Decoding animal genomes into cell types

Introduction

The genome of an animal encodes a large set of regulatory programs that give rise to the thousands of cell types that make up its tissues and organs. Despite recent progress in single-cell omics, our knowledge about the regulatory programs that control the establishment and maintenance of cell type identity remains limited. Moreover, methods are lacking to infer regulatory programs directly from the genome sequence.

Project Overview

In this project, which lies at the interface between the genome and single-cell atlases, we ask how the genome sequence “translates” into cell types. We start with Drosophila as a model organism. Its compactness allows sampling of all its cell types and developmental trajectories from egg to adult, using whole-organism single-cell multi-omics. This approach captures the spectrum of “activation states” that emerge from the regulatory genome.

Methodology

Deep learning models will be trained on regulatory sequences to predict and explain gene regulatory networks (GRN) and GRN transitions between cell states. These are encoded by:

1. Enhancers
2. Promoters
3. Transcription factors (TF)
4. Effector genes
5. Feedback loops

Based on a better mechanistic understanding, we will translate this framework to other animals, including octopus, birds, and mammals. We will investigate how regulatory programs evolve, with a focus on neuronal diversity in the brain.

Innovative Approaches

Using new algorithms for cross-species deep learning and combinatorial optimization, we will study how combinations of expressed TFs co-evolve with genomic enhancer logic.

We are unique in our approach because we will:

• Develop and use new technological assays
• Implement deep learning and massively parallel reporter assays
• Combine these with perturbation experiments and synthetic biology to test our hypotheses

Goals

After iteratively improving our regulatory models, we ultimately aim to predict which regulatory programs, and thus which cell types, are encoded in an animal’s genome. Additionally, we will explore how changes in these programs underlie changes in cell types during evolution.