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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.

No MeSH data available.


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Assessment of clonal CD4+ T cell expansion during Salmonella typhimurium infection. (a) Schematic of timeline for Salmonella infection experiment. (b) Distribution of expanded clonotypes within splenic CD4+ T cell populations analysed by single-cell RNA-seq. The x-axis indicates the number of cells within the expanded clonotypes whilst the y-axis represents the number of clonotypes of each size. (c) Clonotype network graph from day 14, mouse 1. Each node in the graph represents an individual splenic CD4+ T lymphocyte. Coloured bars within the nodes indicate the presence of reconstructed TCR sequences that were detected for each cell. Dark coloured identifiers are productive, light coloured are non-productive. Red edges between the nodes indicate shared TCRα sequences whilst blue edges indicate shared TCRβ sequences. Edge thickness is proportional to the number of shared sequences.
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Figure 2: Assessment of clonal CD4+ T cell expansion during Salmonella typhimurium infection. (a) Schematic of timeline for Salmonella infection experiment. (b) Distribution of expanded clonotypes within splenic CD4+ T cell populations analysed by single-cell RNA-seq. The x-axis indicates the number of cells within the expanded clonotypes whilst the y-axis represents the number of clonotypes of each size. (c) Clonotype network graph from day 14, mouse 1. Each node in the graph represents an individual splenic CD4+ T lymphocyte. Coloured bars within the nodes indicate the presence of reconstructed TCR sequences that were detected for each cell. Dark coloured identifiers are productive, light coloured are non-productive. Red edges between the nodes indicate shared TCRα sequences whilst blue edges indicate shared TCRβ sequences. Edge thickness is proportional to the number of shared sequences.

Mentions: We demonstrated an application of our approach by investigating the CD4+ Tlymphocyte clonotypes present within the spleens of mice prior to, during or after anon-lethal infection with Salmonella typhimurium (Fig. 2a, Supplementary Table 1), a bacterium that elicits a strongtype-1 CD4+ T cell response. We analysed effector cells(CD4+CD8−TCRB+NK1.1−CD44HighCD62LLow) at day 14 when their relative abundanceis close to its maximum, and memory cells(CD4+CD8−TCRB+NK1.1−CD44HighCD62LLowCD127High)at day 49 when the infection has been resolved30 (Supplementary Fig. 2).


T cell fate and clonality inference from single cell transcriptomes
Assessment of clonal CD4+ T cell expansion during Salmonella typhimurium infection. (a) Schematic of timeline for Salmonella infection experiment. (b) Distribution of expanded clonotypes within splenic CD4+ T cell populations analysed by single-cell RNA-seq. The x-axis indicates the number of cells within the expanded clonotypes whilst the y-axis represents the number of clonotypes of each size. (c) Clonotype network graph from day 14, mouse 1. Each node in the graph represents an individual splenic CD4+ T lymphocyte. Coloured bars within the nodes indicate the presence of reconstructed TCR sequences that were detected for each cell. Dark coloured identifiers are productive, light coloured are non-productive. Red edges between the nodes indicate shared TCRα sequences whilst blue edges indicate shared TCRβ sequences. Edge thickness is proportional to the number of shared sequences.
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Related In: Results  -  Collection

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getmorefigures.php?uid=PMC4835021&req=5

Figure 2: Assessment of clonal CD4+ T cell expansion during Salmonella typhimurium infection. (a) Schematic of timeline for Salmonella infection experiment. (b) Distribution of expanded clonotypes within splenic CD4+ T cell populations analysed by single-cell RNA-seq. The x-axis indicates the number of cells within the expanded clonotypes whilst the y-axis represents the number of clonotypes of each size. (c) Clonotype network graph from day 14, mouse 1. Each node in the graph represents an individual splenic CD4+ T lymphocyte. Coloured bars within the nodes indicate the presence of reconstructed TCR sequences that were detected for each cell. Dark coloured identifiers are productive, light coloured are non-productive. Red edges between the nodes indicate shared TCRα sequences whilst blue edges indicate shared TCRβ sequences. Edge thickness is proportional to the number of shared sequences.
Mentions: We demonstrated an application of our approach by investigating the CD4+ Tlymphocyte clonotypes present within the spleens of mice prior to, during or after anon-lethal infection with Salmonella typhimurium (Fig. 2a, Supplementary Table 1), a bacterium that elicits a strongtype-1 CD4+ T cell response. We analysed effector cells(CD4+CD8−TCRB+NK1.1−CD44HighCD62LLow) at day 14 when their relative abundanceis close to its maximum, and memory cells(CD4+CD8−TCRB+NK1.1−CD44HighCD62LLowCD127High)at day 49 when the infection has been resolved30 (Supplementary Fig. 2).

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