Genetics of Cardiovascular Disease: A Candidate Gene Study of USF1

Cardiovascular diseases (CVD) are major contributors to morbidity and mortality worldwide. Several interacting environmental, biochemical, and genetic risk factors can increase disease susceptibility. While some of the genes involved in the etiology of CVD are known, many are yet to be discovered. During the last few decades, scientists have searched for these genes with genome-wide linkage and association methods, and with more targeted candidate gene studies. This thesis investigates variation within the upstream transcription factor 1 (USF1) gene locus in relation to CVD risk factors, atherosclerosis, and incidence and prevalence of CVD. This candidate gene was first identified in Finnish families ascertained for familial combined hyperlipidemia, a common dyslipidemia predisposing to coronary heart disease. The gene is a ubiquitously expressed transcription factor regulating expression of several genes from lipid and glucose metabolism, inflammation, and endothelial function. First, we examined association between USF1 variants and several CVD risk factors, such as lipid phenotypes, body composition measures, and metabolic syndrome, in two prospective population cohorts. Our data suggested that USF1 contributes to these CVD risk factors at the population level. Notably, the associations with quantitative measurements were mostly detected among study subjects with CVD or metabolic syndrome, suggesting complex interactions between USF1 effects and the pathophysiological state of an individual. Second, we investigated how variation at the USF1 locus contributes to atherosclerotic lesions of the coronary arteries and abdominal aorta. For this, we used two study samples of middle-aged men with detailed measurements of atherosclerosis obtained in autopsy. USF1 variation significantly associated with areas of several types of lesions, especially with calcification of the arteries. Next, we tested what effect the USF1 risk variants have on sudden cardiac death and incidence of CVD. The atherosclerosis-associated risk variant increased the risk of sudden cardiac death of the same study subjects. Furthermore, USF1 alleles associated with incidence of CVD in the Finnish population follow-up cohorts. These associations were especially prominent among women, suggesting a sex specific effect, which has also been detected in subsequent studies. Finally, as some of the low-yield DNA samples of the Finnish follow-up study cohort needed to be whole-genome amplified (WGA) prior to genotyping, we evaluated whether the produced WGA genotypes were of good quality. Although the samples giving genotype discrepancies could not be detected before genotyping with standard laboratory quality control methods, our results suggested that enhanced quality control at the time of the genotyping could identify such samples. In addition, combining two WGA reactions into one pooled DNA sample for genotyping markedly reduced the number of discrepancies and samples showing them. In conclusion, USF1 seems to have a role in the etiology of CVD. Additional studies are warranted to identify functional variants and to study interactions between USF1 and other genetic or environmental factors. This USF1 study, and other studies with low DNA yield of some samples, can benefit from whole genome amplification of the low-yield samples prior to genotyping. Careful quality control procedures are, however, needed in WGA genotyping.

Mice lacking the serotonin Htr2B receptor gene present an antipsychotic-sensitive schizophrenic-like phenotype

Impulsivity and hyperactivity share common ground with numerous mental disorders, including schizophrenia. Recently, a population-specific serotonin 2B (5-HT2B) receptor stop codon (ie, HTR2B Q20*) was reported to segregate with severely impulsive individuals, whereas 5-HT2B mutant (Htr2B−/−) mice also showed high impulsivity. Interestingly, in the same cohort, early-onset schizophrenia was more prevalent in HTR2B Q*20 carriers. However, the putative role of 5-HT2B receptor in the neurobiology of schizophrenia has never been investigated. We assessed the effects of the genetic and the pharmacological ablation of 5-HT2B receptors in mice subjected to a comprehensive series of behavioral test screenings for schizophrenic-like symptoms and investigated relevant dopaminergic and glutamatergic neurochemical alterations in the cortex and the striatum. Domains related to the positive, negative, and cognitive symptom clusters of schizophrenia were affected in Htr2B−/− mice, as shown by deficits in sensorimotor gating, in selective attention, in social interactions, and in learning and memory processes. In addition, Htr2B−/− mice presented with enhanced locomotor response to the psychostimulants dizocilpine and amphetamine, and with robust alterations in sleep architecture. Moreover, ablation of 5-HT2B receptors induced a region-selective decrease of dopamine and glutamate concentrations in the dorsal striatum. Importantly, selected schizophrenic-like phenotypes and endophenotypes were rescued by chronic haloperidol treatment. We report herein that 5-HT2B receptor deficiency confers a wide spectrum of antipsychotic-sensitive schizophrenic-like behavioral and psychopharmacological phenotypes in mice and provide first evidence for a role of 5-HT2B receptors in the neurobiology of psychotic disorders

