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Deep mRNA Sequencing Analysis to Capture the Transcriptome Landscape of Zebrafish Embryos and Larvae

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NIAID Data Ecosystem2026-03-07 收录
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https://figshare.com/articles/dataset/_Deep_mRNA_Sequencing_Analysis_to_Capture_the_Transcriptome_Landscape_of_Zebrafish_Embryos_and_Larvae_/704990
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Transcriptome analysis is a powerful tool to obtain large amount genome-scale gene expression profiles. Despite its extensive usage to diverse biological problems in the last decade, transcriptomic researches approaching the zebrafish embryonic development have been very limited. Several recent studies have made great progress in this direction, yet the large gap still exists, especially regarding to the transcriptome dynamics of embryonic stages from early gastrulation onwards. Here, we present a comprehensive analysis about the transcriptomes of 9 different stages covering 7 major periods (cleavage, blastula, gastrula, segmentation, pharyngula, hatching and early larval stage) in zebrafish development, by recruiting the RNA-sequencing technology. We detected the expression for at least 24,065 genes in at least one of the 9 stages. We identified 16,130 genes that were significantly differentially expressed between stages and were subsequently classified into six clusters. Each revealed gene cluster had distinct expression patterns and characteristic functional pathways, providing a framework for the understanding of the developmental transcriptome dynamics. Over 4000 genes were identified as preferentially expressed in one of the stages, which could be of high relevance to stage-specific developmental and molecular events. Among the 68 transcription factor families active during development, most had enhanced average expression levels and thus might be crucial for embryogenesis, whereas the inactivation of the other families was likely required by the activation of the zygotic genome. We discussed our RNA-seq data together with previous findings about the Wnt signaling pathway and some other genes with known functions, to show how our data could be used to advance our understanding about these developmental functional elements. Our study provides ample information for further study about the molecular and cellular mechanisms underlying vertebrate development.
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2013-05-20
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