (T2D) and other metabolic traits. We conducted a meta-analysis of genome-wide association studies in 39,883 individuals of European ancestry to identify genes associated with metabolic disease. We identified 8 novel loci associated with adiponectin levels and confirmed 2 previously reported loci (P = 4.5×10⁻⁸–1.2×10⁻⁴³). Using a novel method to combine data across ethnicities (N = 4,232 African Americans, N = 1,776 Asians, and N = 29,347 Europeans), we identified two additional novel loci. Expression analyses of 436 human adipocyte samples revealed that mRNA levels of 18 genes at candidate regions were associated with adiponectin concentrations after accounting for multiple testing (p<3×10⁻⁴). We next developed a multi-SNP genotypic risk score to test the association of adiponectin decreasing risk alleles on metabolic traits and diseases using consortia-level meta-analytic data. This risk score was associated with increased risk of T2D (p = 4.3×10⁻³, n = 22,044), increased triglycerides (p = 2.6×10⁻¹⁴, n = 93,440), increased waist-to-hip ratio (p = 1.8×10⁻⁵, n = 77,167), increased glucose two hours post oral glucose tolerance testing (p = 4.4×10⁻³, n = 15,234), increased fasting insulin (p = 0.015, n = 48,238), but with lower in HDL-cholesterol concentrations (p = 4.5×10⁻¹³, n = 96,748) and decreased BMI (p = 1.4×10⁻⁴, n = 121,335). These findings identify novel genetic determinants of adiponectin levels, which, taken together, influence risk of T2D and markers of insulin resistance.     

Functional and structural roles of conserved cysteine residues in the carboxyl-terminal domain of the follicle-stimulating hormone receptor in human embryonic kidney 293 cells

The carboxyl-terminal segment of G protein-coupled receptors has one or more conserved cysteine residues that are potential sites for palmitoylation. This posttranslational modification contributes to membrane association, internalization, and membrane targeting of proteins. In contrast to other members of the glycoprotein hormone receptor family (the LH and thyroid-stimulating hormone receptors), it is not known whether the follicle-stimulating hormone receptor (FSHR) is palmitoylated and what are the effects of abolishing its potential palmitoylation sites. In the present study, a functional analysis of the FSHR carboxyl-terminal segment cysteine residues was carried out. We constructed a series of mutant FSHRs by substituting cysteine residues with alanine, serine, or threonine individually and together at positions 629 and 655 (conserved cysteines) and 627 (nonconserved). The results showed that all three cysteine residues are palmitoylated but that only modification at Cys629 is functionally relevant. The lack of palmitoylation does not appear to greatly impair coupling to G(s) but, when absent at position 629, does significantly impair cell surface membrane expression of the partially palmitoylated receptor. All FSHR Cys mutants were capable of binding agonist with the same affinity as the wild-type receptor and internalizing on agonist stimulation. Molecular dynamics simulations at a time scale of approximately 100 nsec revealed that replacement of Cys629 resulted in structures that differed significantly from that of the wild-type receptor. Thus, deviations from wild-type conformation may potentially contribute to the severe impairment in plasma membrane expression and the modest effects on signaling exhibited by the receptors modified in this particular position.     

A Reexamination of Correlations of Amino Acids with Particular Secondary Structures

Using the data from Protein Data Bank the correlations of primary and secondary structures of proteins were analyzed. The correlation values of the amino acids and the eight secondary structure types were calculated, where the position of the amino acid and the position in sequence with the particular secondary structure differ at most 25. The diagrams describing these results indicate that correlations are significant at distances between −9 and 10. The results show that the substituents on Cβ or Cγ atoms of amino acid play major role in their preference for particular secondary structure at the same position in the sequence, while the polarity of amino acid has significant influence on α-helices and strands at some distance in the sequence. The diagrams corresponding to polar amino acids are noticeably asymmetric. The diagrams point out the exchangeability of residues in the proteins; the amino acids with similar diagrams have similar local folding requirements. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.