Aeromonas hydrophila lateral flagella gene transcriptional hierarchy

Aeromonas hydrophila AH-3 lateral flagella are not assembled when bacteria grow in liquid media; however, lateral flagellar genes are transcribed. Our results indicate that A. hydrophila lateral flagellar genes are transcribed at three levels (class I to III genes) and share some similarities with, but have many important differences from, genes of Vibrio parahaemolyticus. A. hydrophila lateral flagellum class I gene transcription is σ70 dependent, which is consistent with the fact that lateral flagellum is constitutively transcribed, in contrast to the characteristics of V. parahaemolyticus. The fact that multiple genes are included in class I highlights that lateral flagellar genes are less hierarchically transcribed than polar flagellum genes. The A. hydrophila lafK-fliEJL gene cluster (where the subscript L distinguishes genes for lateral flagella from those for polar flagella) is exclusively from class I and is in V. parahaemolyticus class I and II. Furthermore, the A. hydrophila flgAMNL cluster is not transcribed from the σ54/LafK-dependent promoter and does not contain class II genes. Here, we propose a gene transcriptional hierarchy for the A. hydrophila lateral flagella.

Aeromonas hydrophila lateral flagella gene transcriptional hierarchy

Aeromonas hydrophila AH-3 lateral flagella are not assembled when bacteria grow in liquid media; however, lateral flagellar genes are transcribed. Our results indicate that A. hydrophila lateral flagellar genes are transcribed at three levels (class I to III genes) and share some similarities with, but have many important differences from, genes of Vibrio parahaemolyticus. A. hydrophila lateral flagellum class I gene transcription is σ(70) dependent, which is consistent with the fact that lateral flagellum is constitutively transcribed, in contrast to the characteristics of V. parahaemolyticus. The fact that multiple genes are included in class I highlights that lateral flagellar genes are less hierarchically transcribed than polar flagellum genes. The A. hydrophila lafK-fliEJL gene cluster (where the subscript L distinguishes genes for lateral flagella from those for polar flagella) is exclusively from class I and is in V. parahaemolyticus class I and II. Furthermore, the A. hydrophila flgAMNL cluster is not transcribed from the σ(54)/LafK-dependent promoter and does not contain class II genes. Here, we propose a gene transcriptional hierarchy for the A. hydrophila lateral flagella.

Use of physiological constraints to identify quantitative design principles for gene expression in yeast adaptation to heat shock

Background: Understanding the relationship between gene expression changes, enzyme activity shifts, and the corresponding physiological adaptive response of organisms to environmental cues is crucial in explaining how cells cope with stress. For example, adaptation of yeast to heat shock involves a characteristic profile of changes to the expression levels of genes coding for enzymes of the glycolytic pathway and some of its branches. The experimental determination of changes in gene expression profiles provides a descriptive picture of the adaptive response to stress. However, it does not explain why a particular profile is selected for any given response. Results: We used mathematical models and analysis of in silico gene expression profiles (GEPs) to understand how changes in gene expression correlate to an efficient response of yeast cells to heat shock. An exhaustive set of GEPs, matched with the corresponding set of enzyme activities, was simulated and analyzed. The effectiveness of each profile in the response to heat shock was evaluated according to relevant physiological and functional criteria. The small subset of GEPs that lead to effective physiological responses after heat shock was identified as the result of the tuning of several evolutionary criteria. The experimentally observed transcriptional changes in response to heat shock belong to this set and can be explained by quantitative design principles at the physiological level that ultimately constrain changes in gene expression. Conclusion: Our theoretical approach suggests a method for understanding the combined effect of changes in the expression of multiple genes on the activity of metabolic pathways, and consequently on the adaptation of cellular metabolism to heat shock. This method identifies quantitative design principles that facilitate understating the response of the cell to stress.

