Distinct waves from the hemogenic endothelium give rise to layered Lymphoid Tissue Inducer cell ontogeny
Article information
Title: Distinct waves from the hemogenic endothelium give rise to layered Lymphoid Tissue Inducer cell ontogeny.
Authors: Milesa Simic 1, Iris Manosalva 1, Lionel Spinelli 1 , Rebecca Gentek 1&, Raheleh R. Shayan 1, Carole Siret 1, Mathilde Girard-Madoux 1, Shuaiwei Wang 1, Lauriane de Fabritus 1, Janneke Verschoor 1, Yann M. Kerdiles 1, Marc Bajenoff 1, Ralf Stumm 2, Rachel Golub 3, Serge A. van de Pavert 1%
1 Aix-Marseille Univ, Centre National de la Recherche Scientifique (CNRS), Institut National de la Santé et de la Recherche Médicale (INSERM), Centre d'Immunologie de Marseille-Luminy (CIML), Marseille, France.
2 Institute of Pharmacology and Toxicology, Jena University Hospital, Friedrich Schiller University Jena, 07747 Jena, Germany. 3 Institut Pasteur, Immunology Department, Lymphopoiesis Unit, Inserm U668, University Paris Diderot, Paris, France.
& Currently at at Centre for Inflammation Research (CIR), Institute of Regeneration and Repair, University of Edinburgh, Edinburgh, United Kingdom
% Corresponding author: E-mail: vandepavert@ciml.univ-mrs.fr
Summary: During embryogenesis Lymphoid Tissue Inducer (LTi) cells are essential for lymph node organogenesis. These cells are part of the Innate Lymphoid Cell (ILC) family. Although their earliest embryonic hematopoietic origin is unclear, other innate immune cells were shown to be derived from both early hemogenic endothelium in the yolk-sac as well as the aorta-gonad-mesonephros. A proper model to discriminate between these locations was unavailable. In this study, using a new Cxcr4-CreERT2 lineage tracing model, we identify a major contribution from embryonic hemogenic endothelium, but not yolk-sac, towards the LTi progenitors. Conversely, embryonic LTi cells are replaced by hematopoietic stem cell derived cells in adult. We further show that within the fetal liver common lymphoid progenitors differentiate into highly dynamic alpha-lymphoid precursor cells, which at this embryonic stage preferentially mature into LTi precursors and establish their functional LTi cell identity only after reaching the periphery.
Goal of the github
This github project contains the instructions and material to reproduce the analysis reported in the article (and more). Source code (scripts and dockerfiles) are available in the github repository. Required data and builded Docker/Singularity images are available on download. Instructions to reproduce the analysis are provided below.
To reproduce the analysis, you have to first, prepare the environments (see "Prepare the Environments" section below), then execute the analysis step by step (see "Run the analysis" section below).
Description of the datasets
As described in the article, there is 5 datasets in this study. One datset is a bulk sequencing of mRNA on two embryo tissues (Fetal Liver and Periphery) at stage 13.5 days. The other 4 datasets are single-cell sequencing of mRNA on two embryo tissues (Fetal Liver and Periphery) and two stages (13.5 and 14.5 days). When downloading the code and data, you will obtains 5 sub-folders with names as below:
BecomingLTi
├── Embryo_Bulk_Stage13.5_2tissues : Bulk RNA-seq of Embryo Fetal Liver and periphery tissues at stage 13.5 days
├── Embryo_Stage13.5_FetalLiver : Single-cell RNA-seq of Embryo Fetal Liver tissue at stage 13.5 days
├── Embryo_Stage13.5_Periphery_CellRangerV3 : Single-cell RNA-seq of Embryo Periphery tissue at stage 13.5 days
├── Embryo_Stage14.5_FetalLiver : : Single-cell RNA-seq of Embryo Fetal Liver tissue at stage 14.5 days
└── Embryo_Stage14.5_Periphery_CellRangerV3 : Single-cell RNA-seq of Embryo Periphery tissue at stage 14.5 days
Prepare the environments
In order to prepare the environment for analysis execution, it is required to:
- Clone the github repository and set the WORKING_DIR environment variable
- Download the docker image tar file and the singularity img files
- Install Docker and Singularity
- Load the docker image on your system
- Download the pre-processed data (Count table for bulk RNA-seq and CellRanger results for single-cell RNA-seq)
Below you will find detailed instruction for each of these steps.
