Pinglay Sudarshan, Lalanne Jean-Benoît, Daza Riza M, Kottapalli Sanjay, Quaisar Faaiz, Koeppel Jonas, Garge Riddhiman K, Li Xiaoyi, Lee David S, Shendure Jay
Department of Genome Sciences, University of Washington, Seattle, WA, USA.
Brotman Baty Institute for Precision Medicine, Seattle, WA, USA.
Science. 2025 Jan 31;387(6733):eado5978. doi: 10.1126/science.ado5978.
Studying the functional consequences of structural variants (SVs) in mammalian genomes is challenging because (i) SVs arise much less commonly than single-nucleotide variants or small indels and (ii) 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, and extrachromosomal circles) throughout mammalian genomes. We also demonstrate the co-capture of SV identity with single-cell transcriptomes, facilitating the measurement of SV impact on gene expression. We anticipate that Genome-Shuffle-seq will be broadly useful for the systematic exploration of the functional consequences of SVs on gene expression, the chromatin landscape, and three-dimensional nuclear architecture, while also initiating a path toward a minimal mammalian genome.
研究哺乳动物基因组中结构变异（SVs）的功能后果具有挑战性，原因如下：（i）SVs出现的频率远低于单核苷酸变异或小插入缺失；（ii）在模型系统中生成、定位和表征SVs的方法尚不完善。为应对这些挑战，我们开发了基因组重排测序（Genome-Shuffle-seq）方法，该方法能够在整个哺乳动物基因组中多重生成和定位数千个SVs（缺失、倒位、易位和染色体外环状结构）。我们还展示了SV身份与单细胞转录组的共同捕获，便于测量SV对基因表达的影响。我们预计，基因组重排测序将广泛应用于系统探索SVs对基因表达、染色质景观和三维核结构的功能后果，同时也为构建最小哺乳动物基因组开辟道路。
