CRISPR-Cas13 Screens Reveal Hundreds of Long Non-Coding RNAs Cells Cannot Live Without

Roughly three-quarters of the human genome is transcribed into RNA, yet fewer than five percent of those sequences carry instructions for making proteins. The rest of this transcriptional output was once dismissed as genomic noise, but decades of research have revealed a sprawling cast of non-coding RNAs that help run the cell’s regulatory machinery. Among them, long non-coding RNAs, or lncRNAs, transcripts longer than 200 nucleotides that make up 80 to 90 percent of all non-coding RNA species, have emerged as major players in development, disease, and everyday cellular housekeeping. The trouble is that figuring out which of these thousands of transcripts actually matter has been extraordinarily difficult, and a new wave of RNA-targeting CRISPR technology is now changing that picture dramatically.

The central problem is technical. Unlike protein-coding genes, lncRNAs show low sequence conservation across species, are expressed at low levels, and often have complex structures that make them hard to detect, quantify, and manipulate. Traditional RNA interference, the workhorse of gene-silencing experiments for two decades, has been applied to only a small number of systematic lncRNA screens because of high costs, incomplete annotation, and limited scalability. CRISPR-based approaches such as CRISPR knockout, CRISPR interference, and CRISPR activation have filled some of the gap, but they share a fundamental limitation: they act on DNA. Because many lncRNAs are produced from overlapping or repetitive genomic regions, a single guide RNA aimed at the genome often fails to abolish the transcript. Complete knockout typically requires dual guide RNAs to create large deletions, or laborious monoclonal screening to generate homozygous knockout lines, all of which is inefficient, prone to off-target effects, and risks accidentally disrupting neighboring protein-coding genes.

To get around these obstacles, Neville E. Sanjana’s team developed CaRPool-seq, short for Cas13 RNA Perturb-seq, a transcriptome-scale screening platform built on CRISPR-Cas13. Unlike Cas9, which cuts DNA, Cas13 is an RNA-guided, RNA-targeting nuclease. Guide RNAs designed against a given transcript bind and silence it directly at the RNA level, leaving the underlying genome untouched. That single design change minimizes nonspecific DNA editing, reduces off-target interference, and makes it possible to knock down lncRNAs precisely and in parallel across thousands of targets at once. In effect, the platform converts the entire transcriptome into a druggable target space for functional screening.

The scale of the experiment is what makes it remarkable. The researchers mined lncRNA expression data from seven human organs sampled across 26 developmental stages, spanning everything from four weeks of gestation to late adulthood, and used that information to build a guide RNA library targeting 6,199 lncRNAs alongside 4,390 protein-coding genes. The library, comprising roughly 75,000 guide RNAs, was delivered into five human cell lines, HAP1, HEK293T, K562, MDA-MB-231, and THP1, using lentiviral vectors. The team then tracked the abundance of each guide RNA at days zero, seven, and fourteen after delivery. The logic is elegantly simple: if depleting a particular lncRNA harms the cell, cells carrying guides against that transcript will underperform, and those guides will become depleted from the population over time. A significant drop in guide abundance therefore signals that the targeted RNA is doing something the cell cannot live without.

The screen identified 778 lncRNAs that are essential for survival in at least one cell line. Of those, 46, including the well-known nuclear speckle transcript MALAT1 and the MIR17HG locus, proved essential across all five cell lines, a universality that suggests deeply conserved, core cellular functions. These universally essential lncRNAs shared several telling characteristics: they tended to be highly expressed, their function appeared conserved, and structurally they were predominantly antisense or bidirectional transcripts rather than isolated intergenic ones. That architectural bias hints that genomic context, the way a lncRNA sits relative to its neighbors on the DNA, may shape what these molecules do. Perhaps most intriguingly, most essential lncRNAs did not show significant co-expression with adjacent protein-coding genes, arguing that they act as functionally independent entities rather than byproducts of nearby gene activity, potentially operating through long-range or cross-regulatory mechanisms.

