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Despite the large evolutionary distances between metazoan species, they can show remarkable commonalities in their biology, and this has helped to establish fly and worm as model organisms for human biology. Although studies of individual elements and factors have explored similarities in gene regulation, a large-scale comparative analysis of basic principles of transcriptional regulatory features is lacking. Here we map the genome-wide binding locations of 165 human, 93 worm and 52 fly transcription regulatory factors, generating a total of 1,019 data sets from diverse cell types, developmental stages, or conditions in the three species, of which 498 (48.9%) are presented here for the first time. We find that structural properties of regulatory networks are remarkably conserved and that orthologous regulatory factor families recognize similar binding motifs in vivo and show some similar co-associations. Our results suggest that gene-regulatory properties previously observed for individual factors are general principles of metazoan regulation that are remarkably well-preserved despite extensive functional divergence of individual network connections. The comparative maps of regulatory circuitry provided here will drive an improved understanding of the regulatory underpinnings of model organism biology and how these relate to human biology, development and disease.

The evolutionarily conserved family of AP-2 transcription factors (TF) regulates proliferation, differentiation, and apoptosis. Mutations in human AP-2 TF have been linked with bronchio-occular-facial syndrome and Char Syndrome, congenital birth defects characterized by craniofacial deformities and patent ductus arteriosus, respectively. How mutations in AP-2 TF cause the disease phenotypes is not well understood. Here, we characterize the aptf-2(qm27) allele in Caenorhabditis elegans, which carries a point mutation in the conserved DNA binding region of AP-2 TF. We show that compromised APTF-2 activity leads to defects in dorsal intercalation, aberrant ventral enclosure and elongation defects, ultimately culminating in the formation of morphologically deformed larvae or complete arrest during epidermal morphogenesis. Using cell lineaging, we demonstrate that APTF-2 regulates the timing of cell division, primarily in ABarp, D and C cell lineages to control the number of neuroblasts, muscle and epidermal cells. Live imaging revealed nuclear enrichment of APTF-2 in lineages affected by the qm27 mutation preceding the relevant morphogenetic events. Finally, we found that another AP-2 TF, APTF-4, is also essential for epidermal morphogenesis, in a similar yet independent manner. Thus, our study provides novel insight on the cellular-level functions of an AP-2 transcription factor in development.

Advances in microscopy and fluorescent reporters have allowed us to detect the onset of gene expression on a cell-by-cell basis in a systemic fashion. This information, however, is often encoded in large repositories of images, and developing ways to extract this spatiotemporal expression data is a difficult problem that often uses complex domain-specific methods for each individual data set. We present a more unified approach that incorporates general previous information into a hierarchical probabilistic model to extract spatiotemporal gene expression from 4D confocal microscopy images of developing Caenorhabditis elegans embryos. This approach reduces the overall error rate of our automated lineage tracing pipeline by 3.8-fold, allowing us to routinely follow the C. elegans lineage to later stages of development, where individual neuronal subspecification becomes apparent. Unlike previous methods that often use custom approaches that are organism specific, our method uses generalized linear models and extensions of standard reversible jump Markov chain Monte Carlo methods that can be readily extended to other organisms for a variety of biological inference problems relating to cell fate specification. This modeling approach is flexible and provides tractable avenues for incorporating additional previous information into the model for similar difficult high-fidelity/low error tolerance image analysis problems for systematically applied genomic experiments.

How cells adopt different expression patterns is a fundamental question of developmental biology. We quantitatively measured reporter expression of 127 genes, primarily transcription factors, in every cell and with high temporal resolution in C. elegans embryos. Embryonic cells are highly distinct in their gene expression; expression of the 127 genes studied here can distinguish nearly all pairs of cells, even between cells of the same tissue type. We observed recurrent lineage-regulated expression patterns for many genes in diverse contexts. These patterns are regulated in part by the TCF-LEF transcription factor POP-1. Other genes' reporters exhibited patterns correlated with tissue, position, and left-right asymmetry. Sequential patterns both within tissues and series of sublineages suggest regulatory pathways. Expression patterns often differ between embryonic and larval stages for the same genes, emphasizing the importance of profiling expression in different stages. This work greatly expands the number of genes in each of these categories and provides the first large-scale, digitally based, cellular resolution compendium of gene expression dynamics in live animals. The resulting data sets will be a useful resource for future research.