TEMPLE: analysing population genetic variation at transcription factor binding sites.
Genetic variation occurring at the level of regulatory sequences can affect phenotypes and fitness in natural populations. This variation can be analysed in a population genetic framework to study how genetic drift and selection affect the evolution of these functional elements. However, doing this requires a good understanding of the location and nature of regulatory regions and has long been a major hurdle. The current proliferation of genomewide profiling experiments of transcription factor occupancies greatly improves our ability to identify genomic regions involved in specific DNA-protein interactions. Although software exists for predicting transcription factor binding sites (TFBS), and the effects of genetic variants on TFBS specificity, there are no tools currently available for inferring this information jointly with the genetic variation at TFBS in natural populations. We developed the software Transcription Elements Mapping at the Population LEvel (TEMPLE), which predicts TFBS, evaluates the effects of genetic variants on TFBS specificity and summarizes the genetic variation occurring at TFBS in intraspecific sequence alignments. We demonstrate that TEMPLE's TFBS prediction algorithms gives identical results to PATSER, a software distribution commonly used in the field. We also illustrate the unique features of TEMPLE by analysing TFBS diversity for the TF Senseless (SENS) in one ancestral and one cosmopolitan population of the fruit fly Drosophila melanogaster. TEMPLE can be used to localize TFBS that are characterized by strong genetic differentiation across natural populations. This will be particularly useful for studies aiming to identify adaptive mutations. TEMPLE is a java-based cross-platform software that easily maps the genetic diversity at predicted TFBSs using a graphical interface, or from the Unix command line.
School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland. maria.litovchenko@epfl.ch.|Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland. maria.litovchenko@epfl.ch.
Maria
M
Litovchenko
School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland. stefan.laurent@epfl.ch.|Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland. stefan.laurent@epfl.ch.
Stefan
S
Laurent
D000818:Animals; D001665:Binding Sites; D019295:Computational Biology / Q000379:methods*; D004247:DNA / Q000235:genetics / Q000378:metabolism*; D004331:Drosophila melanogaster / Q000235:genetics*; D014644:Genetic Variation; D005828:Genetics, Population; D012984:Software; D014157:Transcription Factors / Q000235:genetics / Q000378:metabolism*; D014158:Transcription, Genetic
D014157:Transcription Factors; D004247:DNA
evolution; genetic diversity; population genetics; position weight matrice; regulatory evolution; transcription factor binding sites