Evaluation of the capacities of mouse TCR profiling from short read RNA-seq data.
Yu BaiDavid WangWentian LiYing HuangXuan YeJanelle WaiteThomas BarryKurt H EdelmannNatasha LevenkovaChunguang GuoDimitris SkokosYi WeiLynn E MacdonaldWen FuryPublished in: PloS one (2018)
Profiling T cell receptor (TCR) repertoire via short read transcriptome sequencing (RNA-Seq) has a unique advantage of probing simultaneously TCRs and the genome-wide RNA expression of other genes. However, compared to targeted amplicon approaches, the shorter read length is more prone to mapping error. In addition, only a small percentage of the genome-wide reads may cover the TCR loci and thus the repertoire could be significantly under-sampled. Although this approach has been applied in a few studies, the utility of transcriptome sequencing in probing TCR repertoires has not been evaluated extensively. Here we present a systematic assessment of RNA-Seq in TCR profiling. We evaluate the power of both Fluidigm C1 full-length single cell RNA-Seq and bulk RNA-Seq in characterizing the repertoires of different diversities under either naïve conditions or after immunogenic challenges. Standard read length and sequencing coverage were employed so that the evaluation was conducted in accord with the current RNA-Seq practices. Despite high sequencing depth in bulk RNA-Seq, we encountered difficulty quantifying TCRs with low transcript abundance (<1%). Nevertheless, top enriched TCRs with an abundance of 1-3% or higher can be faithfully detected and quantified. When top TCR sequences are of interest and transcriptome sequencing is available, it is worthwhile to conduct a TCR profiling using the RNA-Seq data.
Keyphrases
- rna seq
- single cell
- genome wide
- regulatory t cells
- high throughput
- single molecule
- dna methylation
- primary care
- healthcare
- electronic health record
- big data
- copy number
- molecular dynamics simulations
- immune response
- binding protein
- optical coherence tomography
- antibiotic resistance genes
- wastewater treatment
- health insurance
- genome wide analysis
- affordable care act