Fungal community structure in disease suppressive soils assessed by 28S LSU gene sequencing

Natural biological suppression of soil-borne diseases is a function of the activity and composition of soil microbial communities. Soil microbe and phytopathogen interactions can occur prior to crop sowing and/or in the rhizosphere, subsequently influencing both plant growth and productivity. Research on suppressive microbial communities has concentrated on bacteria although fungi can also influence soil-borne disease. Fungi were analyzed in co-located soils 'suppressive' or 'non-suppressive' for disease caused by Rhizoctonia solani AG 8 at two sites in South Australia using 454 pyrosequencing targeting the fungal 28S LSU rRNA gene. DNA was extracted from a minimum of 125 g of soil per replicate to reduce the micro-scale community variability, and from soil samples taken at sowing and from the rhizosphere at 7 weeks to cover the peak Rhizoctonia infection period. A total of ∼994,000 reads were classified into 917 genera covering 54% of the RDP Fungal Classifier database, a high diversity for an alkaline, low organic matter soil. Statistical analyses and community ordinations revealed significant differences in fungal community composition between suppressive and non-suppressive soil and between soil type/location. The majority of differences associated with suppressive soils were attributed to less than 40 genera including a number of endophytic species with plant pathogen suppression potentials and mycoparasites such as Xylaria spp. Non-suppressive soils were dominated by Alternaria , Gibberella and Penicillum. Pyrosequencing generated a detailed description of fungal community structure and identified candidate taxa that may influence pathogen-plant interactions in stable disease suppression. © 2014 Penton et al.

Computational Methods for Locating and Analyzing Conserved Gene Regulatory DNA Elements

This thesis presents methods for locating and analyzing cis-regulatory DNA elements involved with the regulation of gene expression in multicellular organisms. The regulation of gene expression is carried out by the combined effort of several transcription factor proteins collectively binding the DNA on the cis-regulatory elements. Only sparse knowledge of the 'genetic code' of these elements exists today. An automatic tool for discovery of putative cis-regulatory elements could help their experimental analysis, which would result in a more detailed view of the cis-regulatory element structure and function. We have developed a computational model for the evolutionary conservation of cis-regulatory elements. The elements are modeled as evolutionarily conserved clusters of sequence-specific transcription factor binding sites. We give an efficient dynamic programming algorithm that locates the putative cis-regulatory elements and scores them according to the conservation model. A notable proportion of the high-scoring DNA sequences show transcriptional enhancer activity in transgenic mouse embryos. The conservation model includes four parameters whose optimal values are estimated with simulated annealing. With good parameter values the model discriminates well between the DNA sequences with evolutionarily conserved cis-regulatory elements and the DNA sequences that have evolved neutrally. In further inquiry, the set of highest scoring putative cis-regulatory elements were found to be sensitive to small variations in the parameter values. The statistical significance of the putative cis-regulatory elements is estimated with the Two Component Extreme Value Distribution. The p-values grade the conservation of the cis-regulatory elements above the neutral expectation. The parameter values for the distribution are estimated by simulating the neutral DNA evolution. The conservation of the transcription factor binding sites can be used in the upstream analysis of regulatory interactions. This approach may provide mechanistic insight to the transcription level data from, e.g., microarray experiments. Here we give a method to predict shared transcriptional regulators for a set of co-expressed genes. The EEL (Enhancer Element Locator) software implements the method for locating putative cis-regulatory elements. The software facilitates both interactive use and distributed batch processing. We have used it to analyze the non-coding regions around all human genes with respect to the orthologous regions in various other species including mouse. The data from these genome-wide analyzes is stored in a relational database which is used in the publicly available web services for upstream analysis and visualization of the putative cis-regulatory elements in the human genome.

