MAMOT: hidden Markov modeling tool.

Hidden Markov models (HMMs) are probabilistic models that are well adapted to many tasks in bioinformatics, for example, for predicting the occurrence of specific motifs in biological sequences. MAMOT is a command-line program for Unix-like operating systems, including MacOS X, that we developed to allow scientists to apply HMMs more easily in their research. One can define the architecture and initial parameters of the model in a text file and then use MAMOT for parameter optimization on example data, decoding (like predicting motif occurrence in sequences) and the production of stochastic sequences generated according to the probabilistic model. Two examples for which models are provided are coiled-coil domains in protein sequences and protein binding sites in DNA. A wealth of useful features include the use of pseudocounts, state tying and fixing of selected parameters in learning, and the inclusion of prior probabilities in decoding. AVAILABILITY: MAMOT is implemented in C++, and is distributed under the GNU General Public Licence (GPL). The software, documentation, and example model files can be found at http://bcf.isb-sib.ch/mamot

Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study.

The identification of genetically homogeneous groups of individuals is a long standing issue in population genetics. A recent Bayesian algorithm implemented in the software STRUCTURE allows the identification of such groups. However, the ability of this algorithm to detect the true number of clusters (K) in a sample of individuals when patterns of dispersal among populations are not homogeneous has not been tested. The goal of this study is to carry out such tests, using various dispersal scenarios from data generated with an individual-based model. We found that in most cases the estimated 'log probability of data' does not provide a correct estimation of the number of clusters, K. However, using an ad hoc statistic DeltaK based on the rate of change in the log probability of data between successive K values, we found that STRUCTURE accurately detects the uppermost hierarchical level of structure for the scenarios we tested. As might be expected, the results are sensitive to the type of genetic marker used (AFLP vs. microsatellite), the number of loci scored, the number of populations sampled, and the number of individuals typed in each sample.

Task-dependent influence of genetic architecture and mating frequency on division of labour in social insect societies.

Division of labour is one of the most prominent features of social insects. The efficient allocation of individuals to different tasks requires dynamic adjustment in response to environmental perturbations. Theoretical models suggest that the colony-level flexibility in responding to external changes and internal perturbation may depend on the within-colony genetic diversity, which is affected by the number of breeding individuals. However, these models have not considered the genetic architecture underlying the propensity of workers to perform the various tasks. Here, we investigated how both within-colony genetic variability (stemming from variation in the number of matings by queens) and the number of genes influencing the stimulus (threshold) for a given task at which workers begin to perform that task jointly influence task allocation efficiency. We used a numerical agent-based model to investigate the situation where workers had to perform either a regulatory task or a foraging task. One hundred generations of artificial selection in populations consisting of 500 colonies revealed that an increased number of matings always improved colony performance, whatever the number of loci encoding the thresholds of the regulatory and foraging tasks. However, the beneficial effect of additional matings was particularly important when the genetic architecture of queens comprised one or a few genes for the foraging task's threshold. By contrast, a higher number of genes encoding the foraging task reduced colony performance with the detrimental effect being stronger when queens had mated with several males. Finally, the number of genes encoding the threshold for the regulatory task only had a minor effect on colony performance. Overall, our numerical experiments support the importance of mating frequency on efficiency of division of labour and also reveal complex interactions between the number of matings and genetic architecture.

The fine-scale architecture of structural variants in 17 mouse genomes.

BACKGROUND: Accurate catalogs of structural variants (SVs) in mammalian genomes are necessary to elucidate the potential mechanisms that drive SV formation and to assess their functional impact. Next generation sequencing methods for SV detection are an advance on array-based methods, but are almost exclusively limited to four basic types: deletions, insertions, inversions and copy number gains. RESULTS: By visual inspection of 100 Mbp of genome to which next generation sequence data from 17 inbred mouse strains had been aligned, we identify and interpret 21 paired-end mapping patterns, which we validate by PCR. These paired-end mapping patterns reveal a greater diversity and complexity in SVs than previously recognized. In addition, Sanger-based sequence analysis of 4,176 breakpoints at 261 SV sites reveal additional complexity at approximately a quarter of structural variants analyzed. We find micro-deletions and micro-insertions at SV breakpoints, ranging from 1 to 107 bp, and SNPs that extend breakpoint micro-homology and may catalyze SV formation. CONCLUSIONS: An integrative approach using experimental analyses to train computational SV calling is essential for the accurate resolution of the architecture of SVs. We find considerable complexity in SV formation; about a quarter of SVs in the mouse are composed of a complex mixture of deletion, insertion, inversion and copy number gain. Computational methods can be adapted to identify most paired-end mapping patterns.

The heterotetrameric architecture of the epithelial sodium channel (ENaC).

