Zebrahub: RNA-sequencing analysis

Schematic of the analysis workflow to understand differences between genetically identical embryos. For each gene, we compare the distribution of counts across single-cells using the Kullback–Leibler divergence metric.

This repository is part of a manuscript: zebrahub

Summary

Elucidating the developmental process of an organism will require the complete cartography of cellular lineages in the spatial, temporal, and molecular domains. We present Zebrahub, a comprehensive dynamic atlas of zebrafish embryonic development that combines single-cell sequencing time course data with light-sheet microscopy-based lineage reconstructions. Zebrahub is a foundational resource to study developmental processes at both transcriptional and spatiotemporal levels. It is publicly accessible as a web-based resource, providing an open-access collection of datasets and tools.

This repository contains a collection of scripts and notebooks to analyze Zebrahub's single-cell RNA seq data and generate the corresponding figures as published in the manuscript.

For analysis of imaging data, please refere to https://github.com/royerlab/in-silico-fate-mapping

The manuscript is published here: https://www.biorxiv.org/content/10.1101/2023.03.06.531398v1 Data is accesible through the Zebrahub portal: https://zebrahub.ds.czbiohub.org/

Table of Contents

• Repo organization
• Setting up an environment
• Citing

Organization

Each folder contains the notebooks used for the following analyses:

• scRNAseq processing (pre_processing + clustering)
• RNA velocity (scVelo + single-cell velocity quantification)
• State transition analysis from RNA velocity methods (state_transitions)
• embryo gene expression variability (Kullback–Leibler divergence)

The structure of this repo is illustrated below.

├── pre-processing (contains pre-processing, timepoint integration and clustering notebooks)
│   ├── Aligned_UMAPs_EarlyTimepoints.ipynb/ (notebook creates aligned UMAP for early timepoints, using k-NN for UMAP clusters in adjacent timepoints)
│   ├── Integrated_Embedding_3D_UMAPs.ipynb/ (notebook for intergration of 3D UMAPs)
│   ├── Integrated_Embedding_EarlyTimepoints.ipynb/ (notebook for integrated UMAP global embedding using Seurat)
│   ├── Sequencing_QualityControl.ipynb/ (notebook loads CellRanger files, generated adata, conducts QC/clustering/UMAP)
├── RNA_velocity (contains RNA velocity analyses)
│   ├── RNA_Velocity_FullAtlas.ipynb/ (notebook creates RNA velocity graph and visualization for all early timepoints)
│   ├── RNA_velocity_NMP_lineages.ipynb/ (notebook creates RNA velocity graph and visualization for NMP lineages, individual timepoints)
├── state_transitions (contains state transitions analysis from RNA velocity notebook)
│   ├── RNA_velocity_transition_graph.ipynb/ (notebook creates state transition graph from single-cell RNA velocity)
├── embryo_gene_expression_variability (contains mpKLD analysis notebooks)
│   ├── Inter-Embryo_Divergence_DataFrames.ipynb/ (notebook that creates mpKLD dataframes, and null model mpKLD dataframe)
│   ├── Inter-Embryo_Divergence_PathwayAnalysis_Plots.ipynb/ (notebook for cleaning, pathway analysis, plots found in Fig2a-2d)
│   ├── zf2mouse.txt/ (file with analogous genes for pathway analysis)
│   ├── README.md/
└── README.md

Setting up a conda environment

We set up the conda environment to run the inter-embryo analysis notebooks by running the following commands in the terminal:

# Create the environment with Python version 3.8.13 to be compatible with other packages
conda create -c conda-forge python=3.8.13 -n zebrahub_inter-embryo_analysis

#Activate the conda environment
conda activate zebrahub_inter-embryo_analysis

# Install Jupyter Lab
conda install -c conda-forge jupyterlab

# Install necessary packages
conda install ipykernel

# we need matplotlib version 3.6 to be compatible with scanpy

conda install seaborn
conda install scanpy
conda install matplotlib=3.6
conda install -c conda-forge re2
conda install -c jmcmurray json
conda install -c anaconda requests

Citing

If used plase cite:

@article{lange2023zebrahub,
  title={Zebrahub-Multimodal Zebrafish Developmental Atlas Reveals the State Transition Dynamics of Late Vertebrate Pluripotent Axial Progenitors},
  author={Lange, Merlin and Granados, Alejandro and VijayKumar, Shruthi and Bragantini, Jordao and Ancheta, Sarah and Santhosh, Sreejith and Borja, Michael and Kobayashi, Hirofumi and McGeever, Erin and Solak, Ahmet Can and others},
  journal={bioRxiv},
  pages={2023--03},
  year={2023},
  publisher={Cold Spring Harbor Laboratory}
}