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T cell fate and clonality inference from single cell transcriptomes

View Article: PubMed Central - PubMed

ABSTRACT

The enormous sequence diversity within T cell receptor (TCR) repertoires allows specific TCR sequences to be used as lineage markers for T cells that derive from a common progenitor. We have developed a computational method, called TraCeR, to reconstruct full-length, paired TCR sequences from T lymphocyte single-cell RNA-seq by combining existing assembly and alignment programs with “combinatorial recombinome” sequences comprising all possible TCR combinations. We validate this method to quantify its accuracy and sensitivity. Inferred TCR sequences reveal clonal relationships between T cells whilst the cells’ complete transcriptional landscapes can be quantified from the remaining RNA-seq data. This provides a powerful tool to link T cell specificity with functional response and we demonstrate this by determining the distribution of members of expanded T cell clonotypes in a mouse Salmonella infection model. Members of the same clonotype span early activated CD4+ T cells, as well as mature effector and memory cells.

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Distribution of expanded clonotypes throughout the Th1 response to S. typhimurium infection. (a) Dimensionality reduction of single-cell gene expression data by independent component analysis (ICA). Each single CD4+ T cell is plotted in reduced two-dimensional space according to its gene expression profile. Points are colored according to the timepoint from which they were sampled or according to their expression of marker genes indicative of their phenotype. Where the expression of a set of genes (Th1 genes and proliferation markers) is plotted, this is the sum of TPM values for the genes within the set. (b) Clonotype distribution in gene-expression space. Three representative expanded clonotypes from day 14 mouse 1 are shown as purple points on top of all other cells within the gene expression space.
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Figure 3: Distribution of expanded clonotypes throughout the Th1 response to S. typhimurium infection. (a) Dimensionality reduction of single-cell gene expression data by independent component analysis (ICA). Each single CD4+ T cell is plotted in reduced two-dimensional space according to its gene expression profile. Points are colored according to the timepoint from which they were sampled or according to their expression of marker genes indicative of their phenotype. Where the expression of a set of genes (Th1 genes and proliferation markers) is plotted, this is the sum of TPM values for the genes within the set. (b) Clonotype distribution in gene-expression space. Three representative expanded clonotypes from day 14 mouse 1 are shown as purple points on top of all other cells within the gene expression space.

Mentions: Single-cell RNA-seq allows cells to be classified according to their gene expression profiles. To combine this with our knowledge of clonal relationships, we quantified gene expression within each single cell and performed independent component analysis (ICA) to reduce the gene expression space to two dimensions (Fig. 3a). We were able to use 14,889 informative genes for ICA. This is a great deal larger than the 17 phenotyping genes that were used in a previous PCR-based approach to determining clonality and cell fate12.


T cell fate and clonality inference from single cell transcriptomes
Distribution of expanded clonotypes throughout the Th1 response to S. typhimurium infection. (a) Dimensionality reduction of single-cell gene expression data by independent component analysis (ICA). Each single CD4+ T cell is plotted in reduced two-dimensional space according to its gene expression profile. Points are colored according to the timepoint from which they were sampled or according to their expression of marker genes indicative of their phenotype. Where the expression of a set of genes (Th1 genes and proliferation markers) is plotted, this is the sum of TPM values for the genes within the set. (b) Clonotype distribution in gene-expression space. Three representative expanded clonotypes from day 14 mouse 1 are shown as purple points on top of all other cells within the gene expression space.
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Related In: Results  -  Collection

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Figure 3: Distribution of expanded clonotypes throughout the Th1 response to S. typhimurium infection. (a) Dimensionality reduction of single-cell gene expression data by independent component analysis (ICA). Each single CD4+ T cell is plotted in reduced two-dimensional space according to its gene expression profile. Points are colored according to the timepoint from which they were sampled or according to their expression of marker genes indicative of their phenotype. Where the expression of a set of genes (Th1 genes and proliferation markers) is plotted, this is the sum of TPM values for the genes within the set. (b) Clonotype distribution in gene-expression space. Three representative expanded clonotypes from day 14 mouse 1 are shown as purple points on top of all other cells within the gene expression space.
Mentions: Single-cell RNA-seq allows cells to be classified according to their gene expression profiles. To combine this with our knowledge of clonal relationships, we quantified gene expression within each single cell and performed independent component analysis (ICA) to reduce the gene expression space to two dimensions (Fig. 3a). We were able to use 14,889 informative genes for ICA. This is a great deal larger than the 17 phenotyping genes that were used in a previous PCR-based approach to determining clonality and cell fate12.

View Article: PubMed Central - PubMed

ABSTRACT

The enormous sequence diversity within T cell receptor (TCR) repertoires allows specific TCR sequences to be used as lineage markers for T cells that derive from a common progenitor. We have developed a computational method, called TraCeR, to reconstruct full-length, paired TCR sequences from T lymphocyte single-cell RNA-seq by combining existing assembly and alignment programs with “combinatorial recombinome” sequences comprising all possible TCR combinations. We validate this method to quantify its accuracy and sensitivity. Inferred TCR sequences reveal clonal relationships between T cells whilst the cells’ complete transcriptional landscapes can be quantified from the remaining RNA-seq data. This provides a powerful tool to link T cell specificity with functional response and we demonstrate this by determining the distribution of members of expanded T cell clonotypes in a mouse Salmonella infection model. Members of the same clonotype span early activated CD4+ T cells, as well as mature effector and memory cells.

No MeSH data available.


Related in: MedlinePlus