Protocol to identify transcription factor target genes using TargetOrtho2: https://star-protocols.cell.com/protocols/4076
Latest Version of TargetOrtho2.0 for Python3: https://github.com/jdrumley1989/TargetOrtho2_Python3/tree/main
Old Version of TargetOrtho2.0: https://github.com/loriglenwinkel/TargetOrtho2.0
Instructional videos for TargetOrtho2.0 use and installation: https://www.youtube.com/@JonathanRumleyPhD
References:
eLife 10:e64906 (2021)
Authors: Glenwinkel L, Taylor SR, Langebeck-Jensen K, Pereira L, Reilly MB, Basavaraju M, Rafi I, Yemini E, Pocock R, Sestan N, Hammarlund M, Miller III DM, Hobert O.
Abstract
The generation of the enormous diversity of neuronal cell types in a differentiating nervous system entails the activation of neuron type-specific gene batteries. To examine the regulatory logic that controls the expression of neuron type-specific gene batteries, we interrogate single cell expression profiles of all 118 neuron classes of the Caenorhabditis elegans nervous system for the presence of DNA binding motifs of 136 neuronally expressed C. elegans transcription factors. Using a phylogenetic footprinting pipeline, we identify cis-regulatory motif enrichments among neuron class-specific gene batteries and we identify cognate transcription factors for 117 of the 118 neuron classes. In addition to predicting novel regulators of neuronal identities, our nervous system-wide analysis at single cell resolution supports the hypothesis that many transcription factors directly co-regulate the cohort of effector genes that define a neuron type, thereby corroborating the concept of so-called terminal selectors of neuronal identity. Our analysis provides a blueprint for how individual components of an entire nervous system are genetically specified.
PMID: 34165430
(2) TargetOrtho: a phylogenetic footprinting tool to identify transcription factor targets.
Genetics. 2014 May;197(1):61-76
Authors: Glenwinkel L, Wu D, Minevich G, Hobert O
Abstract
The identification of the regulatory targets of transcription factors is central to our understanding of how transcription factors fulfill their many key roles in development and homeostasis. DNA-binding sites have been uncovered for many transcription factors through a number of experimental approaches, but it has proven difficult to use this binding site information to reliably predict transcription factor target genes in genomic sequence space. Using the nematode Caenorhabditis elegans and other related nematode species as a starting point, we describe here a bioinformatic pipeline that identifies potential transcription factor target genes from genomic sequences. Among the key features of this pipeline is the use of sequence conservation of transcription-factor-binding sites in related species. Rather than using aligned genomic DNA sequences from the genomes of multiple species as a starting point, TargetOrtho scans related genome sequences independently for matches to user-provided transcription-factor-binding motifs, assigns motif matches to adjacent genes, and then determines whether orthologous genes in different species also contain motif matches. We validate TargetOrtho by identifying previously characterized targets of three different types of transcription factors in C. elegans, and we use TargetOrtho to identify novel target genes of the Collier/Olf/EBF transcription factor UNC-3 in C. elegans ventral nerve cord motor neurons. We have also implemented the use of TargetOrtho in Drosophila melanogaster using conservation among five species in the D. melanogaster species subgroup for target gene discovery.
PMID: 24558259
(3) Protocol to identify transcription factor target genes using TargetOrtho2
STAR Protocols. 2025 (6)1: 103680
TargetOrtho2 uses transcription factor binding site information to predict transcription factor targets in C. elegans, based on an in silico phylogenetic footprinting approach. Here, we present a protocol to identify transcription factor target genes using a new version of TargetOrtho2. We provide instructions for installing TargetOrtho2 and its required suite of programs, for predicting transcription factor target genes, and for updating and adding new genomes to TargetOrtho2.