Involvement of Synthesis and Phosphorylation of Nuclear Protein Factors That Bind to the Positivecis-Acting Element in the Transcriptional Activation of the CYP2B1/B2 Gene by Phenobarbitonein Vivo

The synthesis and phosphorylation of protein factor(s) that bind to the positivecis-acting element (−69 to −98 nt) of the CYP2B1/B2 gene have been examinedin vivoin the rat. Treatment of rats with cycloheximide, a protein synthetic inhibitor, suppresses basal as well as phenobarbitone-induced levels of CYP2B1/B2 mRNA and its run-on transcription. Under these conditions, complex formation of the nuclear extract with the positive element is also inhibited, as judged by gel shift assays. Treatment of rats with 2-aminopurine, a general protein kinase inhibitor, blocks the phenobarbitone-mediated increase in CYP2B1/B2 mRNA, cell-free transcription of a minigene construct containing the positive element, pP450e179DNA, and binding of nuclear proteins to the positive element. Treatment of rats with okadaic acid, a protein phosphatase inhibitor, mimics the effects of phenobarbitone, but only partially. Thus, both phenobarbitone and okadaic acid individually enhance binding of the nuclear protein(s) to the positive element, cell-free transcription of the minigene construct, and phosphorylation of the not, vert, similar26- and 94-kDa proteins binding to the positive element. But unlike phenobarbitone, okadaic acid is not an inducer of CYP2B1/B2 mRNA or its run-on transcription. Thus, phenobarbitone-responsive positive element interactions constitute only a minimal requirement, and okadaic acid is perhaps not able to bring about the total requirement for activation of CYP2B1/B2 gene transcription that should include interaction between the minimal promoter and further upstream elements. An intriguing feature is the antagonistic effect of okadaic acid on phenobarbitone-mediated effects on CYP2B1/B2 mRNA levels, cell-free and run-on transcription, and nuclear protein binding to the positive element. The reason for this antagonism is not clear. It is concluded that phenobarbitone treatment enhancesin vivothe synthesis and phosphorylation of protein factors binding to the positive element and these constitute a minimal requirement for the transcriptional activation of the CYP2B1/B2 gene.

An extragenic suppressor of prp24-1 defines genetic interaction between PRP24 and PRP21 gene products of Saccharomyces cerevisiae

The temperature-sensitive prp24-1 mutation defines a gene product required for the first step in pre-mRNA splicing. PRP24 is probably a component of the U6 snRNP particle. We have applied genetic reversion analysis to identify proteins that interact with PRP24. Spontaneous revertants of the temperature-sensitive (ts) prp24-1 phenotype were analyzed for those that are due to extragenic suppression. We then extended our analysis to screen for suppressors that confer a distinct conditional phenotype. We have identified a temperature-sensitive extragenic suppressor, which was shown by genetic complementation analysis to be allelic to prp21-1. This suppressor, prp21-2, accumulates pre-mRNA at the non-permissive temperature, a phenotype similar to that of prp21-1. prp21-2 completely suppresses the splicing defect and restores in vivo levels of the U6 snRNA in the prp24-1 strain. Genetic analysis of the suppressor showed that prp21-2 is not a bypass suppressor of prp24-1. The suppression of prp24-1 by prp21-2 is gene specific and also allele specific with respect to both the loci. Genetic interactions with other components of the pre-spliceosome have also been studied. Our results indicate an interaction between PRP21, a component of the U2 snRNP, and PRP24, a component of the U6 snRNP. These results substantiate other data showing U2-U6 snRNA interactions.

