LBPO.BCS01 · 生物信息与计算 · Late-Breaking
scVarID：将体细胞变异与单细胞转录组关联，揭示癌症早期相关的细胞状态
scVarID: Linking somatic variants to single-cell transcriptomes to reveal early cancer-associated cell states
作者与单位 Authors & Affiliations
摘要 Abstract
中文摘要
以单细胞分辨率识别体细胞变异如何重塑基因表达，对于理解癌症的发生和演化至关重要，然而在同一细胞中联合测量DNA和RNA在技术上仍具挑战。单细胞RNA测序（scRNA-seq）能够捕获丰富的转录异质性，但通常丢弃变异层面的信息，或将其视为混合（bulk）信号处理。我们开发了scVarID，这是一个转录本感知框架，能够将来自外显子组或panel测序的外部检出体细胞变异映射到单细胞转录组上，生成跨表达分子的每个细胞、每个变异的参考等位基因与替代等位基因计数矩阵。为对scVarID进行基准测试，我们利用了HG002——一个具有金标准基因组变异集和单细胞长读长RNA测序数据的参考个体。将经过整理的变异映射到scRNA-seq读段上，显示出DNA变异在RNA中的高回收率，并以单细胞分辨率揭示了HLA I类和II类基因中不同的等位基因偏好。借助长读长覆盖，scVarID进一步推断了表达的HLA等位基因的单体型，将等位基因特异性表达模式定相（phasing）到单个细胞和状态。随后，我们将scVarID应用于具有配对肿瘤/正常外显子组和scRNA-seq的结直肠癌队列，证实了许多体细胞变异的转录活性，并观察到免疫细胞和上皮细胞区室中类似的以HLA为焦点的等位基因失衡，包括罕见的正常上皮亚群，其HLA-A比值偏斜，与抗原呈递的早期破坏相一致。这些结果确立了scVarID作为一种可扩展方法，用于在参考样本和患者样本中整合外部检出的体细胞变异图谱与单细胞表达程序。通过在细胞分辨率上解析基因型-表型关系，scVarID能够发现免疫监视通路及其他癌症相关过程中混合测序无法察觉的细微扰动，并为在精准肿瘤学中绘制演化轨迹和高危细胞群体提供了一个通用框架。
查看英文原文 English abstract
Identifying how somatic variants reshape gene expression at single-cell resolution is essential for understanding cancer initiation and evolution, yet joint measurement of DNA and RNA in the same cell remains technically demanding. Single-cell RNA sequencing (scRNA-seq) captures rich transcriptional heterogeneity but typically discards variant-level information or treats it as bulk signal. We developed scVarID, a transcript-aware framework that maps externally called somatic variants from exome or panel sequencing onto single-cell transcriptomes, generating per-cell, per-variant matrices of reference and alternate allele counts across expressed molecules. To benchmark scVarID, we leveraged HG002, a reference individual with a gold-standard genomic variant set and single-cell long-read RNA sequencing data. Mapping curated variants onto scRNA-seq reads demonstrated high recovery of DNA variants in RNA and revealed distinct allele preferences in HLA class I and class II genes at single-cell resolution. Taking advantage of long-read coverage, scVarID further inferred haplotypes for expressed HLA alleles, phasing allele-specific expression patterns to individual cells and states. We then applied scVarID to colorectal cancer cohorts with matched tumor/normal exomes and scRNA-seq, confirming transcriptional activity for many somatic variants and observing similar HLA-focused allelic imbalance in immune and epithelial compartments, including rare normal epithelial subpopulations with skewed HLA-A ratios consistent with early disruption of antigen presentation. These results establish scVarID as a scalable approach for integrating externally called somatic variant profiles with single-cell expression programs in both reference and patient samples. By resolving genotype-phenotype relationships at cellular resolution, scVarID enables the discovery of subtle perturbations in immune-surveillance pathways and other cancer-relevant processes that are invisible to bulk sequencing, and provides a general framework for mapping evolutionary trajectories and high-risk cell populations in precision oncology.
利益披露 Disclosure
D. Shin, None..
J. Cho, None..
J. Lee, None..
S. Jang, None.