Chovanec Peter, Ridgley Trevor, Yin Yi
Department of Human Genetics, David Geffen School of Medicine, UCLA, Los Angeles, CA, 90095, USA.
bioRxiv. 2025 May 26:2025.05.19.654945. doi: 10.1101/2025.05.19.654945.
Despite the many advances in single cell genomics, detecting structural rearrangements in single cells, particularly error-free sister-chromatid exchanges, remains challenging. Here we describe sci-L3-Strand-seq, a combinatorial indexing method with linear amplification for DNA template strand sequencing that cost-effectively scales to millions of single cells, as a platform for mapping mitotic crossover and resulting genome instability events. We provide a computational framework to fully leverage the throughput, as well as the relatively sparse but multifaceted genotype information within each cell that includes strandedness, digital counting of copy numbers, and haplotype-aware chromosome segmentation, to systematically distinguish seven possible types of mitotic crossover outcomes. We showcase the power of sci-L3-Strand-seq by quantifying the rates of error-free and mutational crossovers in thousands of cells, enabling us to explore enrichment patterns of genomic and epigenomic features. The throughput of sci-L3-Strand-seq also gave us the ability to measure subtle phenotypes, opening the door for future large mutational screens. Furthermore, mapping clonal lineages provided insights into the temporal order of certain genome instability events, showcasing the potential to dissect cancer evolution. Altogether, we show the wide applicability of sci-L3-Strand-seq to the study of DNA repair and structural variations.
尽管单细胞基因组学取得了诸多进展,但在单细胞中检测结构重排,尤其是无错误的姐妹染色单体交换,仍然具有挑战性。在此,我们描述了sci-L3-Strand-seq,一种用于DNA模板链测序的具有线性扩增的组合索引方法,它能经济高效地扩展到数百万个单细胞,作为绘制有丝分裂交叉及由此产生的基因组不稳定事件的平台。我们提供了一个计算框架,以充分利用通量,以及每个细胞内相对稀疏但多方面的基因型信息,包括链特异性、拷贝数的数字计数和单倍型感知的染色体分割,从而系统地区分七种可能的有丝分裂交叉结果类型。我们通过量化数千个细胞中无错误和突变交叉的发生率来展示sci-L3-Strand-seq的强大功能,使我们能够探索基因组和表观基因组特征的富集模式。sci-L3-Strand-seq的通量还使我们有能力测量细微的表型,为未来大规模突变筛选打开了大门。此外,绘制克隆谱系为某些基因组不稳定事件的时间顺序提供了见解,展示了剖析癌症进化的潜力。总之,我们展示了sci-L3-Strand-seq在DNA修复和结构变异研究中的广泛适用性。