Characterization of LRRTM and NGR gene families: Expression and functions

Some leucine-rich repeat (LRR) -containing membrane proteins are known regulators of neuronal growth and synapse formation. In this work I characterize two gene families encoding neuronal LRR membrane proteins, namely the LRRTM (leucine-rich repeat, transmembrane neuronal) and NGR (Nogo-66 receptor) families. I studied LRRTM and NGR family member's mRNA tissue distribution by RT-PCR and by in situ hybridization. Subcellular localization of LRRTM1 protein was studied in neurons and in non-neuronal cells. I discovered that LRRTM and NGR family mRNAs are predominantly expressed in the nervous system, and that each gene possesses a specific expression pattern. I also established that LRRTM and NGR family mRNAs are expressed by neurons, and not by glial cells. Within neurons, LRRTM1 protein is not transported to the plasma membrane; rather it localizes to endoplasmic reticulum. Nogo-A (RTN4), MAG, and OMgp are myelin-associated proteins that bind to NgR1 to limit axonal regeneration after central nervous system injury. To better understand the functions of NgR2 and NgR3, and to explore the possible redundancy in the signaling of myelin inhibitors of neurite growth, I mapped the interactions between NgR family and the known and candidate NgR1 ligands. I identified high-affinity interactions between RTN2-66, RTN3-66 and NgR1. I also demonstrate that Rtn3 mRNA is expressed in the same glial cell population of mouse spinal cord white matter as Nogo-A mRNA, and thus it could have a role in myelin inhibition of axonal growth. To understand how NgR1 interacts with multiple structurally divergent ligands, I aimed first to map in more detail the nature of Nogo-A:NgR1 interactions, and then to systematically map the binding sites of multiple myelin ligands in NgR1 by using a library of NgR1 expression constructs encoding proteins with one or multiple surface residues mutated to alanine. My analysis of the Nogo-A:NgR1 -interactions revealed a novel interaction site between the proteins, suggesting a trivalent Nogo-A:NgR1-interaction. Our analysis also defined a central binding region on the concave side of NgR1's LRR domain that is required for the binding of all known ligands, and a surrounding region critical for binding MAG and OMgp. To better understand the biological role of LRRTMs, I generated Lrrtm1 and Lrrtm3 knock out mice. I show here that reporter genes expressed from the targeted loci can be used for maping the neuronal connections of Lrrtm1 and Lrrtm3 expressing neurons in finer detail. With regard to LRRTM1's role in humans, we found a strong association between a 70 kb-spanning haplotype in the proposed promoter region of LRRTM1 gene and two possibly related phenotypes: left-handedness and schizophrenia. Interestingly, the responsible haplotype was linked to phenotypic variability only when paternally inherited. In summary, I identified two families of neuronal receptor-like proteins, and mapped their expression and certain protein-protein interactions. The identification of a central binding region in NgR1 shared by multiple ligands may facilitate the design and development of small molecule therapeutics blocking binding of all NgR1 ligands. Additionally, the genetic association data suggests that allelic variation upstream of LRRTM1 may play a role in the development of left-right brain asymmetry in humans. Lrrtm1 and Lrrtm3 knock out mice developed as a part of this study will likely be useful for schizophrenia and Alzheimer s disease research.

NETGEM: Network Embedded Temporal GEnerative Model for gene expression data

Background: Temporal analysis of gene expression data has been limited to identifying genes whose expression varies with time and/or correlation between genes that have similar temporal profiles. Often, the methods do not consider the underlying network constraints that connect the genes. It is becoming increasingly evident that interactions change substantially with time. Thus far, there is no systematic method to relate the temporal changes in gene expression to the dynamics of interactions between them. Information on interaction dynamics would open up possibilities for discovering new mechanisms of regulation by providing valuable insight into identifying time-sensitive interactions as well as permit studies on the effect of a genetic perturbation. Results: We present NETGEM, a tractable model rooted in Markov dynamics, for analyzing the dynamics of the interactions between proteins based on the dynamics of the expression changes of the genes that encode them. The model treats the interaction strengths as random variables which are modulated by suitable priors. This approach is necessitated by the extremely small sample size of the datasets, relative to the number of interactions. The model is amenable to a linear time algorithm for efficient inference. Using temporal gene expression data, NETGEM was successful in identifying (i) temporal interactions and determining their strength, (ii) functional categories of the actively interacting partners and (iii) dynamics of interactions in perturbed networks. Conclusions: NETGEM represents an optimal trade-off between model complexity and data requirement. It was able to deduce actively interacting genes and functional categories from temporal gene expression data. It permits inference by incorporating the information available in perturbed networks. Given that the inputs to NETGEM are only the network and the temporal variation of the nodes, this algorithm promises to have widespread applications, beyond biological systems. The source code for NETGEM is available from https://github.com/vjethava/NETGEM