Comparing the essential lncRNAs with essential protein-coding genes revealed further surprises. Both classes were enriched among the guide RNAs showing the strongest depletion, confirming that the screen was genuinely detecting genes the cells depend on. But unlike essential protein-coding genes, essential lncRNAs tended to exert their effects at relatively low expression levels, meaning that scarcity does not equal insignificance in the RNA world. Functionally, when the researchers depleted these transcripts, cells primarily responded by undergoing apoptosis and losing normal cell-cycle progression, two hallmarks of a cell losing control of its most basic survival programs.

To move beyond survival phenotypes and understand what these lncRNAs are actually doing, the team integrated CaRPool-seq with single-cell transcriptome analysis, allowing them to read out the full gene-expression consequences of each knockdown in individual cells. This revealed that loss of essential lncRNAs impairs cell-cycle progression and promotes programmed cell death. Gene set enrichment analysis pointed to strong associations with the major proliferation-controlling pathways, including MYC, mTOR, p53, E2F, and the G2M checkpoint, and crucially, these effects were independent of changes in neighboring protein-coding genes. The essential lncRNAs also showed dynamic expression during development: they were highly expressed in early embryogenesis, downregulated as development proceeded, and enriched in proliferative tissues such as brain, heart, liver, and kidney. Their expression rose sharply during early stages of cell proliferation and declined later, consistent with a role in shepherding cells through growth phases.

The clinical implications emerged when the team turned to cancer. Analyzing roughly 9,000 tumor transcriptomes, they found that essential lncRNAs display aberrant expression signatures across cancers, co-express with known oncogenic drivers, and correlate with patient survival outcomes. Notably, essential lncRNAs showed greater expression variability in cancer cells than their non-essential counterparts, a pattern that underscores their potential role in tumor heterogeneity, the diversity of cell states within a tumor that makes many cancers so hard to treat. Because lncRNAs are often expressed in a tissue- and disease-specific manner, they are attractive candidates for biomarkers and for therapies that could, in principle, target cancer cells while sparing healthy tissue.

The study, published as an editorial commentary in Advanced Biotechnology, marks a significant advance in lncRNA biology by demonstrating that transcriptome-scale, RNA-targeting CRISPR-Cas13 screens can identify essential non-coding transcripts with high precision and scalability. The approach is not limited to lncRNAs; it can in principle be extended to other non-coding RNA classes, including microRNAs and circular RNAs, opening a systematic path to functional annotation of the entire non-coding transcriptome. Still, the field faces real challenges. The structural complexity of lncRNAs complicates guide RNA design, current libraries do not yet cover the full transcriptome, and downstream validation in disease-relevant models remains necessary before screening hits can be translated into the clinic.

Looking ahead, the authors argue that progress will depend on more sophisticated bioinformatics tools, potentially combining artificial intelligence with RNA structural modeling, to optimize guide design, reduce off-target effects, and push screens to even greater scale. If those improvements materialize, RNA-targeting CRISPR platforms like CaRPool-seq could accelerate the translation of lncRNA research into precision diagnostics and therapies, finally giving the dark matter of the genome the functional map it has long lacked.

Subject of Research: Transcriptome-scale CRISPR-Cas13 screening to identify essential long non-coding RNAs in human cells

Article Title: Uncovering essential lncRNAs through transcriptome-scale CRISPR-Cas13 screening

Article References: Uncovering essential lncRNAs through transcriptome-scale CRISPR-Cas13 screening. (n.d.). https://doi.org/10.1007/s44307-025-00082-8

Image Credits: AI Generated

DOI: 10.1007/s44307-025-00082-8

Keywords: lncRNA, CRISPR-Cas13, CaRPool-seq, non-coding RNA, functional genomics, single-cell transcriptomics, RNA targeting, gene screening, apoptosis, cell cycle, cancer biomarkers, precision medicine