Modeling sequencing errors by combining Hidden Markov models.

Among the largest resources for biological sequence data is the large amount of expressed sequence tags (ESTs) available in public and proprietary databases. ESTs provide information on transcripts but for technical reasons they often contain sequencing errors. Therefore, when analyzing EST sequences computationally, such errors must be taken into account. Earlier attempts to model error prone coding regions have shown good performance in detecting and predicting these while correcting sequencing errors using codon usage frequencies. In the research presented here, we improve the detection of translation start and stop sites by integrating a more complex mRNA model with codon usage bias based error correction into one hidden Markov model (HMM), thus generalizing this error correction approach to more complex HMMs. We show that our method maintains the performance in detecting coding sequences.

Microsatellites can be misleading: an empirical and simulation study.

It has been long recognized that highly polymorphic genetic markers can lead to underestimation of divergence between populations when migration is low. Microsatellite loci, which are characterized by extremely high mutation rates, are particularly likely to be affected. Here, we report genetic differentiation estimates in a contact zone between two chromosome races of the common shrew (Sorex araneus), based on 10 autosomal microsatellites, a newly developed Y-chromosome microsatellite, and mitochondrial DNA. These results are compared to previous data on proteins and karyotypes. Estimates of genetic differentiation based on F- and R-statistics are much lower for autosomal microsatellites than for all other genetic markers. We show by simulations that this discrepancy stems mainly from the high mutation rate of microsatellite markers for F-statistics and from deviations from a single-step mutation model for R-statistics. The sex-linked genetic markers show that all gene exchange between races is mediated by females. The absence of male-mediated gene flow most likely results from male hybrid sterility.

TRPM1 is mutated in patients with autosomal-recessive complete congenital stationary night blindness.

Night vision requires signaling from rod photoreceptors to adjacent bipolar cells in the retina. Mutations in the genes NYX and GRM6, expressed in ON bipolar cells, lead to a disruption of the ON bipolar cell response. This dysfunction is present in patients with complete X-linked and autosomal-recessive congenital stationary night blindness (CSNB) and can be assessed by standard full-field electroretinography (ERG), showing severely reduced rod b-wave amplitude and slightly altered cone responses. Although many cases of complete CSNB (cCSNB) are caused by mutations in NYX and GRM6, in approximately 60% of the patients the gene defect remains unknown. Animal models of human diseases are a good source for candidate genes, and we noted that a cCSNB phenotype present in homozygous Appaloosa horses is associated with downregulation of TRPM1. TRPM1, belonging to the family of transient receptor potential channels, is expressed in ON bipolar cells and therefore qualifies as an excellent candidate. Indeed, mutation analysis of 38 patients with CSNB identified ten unrelated cCSNB patients with 14 different mutations in this gene. The mutation spectrum comprises missense, splice-site, deletion, and nonsense mutations. We propose that the cCSNB phenotype in these patients is due to the absence of functional TRPM1 in retinal ON bipolar cells.

Evolutionary branching in deme-structured populations.

Adaptive dynamics shows that a continuous trait under frequency dependent selection may first converge to a singular point followed by spontaneous transition from a unimodal trait distribution into a bimodal one, which is called "evolutionary branching". Here, we study evolutionary branching in a deme-structured population by constructing a quantitative genetic model for the trait variance dynamics, which allows us to obtain an analytic condition for evolutionary branching. This is first shown to agree with previous conditions for branching expressed in terms of relatedness between interacting individuals within demes and obtained from mutant-resident systems. We then show this branching condition can be markedly simplified when the evolving trait affect fecundity and/or survival, as opposed to affecting population structure, which would occur in the case of the evolution of dispersal. As an application of our model, we evaluate the threshold migration rate below which evolutionary branching cannot occur in a pairwise interaction game. This agrees very well with the individual-based simulation results.

RNA-based gene duplication: mechanistic and evolutionary insights.

Gene copies that stem from the mRNAs of parental source genes have long been viewed as evolutionary dead-ends with little biological relevance. Here we review a range of recent studies that have unveiled a significant number of functional retroposed gene copies in both mammalian and some non-mammalian genomes. These studies have not only revealed previously unknown mechanisms for the emergence of new genes and their functions but have also provided fascinating general insights into molecular and evolutionary processes that have shaped genomes. For example, analyses of chromosomal gene movement patterns via RNA-based gene duplication have shed fresh light on the evolutionary origin and biology of our sex chromosomes.

Activation of peroxisome proliferator-activated receptors (PPARs) by their ligands and protein kinase A activators.

