The NEBNext Immune Sequencing Kit (Human) enables exhaustive profiling of somatic mutations in the full-length immune gene repertoires of B cells and T cells, via the expression of complete antibody chains. This includes modular primer sets, providing information for complete V, D, and J segments and full isotype information analysis (IgM, IgD, IgG, IgA and IgE), and TCRα and TCRβ chain characterization. A unique, UMI-based mRNA barcoding process allows PCR copies derived from an individual molecule to be converted to a consensus sequence. This improves sequence accuracy and eliminates PCR bias. Based on the open-source pRESTO toolkit, a workflow is available via the Galaxy platform to enable robust bioinformatic analysis locally or in a cloud environment. A workflow tutorial ensures that users who are not familiar with Galaxy can successfully use the analysis workflow.
Immune repertoire sequencing is frequently used to analyze immune responses, both current and distant. Areas of particular interest include characterization of autoimmune diseases, oncology, discovery of neutralizing antibodies against infectious disease, tumor-infiltrating lymphocytes and use as a tool to study residual disease. Recent improvements in read lengths and throughputs of next-generation sequencing (NGS) platforms have resulted in a rise in the popularity of immune repertoire sequencing.
Defining features of the NEBNext Immune Sequencing method include:
Generation of full-length variable sequences (including isotype information), allowing downstream antibody synthesis and functional characterization not possible with approaches sequencing only the CDR3 region
Eliminated use of variable region primers, reducing primer pool complexity and realizing unbiased and simultaneous recovery of B cell and T cell receptor transcripts.
Minimized PCR bias and improved sequencing accuracy by allowing a consensus to be generated from duplicate sequencing reads originating from the same transcript; UMIs enable accurate quantitation of each clone present in the sample.
Optimized high target-capture efficiency for immune repertoire sequencing and analysis from sub-microgram quantities of total RNA.
Figure 1: Simplified representation of the structure of an antibody or TCR
Figure 2: Workflow
Figure 3: Utilization of Unique Molecular Identifier (UMI) provides superior accuracy of clonotype detection
Clonotype frequency comparison between analysis with or without UMI annotation for human TCR libraries from 10 ng and 100 ng T cell Total RNA. The top 100 highly expressed clones were ranked by clonotype frequency detected with UMI. Clonotype frequency correlation on overlapped clonotypes was plotted between technical replicates using UMI or without UMI for TCR libraries from 10 ng and 100 ng T cell Total RNA. Each bar or circle represents a unique clone from total read analysis, or filtered using UMI. The use of UMI allows for absolute quantitation of starting RNA molecules present in the original sample. When ranking the clones from most abundant clone to least abundant, the data based on total reads without UMI annotation results in PCR or sequencing amplification bias that can mislead interpretation of clonotype frequency in the samples. The use of UMI corrects the bias by generating absolute quantitation of RNA present in the starting sample. Use of UMI also produces better correlation between replicates, especially for low input. Each library were down sampled to 500,000 reads.
Figure 4: The NEBNext Immune Sequencing Kit (Human) is able to generate both human BCR and human TCR libraries in one tube
Human BCR+TCR libraries were constructed from 1 μg, 100 ng and 10 ng human PBMC Total RNA (Takara Bio #636592) with replicates for each input. Libraries were downsampled to 950,000 reads for all the libraries. pRESTO tools were used for quality filtering of reads, sequence assemble, and generation of consensus sequence UMIs. V, D and J assignment was done using MiGMAP. (A) Number of clonotypes detected for each human PBMC Total RNA input. (B) B cell chains and T cell chains percentages in each library.
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