Clone the github repository
Use you favorite method to clone this repository in a chosen folder. This will create a folder "BecomingLTi" with all the source code.
Then, you must set an environment variable called WORKING_DIR with a value set to the path to this folder.
For instance, if you have chosen to clone the Git repository in "/home/spinellil/workspace", then the WORKING_DIR variable will be set to "/home/spinellil/workspace/BecomingLTi"
On linux:
export WORKING_DIR=/home/spinellil/workspace/BecomingLTi
Download the raw data
Each sample needs its own "00_RawData" sub-folder containing the initial data used by the analysis. Those data can be downloaded from Zenodo and uncompressed. The Zenodo dataset DOI are 
To download and uncompress the data, use the following code:
On linux:
cd $WORKING_DIR
wget https://zenodo.org/record/3946154/files/SPlab_BecomingLTi_Bulk_Stage13.5_2tissues_00_RawData.tar.gz?download=1 -O SPlab_BecomingLTi_Bulk_Stage13.5_2tissues_00_RawData.tar.gz
tar zxvf SPlab_BecomingLTi_Bulk_Stage13.5_2tissues_00_RawData.tar.gz
wget https://zenodo.org/record/3946361/files/SPlab_BecomingLTi_Stage13.5_FetalLiver_00_RawData.tar.gz?download=1 -O SPlab_BecomingLTi_Stage13.5_FetalLiver_00_RawData.tar.gz
tar zxvf SPlab_BecomingLTi_Stage13.5_FetalLiver_00_RawData.tar.gz
wget https://zenodo.org/record/3946154/files/SPlab_BecomingLTi_Stage13.5_Periphery_CellRangerV3_00_RawData.tar.gz?download=1 -O SPlab_BecomingLTi_Stage13.5_Periphery_CellRangerV3_00_RawData.tar.gz
tar zxvf SPlab_BecomingLTi_Stage13.5_Periphery_CellRangerV3_00_RawData.tar.gz
wget https://zenodo.org/record/3947819/files/SPlab_BecomingLTi_Stage14.5_FetalLiver_00_RawData.tar.gz?download=1 -O SPlab_BecomingLTi_Stage14.5_FetalLiver_00_RawData.tar.gz
tar zxvf SPlab_BecomingLTi_Stage14.5_FetalLiver_00_RawData.tar.gz
wget https://zenodo.org/record/3946154/files/SPlab_BecomingLTi_Stage14.5_Periphery_CellRangerV3_00_RawData.tar.gz?download=1 -O SPlab_BecomingLTi_Stage14.5_Periphery_CellRangerV3_00_RawData.tar.gz
tar zxvf SPlab_BecomingLTi_Stage14.5_Periphery_CellRangerV3_00_RawData.tar.gz
Once done, you may obtain the following subfolder structure, each of them containing several files.