Mutations in the EXT1 and EXT2 genes in Spanish patients with multiple osteochondromas

Multiple osteochondromas is an autosomal dominant skeletal disorder characterized by the formation of multiple cartilage-capped tumours. Two causal genes have been identified, EXT1 and EXT2, which account for 65% and 30% of cases, respectively. We have undertaken a mutation analysis of the EXT1 and EXT2 genes in 39 unrelated Spanish patients, most of them with moderate phenotype, and looked for genotype-phenotype correlations. We found the mutant allele in 37 patients, 29 in EXT1 and 8 in EXT2. Five of the EXT1 mutations were deletions identified by MLPA. Two cases of mosaicism were documented. We detected a lower number of exostoses in patients with missense mutation versus other kinds of mutations. In conclusion, we found a mutation in EXT1 or in EXT2 in 95% of the Spanish patients. Eighteen of the mutations were novel.

Mutations in the EXT1 and EXT2 genes in Spanish patients with multiple osteochondromas

Multiple osteochondromas is an autosomal dominant skeletal disorder characterized by the formation of multiple cartilage-capped tumours. Two causal genes have been identified, EXT1 and EXT2, which account for 65% and 30% of cases, respectively. We have undertaken a mutation analysis of the EXT1 and EXT2 genes in 39 unrelated Spanish patients, most of them with moderate phenotype, and looked for genotype-phenotype correlations. We found the mutant allele in 37 patients, 29 in EXT1 and 8 in EXT2. Five of the EXT1 mutations were deletions identified by MLPA. Two cases of mosaicism were documented. We detected a lower number of exostoses in patients with missense mutation versus other kinds of mutations. In conclusion, we found a mutation in EXT1 or in EXT2 in 95% of the Spanish patients. Eighteen of the mutations were novel.

Assembling genes from predicted exons in linear time with dynamic programming

In a number of programs for gene structure prediction in higher eukaryotic genomic sequences, exon prediction is decoupled from gene assembly: a large pool of candidate exons is predicted and scored from features located in the query DNA sequence, and candidate genes are assembled from such a pool as sequences of nonoverlapping frame-compatible exons. Genes are scored as a function of the scores of the assembled exons, and the highest scoring candidate gene is assumed to be the most likely gene encoded by the query DNA sequence. Considering additive gene scoring functions, currently available algorithms to determine such a highest scoring candidate gene run in time proportional to the square of the number of predicted exons. Here, we present an algorithm whose running time grows only linearly with the size of the set of predicted exons. Polynomial algorithms rely on the fact that, while scanning the set of predicted exons, the highest scoring gene ending in a given exon can be obtained by appending the exon to the highest scoring among the highest scoring genes ending at each compatible preceding exon. The algorithm here relies on the simple fact that such highest scoring gene can be stored and updated. This requires scanning the set of predicted exons simultaneously by increasing acceptor and donor position. On the other hand, the algorithm described here does not assume an underlying gene structure model. Indeed, the definition of valid gene structures is externally defined in the so-called Gene Model. The Gene Model specifies simply which gene features are allowed immediately upstream which other gene features in valid gene structures. This allows for great flexibility in formulating the gene identification problem. In particular it allows for multiple-gene two-strand predictions and for considering gene features other than coding exons (such as promoter elements) in valid gene structures.

Characterization and evolution of the novel gene family FAM90A in primates originated by multiple duplication and rearrangement events

Genomic plasticity of human chromosome 8p23.1 region is highly influenced by two groups of complex segmental duplications (SDs), termed REPD and REPP, that mediate different kinds of rearrangements. Part of the difficulty to explain the wide range of phenotypes associated with 8p23.1 rearrangements is that REPP and REPD are not yet well characterized, probably due to their polymorphic status. Here, we describe a novel primate-specific gene family, named FAM90A (family with sequence similarity 90), found within these SDs. According to the current human reference sequence assembly, the FAM90A family includes 24 members along 8p23.1 region plus a single member on chromosome 12p13.31, showing copy number variation (CNV) between individuals. These genes can be classified into subfamilies I and II, which differ in their upstream and 5′-untranslated region sequences, but both share the same open reading frame and are ubiquitously expressed. Sequence analysis and comparative fluorescence in situ hybridization studies showed that FAM90A subfamily II suffered a big expansion in the hominoid lineage, whereas subfamily I members were likely generated sometime around the divergence of orangutan and African great apes by a fusion process. In addition, the analysis of the Ka/Ks ratios provides evidence of functional constraint of some FAM90A genes in all species. The characterization of the FAM90A gene family contributes to a better understanding of the structural polymorphism of the human 8p23.1 region and constitutes a good example of how SDs, CNVs and rearrangements within themselves can promote the formation of new gene sequences with potential functional consequences.

