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首页> 外文期刊>Journal of Probability and Statistics >Finding Transcription Factor Binding Motifs for Coregulated Genes by Combining Sequence Overrepresentation with Cross-Species Conservation
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Finding Transcription Factor Binding Motifs for Coregulated Genes by Combining Sequence Overrepresentation with Cross-Species Conservation

机译:通过将序列过度表达与跨物种保守性相结合来找到核心基因的转录因子结合基序

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摘要

Novel computational methods for finding transcription factor binding motifs have long been sought due to tedious work of experimentally identifying them. However, the current prevailing methods yield a large number of false positive predictions due to the short, variable nature of transcriptional factor binding sites (TFBSs). We proposed here a method that combines sequence overrepresentation and cross-species sequence conservation to detect TFBSs in upstream regions of a given set of coregulated genes. We applied the method to 35S. cerevisiaetranscriptional factors with known DNA binding motifs (with the support of orthologous sequences from genomes ofS. mikatae,S. bayanus, andS. paradoxus), and the proposed method outperformed the single-genome-based motif finding methodsMEMEandAlignACEas well as the multiple-genome-based methodsPHYMEandFootprinterfor the majority of these transcriptional factors. Compared with the prevailing motif finding software, our method has some advantages in finding transcriptional factor binding motifs for potential coregulated genes if the gene upstream sequences of multiple closely related species are available. Although we used yeast genomes to assess our method in this study, it might also be applied to other organisms if suitable related species are available and the upstream sequences of coregulated genes can be obtained for the multiple closely related species.
机译:由于实验性地鉴定转录因子结合基序的繁琐工作,长期以来一直在寻找寻找转录因子结合基序的新型计算方法。但是,由于转录因子结合位点(TFBS)的短而可变的性质,当前流行的方法产生了大量的假阳性预测。我们在这里提出了一种结合序列过度表达和跨物种序列保守性的方法来检测给定的一组有核心基因的上游区域中的TFBS。我们将该方法应用于35S。具有已知DNA结合基序的酿酒酵母转录因子(在mikatae,S.bayanus和S.paradoxus基因组的直系同源序列的支持下),并且该方法优于基于单基因组的基序发现方法MEME和AlignACE以及多基因组基于PHYME和Footprinter的方法可用于大多数这些转录因子。与流行的基序查找软件相比,如果可以找到多个紧密相关物种的上游序列,我们的方法在寻找潜在的被调控基因的转录因子结合基序方面具有一些优势。尽管我们在本研究中使用酵母基因组来评估我们的方法,但如果可获得合适的相关物种,并且可以为多个紧密相关物种获得核心调控基因的上游序列,它也可以应用于其他生物。

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