BecomingLTi
├── Embryo_Bulk_Stage13.5_2tissues
│ └── 00_RawData
├── Embryo_Stage13.5_FetalLiver
│ └── 00_RawData
├── Embryo_Stage13.5_Periphery_CellRangerv3
│ └── 00_RawData
├── Embryo_Stage14.5_FetalLiver
│ └── 00_RawData
└── Embryo_Stage14.5_Periphery_CellRangerv3
└── 00_RawData
Download the reference files
The study uses references (genome annotations) you have to download. The annotations used during the study are available on Zenodo 
Note: Since the reference files are used for the 4 single-cell samples analysis, they must be present in all the sample folder in the same 01_Reference subfolder. Instead of copying the files, we will create symbolic links:
On linux:
cd $WORKING_DIR
wget https://zenodo.org/record/3949849/files/SPlab_BecomingLTi_01_Reference.tar.gz?download=1 -O SPlab_BecomingLTi_01_Reference.tar.gz
tar zxvf SPlab_BecomingLTi_01_Reference.tar.gz
ln -s Embryo_Stage13.5_FetalLiver/01_Reference Embryo_Stage13.5_Periphery_CellRangerV3/01_Reference
ln -s Embryo_Stage13.5_FetalLiver/01_Reference Embryo_Stage14.5_FetalLiver/01_Reference
ln -s Embryo_Stage13.5_FetalLiver/01_Reference Embryo_Stage14.5_Periphery_CellRangerV3/01_Reference
These commands will create 4 sub-folders named 01_Reference:
BecomingLTi
├── Embryo_Stage13.5_FetalLiver
│ └── 01_Reference
├── Embryo_Stage13.5_Periphery_CellRangerv3
│ └── 01_Reference
├── Embryo_Stage14.5_FetalLiver
│ └── 01_Reference
└── Embryo_Stage14.5_Periphery_CellRangerv3
└── 01_Reference
Download the Docker and Singularity images
Docker image tar file and Singularity img files are stored on Zenodo
On linux:
cd $WORKING_DIR
wget https://zenodo.org/record/3949849/files/SPlab_BecomingLTi_02_containers.tar.gz?download=1 -O SPlab_BecomingLTi_02_containers.tar.gz
tar zxvf SPlab_BecomingLTi_02_containers.tar.gz
These commands will create 2 sub-folders named 02_Container:
BecomingLTi
├── Embryo_Bulk_Stage13.5_2tissues
│ └── 02_Container
└── Embryo_Stage13.5_FetalLiver
└── 02_Container
The first one contains a Docker image tar file used for the bulk RNA-seq analysis. The second one contains the Singularity images for the single-cell RNA-seq analysis. Since the singularity images are used for the 4 single-cell samples analysis, they must be present in all the sample folder in the same 02_Container subfolder. Instead of copying the image files, we will create symbolic links:
On linux:
cd $WORKING_DIR
ln -s Embryo_Stage13.5_FetalLiver/02_Container Embryo_Stage13.5_Periphery_CellRangerV3/02_Container
ln -s Embryo_Stage13.5_FetalLiver/02_Container Embryo_Stage14.5_FetalLiver/02_Container
ln -s Embryo_Stage13.5_FetalLiver/02_Container Embryo_Stage14.5_Periphery_CellRangerV3/02_Container
Install Docker and Singularity
You need to install Docker and Singularity v2.6 on your system.
-
To install Docker, follow the instructions here : https://docs.docker.com/get-docker/
-
To install Singularity v2.6, follow the instructions here : https://sylabs.io/guides/2.6/admin-guide/
Load docker images on the system
In order to execute analysis of the bulk RNA-seq, you must load the provided docker image onto your Docker. Docker must be installed on your system. See https://docs.docker.com/install/ for details on Docker installation. Open a shell command and type:
On linux:
docker load -i $WORKING_DIR/Embryo_Bulk_Stage13.5_2tissues/02_Container/splab_ilcyou_deg_gsea.tar
This command may take some time. If you encounter an issue loading some docker image layer, try again. Sometimes issue would be resolved.
Install Snakemake
If you want to take advantage of the workflow management we used for the single-cell RNA-seq analysis, you have to install Snakemake. See the official instruction and use your prefered solution:
https://snakemake.readthedocs.io/en/stable/getting_started/installation.html
Run the analysis
There are two types of analysis in this study : bulk RNA-seq and single-cell RNA-seq. The bulk RNA-seq analysis uses the Docker image you loaded. The single-cell RNA-seq analysis uses the Singularity images and optionnaly Snakemake.
