Development of a bacterial regulatory motif database

O b j e c t i v e s . The amount of data generated by modern methods of high-throughput sequencing is such that their analysis is performed mainly in automatic mode. In particular, the use of newly decoded genomic sequences is possible only after the annotation of functional elements of the genome, which, as a rule, is performed by automatic pipelines. Such annotation pipelines do a good job to identify the genes, but none of them annotate regulatory elements. Without these elements it is not possible to understand when and how genes can be expressed. Information on the regulatory elements of bacteria is collected in several specialized databases (RegulonDB, CollecTF, Prodoric2, etc.), however, only a part of this information can be used for annotation of regulatory elements, and only for a very limited range of bacteria. Previously, we proposed a clear formal criterion for applying regulatory information to any bacterial genome. Such a criterion is the CR tag, a sequence of amino acid residues of a transcriptional regulator that specifically contacts the nitrogenous bases of regulatory element in genomic DNA. The mathematical model of a regulatory element (motif) associated with a CR tag can be correctly applied to annotate similar elements in any genomes encoding a transcriptional regulator with an identical CR tag. The accumulation of motifs associated with CR tags raised the question of their ordered storage for the convenience of subsequent use in the annotation of genomic sequences. Since no one of well-known databases uses the concept of CR tags, a new database ought to be developed. Thus, the goal of this work is to create a database with information about bacterial transcription factors and DNA sequences recognized by them, suitable for annotation of regulatory sequences in bacterial genomes.

M e t h o d s .  Infological  modeling  of  the  subject  area  was  carried  out  using  the  IDEF1X  methodology. The database was developed using the Microsoft SQL Server DBMS. A cross-platform application for importing data into a database is written in C++ using Qt technology.

Re s u l t s . As a result of the study of the subject area, a relational data model was developed and implemented in the Microsoft SQL Server DBMS, which allows holistic storage of information about accumulated transcription regulation motifs in bacteria, including information about the publications confirming their correctness. To automate the process of entering accumulated data, a cross-platform application was developed for importing structured data on transcription factors.

Co n c l u s i o n .  The  main difference of  the  developed database is  the  use  of  CR-tag  concept. Records of mathematical models of regulatory elements (motifs) in the database are associated with a CR tag and, therefore, can be correctly used to annotate similar elements in any genomes encoding a transcriptional regulator with an identical CR tag. The developed database will provide structured and holistic data storage, as well as their quick search when used in the pipeline for automatic annotation of regulatory elements in bacterial genomic sequences.

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