Molecular mechanisms of interleukin-2 gene inducibility: developmental control and combinatorial action of transcription factors

Interleukin-2 is one of the lymphokines secreted by T helper type 1 cells upon activation mediated by T-cell receptor (TCR) and accessory molecules. The ability to express IL-2 is correlated with T-lineage commitment and is regulated during T cell development and differentiation. Understanding the molecular mechanism of how IL-2 gene inducibility is controlled at each transition and each differentiation process of T-cell development is to understand one aspect of T-cell development. In the present study, we first attempted to elucidate the molecular basis for the developmental changes of IL-2 gene inducibility. We showed that IL-2 gene inducibility is acquired early in immature CD4- CD8-TCR- thymocytes prior to TCR gene rearrangement. Similar to mature T cells, a complete set of transcription factors can be induced at this early stage to activate IL-2 gene expression. The progression of these cells to cortical CD4^+CD8^+TCR^(1o) cells is accompanied by the loss of IL-2 gene inducibility. We demonstrated that DNA binding activities of two transcription factors AP-1 and NF-AT are reduced in cells at this stage. Further, the loss of factor binding, especially AP-1, is attributable to the reduced ability to activate expression of three potential components of AP-1 and NF-AT, including c-Fos, FosB, and Fra-2. We next examined the interaction of transcription factors and the IL-2 promoter in vivo by using the EL4 T cell line and two non-T cell lines. We showed an all-or-none phenomenon regarding the factor-DNA interaction, i.e., in activated T cells, the IL-2 promoter is occupied by sequence-specific transcription factors when all the transcription factors are available; in resting T cells or non-T cells, no specific protein-DNA interaction is observed when only a subset of factors are present in the nuclei. Purposefully reducing a particular set of factor binding activities in stimulated T cells using pharmacological agents cyclosporin A or forskolin also abolished all interactions. The results suggest that a combinatorial and coordinated protein-DNA interaction is required for IL-2 gene activation. The thymocyte experiments clearly illustrated that multiple transcription factors are regulated during intrathymic T-cell development, and this regulation in tum controls the inducibility of the lineage-specific IL-2 gene. The in vivo study of protein-DNA interaction stressed the combinatorial action of transcription factors to stably occupy the IL-2 promoter and to initiate its transcription, and provided a molecular mechanism for changes in IL-2 gene inducibility in T cells undergoing integration of multiple environmental signals.

Molecular genetics of the Drosophila eyes absent gene

The Drosophila compound eye has provided a genetic approach to understanding the specification of cell fates during differentiation. The eye is made up of some 750 repeated units or ommatidia, arranged in a lattice. The cellular composition of each ommatidium is identical. The arrangement of the lattice and the specification of cell fates in each ommatidium are thought to occur in development through cellular interactions with the local environment. Many mutations have been studied that disrupt the proper patterning and cell fating in the eye. The eyes absent (eya) mutation, the subject of this thesis, was chosen because of its eyeless phenotype. In eya mutants, eye progenitor cells undergo programmed cell death before the onset of patterning has occurred. The molecular genetic analysis of the gene is presented.

The eye arises from the larval eye-antennal imaginal disc. During the third larval instar, a wave of differentiation progresses across the disc, marked by a furrow. Anterior to the furrow, proliferating cells are found in apparent disarray. Posterior to the furrow, clusters of differentiating cells can be discerned, that correspond to the ommatidia of the adult eye. Analysis of an allelic series of eya mutants in comparison to wild type revealed the presence of a selection point: a wave of programmed cell death that normally precedes the furrow. In eya mutants, an excessive number of eye progenitor cells die at this selection point, suggesting the eya gene influences the distribution of cells between fates of death and differentiation.

