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Crinklaw, A.

Publications and source records attributed to Crinklaw, A..

2 recordsLinked to original sources

A CRISPR/Cas9-based enhancement of high-throughput single-cell transcriptomics

Single-cell transcriptomics suffers from lapses in coverage of the full transcriptome, providing an incomplete gene expression profile of the cell. Here, we introduce single-cell CRISPRclean (scCLEAN), an in vitro molecular method that can be universally inserted into any single-cell RNA-seq workflow to improve the sensitivity of the assay. Utilizing CRISPR/Cas9, scCLEAN works to selectively remove highly abundant uninformative molecules, redistributing ~50% of reads to enrich for lowly expressed transcripts. Utilizing immune cells, we describe a validation of scCLEAN showing a 2.1-fold enrichment in library complexity with negligible off-target effects. Subsequently, applying scCLEAN to single-cell iso-seq samples results in a 4.6-fold improvement in unique isoform detection. Thus, demonstrating a benefit in short and long read sequencing applications. Finally, we illustrate the ability of scCLEAN to elucidate biological insights by applying it to two participant cohorts of cardiovascular samples, bringing to light novel molecular characteristics including inflammatory signatures.

genetics↗

TCRMatch: Predicting T-cell receptor specificity based on sequence similarity to previously characterized receptors

The adaptive immune system in vertebrates has evolved to recognize non-self-antigens, such as proteins expressed by infectious agents and mutated cancer cells. T cells play an important role in antigen recognition by expressing a diverse repertoire of antigen-specific receptors, which bind epitopes to mount targeted immune responses. Recent advances in high-throughput sequencing have enabled the routine generation of T-cell receptor (TCR) repertoire data. Identifying the specific epitopes targeted by different TCRs in these data would be valuable. To accomplish that, we took advantage of the ever-increasing number of TCRs with known epitope specificity curated in the Immune Epitope Database (IEDB) since 2004. We compared six metrics of sequence similarity to determine their power to predict if two TCRs have the same epitope specificity. We found that a comprehensive k-mer matching approach produced the best results, which we have implemented into TCRMatch, an openly accessible tool (http://tools.iedb.org/tcrmatch/) that takes TCR {beta}-chain CDR3 sequences as an input, identifies TCRs with a match in the IEDB, and reports the specificity of each match. We anticipate that this tool will provide new insights into T cell responses captured in receptor repertoire and single cell sequencing experiments and will facilitate the development of new strategies for monitoring and treatment of infectious, allergic, and autoimmune diseases, as well as cancer.

immunology↗