Genome-wide CRISPR interference screen identifies long non-coding RNA loci required for differentiation and pluripotency

Abstract

Although many long non-coding RNAs (lncRNAs) exhibit lineage-specific expression, the vast majority remain functionally uncharacterized in the context of development. Here, we report the first described human embryonic stem cell (hESC) lines to repress (CRISPRi) or activate (CRISPRa) transcription during differentiation into all three germ layers, facilitating the modulation of lncRNA expression during early development. We performed an unbiased, genome-wide CRISPRi screen targeting thousands of lncRNA loci expressed during endoderm differentiation. While dozens of lncRNA loci were required for proper differentiation, most differentially expressed lncRNAs were not, supporting the necessity for functional screening instead of relying solely on gene expression analyses. In parallel, we developed a clustering approach to infer mechanisms of action of lncRNA hits based on a variety of genomic features. We subsequently identified and validated FOXD3-AS1 as a functional lncRNA essential for pluripotency and differentiation. Taken together, the cell lines and methodology described herein can be adapted to discover and characterize novel regulators of differentiation into any lineage.

CRISPR-Based Approaches for the High-Throughput Characterization of Long Non-Coding RNAs

“…Importantly, a positive phenotypic correlation was found for matching cell lines and sgRNAs in the studies of Liu et al and Haswell et al [47,49], indicating the robustness of this approach. Furthermore, both groups analyzed the correlation between different genetic and genomic features and hit lncRNAs.…”

“…More recently, Haswell et al [49] generated a pooled sgRNA CRISPRi library targeting 12,611 lncRNAs that are expressed in human embryonic stem cells (hESCs). The library was designed using the CRISPick tool (formerly Genetic Perturbation Platform) [96,113] based on TSSs predicted by the FANTOM5 CAGE-associated transcriptome (FANTOM-CAT) [114], and contained a total of 111,801 unique sgRNAs (roughly ten sgRNAs per gene).…”

“…The library was designed using the CRISPick tool (formerly Genetic Perturbation Platform) [96,113] based on TSSs predicted by the FANTOM5 CAGE-associated transcriptome (FANTOM-CAT) [114], and contained a total of 111,801 unique sgRNAs (roughly ten sgRNAs per gene). The authors screened for genes affecting hESC differentiation; they identified 60 functional lncRNAs, of which several were functionally validated [49]. However, among the 23 positive control protein-coding genes in the library, only six were identified as positive hits.…”

Emerging Roles and Mechanisms of lncRNA FOXD3-AS1 in Human Diseases

“…FOXD3-AS1 also stimulates differentiation induced by all-trans-retinoic-acid (ATRA) on neuroblastoma IMR32 and BE (2)-C cells through the inhibition of PARP1 and CTCF (41). Additionally, FOXD3-AS1 was first thought to induce pluripotency and differentiation of human embryonic stem cell (hESCs), in which undifferentiated hESCs present a high expression of FOXD3-AS1, while endoderm and mesoderm differentiation is correlated with low FOXD3-AS1 expression (177). Downregulation of FOXD3-AS1 results in pluripotency dysregulation through the inhibition of endoderm pathways.…”

Maximizing CRISPRi efficacy and accessibility with dual-sgRNA libraries and optimal effectors

“…Like other CRISPR approaches, CRISPRi has been paired with large-scale sgRNA libraries to conduct systematic genetic screens. Such screens have been deployed to identify essential protein-coding and non-coding genes (Gilbert et al, 2014; Haswell et al, 2021; Horlbeck et al, 2016a; Liu et al, 2017; Raffeiner et al, 2020), to map the targets of regulatory elements (Fulco et al, 2019, 2016; Gasperini et al, 2019; Kearns et al, 2015; Klann et al, 2017; Thakore et al, 2015), to identify regulators of cellular signaling and metabolism (Coukos et al, 2021; Liang et al, 2020; Luteijn et al, 2019; Semesta et al, 2020), to uncover stress response pathways in stem cell-derived neurons (Tian et al, 2021, 2019), to uncover regulators of disease-associated states in microglia and astrocytes (Dräger et al, 2022; Leng et al, 2022), to decode regulators of cytokine production in primary human T-cells (Schmidt et al, 2022), to define mechanisms of action of bioactive small molecules (Jost et al, 2017; Morgens et al, 2019; Sage et al, 2017), to identify synthetic-lethal genetic interactions in cancer cells (Du et al, 2017; Horlbeck et al, 2018), and to identify genetic determinants of complex transcriptional responses using RNA-seq readouts (Perturb-seq) (Adamson et al, 2016; Replogle et al, 2022, 2020; Tian et al, 2021, 2019), among others.…”