Multiple non-collinear TF-map alignments of promoter regions

Background: The analysis of the promoter sequence of genes with similar expression patterns isa basic tool to annotate common regulatory elements. Multiple sequence alignments are on thebasis of most comparative approaches. The characterization of regulatory regions from coexpressedgenes at the sequence level, however, does not yield satisfactory results in manyoccasions as promoter regions of genes sharing similar expression programs often do not shownucleotide sequence conservation.Results: In a recent approach to circumvent this limitation, we proposed to align the maps ofpredicted transcription factors (referred as TF-maps) instead of the nucleotide sequence of tworelated promoters, taking into account the label of the corresponding factor and the position in theprimary sequence. We have now extended the basic algorithm to permit multiple promotercomparisons using the progressive alignment paradigm. In addition, non-collinear conservationblocks might now be identified in the resulting alignments. We have optimized the parameters ofthe algorithm in a small, but well-characterized collection of human-mouse-chicken-zebrafishorthologous gene promoters.Conclusion: Results in this dataset indicate that TF-map alignments are able to detect high-levelregulatory conservation at the promoter and the 3'UTR gene regions, which cannot be detectedby the typical sequence alignments. Three particular examples are introduced here to illustrate thepower of the multiple TF-map alignments to characterize conserved regulatory elements inabsence of sequence similarity. We consider this kind of approach can be extremely useful in thefuture to annotate potential transcription factor binding sites on sets of co-regulated genes fromhigh-throughput expression experiments.

A targeted association study of immunity genes and networks suggests novel associations with placental malaria infection

A large proportion of the death toll associated with malaria is a consequence of malaria infection during pregnancy, causing up to 200,000 infant deaths annually. We previously published the first extensive genetic association study of placental malaria infection, and here we extend this analysis considerably, investigating genetic variation in over 9,000 SNPs in more than 1,000 genes involved in immunity and inflammation for their involvement in susceptibility to placental malaria infection. We applied a new approach incorporating results from both single gene analysis as well as gene-gene interactionson a protein-protein interaction network. We found suggestive associations of variants in the gene KLRK1 in the single geneanalysis, as well as evidence for associations of multiple members of the IL-7/IL-7R signalling cascade in the combined analysis. To our knowledge, this is the first large-scale genetic study on placental malaria infection to date, opening the door for follow-up studies trying to elucidate the genetic basis of this neglected form of malaria.

Predicting cancer involvement of genes from heterogeneous data

Background: Systematic approaches for identifying proteins involved in different types of cancer are needed. Experimental techniques such as microarrays are being used to characterize cancer, but validating their results can be a laborious task. Computational approaches are used to prioritize between genes putatively involved in cancer, usually based on further analyzing experimental data. Results: We implemented a systematic method using the PIANA software that predicts cancer involvement of genes by integrating heterogeneous datasets. Specifically, we produced lists of genes likely to be involved in cancer by relying on: (i) protein-protein interactions; (ii) differential expression data; and (iii) structural and functional properties of cancer genes. The integrative approach that combines multiple sources of data obtained positive predictive values ranging from 23% (on a list of 811 genes) to 73% (on a list of 22 genes), outperforming the use of any of the data sources alone. We analyze a list of 20 cancer gene predictions, finding that most of them have been recently linked to cancer in literature. Conclusion: Our approach to identifying and prioritizing candidate cancer genes can be used to produce lists of genes likely to be involved in cancer. Our results suggest that differential expression studies yielding high numbers of candidate cancer genes can be filtered using protein interaction networks.

