Transitions in lineage specification and gene regulatory networks in human hematopoietic stem/progenitor cells over human development
Human hematopoiesis is a dynamic process that starts in utero 18 – 21 days postconception. Understanding the site- and stage-specific variation in hematopoiesis is important if we are to understand the origin of hematological disorders, many of which occur at specific points in the human lifespan. To unravel how the hematopoietic stem/progenitor cell (HSPC) compartments change during human ontogeny and the underlying gene regulatory mechanisms, we used 10x genomics platform to profile single-cell transcriptome of HSPCs sampled throughout the course of human ontogeny. This included early fetal liver (eFL) from the first trimester fetuses, paired fetal bone marrow (FBM) and FL from the same second trimester fetuses, paediatric BM (PBM), and adult BM (ABM). To increase the utility and accessibility of our single-cell dataset, we have shared the processed file in h5ad format, which is suitable for the cellxgene (https://chanzuckerberg.github.io/cellxgene/) single-cell visualization software. This platform will enable users to easily interrogate the expression of gene(s) of interest in our dataset. The R object file generated from the SingCellaR analysis (https://github.com/supatt-lab/SingCellaR) is also shared in this database. The users can use the SingCellaR functions to analyse and visualise multiple plots from this R object file.
Steps to reproduce
Demultiplexed FASTQ files were aligned to the human reference genome (GRCh38/hg38) using Cell Ranger software (version 3.0.1) from 10x Genomics. The Cell Ranger ‘‘count’’ standard pipeline was used to obtain the expression matrix of Unique Molecular Identifier (UMI) for each individual sample. We used SingCellaR (https://github.com/supatt-lab/SingCellaR) to process each sample individually. The function ‘load_matrices_from_cellranger’ was used to read in data matrices from the Cell Ranger output. Cell and gene filtering was performed by assessing QC plots using the ‘plot_cells_annotation’ function. Cells meeting the following QC parameters were included in analyses (see our paper in Suppl. Table 1): UMI counts > 1,000 and maximum UMIs; number of detected genes > 500 and maximum number of detected genes; the percentage of mitochondrial gene expression limited percentage of mitochondrial gene expression (10% or 20% depending on an individual sample). Genes expressed in at least 10 cells were included. After filtering according to these criteria, 57,489 cells passed quality control and were included in downstream analyses.