Computational detection of genomic cis-regulatory modules applied to body patterning in the early Drosophila embryo -: art. no. 30
Computational detection of genomic cis-regulatory modules applied to body patterning in the early Drosophila embryo -: art. no. 30
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DOI：
10.1186/1471-2105-3-30
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发表时间：
2002-01-01
影响因子：
3
通讯作者：
Siggia, ED
中科院分区：
文献类型：
--
作者：
Rajewsky, N;Vergassola, M;Siggia, ED
背景：基因转录调控对所有生物的功能和发育至关重要。虽然基因预测程序，确定蛋白质编码序列的注释基因组中取得了显着的成功，计算方法的发展，分析非编码区和描绘转录控制元件仍处于起步阶段。结果：在这里，我们提出了新的算法，通过全基因组范围内的扫描簇的转录因子结合位点使用三个层次的先验信息检测顺式调控模块。当结合位点的因素是已知的，我们的统计分割算法，亚哈，产生约150个推定的差距基因调控模块，没有可调的参数以外的窗口大小。如果已知一个或多个相关模块，但没有结合位点，则可以通过定制的Gibbs采样器找到重复的基序，并将其输入Ahab，以预测具有相似调控的基因。最后，只使用基因组，我们开发了第三种算法Argos，它可以在序列窗口中对过度代表的基序簇进行计数和评分。Argos恢复了许多已知的模块，上游的分割基因，没有training data.Conclusions：我们已经证明，在果蝇胚胎中的身体图案的情况下，我们的算法允许全基因组的监管模块的识别。我们相信Ahab克服了最近方法的许多问题，我们估计假阳性率约为50%。Argos是第一个成功的尝试，预测调控模块只使用基因组没有训练数据。整个果蝇基因组的完整结果和模块预测可在[http://uqbar.rockefeIler.edu/similar tosiggia/]上获得。
Background: Regulation of gene transcription is crucial for the function and development of all organisms. While gene prediction programs that identify protein coding sequence are used with remarkable success in the annotation of genomes, the development of computational methods to analyze noncoding regions and to delineate transcriptional control elements is still in its infancy.Results: Here we present novel algorithms to detect cis-regulatory modules through genome wide scans for clusters of transcription factor binding sites using three levels of prior information. When binding sites for the factors are known, our statistical segmentation algorithm, Ahab, yields about 150 putative gap gene regulated modules, with no adjustable parameters other than a window size. If one or more related modules are known, but no binding sites, repeated motifs can be found by a customized Gibbs sampler and input to Ahab, to predict genes with similar regulation. Finally using only the genome, we developed a third algorithm, Argos, that counts and scores clusters of overrepresented motifs in a window of sequence. Argos recovers many of the known modules, upstream of the segmentation genes, with no training data.Conclusions: We have demonstrated, in the case of body patterning in the Drosophila embryo, that our algorithms allow the genome-wide identification of regulatory modules. We believe that Ahab overcomes many problems of recent approaches and we estimated the false positive rate to be about 50%. Argos is the first successful attempt to predict regulatory modules using only the genome without training data. Complete results and module predictions across the Drosophila genome are available at [http://uqbar.rockefeIler.edu/similar tosiggia/].