Worm Perturb-Seq: massively parallel whole-animal RNAi and RNA-seq.

Area of Science:

• Genomics
• Molecular Biology
• Systems Biology

Background:

• The transcriptome is a key molecular phenotype linking genotype to phenotype, typically measured by RNA-sequencing (RNA-seq).
• Perturbing every gene and measuring transcriptomic changes is a goal, but challenging in intact organisms.
• Existing methods face experimental and computational hurdles for large-scale perturbation analysis.

Purpose of the Study:

• To introduce Worm Perturb-Seq (WPS), a method for high-resolution RNA-seq profiles of numerous replicate perturbations in vivo.
• To present EmpirDE, an analytical framework designed for large WPS datasets to identify differentially expressed genes (DEGs).
• To apply WPS and EmpirDE to delineate a gene regulatory network (GRN) for Caenorhabditis elegans nuclear hormone receptors (NHRs).

Main Methods:

• WPS combines experimental advances from bulk and single-cell RNA-seq for high-throughput analysis in living animals.
• EmpirDE utilizes gene-specific empirical null distributions to identify DEGs, removing technical biases and enhancing statistical rigor.
• The method was applied to 103 C. elegans NHRs to construct a GRN.

Main Results:

• WPS provides high-resolution RNA-seq profiles for hundreds of replicate perturbations simultaneously.
• EmpirDE effectively identifies DEGs by leveraging empirical null distributions, improving statistical power.
• Analysis of 103 NHRs in C. elegans revealed a GRN with significant 'pairwise modularity', where NHR pairs co-regulate target genes.

Conclusions:

• WPS offers a powerful approach for large-scale gene perturbation studies in living organisms.
• The EmpirDE framework enhances the statistical robustness of DEG analysis from large transcriptomic datasets.
• The discovered pairwise modularity in the NHR GRN provides new insights into gene regulation in C. elegans and potentially other model systems, including human cells.