70 research outputs found

    Measuring Biodiversity and Extinction – Present and Past

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    How biodiversity is changing in our time represents a major concern for all organismal biologists. Anthropogenic changes to our planet are decreasing species diversity through the negative effects of pollution, habitat destruction, direct extirpation of species, and climate change. But major biotic changes – including those that have both increased and decreased species diversity – have happened before in Earth’s history. Biodiversity dynamics in past eras provide important context to understand ecological responses to current environmental change. The work of assessing biodiversity is woven into ecology, environmental science, conservation, paleontology, phylogenetics, evolutionary and developmental biology, and many other disciplines; yet, the absolute foundation of how we measure species diversity depends on taxonomy and systematics. The aspiration of this symposium, and complementary contributed talks, was to promote better understanding of our common goals and encourage future interdisciplinary discussion of biodiversity dynamics. The contributions in this collection of papers bring together a diverse group of speakers to confront several important themes. How can biologists best respond to the urgent need to identify and conserve diversity? How can we better communicate the nature of species across scientific disciplines? Where are the major gaps in knowledge about the diversity of living animal and plant groups, and what are the implications for understanding potential diversity loss? How can we effectively use the fossil record of past diversity and extinction to understand current biodiversity loss

    Predicting tissue specific cis-regulatory modules in the human genome using pairs of co-occurring motifs

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    <p>Abstract</p> <p>Background</p> <p>Researchers seeking to unlock the genetic basis of human physiology and diseases have been studying gene transcription regulation. The temporal and spatial patterns of gene expression are controlled by mainly non-coding elements known as cis-regulatory modules (CRMs) and epigenetic factors. CRMs modulating related genes share the regulatory signature which consists of transcription factor (TF) binding sites (TFBSs). Identifying such CRMs is a challenging problem due to the prohibitive number of sequence sets that need to be analyzed.</p> <p>Results</p> <p>We formulated the challenge as a supervised classification problem even though experimentally validated CRMs were not required. Our efforts resulted in a software system named CrmMiner. The system mines for CRMs in the vicinity of related genes. CrmMiner requires two sets of sequences: a mixed set and a control set. Sequences in the vicinity of the related genes comprise the mixed set, whereas the control set includes random genomic sequences. CrmMiner assumes that a large percentage of the mixed set is made of background sequences that do not include CRMs. The system identifies pairs of closely located motifs representing vertebrate TFBSs that are enriched in the training mixed set consisting of 50% of the gene loci. In addition, CrmMiner selects a group of the enriched pairs to represent the tissue-specific regulatory signature. The mixed and the control sets are searched for candidate sequences that include any of the selected pairs. Next, an optimal Bayesian classifier is used to distinguish candidates found in the mixed set from their control counterparts. Our study proposes 62 tissue-specific regulatory signatures and putative CRMs for different human tissues and cell types. These signatures consist of assortments of ubiquitously expressed TFs and tissue-specific TFs. Under controlled settings, CrmMiner identified known CRMs in noisy sets up to 1:25 signal-to-noise ratio. CrmMiner was 21-75% more precise than a related CRM predictor. The sensitivity of the system to locate known human heart enhancers reached up to 83%. CrmMiner precision reached 82% while mining for CRMs specific to the human CD4<sup>+ </sup>T cells. On several data sets, the system achieved 99% specificity.</p> <p>Conclusion</p> <p>These results suggest that CrmMiner predictions are accurate and likely to be tissue-specific CRMs. We expect that the predicted tissue-specific CRMs and the regulatory signatures broaden our knowledge of gene transcription regulation.</p

    PubMed Central

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    Potential immunosuppressive effects of Escherichia coli O157:H7 experimental infection on the bovine host

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    Background: Enterohaemorrhagic Escherichia coli (EHEC), like E. coli O157:H7 are frequently detected in bovine faecal samples at slaughter. Cattle do not show clinical symptoms upon infection, but for humans the consequences after consuming contaminated beef can be severe. The immune response against EHEC in cattle cannot always clear the infection as persistent colonization and shedding in infected animals over a period of months often occurs. In previous infection trials, we observed a primary immune response after infection which was unable to protect cattle from reinfection. These results may reflect a suppression of certain immune pathways, making cattle more prone to persistent colonization after re-infection. To test this, RNA-Seq was used for transcriptome analysis of recto-anal junction tissue and ileal Peyer's patches in nine Holstein-Friesian calves in response to a primary and secondary Escherichia coli O157: H7 infection with the Shiga toxin (Stx) negative NCTC12900 strain. Non-infected calves served as controls. Results: In tissue of the recto-anal junction, only 15 genes were found to be significantly affected by a first infection compared to 1159 genes in the ileal Peyer's patches. Whereas, re-infection significantly changed the expression of 10 and 17 genes in the recto-anal junction tissue and the Peyer's patches, respectively. A significant downregulation of 69 immunostimulatory genes and a significant upregulation of seven immune suppressing genes was observed. Conclusions: Although the recto-anal junction is a major site of colonization, this area does not seem to be modulated upon infection to the same extent as ileal Peyer's patches as the changes in gene expression were remarkably higher in the ileal Peyer's patches than in the recto-anal junction during a primary but not a secondary infection. We can conclude that the main effect on the transcriptome was immunosuppression by E. coli O157: H7 (Stx(-)) due to an upregulation of immune suppressive effects (7/12 genes) or a downregulation of immunostimulatory effects (69/94 genes) in the ileal Peyer's patches. These data might indicate that a primary infection promotes a re-infection with EHEC by suppressing the immune function
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