114 resultados para transcriptomics


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This study used next generation sequencing technologies to investigate growth in a cultured crustacean. The objective was to identify and characterise specific gene loci that contribute important phenotypic variation to growth as well as to develop a large set of SNP markers in candidate genes for assessing correlations between specific mutations and individual growth performance. The genomic dataset generated provides a fundamental resource for application in future crustacean stock improvement programs. Ultimately, the data can be applied to development of culture lines with improved growth performance.

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Enterovirus 71 (EV71) is one of the main etiological agents for Hand, Foot and Mouth Disease (HFMD) and has been shown to be associated with severe clinical manifestation. Currently, there is no antiviral therapeutic for the treatment of HFMD patients owing to a lack of understanding of EV71 pathogenesis. This study seeks to elucidate the transcriptomic changes that result from EV71 infection. Human whole genome microarray was employed to monitor changes in genomic profiles between infected and uninfected cells. The results reveal altered expression of human genes involved in critical pathways including the immune response and the stress response. Together, data from this study provide valuable insights into the host–pathogen interaction between human colorectal cells and EV71.

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Helicobacter pylori is an important human pathogen and one of the most successful chronic colonizers of the human body. H. pylori uses diverse mechanisms to modulate its interaction with the host in order to promote chronic infection and overcome host immune response. Restriction-modification genes are a major part of strain-specific genes present in H. pylori. The role of N-6 -adenine methylation in bacterial gene regulation and virulence is well established but not much is known about the effect of C-5 -cytosine methylation on gene expression in prokaryotes. In this study, it was observed by microarray analysis and RT-PCR, that deletion of an orphan C-5 -cytosine methyltransferase, hpyAVIBM in H. pylori strains AM5and SS1 has a significant effect on the expression of number of genes belonging to motility, adhesion and virulence. AM Delta DhpyAVIBM mutant strain has a different LPS profile and is able to induce high IL-8 production compared to wild-type. hpyAVIBM from strain 26695 is able to complement mutant SS1 and AM5 strains. This study highlights a possible significance of cytosine methylation in the physiology of H. pylori.

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Pseudomonas putida KT2440 is the only fully sequenced P. putida strain. Thus, for transcriptomics and proteomics studies with other P. putida strains, the P. putida KT2440 genomic database serves as standard reference. The utility of KT2440 whole-genome, high-density oligonucleotide microarrays for transcriptomics studies of other Pseudomonas strains was investigated. To this end, microarray hybridizations were performed with genomic DNAs of subcultures of P. putida KT2440 (DSM6125), the type strain (DSM291(T)), plasmid pWW0-containing KT2440-derivative strain mt-2 (DSM3931), the solvent-tolerant P. putida S12, and several other Pseudomonas strains. Depending on the strain tested, 22 to 99% of all genetic elements were identified in the genomic DNAs. The efficacy of these microarrays to study cellular function was determined for all strains included in the study. The vast majority of DSM6125 genes encoding proteins of primary metabolism and genes involved in the catabolism of aromatic compounds were identified in the genomic DNA of strain S12: a prerequisite for reliable transcriptomics analyses. The genomotypic comparisons between Pseudomonas strains were used to construct highly discriminative phylogenetic relationships. DSM6125 and DSM3931 were indistinguishable and clustered together with strain S12 in a separate group, distinct from DSM291(T). Pseudomonas monteilii (DSM14164) clustered well with P. putida strains.

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Unprecedented biotechnological advances in the past decade have delivered powerful transcriptomics methods that provide new opportunities for a risk-based and, hence, more effective control of food quality and safety. The fundamental hypothesis underlying the application of a transcriptomics or other

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To infect their mammalian hosts, Fasciola hepatica larvae must penetrate and traverse the intestinal wall of the duodenum, move through the peritoneum, and penetrate the liver. After migrating through and feeding on the liver, causing extensive tissue damage, the parasites move to their final niche in the bile ducts where they mature and produce eggs. Here we integrated a transcriptomics and proteomics approach to profile Fasciola secretory proteins that are involved in host-pathogen interactions and to correlate changes in their expression with the migration of the parasite. Prediction of F. hepatica secretory proteins from 14,031 expressed sequence tags (ESTs) available from the Wellcome Trust Sanger Centre using the semiautomated EST2Secretome pipeline showed that the major components of adult parasite secretions are proteolytic enzymes including cathepsin L, cathepsin B, and asparaginyl endopeptidase cysteine proteases as well as novel trypsin-like serine proteases and carboxypeptidases. Proteomics analysis of proteins secreted by infective larvae, immature flukes, and adult F. hepatica showed that these proteases are developmentally regulated and correlate with the passage of the parasite through host tissues and its encounters with different host macromolecules. Proteases such as FhCL3 and cathepsin B have specific functions in larvae activation and intestinal wall penetration, whereas FhCL1, FhCL2, and FhCL5 are required for liver penetration and tissue and blood feeding. Besides proteases, the parasites secrete an array of antioxidants that are also highly regulated according to their migration through host tissues. However, whereas the proteases of F. hepatica are secreted into the parasite gut via a classical endoplasmic reticulum/Golgi pathway, we speculate that the antioxidants, which all lack a signal sequence, are released via a non-classical trans-tegumental pathway.