In addition to its role in the eye, the eya gene has an embryonic function. The eye function is autonomous to the eye progenitor cells. Molecular maps of the eye and embryonic phenotypes are different. Therefore, the function of eya in the eye can be treated independently of the embryonic function. Cloning of the gene reveals two cDNA's that are identical except for the use of an alternatively-spliced 5' exon. The predicted protein products differ only at the N-termini. Sequence analysis shows these two proteins to be the first of their kind to be isolated. Trangenic studies using the two cDNA's show that either gene product is able to rescue the eye phenotype of eya mutants.

The eya gene exhibits interallelic complementation. This interaction is an example of an "allelic position effect": an interaction that depends on the relative position in the genome of the two alleles, which is thought to be mediated by chromosomal pairing. The interaction at eya is essentially identical to a phenomenon known as transvection, which is an allelic position effect that is sensitive to certain kinds of chromosomal rearrangements. A current model for the mechanism of transvection is the trans action of gene regulatory regions. The eya locus is particularly well suited for the study of transvection because the mutant phenotypes can be quantified by scoring the size of the eye.

The molecular genetic analysis of eya provides a system for uncovering mechanisms underlying differentiation, developmentally regulated programmed cell death, and gene regulation.

Role of feedback and dynamics in a gene regulatory network

Cells exhibit a diverse repertoire of dynamic behaviors. These dynamic functions are implemented by circuits of interacting biomolecules. Although these regulatory networks function deterministically by executing specific programs in response to extracellular signals, molecular interactions are inherently governed by stochastic fluctuations. This molecular noise can manifest as cell-to-cell phenotypic heterogeneity in a well-mixed environment. Single-cell variability may seem like a design flaw but the coexistence of diverse phenotypes in an isogenic population of cells can also serve a biological function by increasing the probability of survival of individual cells upon an abrupt change in environmental conditions. Decades of extensive molecular and biochemical characterization have revealed the connectivity and mechanisms that constitute regulatory networks. We are now confronted with the challenge of integrating this information to link the structure of these circuits to systems-level properties such as cellular decision making. To investigate cellular decision-making, we used the well studied galactose gene-regulatory network in \textit{Saccharomyces cerevisiae}. We analyzed the mechanism and dynamics of the coexistence of two stable on and off states for pathway activity. We demonstrate that this bimodality in the pathway activity originates from two positive feedback loops that trigger bistability in the network. By measuring the dynamics of single-cells in a mixed sugar environment, we observe that the bimodality in gene expression is a transient phenomenon. Our experiments indicate that early pathway activation in a cohort of cells prior to galactose metabolism can accelerate galactose consumption and provide a transient increase in growth rate. Together these results provide important insights into strategies implemented by cells that may have been evolutionary advantageous in competitive environments.

A ratiometric-based measure of gene co-expression

Current measures of global gene expression analyses, such as correlation and mutual information-based approaches, largely depend on the degree of association between mRNA levels and to a lesser extent on variability. I develop and implement a new approach, called the Ratiometric method, which is based on the coefficient of variation of the expression ratio of two genes, relying more on variation than previous methods. The advantage of such modus operandi is the ability to detect possible gene pair interactions regardless of the degree of expression dispersion across the sample group. Gene pairs with low expression dispersion, i.e., their absolute expressions remain constant across the sample group, are systematically missed by correlation and mutual information analyses. The superiority of the Ratiometric method in finding these gene pair interactions is demonstrated in a data set of RNA-seq B-cell samples from the 1000 Genomes Project Consortium. The Ratiometric method renders a more comprehensive recovery of KEGG pathways and GO-terms.

