Linking Expression of Cell-Surface Receptors with Transcription Factors by Computational Analysis of Paired Single-Cell Proteomes and Transcriptomes

Complex signaling and transcriptional programs control the development and physiology of specialized cell types. Genetic perturbations in these programs cause human cancers to arise from a diverse set of specialized cell types and developmental states. Understanding these complex systems and their p...

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Veröffentlicht in:Methods in molecular biology (Clifton, N.J.) Jg. 2660; S. 149
Hauptverfasser: Sagan, April, Ma, Xiaojun, Ramjattun, Koushul, Osmanbeyoglu, Hatice Ulku
Format: Journal Article
Sprache:Englisch
Veröffentlicht: United States 2023
Schlagworte:
Humans
Leukocytes, Mononuclear
Proteome
Proteomics
Single-Cell Analysis
Transcription Factors - genetics
Transcriptome
Droplet-based scRNA-seq
scVerse and Scanpy ecosystems
Affinity regression (AR)
scADT-seq
Jupyter notebook
pySPaRTAN package
DoRothEA database
Single-cell Proteomic and RNA-based Transcription factor Activity Network (SPaRTAN)
Python package
Cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq)
Antibody-derived tags (ADTs)
ISSN:1940-6029, 1940-6029
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Abstract Complex signaling and transcriptional programs control the development and physiology of specialized cell types. Genetic perturbations in these programs cause human cancers to arise from a diverse set of specialized cell types and developmental states. Understanding these complex systems and their potential to drive cancer is critical for the development of immunotherapies and druggable targets. Pioneering single-cell multi-omics technologies that analyze transcriptional states have been coupled with the expression of cell-surface receptors. This chapter describes SPaRTAN (Single-cell Proteomic and RNA-based Transcription factor Activity Network), a computational framework, to link transcription factors with cell-surface protein expression. SPaRTAN uses CITE-seq (cellular indexing of transcriptomes and epitopes by sequencing) data and cis-regulatory sites to model the effect of interactions between transcription factors and cell-surface receptors on gene expression. We demonstrate the pipeline for SPaRTAN using CITE-seq data from peripheral blood mononuclear cells.
AbstractList Complex signaling and transcriptional programs control the development and physiology of specialized cell types. Genetic perturbations in these programs cause human cancers to arise from a diverse set of specialized cell types and developmental states. Understanding these complex systems and their potential to drive cancer is critical for the development of immunotherapies and druggable targets. Pioneering single-cell multi-omics technologies that analyze transcriptional states have been coupled with the expression of cell-surface receptors. This chapter describes SPaRTAN (Single-cell Proteomic and RNA-based Transcription factor Activity Network), a computational framework, to link transcription factors with cell-surface protein expression. SPaRTAN uses CITE-seq (cellular indexing of transcriptomes and epitopes by sequencing) data and cis-regulatory sites to model the effect of interactions between transcription factors and cell-surface receptors on gene expression. We demonstrate the pipeline for SPaRTAN using CITE-seq data from peripheral blood mononuclear cells.
Complex signaling and transcriptional programs control the development and physiology of specialized cell types. Genetic perturbations in these programs cause human cancers to arise from a diverse set of specialized cell types and developmental states. Understanding these complex systems and their potential to drive cancer is critical for the development of immunotherapies and druggable targets. Pioneering single-cell multi-omics technologies that analyze transcriptional states have been coupled with the expression of cell-surface receptors. This chapter describes SPaRTAN (Single-cell Proteomic and RNA-based Transcription factor Activity Network), a computational framework, to link transcription factors with cell-surface protein expression. SPaRTAN uses CITE-seq (cellular indexing of transcriptomes and epitopes by sequencing) data and cis-regulatory sites to model the effect of interactions between transcription factors and cell-surface receptors on gene expression. We demonstrate the pipeline for SPaRTAN using CITE-seq data from peripheral blood mononuclear cells.Complex signaling and transcriptional programs control the development and physiology of specialized cell types. Genetic perturbations in these programs cause human cancers to arise from a diverse set of specialized cell types and developmental states. Understanding these complex systems and their potential to drive cancer is critical for the development of immunotherapies and druggable targets. Pioneering single-cell multi-omics technologies that analyze transcriptional states have been coupled with the expression of cell-surface receptors. This chapter describes SPaRTAN (Single-cell Proteomic and RNA-based Transcription factor Activity Network), a computational framework, to link transcription factors with cell-surface protein expression. SPaRTAN uses CITE-seq (cellular indexing of transcriptomes and epitopes by sequencing) data and cis-regulatory sites to model the effect of interactions between transcription factors and cell-surface receptors on gene expression. We demonstrate the pipeline for SPaRTAN using CITE-seq data from peripheral blood mononuclear cells.
Author Osmanbeyoglu, Hatice Ulku
Sagan, April
Ma, Xiaojun
Ramjattun, Koushul
Author_xml – sequence: 1
  givenname: April
  surname: Sagan
  fullname: Sagan, April
  organization: UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, PA, USA
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  givenname: Xiaojun
  surname: Ma
  fullname: Ma, Xiaojun
  organization: UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, PA, USA
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  givenname: Koushul
  surname: Ramjattun
  fullname: Ramjattun, Koushul
  organization: UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, PA, USA
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  givenname: Hatice Ulku
  surname: Osmanbeyoglu
  fullname: Osmanbeyoglu, Hatice Ulku
  email: osmanbeyogluhu@pitt.edu, osmanbeyogluhu@pitt.edu, osmanbeyogluhu@pitt.edu, osmanbeyogluhu@pitt.edu
  organization: Department of Biostatistics, University of Pittsburgh, Pittsburgh, PA, USA. osmanbeyogluhu@pitt.edu
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Keywords Droplet-based scRNA-seq
scVerse and Scanpy ecosystems
Affinity regression (AR)
scADT-seq
Jupyter notebook
pySPaRTAN package
DoRothEA database
Single-cell Proteomic and RNA-based Transcription factor Activity Network (SPaRTAN)
Python package
Cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq)
Antibody-derived tags (ADTs)
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SubjectTerms Humans
Leukocytes, Mononuclear
Proteome
Proteomics
Single-Cell Analysis
Transcription Factors - genetics
Transcriptome
Title Linking Expression of Cell-Surface Receptors with Transcription Factors by Computational Analysis of Paired Single-Cell Proteomes and Transcriptomes
URI https://www.ncbi.nlm.nih.gov/pubmed/37191796
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