CelEst: a unified gene regulatory network for estimating transcription factor activities in C. elegans

Transcription factors (TFs) play a pivotal role in orchestrating critical intricate patterns of gene regulation. Although gene expression is complex, differential expression of hundreds of genes is often due to regulation by just a handful of TFs. Despite extensive efforts to elucidate TF-target regulatory relationships in Caenorhabditis elegans, existing experimental datasets cover distinct subsets of TFs and leave data integration challenging. Here, I introduce CelEst, a unified gene regulatory network designed to estimate the activity of 487 distinct C. elegans TFs-∼58% of the total-from gene expression data. To integrate data from ChIP-seq, DNA-binding motifs, and eY1H screens, optimal processing of each data type was benchmarked against a set of TF perturbation RNA-seq experiments. Moreover, I showcase how leveraging TF motif conservation in target promoters across genomes of related species can distinguish highly informative interactions, a strategy which can be applied to many model organisms. Integrated analyses of data from commonly studied conditions including heat shock, bacterial infection, and sex differences validates CelEst's performance and highlights overlooked TFs that likely play major roles in coordinating the transcriptional response to these conditions. CelEst can infer TF activity on a standard laptop computer within minutes. Furthermore, an R Shiny app with a step-by-step guide is provided for the community to perform rapid analysis with minimal coding required. I anticipate that widespread adoption of CelEsT will significantly enhance the interpretive power of transcriptomic experiments, both present and retrospective, thereby advancing our understanding of gene regulation in C. elegans and beyond.