Interpreting the B-cell receptor repertoire with single-cell gene expression using Benisse
نویسندگان
چکیده
B-cell receptors (BCRs) are a crucial player in the development and activation of B cells, their mature forms secreted as antibodies, which execute functions such neutralization invading pathogens. All current analytical approaches for BCRs solely investigate BCR sequences ignore correlations with transcriptomics yielding conclusions unknown functional relevance regarding roles could generate biased interpretation. Many single-cell RNA-sequencing (scRNA-seq) techniques can now capture both gene expression each cell, potentially address this issue. Here, we investigated 43,938 cells from 13 scRNA-seq datasets matched scBCR sequencing, observed an association between cells’ transcriptomics. Motivated by this, developed Benisse model (BCR embedding graphical network informed scRNA-seq) to provide refined analyses guided expression. revealed gradient along trajectories. We discovered stronger coupling during COVID-19 infections. found that form directed pattern continuous linear evolution achieve highest antigen targeting efficiency, compared convergent T-cell receptors. Overall, simultaneous digestion viewed through lens Benisse, will lead more insightful interpretation repertoire different biological contexts. impact on play vital role our immune system; however, manner activated still poorly understood. Ze Zhang colleagues present graph-based method connects single RNA sequencing data identifies notable COVID-19.
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ژورنال
عنوان ژورنال: Nature Machine Intelligence
سال: 2022
ISSN: ['2522-5839']
DOI: https://doi.org/10.1038/s42256-022-00492-6