Analysis of Genomic Sequence Motifs for Deciphering Transcription Factor Binding and Transcriptional Regulation in Eukaryotic Cells

Abstract : Eukaryotic genomes contain a variety of structured patterns: repetitive elements, binding sites of DNA and RNA associated proteins, splice sites, and so on. Often, these structured patterns can be formalized as motifs and described using a proper mathematical model such as position weight matrix and IUPAC consensus. Two key tasks are typically carried out for motifs in the context of the analysis of genomic sequences. These are: identification in a set of DNA regions of over-represented motifs from a particular motif database, and de novo discovery of over-represented motifs. Here we describe existing methodology to perform these two tasks for motifs characterizing transcription factor binding. When applied to the output of ChIP-seq and ChIP-exo experiments, or to promoter regions of co-modulated genes, motif analysis techniques allow for the prediction of transcription factor binding events and enable identification of transcriptional regulators and co-regulators. The usefulness of motif analysis is further exemplified in this review by how motif discovery improves peak calling in ChIP-seq and ChIP-exo experiments and, when coupled with information on gene expression, allows insights into physical mechanisms of transcriptional modulation.
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Frontiers in Genetics, Frontiers, 2016, 7, 〈10.3389/fgene.2016.00024〉
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Valentina Boeva. Analysis of Genomic Sequence Motifs for Deciphering Transcription Factor Binding and Transcriptional Regulation in Eukaryotic Cells. Frontiers in Genetics, Frontiers, 2016, 7, 〈10.3389/fgene.2016.00024〉. 〈inserm-01291222〉

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