Affiliations: Institute for Information Transmission Problems of the
Russian Academy of Sciences (Kharkevich Institute), Moscow, Russia | State Research Institute for Genetics and Selection of
Industrial Microorganisms, Moscow, Russia | Burnham Institute, La Jolla, CA, USA
Abstract: Unlike evolution of genes and proteins, evolution of regulatory
systems is a relatively new area of research. In particular, little systematic
study has been done on evolution of DNA binding motifs in transcription factor
families. We suggest an algorithm that reconstructs the most parsimonious
scenario for changes in DNA binding motifs along an evolutionary tree of
transcription factor binding sites. The algorithm was validated on several
artificial datasets and then applied to reconstruct the evolutionary history of
the NrdR, MntR, LacI, FNR, Irr, Fur and Rrf2 transcription factor families. The
algorithm seems to be sufficiently robust to be applicable in realistic
situations. In most transcription factor families the changes in binding motifs
are limited to several branches. Changes in consensus nucleotides proceed via
an intermediate stage when the respective position is not conserved.
Keywords: Evolutionary scenario, regulatory signal, frequency matrix, evolution along a tree, transcription factor tree