The nuclear peroxisome proliferator-activated receptors (PPARs) alpha, beta, and gamma activate the transcription of multiple genes involved in lipid metabolism. Several natural and synthetic ligands have been identified for each PPAR isotype but little is known about the phosphorylation state of these receptors. We show here that activators of protein kinase A (PKA) can enhance mouse PPAR activity in the absence and the presence of exogenous ligands in transient transfection experiments. Activation function 1 (AF-1) of PPARs was dispensable for transcriptional enhancement, whereas activation function 2 (AF-2) was required for this effect. We also show that several domains of PPAR can be phosphorylated by PKA in vitro. Moreover, gel retardation experiments suggest that PKA stabilizes binding of the liganded PPAR to DNA. PKA inhibitors decreased not only the kinase-dependent induction of PPARs but also their ligand-dependent induction, suggesting an interaction between both pathways that leads to maximal transcriptional induction by PPARs. Moreover, comparing PPAR alpha knockout (KO) with PPAR alpha WT mice, we show that the expression of the acyl CoA oxidase (ACO) gene can be regulated by PKA-activated PPAR alpha in liver. These data demonstrate that the PKA pathway is an important modulator of PPAR activity, and we propose a model associating this pathway in the control of fatty acid beta-oxidation under conditions of fasting, stress, and exercise.

Male mutation bias and possible long-term effects of human activities.

The ability of a population to adapt to changing environments depends critically on the amount and kind of genetic variability it possesses. Mutations are an important source of new genetic variability and may lead to new adaptations, especially if the population size is large. Mutation rates are extremely variable between and within species, and males usually have higher mutation rates as a result of elevated rates of male germ cell division. This male bias affects the overall mutation rate. We examined the factors that influence male mutation bias, and focused on the effects of classical life-history parameters, such as the average age at reproduction and elevated rates of sperm production in response to sexual selection and sperm competition. We argue that human-induced changes in age at reproduction or in sexual selection will affect male mutation biases and hence overall mutation rates. Depending on the effective population size, these changes are likely to influence the long-term persistence of a population.

Phenotypic consequences of copy number variation: insights from Smith-Magenis and Potocki-Lupski syndrome mouse models.

A large fraction of genome variation between individuals is comprised of submicroscopic copy number variation of genomic DNA segments. We assessed the relative contribution of structural changes and gene dosage alterations on phenotypic outcomes with mouse models of Smith-Magenis and Potocki-Lupski syndromes. We phenotyped mice with 1n (Deletion/+), 2n (+/+), 3n (Duplication/+), and balanced 2n compound heterozygous (Deletion/Duplication) copies of the same region. Parallel to the observations made in humans, such variation in gene copy number was sufficient to generate phenotypic consequences: in a number of cases diametrically opposing phenotypes were associated with gain versus loss of gene content. Surprisingly, some neurobehavioral traits were not rescued by restoration of the normal gene copy number. Transcriptome profiling showed that a highly significant propensity of transcriptional changes map to the engineered interval in the five assessed tissues. A statistically significant overrepresentation of the genes mapping to the entire length of the engineered chromosome was also found in the top-ranked differentially expressed genes in the mice containing rearranged chromosomes, regardless of the nature of the rearrangement, an observation robust across different cell lineages of the central nervous system. Our data indicate that a structural change at a given position of the human genome may affect not only locus and adjacent gene expression but also "genome regulation." Furthermore, structural change can cause the same perturbation in particular pathways regardless of gene dosage. Thus, the presence of a genomic structural change, as well as gene dosage imbalance, contributes to the ultimate phenotype.

Genetic dissection of sodium and potassium transport along the aldosterone-sensitive distal nephron: Importance in the control of blood pressure and hypertension.

In this review, we discuss genetic evidence supporting Guyton's hypothesis stating that blood pressure control is critically depending on fluid handling by the kidney. The review is focused on the genetic dissection of sodium and potassium transport in the distal nephron and the collecting duct that are the most important sites for the control of sodium and potassium balance by aldosterone and angiotensin II. Thanks to the study of Mendelian forms of hypertension and their corresponding transgenic mouse models, three main classes of diuretic receptors (furosemide, thiazide, amiloride) and the main components of the aldosterone- and angiotensin-dependent signaling pathways were molecularly identified over the past 20years. This will allow to design rational strategies for the treatment of hypertension and for the development of the next generation of diuretics.

Broad-scale adaptive genetic variation in alpine plants is driven by temperature and precipitation.

Identifying adaptive genetic variation is a challenging task, in particular in non-model species for which genomic information is still limited or absent. Here, we studied distribution patterns of amplified fragment length polymorphisms (AFLPs) in response to environmental variation, in 13 alpine plant species consistently sampled across the entire European Alps. Multiple linear regressions were performed between AFLP allele frequencies per site as dependent variables and two categories of independent variables, namely Moran's eigenvector map MEM variables (to account for spatial and unaccounted environmental variation, and historical demographic processes) and environmental variables. These associations allowed the identification of 153 loci of ecological relevance. Univariate regressions between allele frequency and each environmental factor further showed that loci of ecological relevance were mainly correlated with MEM variables. We found that precipitation and temperature were the best environmental predictors, whereas topographic factors were rarely involved in environmental associations. Climatic factors, subject to rapid variation as a result of the current global warming, are known to strongly influence the fate of alpine plants. Our study shows, for the first time for a large number of species, that the same environmental variables are drivers of plant adaptation at the scale of a whole biome, here the European Alps.