Terapia sostitutiva renale e pensiero bioetico: i risultati di un audit sulle équipes nefro-dialitiche torinesi

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A factor model to analyze heterogeneity in gene expression

<p>Abstract</p> <p>Background</p> <p>Microarray technology allows the simultaneous analysis of thousands of genes within a single experiment. Significance analyses of transcriptomic data ignore the gene dependence structure. This leads to correlation among test statistics which affects a strong control of the false discovery proportion. A recent method called FAMT allows capturing the gene dependence into factors in order to improve high-dimensional multiple testing procedures. In the subsequent analyses aiming at a functional characterization of the differentially expressed genes, our study shows how these factors can be used both to identify the components of expression heterogeneity and to give more insight into the underlying biological processes.</p> <p>Results</p> <p>The use of factors to characterize simple patterns of heterogeneity is first demonstrated on illustrative gene expression data sets. An expression data set primarily generated to map QTL for fatness in chickens is then analyzed. Contrarily to the analysis based on the raw data, a relevant functional information about a QTL region is revealed by factor-adjustment of the gene expressions. Additionally, the interpretation of the independent factors regarding known information about both experimental design and genes shows that some factors may have different and complex origins.</p> <p>Conclusions</p> <p>As biological information and technological biases are identified in what was before simply considered as statistical noise, analyzing heterogeneity in gene expression yields a new point of view on transcriptomic data.</p

Transcriptional Responses of Resistant and Susceptible Fish Clones to the Bacterial Pathogen Flavobacterium psychrophilum

Flavobacterium psychrophilum is a bacterial species that represents one of the most important pathogens for aquaculture worldwide, especially for salmonids. To gain insights into the genetic basis of the natural resistance to F. psychrophilum, we selected homozygous clones of rainbow trout with contrasted susceptibility to the infection. We compared the transcriptional response to the bacteria in the pronephros of a susceptible and a resistant line by micro-array analysis five days after infection. While the basal transcriptome of healthy fish was significantly different in the resistant and susceptible lines, the transcriptome modifications induced by the bacteria involved essentially the same genes and pathways. The response to F. psychrophilum involved antimicrobial peptides, complement, and a number of enzymes and chemokines. The matrix metalloproteases mmp9 and mmp13 were among the most highly induced genes in both genetic backgrounds. Key genes of both pro- and anti-inflammatory response such as IL1 and IL10, were up-regulated with a greater magnitude in susceptible animals where the bacterial load was also much higher. While higher resistance to F. psychrophilum does not seem to be based on extensive differences in the orientation of the immune response, several genes including complement C3 showed stronger induction in the resistant fish. They may be important for the variation of susceptibility to the infection

Gene expression patterns in four brain areas associate with quantitative measure of estrous behavior in dairy cows

<p>Abstract</p> <p>Background</p> <p>The decline noticed in several fertility traits of dairy cattle over the past few decades is of major concern. Understanding of the genomic factors underlying fertility, which could have potential applications to improve fertility, is very limited. Here, we aimed to identify and study those genes that associated with a key fertility trait namely estrous behavior, among genes expressed in four bovine brain areas (hippocampus, amygdala, dorsal hypothalamus and ventral hypothalamus), either at the start of estrous cycle, or at mid cycle, or regardless of the phase of cycle.</p> <p>Results</p> <p>An average heat score was calculated for each of 28 primiparous cows in which estrous behavior was recorded for at least two consecutive estrous cycles starting from 30 days post-partum. Gene expression was then measured in brain tissue samples collected from these cows, 14 of which were sacrificed at the start of estrus and 14 around mid cycle. For each brain area, gene expression was modeled as a function of the orthogonally transformed average heat score values using a Bayesian hierarchical mixed model. Genes whose expression patterns showed significant linear or quadratic relationships with heat scores were identified. These included genes expected to be related to estrous behavior as they influence states like socio-sexual behavior, anxiety, stress and feeding motivation (<it>OXT, AVP, POMC, MCHR1</it>), but also genes whose association with estrous behavior is novel and warrants further investigation.</p> <p>Conclusions</p> <p>Several genes were identified whose expression levels in the bovine brain associated with the level of expression of estrous behavior. The genes <it>OXT </it>and <it>AVP </it>play major roles in regulating estrous behavior in dairy cows. Genes related to neurotransmission and neuronal plasticity are also involved in estrous regulation, with several genes and processes expressed in mid-cycle probably contributing to proper expression of estrous behavior in the next estrus. Studying these genes and the processes they control improves our understanding of the genomic regulation of estrous behavior expression.</p

Transcriptomic analysis of milk somatic cells in mastitis resistant and susceptible sheep upon challenge with Staphylococcus epidermidis and Staphylococcus aureus

<p>Abstract</p> <p>Background</p> <p>The existence of a genetic basis for host responses to bacterial intramammary infections has been widely documented, but the underlying mechanisms and the genes are still largely unknown. Previously, two divergent lines of sheep selected for high/low milk somatic cell scores have been shown to be respectively susceptible and resistant to intramammary infections by <it>Staphylococcus spp</it>. Transcriptional profiling with an 15K ovine-specific microarray of the milk somatic cells of susceptible and resistant sheep infected successively by <it>S. epidermidis </it>and <it>S. aureus </it>was performed in order to enhance our understanding of the molecular and cellular events associated with mastitis resistance.</p> <p>Results</p> <p>The bacteriological titre was lower in the resistant than in the susceptible animals in the 48 hours following inoculation, although milk somatic cell concentration was similar. Gene expression was analysed in milk somatic cells, mainly represented by neutrophils, collected 12 hours post-challenge. A high number of differentially expressed genes between the two challenges indicated that more T cells are recruited upon inoculation by <it>S. aureus </it>than <it>S. epidermidis</it>. A total of 52 genes were significantly differentially expressed between the resistant and susceptible animals. Further Gene Ontology analysis indicated that differentially expressed genes were associated with immune and inflammatory responses, leukocyte adhesion, cell migration, and signal transduction. Close biological relationships could be established between most genes using gene network analysis. Furthermore, gene expression suggests that the cell turn-over, as a consequence of apoptosis/granulopoiesis, may be enhanced in the resistant line when compared to the susceptible line.</p> <p>Conclusions</p> <p>Gene profiling in resistant and susceptible lines has provided good candidates for mapping the biological pathways and genes underlying genetically determined resistance and susceptibility towards <it>Staphylococcus </it>infections, and opens new fields for further investigation.</p

