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      Whole-transcriptome, high-throughput RNA sequence analysis of the bovine macrophage response to Mycobacterium bovis infection in vitro

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          Abstract

          Background

          Mycobacterium bovis, the causative agent of bovine tuberculosis, is an intracellular pathogen that can persist inside host macrophages during infection via a diverse range of mechanisms that subvert the host immune response. In the current study, we have analysed and compared the transcriptomes of M. bovis-infected monocyte-derived macrophages (MDM) purified from six Holstein-Friesian females with the transcriptomes of non-infected control MDM from the same animals over a 24 h period using strand-specific RNA sequencing (RNA-seq). In addition, we compare gene expression profiles generated using RNA-seq with those previously generated by us using the high-density Affymetrix® GeneChip® Bovine Genome Array platform from the same MDM-extracted RNA.

          Results

          A mean of 7.2 million reads from each MDM sample mapped uniquely and unambiguously to single Bos taurus reference genome locations. Analysis of these mapped reads showed 2,584 genes (1,392 upregulated; 1,192 downregulated) and 757 putative natural antisense transcripts (558 upregulated; 119 downregulated) that were differentially expressed based on sense and antisense strand data, respectively (adjusted P-value ≤ 0.05). Of the differentially expressed genes, 694 were common to both the sense and antisense data sets, with the direction of expression ( i.e. up- or downregulation) positively correlated for 693 genes and negatively correlated for the remaining gene. Gene ontology analysis of the differentially expressed genes revealed an enrichment of immune, apoptotic and cell signalling genes. Notably, the number of differentially expressed genes identified from RNA-seq sense strand analysis was greater than the number of differentially expressed genes detected from microarray analysis (2,584 genes versus 2,015 genes). Furthermore, our data reveal a greater dynamic range in the detection and quantification of gene transcripts for RNA-seq compared to microarray technology.

          Conclusions

          This study highlights the value of RNA-seq in identifying novel immunomodulatory mechanisms that underlie host-mycobacterial pathogen interactions during infection, including possible complex post-transcriptional regulation of host gene expression involving antisense RNA.

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          Most cited references59

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          Computational methods for transcriptome annotation and quantification using RNA-seq.

          High-throughput RNA sequencing (RNA-seq) promises a comprehensive picture of the transcriptome, allowing for the complete annotation and quantification of all genes and their isoforms across samples. Realizing this promise requires increasingly complex computational methods. These computational challenges fall into three main categories: (i) read mapping, (ii) transcriptome reconstruction and (iii) expression quantification. Here we explain the major conceptual and practical challenges, and the general classes of solutions for each category. Finally, we highlight the interdependence between these categories and discuss the benefits for different biological applications.
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            Deep sequencing-based expression analysis shows major advances in robustness, resolution and inter-lab portability over five microarray platforms

            The hippocampal expression profiles of wild-type mice and mice transgenic for δC-doublecortin-like kinase were compared with Solexa/Illumina deep sequencing technology and five different microarray platforms. With Illumina's digital gene expression assay, we obtained ∼2.4 million sequence tags per sample, their abundance spanning four orders of magnitude. Results were highly reproducible, even across laboratories. With a dedicated Bayesian model, we found differential expression of 3179 transcripts with an estimated false-discovery rate of 8.5%. This is a much higher figure than found for microarrays. The overlap in differentially expressed transcripts found with deep sequencing and microarrays was most significant for Affymetrix. The changes in expression observed by deep sequencing were larger than observed by microarrays or quantitative PCR. Relevant processes such as calmodulin-dependent protein kinase activity and vesicle transport along microtubules were found affected by deep sequencing but not by microarrays. While undetectable by microarrays, antisense transcription was found for 51% of all genes and alternative polyadenylation for 47%. We conclude that deep sequencing provides a major advance in robustness, comparability and richness of expression profiling data and is expected to boost collaborative, comparative and integrative genomics studies.
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              Cadherins in development: cell adhesion, sorting, and tissue morphogenesis.

              Tissue morphogenesis during development is dependent on activities of the cadherin family of cell-cell adhesion proteins that includes classical cadherins, protocadherins, and atypical cadherins (Fat, Dachsous, and Flamingo). The extracellular domain of cadherins contains characteristic repeats that regulate homophilic and heterophilic interactions during adhesion and cell sorting. Although cadherins may have originated to facilitate mechanical cell-cell adhesion, they have evolved to function in many other aspects of morphogenesis. These additional roles rely on cadherin interactions with a wide range of binding partners that modify their expression and adhesion activity by local regulation of the actin cytoskeleton and diverse signaling pathways. Here we examine how different members of the cadherin family act in different developmental contexts, and discuss the mechanisms involved.
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                Author and article information

                Journal
                BMC Genomics
                BMC Genomics
                BMC Genomics
                BioMed Central
                1471-2164
                2013
                8 April 2013
                : 14
                : 230
                Affiliations
                [1 ]Animal Genomics Laboratory, UCD School of Agriculture and Food Science, University College Dublin, Belfield, Dublin, Dublin 4, Ireland
                [2 ]UCD School of Veterinary Medicine, University College Dublin, Belfield, Dublin, Dublin 4, Ireland
                [3 ]Smurfit Institute of Genetics, Trinity College Dublin, Trinity College, Dublin, Ireland
                [4 ]UCD Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Belfield, Dublin, Dublin 4, Ireland
                [5 ]Tuberculosis Diagnostics and Immunology Research Centre, UCD School of Veterinary Medicine, University College Dublin, Belfield, Dublin, Dublin 4, Ireland
                Article
                1471-2164-14-230
                10.1186/1471-2164-14-230
                3640917
                23565803
                b0c7d560-2eea-4ef3-abfb-1cb150c4d2ff
                Copyright ©2013 Nalpas et al.; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 30 August 2012
                : 8 March 2013
                Categories
                Research Article

                Genetics
                bovine tuberculosis,immune response,microarray,mycobacterium bovis,natural antisense transcript,rna-sequencing,transcriptome

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