48 research outputs found

    Long-term effects of gestational nicotine exposure and food-restriction on gene expression in the striatum of adolescent rats

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    Gestational exposure to environmental toxins such as nicotine may result in detectable gene expression changes in later life. To investigate the direct toxic effects of prenatal nicotine exposure on later brain development, we have used transcriptomic analysis of striatal samples to identify gene expression differences between adolescent Lister Hooded rats exposed to nicotine in utero and controls. Using an additional group of animals matched for the reduced food intake experienced in the nicotine group, we were also able to assess the impact of imposed food-restriction on gene expression profiles. We found little evidence for a role of gestational nicotine exposure on altered gene expression in the striatum of adolescent offspring at a significance level of p0.5|, although we cannot exclude the possibility of nicotine-induced changes in other brain regions, or at other time points. We did, however, find marked gene expression differences in response to imposed food-restriction. Food-restriction resulted in significant group differences for a number of immediate early genes (IEGs) including Fos, Fosb, Fosl2, Arc, Junb, Nr4a1 and Nr4a3. These genes are associated with stress response pathways and therefore may reflect long-term effects of nutritional deprivation on the development of the stress system

    Defining the microbial transcriptional response to colitis through integrated host and microbiome profiling

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    The gut microbiome is significantly altered in inflammatory bowel diseases, but the basis of these changes is not well understood. We have combined metagenomic and metatranscriptomic profiling of the gut microbiome to assess modifications to both bacterial community structure and transcriptional activity in a mouse model of colitis. By using transcriptomic analysis of colonic tissue and luminal RNA derived from the host, we have also characterised how host transcription relates to the microbial transcriptional response in inflammation. In colitis, increased abundance and transcription of diverse microbial gene families involved in responses to nutrient deprivation, antimicrobial peptide production and oxidative stress support an adaptation of multiple commensal genera to withstand a diverse set of environmental stressors in the inflammatory environment. These data are supported by a transcriptional signature of activated macrophages and granulocytes in the gut lumen during colitis, a signature that includes the transcription of the key antimicrobial genes S100a8 and S100a9 (calprotectin). Genes involved in microbial resistance to oxidative stress, including Dps/ferritin, Fe-dependent peroxidase and glutathione S-transferase were identified as changing to a greater extent at the level of transcription than would be predicted by DNA abundance changes, implicating a role for increased oxygen tension and/or host-derived reactive oxygen species in driving transcriptional changes in commensal microbes

    Alterations in the gut microbiome implicate key taxa and metabolic pathways across inflammatory arthritis phenotypes

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    Musculoskeletal diseases affect up to 20% of adults worldwide. The gut microbiome has been implicated in inflammatory conditions, but large-scale metagenomic evaluations have not yet traced the routes by which immunity in the gut affects inflammatory arthritis. To characterize the community structure and associated functional processes driving gut microbial involvement in arthritis, the Inflammatory Arthritis Microbiome Consortium investigated 440 stool shotgun metagenomes comprising 221 adults diagnosed with rheumatoid arthritis, ankylosing spondylitis, or psoriatic arthritis and 219 healthy controls and individuals with joint pain without an underlying inflammatory cause. Diagnosis explained about 2% of gut taxonomic variability, which is comparable in magnitude to inflammatory bowel disease. We identified several candidate microbes with differential carriage patterns in patients with elevated blood markers for inflammation. Our results confirm and extend previous findings of increased carriage of typically oral and inflammatory taxa and decreased abundance and prevalence of typical gut clades, indicating that distal inflammatory conditions, as well as local conditions, correspond to alterations to the gut microbial composition. We identified several differentially encoded pathways in the gut microbiome of patients with inflammatory arthritis, including changes in vitamin B salvage and biosynthesis and enrichment of iron sequestration. Although several of these changes characteristic of inflammation could have causal roles, we hypothesize that they are mainly positive feedback responses to changes in host physiology and immune homeostasis. By connecting taxonomic alternations to functional alterations, this work expands our understanding of the shifts in the gut ecosystem that occur in response to systemic inflammation during arthritis

    Genetic influences on attention deficit hyperactivity disorder symptoms from age 2 to 3: A quantitative and molecular genetic investigation

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    <p>Abstract</p> <p>Background</p> <p>A twin study design was used to assess the degree to which additive genetic variance influences ADHD symptom scores across two ages during infancy. A further objective in the study was to observe whether genetic association with a number of candidate markers reflects results from the quantitative genetic analysis.</p> <p>Method</p> <p>We have studied 312 twin pairs at two time-points, age 2 and age 3. A composite measure of ADHD symptoms from two parent-rating scales: The Child Behavior Checklist/1.5 - 5 years (CBCL) hyperactivity scale and the Revised Rutter Parent Scale for Preschool Children (RRPSPC) was used for both quantitative and molecular genetic analyses.</p> <p>Results</p> <p>At ages 2 and 3 ADHD symptoms are highly heritable (<it>h</it><sup><it>2 </it></sup><it>= </it>0.79 and 0.78, respectively) with a high level of genetic stability across these ages. However, we also observe a significant level of genetic change from age 2 to age 3. There are modest influences of non-shared environment at each age independently (<it>e</it><sup><it>2 </it></sup>= 0.22 and 0.21, respectively), with these influences being largely age-specific. In addition, we find modest association signals in <it>DAT1 </it>and <it>NET1 </it>at both ages, along with suggestive specific effects of <it>5-HTT </it>and <it>DRD4 </it>at age 3.</p> <p>Conclusions</p> <p>ADHD symptoms are heritable at ages 2 and 3. Additive genetic variance is largely shared across these ages, although there are significant new effects emerging at age 3. Results from our genetic association analysis reflect these levels of stability and change and, more generally, suggest a requirement for consideration of age-specific genotypic effects in future molecular studies.</p