Rastreamento de mutações no gene GBA como fator de risco ao desenvolvimento da doença de Parkinson na população brasileira

A doença de Parkinson (DP) é a segunda doença neurodegenerativa mais frequente, depois da doença de Alzheimer, com uma incidência de aproximadamente 3,3% na população brasileira acima dos 60 anos. Ela é caracterizada por uma perda dos neurônios dopaminérgicos da parte compacta da substância negra e pela presença de inclusões protéicas intracelulares denominadas corpúsculos de Lewy nos neurônios sobreviventes. A DP tem uma etiologia complexa que envolve interações genes-ambiente e múltiplos genes de susceptibilidade. Nesse contexto, mutações de perda de função no gene da glicocerebrosidase (GBA) têm sido bem validadas como importantes fatores de risco para a DP. Esse gene está localizado na região 1q21 e compreende 11 exons que codificam a enzima lisossômica glicocerebrosidase. O principal objetivo deste estudo foi investigar se alterações no gene GBA constituem um fator de predisposição para o desenvolvimento da DP na população brasileira. Para isso, um grupo de 126 pacientes brasileiros, não-aparentados, com DP (24 casos familiares e 102 isolados; idade média 66,4 11,4) foram analisados para mutações no GBA através do seqüenciamento completo de todos os exons e alguns íntrons. Sete alterações e um alelo recombinante, anteriormente encontrados em pacientes com a DP analisados em outros estudos, foram detectados (K(-)27R, IVS2+1G>A, N370S, L444P, T369M, A456P, E326K e RecNciI), assim como, uma variante nunca antes identificada associada à DP (G325G) e uma nova mutação (W378C), num total de 18 pacientes (14,3%). Além disso, foram encontradas três alterações intrônicas (c.454+47G>A, c.589-86A>G e c.1225-34C>A), que constam do banco de SNPs, entretanto, não foram associadas a nenhuma doença. Dentre todas as variantes identificadas, três são comprovadamente patogênicas (IVS2+1G>A, L444P e N370S) e foram encontradas em 5,5% da amostra, não sendo detectadas na amostra controle, indicando uma freqüência significativamente alta dessas mutações em pacientes com DP quando comparadas aos controles (P=0,0033). Esses resultados reforçam a associação entre o gene GBA e a DP na população brasileira, além de apoiar a hipótese de que alterações nesse gene representam um importante fator de susceptibilidade ao desenvolvimento da DP

Gene function prediction from synthetic lethality networks via ranking on demand.

MOTIVATION: Synthetic lethal interactions represent pairs of genes whose individual mutations are not lethal, while the double mutation of both genes does incur lethality. Several studies have shown a correlation between functional similarity of genes and their distances in networks based on synthetic lethal interactions. However, there is a lack of algorithms for predicting gene function from synthetic lethality interaction networks. RESULTS: In this article, we present a novel technique called kernelROD for gene function prediction from synthetic lethal interaction networks based on kernel machines. We apply our novel algorithm to Gene Ontology functional annotation prediction in yeast. Our experiments show that our method leads to improved gene function prediction compared with state-of-the-art competitors and that combining genetic and congruence networks leads to a further improvement in prediction accuracy.

Adaptive evolution of MRGX2, a human sensory neuron specific gene involved in nociception

MRGX2, a G-protein-coupled receptor, is specifically expressed in the sensory neurons of the human peripheral nervous system and involved in nociception. Here, we studied DNA polymorphism patterns and evolution of the MRGX2 gene in world-wide human populations and the representative nonhuman primate species. Our results demonstrated that MRGX2 had undergone adaptive changes in the path of human evolution, which were likely caused by Darwinian positive selection. The patterns of DNA sequence polymorphisms in human populations showed an excess of derived substitutions, which against the expectation of neutral evolution, implying that the adaptive evolution of MRGX2 in humans was a relatively recent event. The reconstructed secondary structure of the human MRGX2 revealed that three of the four human-specific amino acid substitutions were located in the extra-cellular domains. Such critical substitutions may alter the interactions between MRGX2 protein and its ligand, thus, potentially led to adaptive changes of the pain-perception-related nervous system during human evolution. (c) 2005 Elsevier B.V. All rights reserved.