The cell cycle–regulated genes of schizosaccharomyces pombe

Many genes are regulated as an innate part of the eukaryotic cell cycle, and a complex transcriptional network helps enable the cyclic behavior of dividing cells. This transcriptional network has been studied in Saccharomyces cerevisiae (budding yeast) and elsewhere. To provide more perspective on these regulatory mechanisms, we have used microarrays to measure gene expression through the cell cycle of Schizosaccharomyces pombe (fission yeast). The 750 genes with the most significant oscillations were identified and analyzed. There were two broad waves of cell cycle transcription, one in early/mid G2 phase, and the other near the G2/M transition. The early/mid G2 wave included many genes involved in ribosome biogenesis, possibly explaining the cell cycle oscillation in protein synthesis in S.pombe. The G2/M wave included at least three distinctly regulated clusters of genes: one large cluster including mitosis, mitotic exit, and cell separation functions, one small cluster dedicated to DNA replication, and another small cluster dedicated to cytokinesis and division. S. pombe cell cycle genes have relatively long, complex promoters containing groups of multiple DNA sequence motifs, often of two, three, or more different kinds. Many of the genes, transcription factors, and regulatory mechanisms are conserved between S. pombe and S. cerevisiae. Finally, we found preliminary evidence for a nearly genome-wide oscillation in gene expression: 2,000 or more genes undergo slight oscillations in expression as a function of the cell cycle, although whether this is adaptive, or incidental to other events in the cell, such as chromatin condensation, we do not know.

CBS: an open platform that integrates predictive methods and epigenetics information to characterize conserved regulatory features in multiple Drosophila genomes.

Background: Information about the composition of regulatory regions is of great value for designing experiments to functionally characterize gene expression. The multiplicity of available applications to predict transcription factor binding sites in a particular locus contrasts with the substantial computational expertise that is demanded to manipulate them, which may constitute a potential barrier for the experimental community. Results: CBS (Conserved regulatory Binding Sites, http://compfly.bio.ub.es/CBS) is a public platform of evolutionarily conserved binding sites and enhancers predicted in multiple Drosophila genomes that is furnished with published chromatin signatures associated to transcriptionally active regions and other experimental sources of information. The rapid access to this novel body of knowledge through a user-friendly web interface enables non-expert users to identify the binding sequences available for any particular gene, transcription factor, or genome region. Conclusions: The CBS platform is a powerful resource that provides tools for data mining individual sequences and groups of co-expressed genes with epigenomics information to conduct regulatory screenings in Drosophila.

Inverse Problems for multiple invariant curves

Planar polynomial vector fields which admit invariant algebraic curves, Darboux integrating factors or Darboux first integrals are of special interest. In the present paper we solve the inverse problem for invariant algebraic curves with a given multiplicity and for integrating factors, under generic assumptions regarding the (multiple) invariant algebraic curves involved. In particular we prove, in this generic scenario, that the existence of a Darboux integrating factor implies Darboux integrability. Furthermore we construct examples where the genericity assumption does not hold and indicate that the situation is different for these.

Aplicaciones Single Program Multiple Data (SPMD) en ambientes distribuidos

Un reto al ejecutar las aplicaciones en un cluster es lograr mejorar las prestaciones utilizando los recursos de manera eficiente, y este reto es mayor al utilizar un ambiente distribuido. Teniendo en cuenta este reto, se proponen un conjunto de reglas para realizar el cómputo en cada uno de los nodos, basado en el análisis de cómputo y comunicaciones de las aplicaciones, se analiza un esquema de mapping de celdas y un método para planificar el orden de ejecución, tomando en consideración la ejecución por prioridad, donde las celdas de fronteras tienen una mayor prioridad con respecto a las celdas internas. En la experimentación se muestra el solapamiento del computo interno con las comunicaciones de las celdas fronteras, obteniendo resultados donde el Speedup aumenta y los niveles de eficiencia se mantienen por encima de un 85%, finalmente se obtiene ganancias de los tiempos de ejecución, concluyendo que si se puede diseñar un esquemas de solapamiento que permita que la ejecución de las aplicaciones SPMD en un cluster se hagan de forma eficiente.