Proper cell fate determination is largely orchestrated by complex gene regulatory networks centered around transcription factors. However, experimental elucidation of key transcription factors that drive cellular identity is currently often intractable. Here, we present ANANSE (ANalysis Algorithm for Networks Specified by Enhancers), a network-based method that exploits enhancer-encoded regulatory information to identify the key transcription factors in cell fate determination. As cell type-specific transcription factors predominantly bind to enhancers, we use regulatory networks based on enhancer properties to prioritize transcription factors. First, we predict genome-wide binding profiles of transcription factors in various cell types using enhancer activity and transcription factor binding motifs. Subsequently, applying these inferred binding profiles, we construct cell type-specific gene regulatory networks, and then predict key transcription factors controlling cell fate transitions using differential networks between cell types. This method outperforms existing approaches in correctly predicting major transcription factors previously identified to be sufficient for trans-differentiation. Finally, we apply ANANSE to define an atlas of key transcription factors in 18 normal human tissues. In conclusion, we present a ready-to-implement computational tool for efficient prediction of transcription factors in cell fate determination and to study transcription factor-mediated regulatory mechanisms. ANANSE is freely available at https://github.com/vanheeringen-lab/ANANSE.

Highlights d Nonhuman primates recapitulate trained immunity upon live attenuated TB vaccination d Intravenous BCG induces changes in H3K27 acetylation and enhances cytokine production d Mucosal BCG improves induction of trained immunity of monocytes over intradermal BCG d The M. tuberculosis-derived candidate vaccine MTBVAC appears equally potent as BCG

During vertebrate gastrulation, mesoderm is induced in pluripotent cells, concomitant with dorsal-ventral patterning and establishing of the dorsal axis. We applied single-cell chromatin accessibility and transcriptome analyses to explore the emergence of cellular heterogeneity during gastrulation in Xenopus tropicalis. Transcriptionally inactive lineage-restricted genes exhibit relatively open chromatin in animal caps, whereas chromatin accessibility in dorsal marginal zone cells more closely reflects transcriptional activity. We characterized single-cell trajectories and identified head and trunk organizer cell clusters in early gastrulae. By integrating chromatin accessibility and transcriptome data, we inferred the activity of transcription factors in single-cell clusters and tested the activity of organizer-expressed transcription factors in animal caps, alone or in combination. The expression profile induced by a combination of Foxb1 and Eomes most closely resembles that observed in the head organizer. Genes induced by Eomes, Otx2, or the Irx3-Otx2 combination are enriched for maternally regulated H3K4me3 modifications, whereas Lhx8induced genes are marked more frequently by zygotically controlled H3K4me3. Taken together, our results show that transcription factors cooperate in a combinatorial fashion in generally open chromatin to orchestrate zygotic gene expression.