John Isaac Murray - US grants

Animal development requires the differentiation of the progeny ofa single cell, the zygote, into all of the cell tj^es of the organism. One way that cells distinguish themselves from other cells is through differential 1 expression of transcriptional regulatory proteins. Specific patterns of transcription factor expression in each cell can in turn regulate downstream differentiation decisions. This project focuses on defining how transcription factors pattern the increasingly complex array of cell types during the progression of development. The ultimate goal of this work is to uncover general rules through which interactions between transcription factors, chromatin modifications and other genomic features lead to appropriate regulation of downstream target genes. We aim to generate a validated cellular resolution regulatory network of early development in the C. elegans embryo by combining genetic perturbation with in vivo resolution expression profiling. In parallel, we will test combinatorial models of transcription factor regulation of cell fate and identify direct functional targets for developmentally active transcription factors by examining the consequences of ectopic expression of each factor. When combined with other types of genomic data currently available, the results ofthese experiments will provide the basis to identify general rules governing the activity of transcription factor binding sites.

DESCRIPTION (provided by applicant): Context-dependent transcription factors play a critical role in defining which genes are regulated during development and disease, allowing the same factors to play different roles in different cells. The C. elegans embryo is an deal system for a comprehensive study of the role of lineage history in the context-dependent regulation of cell fate because of its invariant lineage and powerful experimental tools. We recently developed automated lineage tracing and expression mapping methods for C. elegans embryogenesis and measured the expression of over 127 fluorescent reporters for transcription factor (TF) expression in every cell of developing embryos. From this dataset, we identified over 30 TFs whose expression correlates directly with both lineage identity and Wnt signaling but not with terminal fate. In Aim 1, we will apply our lineage tracing methods to elucidate how context factors determine differential cellular respones to Wnt signaling, a key cell fate regulator and driver of oncogenesis. We will do this by assaying binding of the Wnt effector POP-1 to candidate targets, genome-wide mapping of POP-1 binding and detailed cis-regulatory analysis. In Aim 2, we will determine the function of TFs with lineage-specific expression by high-resolution phenotyping and genome-wide expression profiling of mutants. These studies will define mechanisms by which lineage identity is translated into cell fate and shed light on context-dependent differences in TF and Wnt targets in C. elegans and other organisms.

? DESCRIPTION (provided by applicant): Reconstructing lineage-specific gene expression in C. elegans embryos by shotgun single cell RNA-seq. A major question in biology is how cells diversify their transcriptional states to adopt unique and diverse behaviors. Single cell RNA-sequencing methods now allow analysis of many individual cells from a single population. Analysis of such shotgun single cell transcriptome data can allow inference of diverse cell states in a heterogeneous population but improved computational methods are needed to accurately reconstruct cell lineage relationships from these data. We propose here to apply shotgun single-cell RNA-seq to define lineage and cell type-specific expression dynamics and variability genome-wide and at single cell resolution in C. elegans embryos. C. elegans is an ideal system to develop methods for lineage reconstruction from single cell RNA-seq data because its invariant cell lineage and reproducible patterns of fate specification and gene expression allow mapping the single cell data to a known lineage. In addition, our previous use of imaging to define cellular resolution expression patterns for over 100 genes provides landmark genes that we will use to anchor expression patterns to the lineage. In Aim 1, we will sequence RNA from ~200 single cells from a simple lineage, `ABpxpaaaap' consisting of a mother cell and two daughters that adopt distinct fates. In Aim 2, we will develop and optimize algorithms to align the single cell data to the lineage and estimate the temporal progression and biological noise during these cells' development. The methods we propose to develop are general and could be applied to any developmental system where lineally related cells can be isolated.

To understand how cells develop or function, it is important to study equivalent cells across individuals. Comparing a cell's fate between mutant and wild-type individuals can reveal how a gene regulates development. Similarly, combining information about a neuron's structure from one animal with functional recordings of its activity in another can reveal that neuron's contribution to a circuit. Comparing information across animals requires identifying cells by some combination of cell shape, position, gene expression and lineage. However, methods to identify cell fates in complex tissues are simplex, focusing on one or a small number of cell types at a time, making it hard to assess the behavior of the full population. We propose to develop multiplexed 3D multicolor fluorescent labeling and associated hardware and software to automate cell identification in live animals. In Aim 1 we will develop this approach in the nematode C. elegans because its invariant developmental lineage and known wiring of every neuron provides a powerful platform on which to build, test and validate this approach. In Aim 2 we will apply this to understand patterns of fate transformations across the entire organism in developmental mutants. Finally in Aim 3, we will use our labeling method to identify all neurons in the adult nerve ring (brain), and combine this with whole-brain imaging methods to map for the first time activity of every neuron onto the wiring diagram.