The epithelial sodium channel (ENaC) is a key element for the maintenance of sodium balance and the regulation of blood pressure. Three homologous ENaC subunits (alpha, beta and gamma) assemble to form a highly Na+-selective channel. However, the subunit stoichiometry of ENaC has not yet been solved. Quantitative analysis of cell surface expression of ENaC alpha, beta and gamma subunits shows that they assemble according to a fixed stoichiometry, with alpha ENaC as the most abundant subunit. Functional assays based on differential sensitivities to channel blockers elicited by mutations tagging each alpha, beta and gamma subunit are consistent with a four subunit stoichiometry composed of two alpha, one beta and one gamma. Expression of concatameric cDNA constructs made of different combinations of ENaC subunits confirmed the four subunit channel stoichiometry and showed that the arrangement of the subunits around the channel pore consists of two alpha subunits separated by beta and gamma subunits.

Yingti/ruanti (hardware/software). La création d'un hall culturel hakka à Taiwan

Dans le cadre de la politique multiculturelle de protection des minorités menée par le gouvernement taïwanais, le Comité ministériel aux affaires hakka (keweihui) a planifié dix-huit « halls culturels hakkas » dans chaque comté et municipalité. L'article retrace le processus de création d'un de ces halls, dans le nord de l'île de Taiwan, au cours de la décennie 2000. L'aménagement du hall procède à l'incorporation d'artistes locaux dans une tradition nationale hakka réinventée. Il est montré comment sa genèse s'est produite à l'intersection d'une politique impulsée par « le haut » et d'un projet émanant d'acteurs locaux. L'article met en évidence comment les catégories yingti (hardware) et ruanti (software) président à sa fabrication et impliquent une opposition et une complémentarité entre « contenant » et « contenu », entre « État » et « société », qui agissent à toutes les étapes de sa mise en oeuvre.

The shared allelic architecture of adiponectin levels and coronary artery disease.

OBJECTIVE: A large body of epidemiologic data strongly suggests an association between excess adiposity and coronary artery disease (CAD). Low adiponectin levels, a hormone secreted only from adipocytes, have been associated with an increased risk of CAD in observational studies. However, these associations cannot clarify whether this relationship is causal or due to a shared set of causal factors or even confounding. Genome-wide association studies have identified common variants that influence adiponectin levels, providing valuable tools to examine the genetic relationship between adiponectin and CAD. METHODS: Using 145 genome wide significant SNPs for adiponectin from the ADIPOGen consortium (n = 49,891), we tested whether adiponectin-decreasing alleles influenced risk of CAD in the CARDIoGRAM consortium (n = 85,274). RESULTS: In single-SNP analysis, 5 variants among 145 SNPs were associated with increased risk of CAD after correcting for multiple testing (P < 4.4 × 10(-4)). Using a multi-SNP genotypic risk score to test whether adiponectin levels and CAD have a shared genetic etiology, we found that adiponectin-decreasing alleles increased risk of CAD (P = 5.4 × 10(-7)). CONCLUSION: These findings demonstrate that adiponectin levels and CAD have a shared allelic architecture and provide rationale to undertake a Mendelian randomization studies to understand if this relationship is causal.

Defining the role of common variation in the genomic and biological architecture of adult human height.

Using genome-wide data from 253,288 individuals, we identified 697 variants at genome-wide significance that together explained one-fifth of the heritability for adult height. By testing different numbers of variants in independent studies, we show that the most strongly associated ∼2,000, ∼3,700 and ∼9,500 SNPs explained ∼21%, ∼24% and ∼29% of phenotypic variance. Furthermore, all common variants together captured 60% of heritability. The 697 variants clustered in 423 loci were enriched for genes, pathways and tissue types known to be involved in growth and together implicated genes and pathways not highlighted in earlier efforts, such as signaling by fibroblast growth factors, WNT/β-catenin and chondroitin sulfate-related genes. We identified several genes and pathways not previously connected with human skeletal growth, including mTOR, osteoglycin and binding of hyaluronic acid. Our results indicate a genetic architecture for human height that is characterized by a very large but finite number (thousands) of causal variants.

Tumor architecture exerts no bias on nuclear grading in breast cancer diagnosis.

We recently reported that nuclear grading in prostate cancer is subject to a strong confirmation bias induced by the tumor architecture. We now wondered whether a similar bias governs nuclear grading in breast carcinoma. An unannounced test was performed at a pathology conference. Pathologists were asked to grade nuclei in a PowerPoint presentation. Circular high power fields of 27 invasive ductal carcinomas were shown, superimposed over low power background images of either tubule-rich or tubule-poor carcinomas. We found (a) that diagnostic reproducibility of nuclear grades was poor to moderate (weighed kappa values between 0.07 and 0.54, 27 cases, 44 graders), but (b) that nuclear grades were not affected by the tumor architecture. We speculate that the categorized grading in breast cancer, separating tubule formation, nuclear pleomorphism, and mitotic figure counts in a combined three tier score, prevents the bias that architecture exerts on nuclear grades in less well-controlled situations.