As one of the most abundant and conserved RNA species, transfer RNAs (tRNAs) are well known for their role in reading the codons on messenger RNAs and translating them into proteins. In this review, we discuss the noncanonical functions of tRNAs. These include tRNAs as precursors to novel small RNA molecules derived from tRNAs, also called tRNA-derived fragments, that are abundant across species and have diverse functions in different biological processes, including regulating protein translation, Argonaute-dependent gene silencing, and more. Furthermore, the role of tRNAs in biosynthesis and other regulatory pathways, including nutrient sensing, splicing, transcription, retroelement regulation, immune response, and apoptosis, is reviewed. Genome organization and sequence variation of tRNA genes are also discussed in light of their noncanonical functions. Lastly, we discuss the recent applications of tRNAs in genome editing and microbiome sequencing. Expected final online publication date for the Annual Review of Genetics, Volume 54 is November 23, 2020. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

RNA modifications are important regulatory elements of RNA functions. However, most genome-wide mapping of RNA modifications has focused on messenger RNAs and transfer RNAs, but such datasets have been lacking for small RNAs. Here we mapped N1-methyladenosine (m1A) in the cellular small RNA space. Benchmarked with synthetic m1A RNAs, our workflow identified specific groups of m1A-containing small RNAs, which are otherwise disproportionally under-represented. In particular, 22-nucleotides long 3′ tRNA-fragments are highly enriched for TRMT6/61A-dependent m1A located within the seed region. TRMT6/61A-dependent m1A negatively affects gene silencing by tRF-3s. In urothelial carcinoma of the bladder, where TRMT6/61A is over-expressed, higher m1A modification on tRFs is detected, correlated with a dysregulation of tRF targetome. Lastly, TRMT6/61A regulates tRF-3 targets involved in unfolded protein response. Together, our results reveal a mechanism of regulating gene expression via base modification of small RNA.

Extrachromosomal circular DNA (eccDNA) are present within all eukaryotic organisms and actively contribute to gene expression changes. MicroDNA (200-1000bp) are the most abundant type of eccDNA and can amplify tRNA, microRNA, and novel si-like RNA sequences. Due to the heterogeneity of microDNA and the limited technology to directly quantify circular DNA molecules, the specific DNA repair pathways that contribute to microDNA formation have not been fully elucidated. Using a sensitive and quantitative assay that quantifies eight known abundant microDNA, we report that microDNA levels are dependent on resection after double-strand DNA break (DSB) and repair by Microhomology Mediated End Joining (MMEJ). Further, repair of DSB without resection by canonical Non-Homologous End Joining (c-NHEJ) diminishes microDNA formation. MicroDNA levels are induced locally even by a single site-directed DSB, suggesting that excision of genomic DNA by two closely spaced DSB is not necessary for microDNA formation. Consistent with all this, microDNA levels accumulate as cells undergo replication in S-phase, when DNA breaks and repair are elevated, and microDNA levels are decreased if DNA synthesis is prevented. Thus, formation of microDNA occurs during the repair of endogenous or induced DNA breaks by resection-based DNA repair pathways.

The Bcl-2 inhibitor venetoclax (VEN) has yielded exceptional clinical responses in chronic lymphocytic leukemia (CLL). However, de novo resistance can result in failure to achieve negative minimal residual disease and predicts poor treatment outcomes. Consequently, additional pro-apoptotic drugs, such as inhibitors of Mcl-1 and Bcl-xL, are in development. By profiling anti-apoptotic proteins using flow cytometry, we find that leukemic B-cells recently emigrated from the lymph node (LN) (CD69Pos/CXCR4Low) in vivo are enriched for cell clusters simultaneously overexpressing multiple anti-apoptotic proteins (Mcl-1high/Bcl-xLhigh/Bcl-2high), in both treated and treatment naïve CLL patients. These cells exhibited anti-apoptotic resistance to multiple BH-domain antagonists, including inhibitors of Bcl-2, Mcl-1, and Bcl-xL, when tested as single agents in a flow cytometry-based functional assay. Anti-apoptotic multi-drug resistance declines ex vivo, consistent with resistance being generated in vivo by extrinsic microenvironmental interactions. Surviving "persister" cells in patients undergoing venetoclax treatment are enriched for CLL cells displaying the functional and molecular properties of microenvironmentally-induced multi-drug resistance. Overcoming this resistance required simultaneous inhibition of multiple anti-apoptotic proteins, with potential for unwanted toxicities. Using a drug screen performed using patient PBMCs cultured in an ex vivo microenvironment model we identify novel venetoclax drug combinations that induce selective cytotoxicity in multi-drug resistant CLL cells. Thus, we demonstrate that anti-apoptotic multi-drug resistant CLL cells exist in patients de novo, and show that these cells persist during pro-apoptotic treatment such as venetoclax. We validate clinically actionable approaches to selectively deplete this reservoir in patients.

