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Assessing TF regulatory relationships of divergently transcribed genes
Lan Chen1, Lun Cai, Geir Skogerbø
1Bioinformatics Research Group, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China.
Abstract:
Ambiguously located transcription factor (TF) binding sites may introduce a large number of potentially erroneous regulatory associations into models of transcriptional regulatory networks. We have used a two-step expression similarity strategy to distinguish between likely and unlikely regulatory associations for TFs located between divergently transcribed genes in the yeast genome. Most regulatory associations of divergently transcribed genes could be assigned to either high-confidence (HC) or low-confidence (LC) groups. In support of our result, we found that most of the previously characterized regulatory associations reported in the literature fell into the HC group rather than the LC group. Moreover, genomic distance analysis showed that TF binding sites tend to be located in relative proximity to the gene that is most likely to be regulated by this TF. Finally, removal of low-confidence (i.e., most probably erroneous) regulatory associations from the transcriptional regulatory network barely affected its basic architecture.
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