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Albany 2015:Book of Abstracts

Albany 2015
Conversation 19
June 9-13 2015
©Adenine Press (2012)

Quantitative Modeling of Transcription Factor Binding Specificities Using DNA Shape

DNA binding specificities of transcription factors (TFs) are a key component of gene regulatory processes. Underlying mechanisms that explain the highly specific binding of TFs to their genomic target sites are poorly understood. A better understanding of TF-DNA binding requires the ability to quantitatively model TF binding to accessible DNA as its basic step, before additional in vivo components can be considered. Traditionally, these models were built based on nucleotide sequence. Here, we integrated three-dimensional DNA shape information derived with a high-throughput approach into the modeling of TF binding specificities. Using support vector regression, we trained quantitative models of TF binding specificity based on protein binding microarray (PBM) data for 68 mammalian TFs. The evaluation of our models included cross-validation on specific PBM array designs, testing across different PBM array designs, and using PBM-trained models to predict relative binding affinities derived from SELEX-seq data. Our results showed that shape-augmented models compared favorably to sequence-based models. Although both k-mer and DNA shape features can encode interdependencies between nucleotide positions of the binding site, using DNA shape features reduced the dimensionality of the feature space. In addition, analyzing the feature weights of DNA shape-augmented models uncovered TF family-specific structural readout mechanisms that were not revealed by the DNA sequence. As such, this work combines knowledge from structural biology and genomics, and suggests a new path towards understanding TF binding and genome function.

Tianyin Zhou1
Ning Shen2
Lin Yang1
Namiko Abe3
John Horton2
Richard S. Mann3
Harmen J. Bussemaker4
Raluca Gordan2
Remo Rohs1

1Molecular and Computational Biology Program
University of Southern California
Los Angeles, CA 90089, USA
2Center for Genomic and Computational Biology
Duke University
Durham, NC 27708, USA
3Department of Biochemistry and Molecular Biophysics
Columbia University Medical Center
New York, NY 10032, USA
4Department of Biological Sciences
Columbia University
New York, NY 10027, USA

rohs@usc.edu