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ExUTR: a novel pipeline for large-scale prediction of 3′-UTR sequences from NGS data

机译:ExUTR:从NGS数据大规模预测3-UTR序列的新型流水线

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摘要

BackgroundThe three prime untranslated region (3′-UTR) is known to play a pivotal role in modulating gene expression by determining the fate of mRNA. Many crucial developmental events, such as mammalian spermatogenesis, tissue patterning, sex determination and neurogenesis, rely heavily on post-transcriptional regulation by the 3′-UTR. However, 3′-UTR biology seems to be a relatively untapped field, with only limited tools and 3′-UTR resources available. To elucidate the regulatory mechanisms of the 3′-UTR on gene expression, firstly the 3′-UTR sequences must be identified. Current 3′-UTR mining tools, such as GETUTR, 3USS and UTRscan, all depend on a well-annotated reference genome or curated 3′-UTR sequences, which hinders their application on a myriad of non-model organisms where the genomes are not available. To address these issues, the establishment of an NGS-based, automated pipeline is urgently needed for genome-wide 3′-UTR prediction in the absence of reference genomes.
机译:背景已知三个主要的非翻译区(3'-UTR)通过确定mRNA的命运在调节基因表达中起关键作用。许多关键的发育事件,例如哺乳动物的精子发生,组织模式,性别决定和神经发生,都严重依赖于3'-UTR的转录后调控。但是,3'-UTR生物学似乎是一个相对尚未开发的领域,只有有限的工具和3'-UTR资源可用。为了阐明3'-UTR对基因表达的调控机制,首先必须鉴定3'-UTR序列。当前的3'-UTR挖掘工具,例如GETUTR,3USS和UTRscan,都依赖于标注正确的参考基因组或经过精心策划的3'-UTR序列,这阻碍了它们在无基因组的无模型生物中的应用。可用。为了解决这些问题,在没有参考基因组的情况下,迫切需要建立基于NGS的自动化管道来进行全基因组3'-UTR预测。

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