ABSTRACT Combinatorial regulation by developmentally regulated transcription factors play a central role in defining which genes are regulated in each cell during development and disease, and allows the same factors to play different roles in different cells. The C. elegans embryo is an ideal system for a comprehensive study of the role of lineage history in the context-dependent regulation of cell fate because of its invariant lineage and powerful experimental tools. We recently developed automated lineage tracing and expression mapping methods for C. elegans embryogenesis and have built the ?Expression Patterns in Caenorhabditis? (EPIC) database that contains the expression of over 250 fluorescent reporters for transcription factor (TF) expression in every cell of developing embryos. In our past work, we have shown the potential for this resource as a starting point for defining mechanisms controlling development. While we will continue to map the expression of novel regulators, the main focus of this proposal is to use this database and our methods to address poorly understood questions in developmental biology. 1) How do cells know their lineage history and translate this information into correct terminal cell fates? We have identified a set of ~15 lineage-specific TFs whose expression distinguishes a group of progenitor cells for diverse tissues descended from the ?ABpxp? blastomeres. We plan to test whether these TFs are necessary and sufficient individually and in combination to specify the lineage identity of these progenitor cells, and to identify their targets, by imaging and genomics analysis of loss and gain-of-function mutants. We will complement this by a detailed analysis of the cis- regulatory sequences controlling terminal differentiation genes to identify their upstream regulators. These ?top-down? and ?bottom-up? approaches should eventually converge to a common regulatory network. 2) What mechanisms allow reuse of the same regulator(s) for different purposes in different developmental contexts, such as different lineages? We have identified two sets of genes, expressed in either posterior or anterior daughter cells after cell division, both of which are regulated by the Wnt pathway. We will combine enhancer fine-mapping, expression mapping of synthetic enhancers, and genome-wide binding assays for the Wnt-regulated TF POP-1/TCF to determine how each gene's response (activation or repression) to this pathway is regulated differently in different cells. 3) How does redundancy of genes and enhancers influence developmental robustness? Redundancy is extremely common in the early embryo, and we will test the hypothesis that this redundancy exists to ensure robust development in the face of environmental variability by detailed phenotyping of mutants in different conditions. In summary, the work we propose will begin to complete the early embryonic regulatory network and answer important questions about principles of development that are likely to be conserved across animals.

ABSTRACT Single cell gene expression atlases are now routinely generated for human tissues and entire model organism embryos and have shed light on the diversity of cell types and regulation of gene expression. While these wild-type single cell atlases can predict candidate regulatory genes across development for focused studies, further work is needed to determine the regulatory mechanisms and functional importance of the observed expression patterns at scale. A key problem is how to identify homologous cells between datasets in which their expression may be altered, for example data from the same tissue across evolution, or from animals that have experienced a genetic or pharmacological perturbation. This project will use the widely used model organism Caenorhabditis elegans to develop and test methods to compare cells across such conditions. Our focus is on two biological problems. In Aim 1, we will compare expression in single cells between C. elegans and four other related nematode embryos. These nematode species have nearly identical embryonic lineages to C. elegans despite substantial sequence divergence (>1 substitution per neutral site), making them an ideal test case for alignment of single cell datasets across evolution. We will generate large single cell RNA-sequencing datasets for embryos of each species (C. remanei, C. brenneri, C. briggsae and C. nigoni). We will compare both automated homology transfer and de novo lineage inference methods to identify cell types in each species. We will use quantitative imaging approaches (smFISH and live imaging of GFP knock ins) to validate the results of the single cell experiments. The resulting data will allow us to classify genes and cell types by the conservation of their gene expression, providing insight into the evolution of cell types. In Aim 2, we will test the role of conserved regulators in the specification and diversification of the mesodermal ?MS? lineage (which produces pharynx, body wall muscle, and some specialized mesodermal cell types). We will measure gene expression by scRNA-seq after conditional loss of these mesodermal regulators using an auxin degron approach. As in Aim 1, we will test and validate automated alignment methods for these datasets to identify cells. The resulting data will allow us to distinguish homeotic fate transformations from the formation of novel cell states, to distinguish likely direct or context specific targets from indirect targets of each regulator, and to generate a genome-wide mesodermal regulatory network of a developing animal embryo.