A Systematic Bioinformatics Approach to Motif-Based Analysis of Human Locus Control Regions

Locus control regions (LCRs), cis-acting, noncoding regulatory elements with strong transcription-enhancing activity, are conserved in sequence and organization, and exhibit strict gene-specific expression. LCRs have been reported and studied in several mammalian gene systems, signifying that they play an important role in eukaryotic gene expression control. Their highly regulated, stable, and precise levels of expression have made them a strong candidate for use in gene therapy vectors. In this study, we attempted to determine the unique signatures of human LCRs by analyzing a data set of LCR sequences for the presence of motifs through systematic bioinformatics approach. Using web-based regulatory sequence analysis tools (RSAT), motif-based analysis was performed. Detected significant motifs were analyzed further for their identity using Tomtom tool. RSAT analysis revealed that significant motifs are existent within the LCRs. Identity analysis using Tomtom showed that detected significant motifs were comparable with known transcription factor (TF) binding sites and the top scoring motifs belong to zinc finger-containing proteins, an important group of proteins involved in a variety of cellular activities. Correspondence to segment of known motif indicates the biological relevance of the detected motifs. Motif-based analysis is valuable for analyzing the various characteristics of sequences, notably TF binding models in this study. Owning to their unique expression control abilities, LCRs form an important component of integrating vectors, therefore identification of unique signatures present within LCR sequences will be instrumental in the design of new generation of regulatory elements containing LCR sequences.