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BACKGROUND: Understanding the heterogeneous genotypes and phenotypes of prostate cancer is fundamental to improving the way we treat this disease. As yet, there are no validated descriptions of prostate cancer subgroups derived from integrated genomics linked with clinical outcome.

METHODS: In a study of 482 tumour, benign and germline samples from 259 men with primary prostate cancer, we used integrative analysis of copy number alterations (CNA) and array transcriptomics to identify genomic loci that affect expression levels of mRNA in an expression quantitative trait loci (eQTL) approach, to stratify patients into subgroups that we then associated with future clinical behaviour, and compared with either CNA or transcriptomics alone.

FINDINGS: We identified five separate patient subgroups with distinct genomic alterations and expression profiles based on 100 discriminating genes in our separate discovery and validation sets of 125 and 103 men. These subgroups were able to consistently predict biochemical relapse (p = 0.0017 and p = 0.016 respectively) and were further validated in a third cohort with long-term follow-up (p = 0.027). We show the relative contributions of gene expression and copy number data on phenotype, and demonstrate the improved power gained from integrative analyses. We confirm alterations in six genes previously associated with prostate cancer (MAP3K7, MELK, RCBTB2, ELAC2, TPD52, ZBTB4), and also identify 94 genes not previously linked to prostate cancer progression that would not have been detected using either transcript or copy number data alone. We confirm a number of previously published molecular changes associated with high risk disease, including MYC amplification, and NKX3-1, RB1 and PTEN deletions, as well as over-expression of PCA3 and AMACR, and loss of MSMB in tumour tissue. A subset of the 100 genes outperforms established clinical predictors of poor prognosis (PSA, Gleason score), as well as previously published gene signatures (p = 0.0001). We further show how our molecular profiles can be used for the early detection of aggressive cases in a clinical setting, and inform treatment decisions.

INTERPRETATION: For the first time in prostate cancer this study demonstrates the importance of integrated genomic analyses incorporating both benign and tumour tissue data in identifying molecular alterations leading to the generation of robust gene sets that are predictive of clinical outcome in independent patient cohorts.

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Land plant evolution required the generation of a new body plan that could resist the harsher and fluctuating environmental conditions found outside of aquatic environments. Unraveling the genetic basis of plant developmental innovations is not only revealing in terms of an evolutionary point of view, but it is also important for understanding the emergence of agronomically important traits. Comparative genetic studies between basal and modern land plants, both at the genome and trancriptome levels, can help in the generation of hypotheses related to the genetic basis of plant evolutionary development.(...)

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Background The rhizosphere is the microbe-rich zone around plant roots and is a key determinant of the biosphere's productivity. Comparative transcriptomics was used to investigate general and plant-specific adaptations during rhizosphere colonization. Rhizobium leguminosarum biovar viciae was grown in the rhizospheres of pea (its legume nodulation host), alfalfa (a non-host legume) and sugar beet (non-legume). Gene expression data were compared to metabolic and transportome maps to understand adaptation to the rhizosphere. Results Carbon metabolism was dominated by organic acids, with a strong bias towards aromatic amino acids, C1 and C2 compounds. This was confirmed by induction of the glyoxylate cycle required for C2 metabolism and gluconeogenesis in all rhizospheres. Gluconeogenesis is repressed in R. leguminosarum by sugars, suggesting that although numerous sugar and putative complex carbohydrate transport systems are induced in the rhizosphere, they are less important carbon sources than organic acids. A common core of rhizosphere-induced genes was identified, of which 66% are of unknown function. Many genes were induced in the rhizosphere of the legumes, but not sugar beet, and several were plant specific. The plasmid pRL8 can be considered pea rhizosphere specific, enabling adaptation of R. leguminosarum to its host. Mutation of many of the up-regulated genes reduced competitiveness for pea rhizosphere colonization, while two genes specifically up-regulated in the pea rhizosphere reduced colonization of the pea but not alfalfa rhizosphere. Conclusions Comparative transcriptome analysis has enabled differentiation between factors conserved across plants for rhizosphere colonization as well as identification of exquisite specific adaptation to host plants.

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Epidemiologic studies highlight the potential role of dietary selenium (Se) in colorectal cancer prevention. Our goal was to elucidate whether expression of factors crucial for colorectal homoeostasis is affected by physiologic differences in Se status. Using transcriptomics and proteomics followed by pathway analysis, we identified pathways affected by Se status in rectal biopsies from 22 healthy adults, including 11 controls with optimal status (mean plasma Se = 1.43 μM) and 11 subjects with suboptimal status (mean plasma Se = 0.86 μM). We observed that 254 genes and 26 proteins implicated in cancer (80%), immune function and inflammatory response (40%), cell growth and proliferation (70%), cellular movement, and cell death (50%) were differentially expressed between the 2 groups. Expression of 69 genes, including selenoproteins W1 and K, which are genes involved in cytoskeleton remodelling and transcription factor NFκB signaling, correlated significantly with Se status. Integrating proteomics and transcriptomics datasets revealed reduced inflammatory and immune responses and cytoskeleton remodelling in the suboptimal Se status group. This is the first study combining omics technologies to describe the impact of differences in Se status on colorectal expression patterns, revealing that suboptimal Se status could alter inflammatory signaling and cytoskeleton in human rectal mucosa and so influence cancer risk.