Background: While clinical factors such as age, grade, stage, and histological subtype provide physicians with information about patient prognosis, genomic data can further improve these predictions. Previous studies have shown that germline variants in known cancer driver genes are predictive of patient outcome, but no study has systematically analyzed multiple cancers in an unbiased way to identify genetic loci that can improve patient outcome predictions made using clinical factors. Methods: We analyzed sequencing data from the over 10,000 cancer patients available through The Cancer Genome Atlas to identify germline variants associated with patient outcome using multivariate Cox regression models. Results: We identified 79 prognostic germline variants in individual cancers and 112 prognostic germline variants in groups of cancers. The germline variants identified in individual cancers provide additional predictive power about patient outcomes beyond clinical information currently in use and may therefore augment clinical decisions based on expected tumor aggressiveness. Molecularly, at least 12 of the germline variants are likely associated with patient outcome through perturbation of protein structure and at least five through association with gene expression differences. Almost half of these germline variants are in previously reported tumor suppressors, oncogenes or cancer driver genes with the other half pointing to genomic loci that should be further investigated for their roles in cancers. Conclusions: Germline variants are predictive of outcome in cancer patients and specific germline variants can improve patient outcome predictions beyond predictions made using clinical factors alone. The germline variants also implicate new means by which known oncogenes, tumor suppressor genes, and driver genes are perturbed in cancer and suggest roles in cancer for other genes that have not been extensively studied in oncology. Further studies in other cancer cohorts are necessary to confirm that germline variation is associated with outcome in cancer patients as this is a proof-of-principle study.

LncRNAs are long RNA transcripts that do not code for proteins and that have been shown to play a major role in cellular processes through diverse mechanisms. DRAIC, a lncRNA which is downregulated in castration-resistant advanced prostate cancer, inhibits the NF-kB pathway by inhibiting the IκB kinase. Decreased DRAIC expression predicted poor patient outcome in gliomas and seven other cancers. We now report that DRAIC suppresses invasion, migration, colony formation and xenograft growth of glioblastoma derived cell lines. DRAIC activates AMPK by downregulating the NF-κB target gene GLUT1, and thus represses mTOR, leading to downstream effects such as decrease in protein translation and increase in autophagy. DRAIC, therefore, has an effect on multiple signal transduction pathways that are important for oncogenesis: the NF-κB pathway and AMPK-mTOR-S6K/ULK1 pathway. The regulation of NF-κB, protein translation and autophagy by the same lncRNA explains the tumor suppressive role of DRAIC in different cancers and reinforces the importance of lncRNAs as emerging regulators of signal transduction pathways.

tRNA derived small RNAs are mainly composed of tRNA fragments (tRFs) and tRNA halves (tiRs). Several functions have been attributed to tRFs and tiRs since their initial characterizations, spanning all aspects of regulation of the Central Dogma: from nascent RNA silencing, to post-transcriptional gene silencing, and finally, to translational regulation. The length distribution, sequence diversity, and multifaceted functions of tRFs and tiRs positions them as attractive new models for small RNA therapeutics. In this review, we will discuss the principles of tRF biogenesis and function in order to highlight their therapeutic potential.

While clinical data provides physicians with information about patient prognosis, genomic data can further improve these predictions. We analyzed sequencing data from over 10,000 cancer patients and identified hundreds of prognostic germline variants using multivariate Cox regression models. These variants provide information about patient outcomes beyond clinical information currently in use and may augment clinical decisions based on expected tumor aggressiveness. Molecularly, at least twelve of the germline variants are likely associated with patient outcome through perturbation of protein structure and at least five through association with gene expression differences. About half of these germline variants are in previously reported tumor suppressors or oncogenes, with the other half pointing to loci of previously unstudied genes in the literature that should be further investigated for roles in cancers. Our results suggest that germline variation contributes to tumor progression across most cancers and contains patient outcome information not captured by clinical factors.