Application of nonsense-mediated primer exclusion (NOPE) for preparation of unique molecular barcoded libraries

Abstract Background Recently we proposed efficient method to exclude undesirable primers at any stage of amplification reaction, here termed NOPE (NOnsense-mediated Primer Exclusion). According to this method, added oligonucleotide overlapping with the 3′-end of unwanted amplification primer (NOPE oligo) simultaneously provides a template for its elongation. This elongation disrupts specificity of unwanted primer, preventing its further participation in PCR. The suggested approach allows to rationally manage the course of PCR reactions in order to facilitate analysis of complex DNA mixtures as well as to perform multistage PCR bypassing intermediate purification steps. Results Here we apply NOPE method to DNA library preparation for the high-throughput sequencing (HTS) with the PCR-based introduction of unique molecular identifiers (UMI). We show that NOPE oligo efficiently neutralizes UMI-containing oligonucleotides after introduction of UMI into sample DNA molecules, thus allowing to proceed with further amplification steps without purification and associated loss of starting material. At the same time, NOPE oligo does not affect the efficiency of target PCR amplification. Conclusion We describe a simple, robust and cheap modification of UMI-labeled HTS libraries preparation procedure, that allows to bypass purification step and thus to preserve starting material which may be limited, e.g. circulating tumor DNA, circulating fetal DNA, or small amounts of isolated cells of interest. Furthermore, demonstrated simplicity and robustness of NOPE method should make it popular in various PCR protocols

VDJtools: Unifying Post-analysis of T Cell Receptor Repertoires

<div><p>Despite the growing number of immune repertoire sequencing studies, the field still lacks software for analysis and comprehension of this high-dimensional data. Here we report VDJtools, a complementary software suite that solves a wide range of T cell receptor (TCR) repertoires post-analysis tasks, provides a detailed tabular output and publication-ready graphics, and is built on top of a flexible API. Using TCR datasets for a large cohort of unrelated healthy donors, twins, and multiple sclerosis patients we demonstrate that VDJtools greatly facilitates the analysis and leads to sound biological conclusions. VDJtools software and documentation are available at <a href="https://github.com/mikessh/vdjtools" target="_blank">https://github.com/mikessh/vdjtools</a>.</p></div

Estimation of repertoire diversity using multinomial model.

<p><b>A.</b> Rarefaction analysis of repertoire samples from healthy donors and multiple sclerosis patients. The number of unique clonotypes in a sub-sample plotted against its size (number of T-cell receptor cDNA molecules, TRBM). Solid and dashed lines are diversity estimates computed by interpolating and extrapolating using a multinomial model respectively [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1004503#pcbi.1004503.ref029" target="_blank">29</a>]. Note that generally rarefaction curves for MS samples go below those of control donors. Post-HSCT sample (MS8-HSCT) displays the lowest diversity. <b>B.</b> Comparison of repertoire diversity using normalized Chao1 estimate. Normalization is performed by down-sampling datasets to the size of smallest dataset and computing the estimate for resulting datasets (mean estimate value from n = 3 re-samples is used). MS8-HSCT sample is discarded from calculations. *—P = 0.022, two-tailed T-test; effect size estimated by Cohen’s d is 0.98.</p