Human embryonic liver CITE-seq data
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB52059 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| Other | ||||
| ERR9469143_1.fastq.gz | Fastqsanger.gz | |||
| ERR9469143_2.fastq.gz | Fastqsanger.gz | |||
| ERR9469098_1.fastq.gz | Fastqsanger.gz | |||
| ERR9469098_2.fastq.gz | Fastqsanger.gz |
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Project description:In this study we used single cell multi-omics profiling to create an atlas of the human YS to gain insights into its haematopoietic, metabolic and nutritive functions during early embryonic development. This contains embryonic liver CITE-seq (surface protein and cytosolic RNA content) data from three biological replicates. Pooled lanes were demultiplexed using SoupOrCell (for alignment and demultiplexing software and version numbers, please see accompanying manuscript and protocols within this accession). Raw count files provided are directly as output by alignment software, without any quality control applied. Quality control is described in accompanying manuscript methods. Metadata by barcode are provided as supplementary tables in accompanying manuscript.
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Project description:In this study we used single cell multi-omics profiling to create an atlas of the human YS to gain insights into its haematopoietic, metabolic and nutritive functions during early embryonic development. This contains fetal liver CITE-seq (surface protein and cytosolic RNA content) data from six biological replicates. Pooled lanes were demultiplexed using SoupOrCell (for alignment and demultiplexing software and version numbers, please see accompanying manuscript and protocols within this accession). Raw count files provided are directly as output by alignment software, without any quality control applied. Quality control is described in accompanying manuscript methods. Metadata by barcode are provided as supplementary tables in accompanying manuscript.
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Project description:We used scRNAseq to profile CD71/CD24low fetal liver erythroid progenitor cells isolated by 2 distinct methods: FACS and immunomagnetic isolation. Cells from both isolation methods were hashtagged using Biolegend mouse hashtag antibodies and library prepped together on the 10X chromium platform with the 3'RNA v3 kit. We also performed CITE-seq to profile proteogenomic expression of CD117 and CD71 on lineage-depleted mouse fetal liver erythroid progenitor cells. CITE-seq was performed through a separate library prep on the 10X chromium platform with the 3'RNAv3 kit.
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Project description:Single-cell RNA-sequencing (scRNA-Seq) is widely used to characterize immune cell populations. However, mRNA levels correlate poorly with expression of surface proteins, which are well established to define immune cell types. CITE-Seq (cellular indexing of transcriptomes and epitopes by sequencing) utilizes oligonucleotide-tagged antibodies to simultaneously analyze surface phenotypes and transcriptomes. Considering the high costs of adding surface phenotyping to scRNA-Seq, we aimed to determine which of 188 tested CITE-Seq antibodies can detect their antigens on human peripheral blood mononuclear cells (PBMCs), a commonly interrogated cell population in immunology, and find the optimal concentration for staining. The recommended concentration was optimal for 76 antibodies, whereas staining quality of 7 antibodies improved when the concentration was doubled. 33 and 8 antibodies still worked well when the concentration was reduced to 1/5 or 1/25, respectively. 64 antigens were not detected at any antibody concentration. Optimizing the antibody panel by removing antibodies not able to detect their target antigens and adjusting concentrations of the remaining antibodies could enable a cost reduction of almost 50%. In conclusion, our data are a resource for building an informative and cost-effective panel of CITE-Seq antibodies and use them at their optimal concentrations in future CITE-seq experiments on human PBMCs.
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