Run the bulk RNA-seq analysis
The RNA-seq analysis are in two steps (step1 and step2). The first step make the QC, study the differentially expressed genes and their functionnal enrichment. The second step study the pattern of evolution of group of genes along the cell types (see article methods).
To run the step1 analysis, use the following command:
On Linux:
docker run -v $WORKING_DIR:$WORKING_DIR -e WORKING_DIR=$WORKING_DIR splab_ilcyou_deg_gsea 'cd $WORKING_DIR/Embryo_Bulk_Stage13.5_2tissues/03_Script/step1;Rscript launch_reports_compilation.R'
To run the step2 analysis, use the following command:
On Linux:
docker run -v $WORKING_DIR:$WORKING_DIR -e WORKING_DIR=$WORKING_DIR splab_ilcyou_deg_gsea 'cd $WORKING_DIR/Embryo_Bulk_Stage13.5_2tissues/03_Script/step2;Rscript launch_reports_compilation.R'
Each analysis will generate a result in $WORKING_DIR/Embryo_Bulk_Stage13.5_2tissues/05_output/step1 or $WORKING_DIR/Embryo_Bulk_Stage13.5_2tissues/05_output/step2. In the output of the analysis, you will find a HTML file that contains the report of the analysis, with all figures. Some extra file are generated to export data in plain text.
Run the single-cell RNA-seq analysis
The study contains 4 samples of single-cell RNA-seq data. Each sample have 5 step of analysis you will find the R script files in the subfolder 03_Script. The 5 steps are:
- 01_QC : General quality control and bad cell removal
- 02_GlobalHeterogeneity : First study of cell heterogeneity and sample contamination by undesired cell types
- 03_GlobalHeterogeneity_NoContamination : Study of cell heterogeniety in absence of contamination
- 04_Dynamics_Monocle : analysis of the cellular process dynamics using pseudotime analysis by Monocle
- 05_Dynamics_RNAVelocity : analysis of the cellular process dynamics using RNA velocity (Velocyto)
Each step of analysis generates its own HTML report file and several output files. Some output files of some steps are used by other steps, making a complete workflow of analysis.
The simpliest way to run the complete single-cell analysis of a sample is to use the Snakemake workflow dedicated to each sample. The workflow is controled by a snakefile stored in the 04_Workflow subfolder of each sample folder. This workflow uses Singularity images (see above) to control the software environment for each analysis step. So you need both Snakemake and Singularity installed on your system to use this workflow.
In order to use the snakemake workflow, please type first the following commands:
cd $WORKING_DIR
ln -s Embryo_Stage13.5_FetalLiver/04_Workflow/snakefile.yml Embryo_Stage13.5_FetalLiver/snakefile.yml
ln -s Embryo_Stage13.5_Periphery_CellRangerV3/04_Workflow/snakefile.yml Embryo_Stage13.5_Periphery_CellRangerV3/snakefile.yml
ln -s Embryo_Stage14.5_FetalLiver/04_Workflow/snakefile.yml Embryo_Stage14.5_FetalLiver/snakefile.yml
ln -s Embryo_Stage14.5_Periphery_CellRangerV3/04_Workflow/snakefile.yml Embryo_Stage14.5_Periphery_CellRangerV3/snakefile.yml
To run the analysis for the Embryo_Stage13.5_FetalLiver (for instance), then run the following commands:
Note: you have to manually change the "$WORKING_DIR" string in the snakemake command below by the value of the environment variable (i.e the path where you clone the project) because snakemake may not interpret the variable name correctly:
cd $WORKING_DIR/Embryo_Stage13.5_FetalLiver
snakemake -r --snakefile snakefile.yml --use-singularity --singularity-args "-B $WORKING_DIR:$WORKING_DIR"
To execute the analysis of the other sample, simply change folder to the target sample and run again the same snakemake command.