49 research outputs found

    Additional file 12: of Deep sequencing of small RNA facilitates tissue and sex associated microRNA discovery in zebrafish

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    Comprises of additional details of the methods, including the options and parameters of the tools used for processing of the reads, known miRNA expression profile generation, normalization and clustering and novel miRNA prediction pipeline. (PDF 1468 kb

    Additional file 3: of Deep sequencing of small RNA facilitates tissue and sex associated microRNA discovery in zebrafish

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    Comprises of the details of the sex associated known miRNAs including the logFC, logCPM, P-value and FDR values. Sheet1: brain, Sheet2: gut, Sheet3: liver, Sheet4: ovary vs. testis. (XLSX 20 kb

    Additional file 6: of Deep sequencing of small RNA facilitates tissue and sex associated microRNA discovery in zebrafish

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    Comprises of the details of the predicted novel miRNAs of all the samples including the IDs, miRDeep2 scores, read counts, precursor and mature sequences and precursor coordinates. Sheet1: embryo predicted novel miRNAs, Sheet2: male brain predicted novel miRNAs, Sheet3: female brain predicted novel miRNAs, Sheet4: male gut predicted novel miRNAs, Sheet5: female gut predicted novel miRNAs, Sheet6: male liver predicted novel miRNAs, Sheet7: female liver predicted novel miRNAs, Sheet8: ovary predicted novel miRNAs, Sheet9: testis predicted novel miRNAs, Sheet10: eye predicted novel miRNAs, Sheet11: heart predicted novel miRNAs). (XLSX 159 kb

    Additional file 5: of Deep sequencing of small RNA facilitates tissue and sex associated microRNA discovery in zebrafish

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    Is a plot showing the sensitivity of MiRDeep2 for identification of known miRNAs from zebrafish. The number of known miRNAs picked up by miRDeep2 in comparison to the total number of miRNAs in the sample; at the similar cut-off used for novel miRNA prediction was used as an indicator of its sensitivity. The sensitivity of miRDeep2 ranged from 89 to 95 % with the exception of one female liver sample, for which the sensitivity was 81 %. (PDF 26 kb

    L'Écho : grand quotidien d'information du Centre Ouest

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    20 décembre 19171917/12/20 (A46).Appartient à l’ensemble documentaire : PoitouCh

    Additional file 7: of Deep sequencing of small RNA facilitates tissue and sex associated microRNA discovery in zebrafish

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    Figure showing the structure of a predicted novel miRNA from miRdeep2 with its aligned read sequences. MiRdeep2 gives as output the pdfs of the structure of the predicted novel miRNA along with the reads mapping to its mature, star and loop sequences. The top left corner has the score distribution for the predicted novel miRNA, the top right corner has the predicted hairpin structure for the novel pre-miRNA and the major part comprises of the alignment of the reads to the mature (red), loop (yellow) and the star regions (purple) of the precursor miRNA. For each read mapped, its frequency value, the number of mismatches with which it maps, and the sample it belongs to is given at the bottom right. (PDF 221 kb

    Additional file 10: of Deep sequencing of small RNA facilitates tissue and sex associated microRNA discovery in zebrafish

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    Figure showing the schematic representation of obtaining specific novel pre-miRNAs for embryo. The coloured circles represent the set of predicted novel pre-miRNAs for each tissue sample. The 78 predicted novel pre-miRNAs of embryo were compared with the set of predicted novel pre-miRNAs of other tissues to find the ones that matched. The total set of matched novel pre-miRNAs were 59. Therefore the unmatched set of 19 was considered as specific novel pre-miRNAs for embryo. This procedure was followed for the other tissue samples to obtain the novel pre-miRNAs specific to them. (PDF 30 kb

    Genome Wide Expression Profiling during Spinal Cord Regeneration Identifies Comprehensive Cellular Responses in Zebrafish

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    <div><p>Background</p><p>Among the vertebrates, teleost and urodele amphibians are capable of regenerating their central nervous system. We have used zebrafish as a model to study spinal cord injury and regeneration. Relatively little is known about the molecular mechanisms underlying spinal cord regeneration and information based on high density oligonucleotide microarray was not available. We have used a high density microarray to profile the temporal transcriptome dynamics during the entire phenomenon.</p><p>Results</p><p>A total of 3842 genes expressed differentially with significant fold changes during spinal cord regeneration. Cluster analysis revealed event specific dynamic expression of genes related to inflammation, cell death, cell migration, cell proliferation, neurogenesis, neural patterning and axonal regrowth. Spatio-temporal analysis of <i>stat3</i> expression suggested its possible function in controlling inflammation and cell proliferation. Genes involved in neurogenesis and their dorso-ventral patterning (<i>sox2</i> and <i>dbx2</i>) are differentially expressed. Injury induced cell proliferation is controlled by many cell cycle regulators and some are commonly expressed in regenerating fin, heart and retina. Expression pattern of certain pathway genes are identified for the first time during regeneration of spinal cord. Several genes involved in PNS regeneration in mammals like <i>stat3</i>, <i>socs3</i>, <i>atf3</i>, <i>mmp9</i> and <i>sox11</i> are upregulated in zebrafish SCI thus creating PNS like environment after injury.</p><p>Conclusion</p><p>Our study provides a comprehensive genetic blue print of diverse cellular response(s) during regeneration of zebrafish spinal cord. The data highlights the importance of different event specific gene expression that could be better understood and manipulated further to induce successful regeneration in mammals.</p></div
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