    Cross-species inference of long non-coding RNAs greatly expands the ruminant transcriptome

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    Additional file 3. This file contains all supplementary tables relating to lncRNA identification via the conservation of synteny. Table S3. lncRNAs inferred in one species by the genomic alignment of a transcript assembled with the RNA-seq libraries from a related spdecies. Table S12. Presence of intergenic lncRNAs both in sheep and cattle, in regions of conserved synteny. Table S13. Presence of intergenic lncRNAs both in sheep and goat, in regions of conserved synteny. Table S14. Presence of intergenic lncRNAs both in cattle and goat, in regions of conserved synteny. Table S15. Presence of intergenic lncRNAs both in sheep and humans, in regions of conserved synteny. Table S16. Presence of intergenic lncRNAs both in goat and humans, in regions of conserved synteny. Table S17. Presence of intergenic lncRNAs both in cattle and humans, in regions of conserved synteny. Table S18. High-confidence lncRNA pairs, those conserved across species both sequentially and positionally

    Predicting long non-coding RNAs using RNA sequencing

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    The advent of next-generation sequencing, and in particular RNA-sequencing (RNA-seq), technologies has expanded our knowledge of the transcriptional capacity of human and other animal, genomes. In particular, recent RNA-seq studies have revealed that transcription is widespread across the mammalian genome, resulting in a large increase in the number of putative transcripts from both within, and intervening between, known protein-coding genes. Long transcripts that appear to lack protein-coding potential (long non-coding RNAs, lncRNAs) have been the focus of much recent research, in part owing to observations of their cell-type and developmental time-point restricted expression patterns. A variety of sequencing protocols are currently available for identifying lncRNAs including RNA polymerase II occupancy, chromatin state maps and - the focus of this review - deep RNA sequencing. In addition, there are numerous analytical methods available for mapping reads and assembling transcript models that predict the presence and structure of lncRNAs from RNA-seq data. Here we review current methods for identifying lncRNAs using large-scale sequencing data from RNA-seq experiments and highlight analytical considerations that are required when undertaking such projects. © 2013 Elsevier Inc. All rights reserved

    Sequencing depth and coverage: key considerations in genomic analyses.

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    Sequencing technologies have placed a wide range of genomic analyses within the capabilities of many laboratories. However, sequencing costs often set limits to the amount of sequences that can be generated and, consequently, the biological outcomes that can be achieved from an experimental design. In this Review, we discuss the issue of sequencing depth in the design of next-generation sequencing experiments. We review current guidelines and precedents on the issue of coverage, as well as their underlying considerations, for four major study designs, which include de novo genome sequencing, genome resequencing, transcriptome sequencing and genomic location analyses (for example, chromatin immunoprecipitation followed by sequencing (ChIP-seq) and chromosome conformation capture (3C))

    Sequencing depth and coverage: key considerations in genomic analyses.

    No full text
    Sequencing technologies have placed a wide range of genomic analyses within the capabilities of many laboratories. However, sequencing costs often set limits to the amount of sequences that can be generated and, consequently, the biological outcomes that can be achieved from an experimental design. In this Review, we discuss the issue of sequencing depth in the design of next-generation sequencing experiments. We review current guidelines and precedents on the issue of coverage, as well as their underlying considerations, for four major study designs, which include de novo genome sequencing, genome resequencing, transcriptome sequencing and genomic location analyses (for example, chromatin immunoprecipitation followed by sequencing (ChIP-seq) and chromosome conformation capture (3C))

    A large polysaccharide produced by helicobacter hepaticus induces an anti-inflammatory gene signature in macrophages

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    Interactions between the host and its microbiota are of mutual benefit and promote health. Complex molecular pathways underlie this dialog, but the identity of microbe-derived molecules that mediate the mutualistic state remains elusive. Helicobacter hepaticus is a member of the mouse intestinal microbiota that is tolerated by the host. In the absence of an intact IL-10 signaling, H. hepaticus induces an IL-23-driven inflammatory response in the intestine. Here we investigate the interactions between H. hepaticus and host immune cells that may promote mutualism, and the microbe-derived molecule(s) involved. Our results show that H. hepaticus triggers early IL-10 induction in intestinal macrophages and produces a large soluble polysaccharide that activates a specific MSK/CREB-dependent anti-inflammatory and repair gene signature via the receptor TLR2. These data identify a host-bacterial interaction that promotes mutualistic mechanisms at the intestinal interface. Further understanding of this pathway may provide novel prevention and treatment strategies for inflammatory bowel disease
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