美国波士顿大学Brian Cleary研究小组利用压缩的Perturb-seq对调控回路进行可扩展的遗传筛选。相关论文于2023年10月23日在线发表在《自然—生物技术》杂志上。

研究人员修改了带有单细胞RNA测序读出的集合CRISPR筛选（Perturb-seq）的设计，将算法应用于随机低维观测。压缩的Perturb-seq对每个细胞或每个液滴的多个细胞进行多次随机扰动测量，并利用调控回路的稀疏结构对这些测量结果进行计算解压缩。将压缩的Perturb-seq应用于细菌脂多糖免疫反应中的598个基因，其精确度与传统Perturb-seq相当，但成本却降低了一个数量级，而且学习基因相互作用的能力更强。

研究人员发现了已知的和新的免疫反应调节因子，并发现了受演化制约的基因，其下游靶标富含免疫疾病遗传性，包括现有全基因组关联研究遗漏的许多基因。这个框架为功能基因组学中的一种基础方法提供了新的研究范围。

据了解，Perturb-seq已成为功能基因组学的一项关键技术，但其规模受到成本和组合复杂性的限制。

附：英文原文

Title: Scalable genetic screening for regulatory circuits using compressed Perturb-seq

Author: Yao, Douglas, Binan, Loic, Bezney, Jon, Simonton, Brooke, Freedman, Jahanara, Frangieh, Chris J., Dey, Kushal, Geiger-Schuller, Kathryn, Eraslan, Basak, Gusev, Alexander, Regev, Aviv, Cleary, Brian

Issue&Volume: 2023-10-23

Abstract: Pooled CRISPR screens with single-cell RNA sequencing readout (Perturb-seq) have emerged as a key technique in functional genomics, but they are limited in scale by cost and combinatorial complexity. In this study, we modified the design of Perturb-seq by incorporating algorithms applied to random, low-dimensional observations. Compressed Perturb-seq measures multiple random perturbations per cell or multiple cells per droplet and computationally decompresses these measurements by leveraging the sparse structure of regulatory circuits. Applied to 598 genes in the immune response to bacterial lipopolysaccharide, compressed Perturb-seq achieves the same accuracy as conventional Perturb-seq with an order of magnitude cost reduction and greater power to learn genetic interactions. We identified known and novel regulators of immune responses and uncovered evolutionarily constrained genes with downstream targets enriched for immune disease heritability, including many missed by existing genome-wide association studies. Our framework enables new scales of interrogation for a foundational method in functional genomics.

DOI: 10.1038/s41587-023-01964-9

Source: https://www.nature.com/articles/s41587-023-01964-9