Fan Gao

The human genome encodes a multitude of different noncoding transcripts that have been traditionally separated on the basis of their lengths into long (>200 nt) or small (40%) of unannotated sncRNAs appear to have biological relevance. Furthermore, contrary to the expectation, the potentially functional transcripts are not highly abundant and can be derived from protein-coding mRNAs. These results strongly suggest that the small noncoding transcriptome can harbor multiple functional transcripts that warrant future studies.

Early cancer detection is the key to a positive clinical outcome. While a number of early diagnostics methods exist in clinics today, they tend to be invasive and limited to a few cancer types. Thus, a clear need exists for non-invasive diagnostics methods that can be used to detect the presence of cancer of any type. Liquid biopsy based on analysis of molecular components of peripheral blood has shown significant promise in such pan-cancer diagnostics; however, existing methods based on this approach require improvements, especially in sensitivity of early-stage cancer detection. The improvement would likely require diagnostics assays based on multiple different types of biomarkers and, thus, calls for identification of novel types of cancer-related biomarkers that can be used in liquid biopsy. Whole-blood transcriptome, especially its non-coding component, represents an obvious yet under-explored biomarker for pan-cancer detection. In this study, we show that whole transcriptome analysis using RNA-seq could indeed serve as a viable biomarker for pan-cancer detection. Furthermore, a class of long non-coding (lnc) RNAs, very long intergenic non-coding (vlinc) RNAs, demonstrated superior performance compared with protein-coding mRNAs. Finally, we show that age and presence of non-blood cancers change transcriptome in similar, yet not identical, directions and explore implications of this observation for pan-cancer diagnostics.

Although naturally occurring catalytic RNA molecules—ribozymes—have attracted a great deal of research interest, very few have been identified in humans. Here, we developed a genome-wide approach to discovering self-cleaving ribozymes and identified a naturally occurring ribozyme in humans. The secondary structure and biochemical properties of this ribozyme indicate that it belongs to an unidentified class of small, self-cleaving ribozymes. The sequence of the ribozyme exhibits a clear evolutionary path, from its appearance between ~130 and ~65 million years ago (Ma), to acquiring self-cleavage activity very recently, ~13–10 Ma, in the common ancestors of humans, chimpanzees and gorillas. The ribozyme appears to be functional in vivo and is embedded within a long noncoding RNA belonging to a class of very long intergenic noncoding RNAs. The presence of a catalytic RNA enzyme in lncRNA creates the possibility that these transcripts could function by carrying catalytic RNA domains.

Long non-coding RNAs (lncRNAs) represent a major fraction of the transcriptome in multicellular organisms. Although a handful of well-studied lncRNAs are broadly recognized as biologically meaningful, the fraction of such transcripts out of the entire collection of lncRNAs remains a subject of vigorous debate. Here we review the evidence for and against biological functionalities of lncRNAs and attempt to arrive at potential modes of lncRNA functionality that would reconcile the contradictory conclusions. Finally, we discuss different strategies of phenotypic analyses that could be used to investigate such modes of lncRNA functionality.

Long non-coding (lnc) RNAs represent a fascinating class of transcripts that remains highly controversial mainly due to ambiguity surrounding overall biological relevance of these RNAs. Multitude of reverse genetics studies showing functionality of lncRNAs are unfortunately based on assays that are either plagued by non-specific effects and/or cannot unambiguously assign observed phenotypes to the transcript per se. Here, we show application of the novel CRISPR/Cas13 RNA knockdown system that has superior specificity compared to other transcript-targeting knockdown methods like RNAi. We applied this method to a novel widespread subclass of nuclear lncRNAs — very long intergenic non-coding (vlinc) RNAs — in a high-throughput phenotypic assay based on survival challenge in response to anticancer drug treatments. We used multiple layers of controls including mismatch control for each targeting gRNA to ensure uncovering true phenotype-transcript relationships. We found evidence supporting importance for cellular survival for up to 60% of the tested protein-coding mRNAs and, importantly, 64% of vlincRNAs. Overall, this study demonstrates utility of CRISPR/Cas13 as a highly sensitive and specific tool for reverse genetics study of both protein-coding genes and lncRNAs. Furthermore, importantly, this approach provides evidence supporting biological significance of the latter transcripts in anticancer drug response.

Single-strand breaks (SSBs) represent the major form of DNA damage, yet techniques to map these lesions genome-wide with nucleotide-level precision are limited. Here, we present a method, termed SSiNGLe, and demonstrate its utility to explore the distribution and dynamic changes in genome-wide SSBs in response to different biological and environmental stimuli. We validate SSiNGLe using two very distinct sequencing techniques and apply it to derive global profiles of SSBs in different biological states. Strikingly, we show that patterns of SSBs in the genome are non-random, specific to different biological states, enriched in regulatory elements, exons, introns, specific types of repeats and exhibit differential preference for the template strand between exons and introns. Furthermore, we show that breaks likely contribute to naturally occurring sequence variants. Finally, we demonstrate strong links between SSB patterns and age. Overall, SSiNGLe provides access to unexplored realms of cellular biology, not obtainable with current approaches.