Haemopedia RNA-seq: a database of gene expression during haematopoiesis in mice and humans

Abstract

During haematopoiesis, haematopoietic stem cells differentiate into restricted potential progenitors before maturing into the many lineages required for oxygen transport, wound healing and immune response. We have updated Haemopedia, a database of gene-expression profiles from a broad spectrum of haematopoietic cells, to include RNA-seq gene-expression data from both mice and humans. The Haemopedia RNA-seq data set covers a wide range of lineages and progenitors, with 57 mouse blood cell types (flow sorted populations from healthy mice) and 12 human blood cell types. This data set has been made accessible for exploration and analysis, to researchers and clinicians with limited bioinformatics experience, on our online portal Haemosphere: https://www.haemosphere.org. Haemosphere also includes nine other publicly available high-quality data sets relevant to haematopoiesis. We have added the ability to compare gene expression across data sets and species by curating data sets with shared lineage designations or to view expression gene vs gene, with all plots available for download by the user.

Flexible Experimental Designs for Valid Single-cell RNA-sequencing Experiments Allowing Batch Effects Correction

“…Haemopedia is a database of gene expression profiles from diverse types of haematopoietic cells (Choi et al, 2018). It collected flow sorted cell populations from healthy mice.…”

“…Moreover, we find that well known B-cell lineage genes (Herman et al, 2018), Ebf1, Vpreb1, Vpreb3, and Igll1, are highly expressed in Cluster 3, but not in the other clusters (Figure 6 (c, e)). To identify Cluster 3, which is dominated by cells labeled as "other" byNestorowa et al (2016), we map the mean expression profile of each cluster learned by BUSseq to the Haemopedia RNA-seq dataset(Choi et al, 2018). It turns out that Cluster 3 aligns well to common lymphoid progenitors (CLP) that give rise to T-lineage cells, B-lineage cells and natural killer cells (Figure 6(d)).…”

Common neurodegeneration-associated proteins are physiologically expressed by antigen-presenting cells and are interconnected via the inflammation/autophagy-related proteins TRAF6 and SQSTM1

“…-The Haemosphere database (39) compiles RNA-seq data obtained in purified populations of peripheral blood mononuclear cells derived from healthy human subjects. Two independent studies may be surveyed via the "Heamosphere" database: i) the "Haemopedia" study (39) in which normalized expression data were obtained from 42 samples in 12 immune cell types across 7 lineages and ii) the Linsley study (40) in which normalized expression data were obtained from 24 samples in 6 immune cell types across 5 lineages. We focused our initial searches on the "Haemopedia" dataset as, contrary to the "Linsley" dataset, it includes results -The Immune Epitope Database and Analysis Resource (IEDB-AR) (42) compiles experimental data on antibody and T-cell epitopes in humans, non-human primates and other animal species.…”

“…To determine whether genes coding for neurodegeneration-associated proteins are expressed by APCs under physiological conditions, we queried the "Haemosphere" database which compiles normalized RNA-seq data obtained from the analysis of pure subpopulations of peripheral blood mononuclear cells (39). In the "Haemosphere" database, we first surveyed the "Haemopedia" dataset (39) in which normalized RNA-seq expression data were obtained from 42 samples in 12 immune cell types across 7 lineages. Our search was restricted to 2 cell lineages which harbor demonstrated antigen-presenting functions: B-cells (45)(46)(47) and dendritic cells (48)(49)(50).…”

“…Proteins that are detectable by mass spectrometry in human B-cells, according to the "Human Proteome Map" database (41), are highlighted in yellow. The corresponding mRNAs are all detectable by RNAseq in Bcells according to the "Haemosphere" database (39 However, one may argue that the list of currently-known TRAF6 partners might be enriched in not only neurodegeneration-associated proteins but also other sets of proteins which do not relate with neurodegeneration. To address this issue, we performed on the whole list of TRAF6 partners a non a priori enrichment analysis using the "JENSEN Disease" text-mining webtool (37) embedded in the "Enrichr" analysis platform (36).…”