Multiplex generation and single cell analysis of structural variants in mammalian genomes [IVT-seq]

Studying the functional consequences of structural variants (SVs) in mammalian genomes is challenging because: 1) SVs arise much less commonly than single nucleotide variants or small indels; and 2) methods to generate, map and characterize SVs in model systems are underdeveloped. To address these challenges, we developed Genome-Shuffle-seq, a method that enables the multiplex generation and mapping of thousands of SVs (deletions, inversions, translocations, extrachromosomal circles) throughout mammalian genomes. We also demonstrate the co-capture of SV identity with single-cell transcriptomes, facilitating the measurement of SVs’ impact on gene expression. We anticipate Genome-Shuffle-seq will be broadly useful for the systematic exploration of the functional consequences of SVs on gene expression, chromatin landscape, and 3D nuclear architecture, while also initiating a path towards a minimal mammalian genome. IVT-seq libraries were constructed with T7 In vitro transcription (IVT) derived RNA from genomic DNA extracted from mammalian cell lines (mESC, K562) in which shuffle cassettes were integrated. IVT-seq was largely performed to map integration sites of shuffle cassettes in parental populations but also to validate rearrangements induced by the recombinase.

探究哺乳动物基因组中结构变异（structural variants, SVs）的功能性影响颇具挑战，原因在于：1）结构变异的发生频率远低于单核苷酸变异或小片段插入缺失；2）在模型系统中生成、定位并表征结构变异的方法尚不完善。为应对这些挑战，我们开发了Genome-Shuffle-seq，一种可在哺乳动物全基因组范围内多重生成并定位数千个结构变异（缺失、倒位、易位、染色体外环状结构）的方法。我们还证实了可实现结构变异特征与单细胞转录组的共捕获，从而便于量化结构变异对基因表达的影响。我们预计Genome-Shuffle-seq将可广泛用于系统探究结构变异对基因表达、染色质景观及三维细胞核架构的功能性影响，同时也将为构建最小化哺乳动物基因组开辟可行路径。本研究采用从整合了洗牌盒的哺乳动物细胞系（小鼠胚胎干细胞mESC、K562细胞）的基因组DNA中提取的、经T7体外转录（IVT）得到的RNA，构建了IVT-seq文库。IVT-seq主要用于定位亲本细胞群体中洗牌盒的整合位点，同时也可用于验证重组酶诱导的染色体重排。