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Updated: Jul 5, 2025
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High Sensitivity Measurement of Transcription Factor-DNA Binding Affinities by Competitive Titration Using Fluorescence Microscopy
Published on: February 7, 2019
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Position-specific evolution in transcription factor binding sites, and a fast likelihood calculation for the F81
Pavitra Selvakumar1,2, Rahul Siddharthan1,2
1The Institute of Mathematical Sciences, Chennai, India.
Royal Society Open Science
|January 25, 2024
Summary
New position-specific stationary vectors (PSSVs) reveal how nucleotide fitness shapes transcription factor binding sites (TFBS) evolution. This method uncovers evolutionary pressures exerted by ancestral nucleotides on DNA sequences.
Area of Science:
- Evolutionary biology
- Bioinformatics
- Genomics
Background:
- Transcription factor binding sites (TFBS) are crucial DNA sequences that regulate gene expression.
- Understanding the evolutionary dynamics of TFBS is essential for deciphering gene regulation.
- Existing models often assume uniform nucleotide evolution, which may not accurately represent functional DNA sites like TFBS.
Purpose of the Study:
- To introduce and validate a new method, position-specific stationary vectors (PSSVs), for analyzing TFBS evolution.
- To compare PSSVs with traditional position weight matrices (PWMs) in characterizing TFBS nucleotide distributions.
- To investigate the influence of ancestral nucleotides on the evolutionary trajectory of TFBS.
Main Methods:
- Inferred PSSVs for human transcription factors using two established evolutionary models: Felsenstein 1981 (F81) and Hasegawa-Kishino-Yano 1985 (HKY85).
- Compared inferred PSSVs with nucleotide distributions derived from PWMs.
- Calculated conditional PSSVs based on inferred ancestral nucleotide states to assess evolutionary pressures.
Main Results:
- PSSVs successfully capture nucleotide distributions within TFBS, analogous to PWMs but with potentially reduced specificity.
- Analysis revealed that certain ancestral nucleotides exert significant evolutionary pressure on neighboring sequences within TFBS.
- A computationally efficient likelihood calculation for the F81 model was developed, enabling large-scale TFBS evolutionary studies.
Conclusions:
- PSSVs offer a novel, evolutionarily informed perspective on TFBS sequence composition and function.
- The inferred evolutionary pressures highlight the complex interplay between nucleotide identity, position, and functional constraint in TFBS.
- The developed computational methods facilitate broader application of evolutionary sequence analysis to TFBS research.
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