Multiplex BCR UMI cDNA libraries

For this tutorial we will use the data published in the following article:

Chen JS, Chow RD, Song E, Mao T, Israelow B, Kamath K, Bozekowski J, Haynes WA, Filler RB, Menasche BL, Wei J, Alfajaro MM, Song W, Peng L, Carter L, Weinstein JS, Gowthaman U, Chen S, Craft J, Shon JC, Iwasaki A, Wilen CB, Eisenbarth SC. High-affinity, neutralizing antibodies to SARS-CoV-2 can be made without T follicular helper cells. Sci Immunol. 2022 Feb 4;7(68):eabl5652. doi: 10.1126/sciimmunol.abl5652. Epub 2022 Feb 4. PMID: 34914544; PMCID: PMC8977051.

Experiment setting

The experiment includes 8 mice that express angiotensin-converting enzyme 2 (ACE2) in epithelial cells thus vulnerable to SARS-CoV-2. 4 K18-hACE2 Bcl6fl/fl mice and 4 Bcl6fl/flCd4Cre (T_FH cell deficiency model) mice. Mice were infected intranasally with SARS-CoV-2 (isolate USA-WA1/2020) and 14 days post-infection S-specific plasmablasts were isolated. RNA from spike-specific B cells was isolated using the RNeasy Plus Micro Kit (Qiagen) following the manufacturer’s instructions. BCR libraries were prepared using the NEBNext Single Cell/Low Input cDNA Synthesis & Amplification Module (New England Biolabs (NEB), E6421) and NEBNext Immune Sequencing Kit (NEB, E6330), with additional reagents provided by NEB to integrate the two kits. High-quality RNA (1 to 20 ng) with RNA integrity number ≥ 8 was used as input. Libraries were analyzed by Bioanalyzer High Sensitivity DNA assay, pooled in equal amounts with PhiX spike-in, and sequenced on an Illumina MiSeq using the V3 kit, with 325 base pairs (bp) for read 1 and 275 bp for read 2.

All data may be downloaded directly from SRA (PRJNA780318) using e.g. SRA Explorer.

mkdir -p raw
aria2c -c -s 16 -x 16 -k 1M -j 8 -i download-list.txt

ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR169/022/SRR16943422/SRR16943422_1.fastq.gz
  out=raw/mouse_3_Cd4Cre_R1.fastq.gz
ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR169/022/SRR16943422/SRR16943422_2.fastq.gz
  out=raw/mouse_3_Cd4Cre_R2.fastq.gz
ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR169/025/SRR16943425/SRR16943425_1.fastq.gz
  out=raw/mouse_4_R1.fastq.gz
ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR169/025/SRR16943425/SRR16943425_2.fastq.gz
  out=raw/mouse_4_R2.fastq.gz
ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR169/028/SRR16943428/SRR16943428_1.fastq.gz
  out=raw/mouse_1_R1.fastq.gz
ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR169/028/SRR16943428/SRR16943428_2.fastq.gz
  out=raw/mouse_1_R2.fastq.gz
ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR169/021/SRR16943421/SRR16943421_1.fastq.gz
  out=raw/mouse_4_Cd4Cre_R1.fastq.gz
ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR169/021/SRR16943421/SRR16943421_2.fastq.gz
  out=raw/mouse_4_Cd4Cre_R2.fastq.gz
ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR169/023/SRR16943423/SRR16943423_1.fastq.gz
  out=raw/mouse_2_Cd4Cre_R1.fastq.gz
ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR169/023/SRR16943423/SRR16943423_2.fastq.gz
  out=raw/mouse_2_Cd4Cre_R2.fastq.gz
ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR169/027/SRR16943427/SRR16943427_1.fastq.gz
  out=raw/mouse_2_R1.fastq.gz
ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR169/027/SRR16943427/SRR16943427_2.fastq.gz
  out=raw/mouse_2_R2.fastq.gz
ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR169/024/SRR16943424/SRR16943424_1.fastq.gz
  out=raw/mouse_1_Cd4Cre_R1.fastq.gz
ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR169/024/SRR16943424/SRR16943424_2.fastq.gz
  out=raw/mouse_1_Cd4Cre_R2.fastq.gz
ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR169/026/SRR16943426/SRR16943426_1.fastq.gz
  out=raw/mouse_3_R1.fastq.gz
ftp://ftp.sra.ebi.ac.uk/vol1/fastq/SRR169/026/SRR16943426/SRR16943426_2.fastq.gz
  out=raw/mouse_3_R2.fastq.gz

One command Solution

The data was obtained using NEBNext Immune Sequencing Kit for BCR repertoire. The easiest way to perform upstream analysis for this data would be to use a dedicated mixcr preset neb-mouse-rna-xcr-umi-nebnext with mixcr analyze command. This preset was spesifically designed for this kit and includes UMI correction, primer sequences trimming and assembles clonotypes by VDJRegion.

The exact command for a single sample you can see bellow:

mixcr analyze neb-mouse-rna-xcr-umi-nebnext \
    raw/mouse_3_Cd4Cre_R1.fastq.gz \
    raw/mouse_3_Cd4Cre_R2.fastq.gz \
    results/mouse_3_Cd4Cre_R1

The command above will generate the following output files:

> ls results/

# human-readable reports for every step of the pipeline in txt and json formats
mouse_3_Cd4Cre.align.report.txt
mouse_3_Cd4Cre.align.report.json
mouse_3_Cd4Cre.refine.report.txt
mouse_3_Cd4Cre.refine.report.json
mouse_3_Cd4Cre.assemble.report.txt
mouse_3_Cd4Cre.assemble.report.json

# raw alignments (highly compressed binary file)
mouse_3_Cd4Cre.vdjca

# alignments with corrected UMI barcode sequences 
mouse_3_Cd4Cre.refined.vdjca

# IG clonotypes (highly compressed binary file)
mouse_3_Cd4Cre.clns

# IG clonotypes exported in tab-delimited tsv
mouse_3_Cd4Cre.clones_IGH.tsv
mouse_3_Cd4Cre.clones_IGK.tsv 
mouse_3_Cd4Cre.clones_IGL.tsv   

Clonotype tables is the main result of the upstream analysis. They are stored in a highly compressed and efficient binary .clns file and can be exported in many ways: detailed tab-delimited format with dozens of customizable columns, human-readable for manual inspection, and AIRR format suitable for many scientific downstream analysis tools. .clns files can be also used for downstream analysis using mixcr postanalisis.

By default, MiXCR exports clonotypes in a tab-delimited format separately for each immunological chain.