Strengthening insights into host responses to mastitis infection in ruminants by combining heterogeneous microarray data sources

<p>Abstract</p> <p>Background</p> <p>Gene expression profiling studies of mastitis in ruminants have provided key but fragmented knowledge for the understanding of the disease. A systematic combination of different expression profiling studies via meta-analysis techniques has the potential to test the extensibility of conclusions based on single studies. Using the program Pointillist, we performed meta-analysis of transcription-profiling data from six independent studies of infections with mammary gland pathogens, including samples from cattle challenged <it>in vivo </it>with <it>S. aureus</it>, <it>E. coli</it>, and <it>S. uberis</it>, samples from goats challenged <it>in vivo </it>with <it>S. aureus</it>, as well as cattle macrophages and ovine dendritic cells infected <it>in vitro </it>with <it>S. aureus</it>. We combined different time points from those studies, testing different responses to mastitis infection: overall (common signature), early stage, late stage, and cattle-specific.</p> <p>Results</p> <p>Ingenuity Pathway Analysis of affected genes showed that the four meta-analysis combinations share biological functions and pathways (e.g. protein ubiquitination and polyamine regulation) which are intrinsic to the general disease response. In the overall response, pathways related to immune response and inflammation, as well as biological functions related to lipid metabolism were altered. This latter observation is consistent with the milk fat content depression commonly observed during mastitis infection. Complementarities between early and late stage responses were found, with a prominence of metabolic and stress signals in the early stage and of the immune response related to the lipid metabolism in the late stage; both mechanisms apparently modulated by few genes, including <it>XBP1 </it>and <it>SREBF1</it>.</p> <p>The cattle-specific response was characterized by alteration of the immune response and by modification of lipid metabolism. Comparison of <it>E. coli </it>and <it>S. aureus </it>infections in cattle <it>in vivo </it>revealed that affected genes showing opposite regulation had the same altered biological functions and provided evidence that <it>E. coli </it>caused a stronger host response.</p> <p>Conclusions</p> <p>This meta-analysis approach reinforces previous findings but also reveals several novel themes, including the involvement of genes, biological functions, and pathways that were not identified in individual studies. As such, it provides an interesting proof of principle for future studies combining information from diverse heterogeneous sources.</p

Methods for interpreting lists of affected genes obtained in a DNA microarray experiment

BACKGROUND: The aim of this paper was to describe and compare the methods used and the results obtained by the participants in a joint EADGENE (European Animal Disease Genomic Network of Excellence) and SABRE (Cutting Edge Genomics for Sustainable Animal Breeding) workshop focusing on post analysis of microarray data. The participating groups were provided with identical lists of microarray probes, including test statistics for three different contrasts, and the normalised log-ratios for each array, to be used as the starting point for interpreting the affected probes. The data originated from a microarray experiment conducted to study the host reactions in broilers occurring shortly after a secondary challenge with either a homologous or heterologous species of Eimeria. RESULTS: Several conceptually different analytical approaches, using both commercial and public available software, were applied by the participating groups. The following tools were used: Ingenuity Pathway Analysis, MAPPFinder, LIMMA, GOstats, GOEAST, GOTM, Globaltest, TopGO, ArrayUnlock, Pathway Studio, GIST and AnnotationDbi. The main focus of the approaches was to utilise the relation between probes/genes and their gene ontology and pathways to interpret the affected probes/genes. The lack of a well-annotated chicken genome did though limit the possibilities to fully explore the tools. The main results from these analyses showed that the biological interpretation is highly dependent on the statistical method used but that some common biological conclusions could be reached. CONCLUSION: It is highly recommended to test different analytical methods on the same data set and compare the results to obtain a reliable biological interpretation of the affected genes in a DNA microarray experimen

The node weight dependent Traveling Salesperson Problem: Approximation algorithms and randomized search heuristics

Several important optimization problems in the area of vehicle routing can be seen as variants of the classical Traveling Salesperson Problem (TSP). In the area of evolutionary computation, the Traveling Thief Problem (TTP) has gained increasing interest over the last 5 years. In this paper, we investigate the effect of weights on such problems, in the sense that the cost of traveling increases with respect to the weights of nodes already visited during a tour. This provides abstractions of important TSP variants such as the Traveling Thief Problem and time dependent TSP variants, and allows to study precisely the increase in difficulty caused by weight dependence. We provide a 3.59-approximation for this weight dependent version of TSP with metric distances and bounded positive weights. Furthermore, we conduct experimental investigations for simple randomized local search with classical mutation operators and two variants of the state-of-the-art evolutionary algorithm EAX adapted to the weighted TSP. Our results show the impact of the node weights on the position of the nodes in the resulting tour.Jakob Bossek, Katrin Casel, Pascal Kerschke, Frank Neuman