论文标题

将突变和重组统计数据结合起来,以推断抗体库中的克隆家族

Combining mutation and recombination statistics to infer clonal families in antibody repertoires

论文作者

Spisak, Natanael, Athènes, Gabriel, Dupic, Thomas, Mora, Thierry, Walczak, Aleksandra M.

论文摘要

B细胞曲目的特征是通过两个躯体多样化过程产生的不同特异性的多种受体:V(d)J重组和躯体过度过度。 B细胞克隆家族源于相同的V(d)J重组事件,但其高温却有所不同。克隆家族识别是了解B细胞曲目功能,进化和动态的关键。我们提出了Hilary(抗体曲目中谱系的高精度推断),这是一种有效,快速和精确的方法,可从单或成对的链曲目测序数据集中识别克隆家族。 Hilary结合了概率模型,这些模型将受体的产生和选择统计数据与适应的聚类方法捕获,以达到一致的推理精度。它会自动利用困难曲目子集中共享突变的系统发育信号。利用该方法的高灵敏度,我们发现了进化特性(例如位点频谱和DN/DS比率)的统计数据不取决于连接长度。我们还确定了跨越两个数量级的广泛选择压力。

B-cell repertoires are characterized by a diverse set of receptors of distinct specificities generated through two processes of somatic diversification: V(D)J recombination and somatic hypermutations. B cell clonal families stem from the same V(D)J recombination event, but differ in their hypermutations. Clonal families identification is key to understanding B-cell repertoire function, evolution and dynamics. We present HILARy (High-precision Inference of Lineages in Antibody Repertoires), an efficient, fast and precise method to identify clonal families from single- or paired-chain repertoire sequencing datasets. HILARy combines probabilistic models that capture the receptor generation and selection statistics with adapted clustering methods to achieve consistently high inference accuracy. It automatically leverages the phylogenetic signal of shared mutations in difficult repertoire subsets. Exploiting the high sensitivity of the method, we find the statistics of evolutionary properties such as the site frequency spectrum and dN/dS ratio do not depend on the junction length. We also identify a broad range of selection pressures spanning two orders of magnitude.

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