Our understanding of the maternal factors that initiate early chordate development, and of their direct zygotic targets, is still fragmentary. A molecular cascade is emerging for the mesendoderm, but less is known about the ectoderm, giving rise to epidermis and nervous tissue. Our cis-regulatory analysis surprisingly places the maternal transcription factor Ci-GATAa (GATA4/5/6) at the top of the ectodermal regulatory network in ascidians. Initially distributed throughout the embryo, Ci-GATAa activity is progressively repressed in vegetal territories by accumulating maternal ␤-catenin. Once restricted to the animal hemisphere, Ci-GATAa directly activates two types of zygotic ectodermal genes. First, Ci-fog is activated from the 8-cell stage throughout the ectoderm, then Ci-otx is turned on from the 32-cell stage in neural precursors only. Whereas the enhancers of both genes contain critical and interchangeable GATA sites, their distinct patterns of activation stem from the additional presence of two Ets sites in the Ci-otx enhancer. Initially characterized as activating elements in the neural lineages, these Ets sites additionally act as repressors in nonneural lineages, and restrict GATA-mediated activation of Ci-otx. We thus identify a precise combinatorial code of maternal factors responsible for zygotic onset of a chordate ectodermal genetic program.

BackgroundThe past few years have seen a vast increase in the amount of genomic data available for a growing number of taxa, including sets of full length cDNA clones and cis-regulatory sequences. Large scale cross-species comparisons of protein function and cis-regulatory sequences may help to understand the emergence of specific traits during evolution.Principal FindingsTo facilitate such comparisons, we developed a Gateway compatible vector set, which can be used to systematically dissect cis-regulatory sequences, and overexpress wild type or tagged proteins in a variety of chordate systems. It was developed and first characterised in the embryos of the ascidian Ciona intestinalis, in which large scale analyses are easier to perform than in vertebrates, owing to the very efficient embryo electroporation protocol available in this organism. Its use was then extended to fish embryos and cultured mammalian cells.ConclusionThis versatile vector set opens the way to the mid- to large-scale comparative analyses of protein function and cis-regulatory sequences across chordate evolution. A complete user manual is provided as supplemental material.

Developmental biology aims to understand how the dynamics of embryonic shapes and organ functions are encoded in linear DNA molecules. Thanks to recent progress in genomics and imaging technologies, systemic approaches are now used in parallel with small-scale studies to establish links between genomic information and phenotypes, often described at the subcellular level. Current model organism databases, however, do not integrate heterogeneous data sets at different scales into a global view of the developmental program. Here, we present a novel, generic digital system, NISEED, and its implementation, ANISEED, to ascidians, which are invertebrate chordates suitable for developmental systems biology approaches. ANISEED hosts an unprecedented combination of anatomical and molecular data on ascidian development. This includes the first detailed anatomical ontologies for these embryos, and quantitative geometrical descriptions of developing cells obtained from reconstructed three-dimensional (3D) embryos up to the gastrula stages. Fully annotated gene model sets are linked to 30,000 high-resolution spatial gene expression patterns in wild-type and experimentally manipulated conditions and to 528 experimentally validated cis-regulatory regions imported from specialized databases or extracted from 160 literature articles. This highly structured data set can be explored via a Developmental Browser, a Genome Browser, and a 3D Virtual Embryo module. We show how integration of heterogeneous data in ANISEED can provide a system-level understanding of the developmental program through the automatic inference of gene regulatory interactions, the identification of inducing signals, and the discovery and explanation of novel asymmetric divisions.