Neville Sanjana, PhD

Professor of Biology, Neuroscience and Physiology, New York University

Massively-parallel approaches to understand the human noncoding genome and transcriptome

Neville E. Sanjana^1,2

¹ New York Genome Center, New York, NY USA

² Department of Biology, New York University, New York, NY USA

I will present recent work from our lab on two topics: variant-to-function challenges in noncoding genomics and the development of RNA-targeting CRISPR screens to pinpoint functional noncoding RNAs.

Most variants associated with complex traits and diseases identified by genome-wide association studies (GWAS) map to noncoding regions of the genome with unknown effects. Using ancestrally diverse biobank-scale GWAS data, massively parallel CRISPR screens, and single cell transcriptomic and proteomic sequencing, we discovered 124 cis-target genes of 91 noncoding blood trait GWAS loci. Using precise variant insertion via base editing, we connected specific variants with gene expression changes. We also identified trans-effect networks of noncoding loci when cis target genes encoded transcription factors or microRNAs. Networks were themselves enriched for GWAS variants and demonstrated polygenic contributions to complex traits. This platform enables massively-parallel characterization of the target genes and mechanisms of human noncoding variants in both cis and trans.

The human genome is pervasively transcribed into RNA and encodes thousands of long noncoding RNAs (lncRNAs) that are often spliced and polyadenylated but not translated into proteins. Of annotated lncRNAs, less than 1% have been linked with a clear functional role. Using RNA-targeting CRISPR-Cas13 screens, we probed how the loss of 5,500 lncRNAs impacts cell fitness across five human cell lines and identified 788 lncRNAs with context-specific or broad essentiality. We confirm their essentiality with individual perturbations and find that the majority of essential lncRNAs operate independently of their nearest protein-coding genes. With  transcriptome profiling in single cells, we discover that the loss of essential lncRNAs impairs cell-cycle progression and drives apoptosis. Many essential lncRNAs demonstrate dynamic expression across tissues during development. Using 9,000 primary tumors, we pinpoint those lncRNAs whose expression in tumors correlates with survival, yielding new biomarkers and potential therapeutic targets.