Secondary Structural Model of MALAT1 Becomes Unstructured in Chronic Myeloid Leukemia and Undergoes Structural Rearrangement in Cervical Cancer.

Long noncoding RNAs (lncRNAs) influence cellular function through binding events that often depend on the lncRNA secondary structure. One such lncRNA, metastasis-associated lung adenocarcinoma transcript 1 (MALAT1), is upregulated in many cancer types and has a myriad of protein- and miRNA-binding sites. Recently, a secondary structural model of MALAT1 in noncancerous cells was proposed to form 194 hairpins and 13 pseudoknots. That study postulated that, in cancer cells, the MALAT1 structure likely varies, thereby influencing cancer progression. This work analyzes how that structural model is expected to change in K562 cells, which originated from a patient with chronic myeloid leukemia (CML), and in HeLa cells, which originated from a patient with cervical cancer. Dimethyl sulfate-sequencing (DMS-Seq) data from K562 cells and psoralen analysis of RNA interactions and structure (PARIS) data from HeLa cells were compared to the working structural model of MALAT1 in noncancerous cells to identify sites that likely undergo structural alterations. MALAT1 in K562 cells is predicted to become more unstructured, with almost 60% of examined hairpins in noncancerous cells losing at least half of their base pairings. Conversely, MALAT1 in HeLa cells is predicted to largely maintain its structure, undergoing 18 novel structural rearrangements. Moreover, 50 validated miRNA-binding sites are affected by putative secondary structural changes in both cancer types, such as miR-217 in K562 cells and miR-20a in HeLa cells. Structural changes unique to K562 cells and HeLa cells provide new mechanistic leads into how the structure of MALAT1 may mediate cancer in a cell-type specific manner.

Naturally occurring modified ribonucleosides.

The chemical identity of RNA molecules beyond the four standard ribonucleosides has fascinated scientists since pseudouridine was characterized as the "fifth" ribonucleotide in 1951. Since then, the ever-increasing number and complexity of modified ribonucleosides have been found in viruses and throughout all three domains of life. Such modifications can be as simple as methylations, hydroxylations, or thiolations, complex as ring closures, glycosylations, acylations, or aminoacylations, or unusual as the incorporation of selenium. While initially found in transfer and ribosomal RNAs, modifications also exist in messenger RNAs and noncoding RNAs. Modifications have profound cellular outcomes at various levels, such as altering RNA structure or being essential for cell survival or organism viability. The aberrant presence or absence of RNA modifications can lead to human disease, ranging from cancer to various metabolic and developmental illnesses such as Hoyeraal-Hreidarsson syndrome, Bowen-Conradi syndrome, or Williams-Beuren syndrome. In this review article, we summarize the characterization of all 143 currently known modified ribonucleosides by describing their taxonomic distributions, the enzymes that generate the modifications, and any implications in cellular processes, RNA structure, and disease. We also highlight areas of active research, such as specific RNAs that contain a particular type of modification as well as methodologies used to identify novel RNA modifications. This article is categorized under: RNA Processing > RNA Editing and Modification.

Secondary Structural Model of Human MALAT1 Reveals Multiple Structure-Function Relationships.

Human metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) is an abundant nuclear-localized long noncoding RNA (lncRNA) that has significant roles in cancer. While the interacting partners and evolutionary sequence conservation of MALAT1 have been examined, much of the structure of MALAT1 is unknown. Here, we propose a hypothetical secondary structural model for 8425 nucleotides of human MALAT1 using three experimental datasets that probed RNA structures in vitro and in various human cell lines. Our model indicates that approximately half of human MALAT1 is structured, forming 194 helices, 13 pseudoknots, five structured tetraloops, nine structured internal loops, and 13 intramolecular long-range interactions that give rise to several multiway junctions. Evolutionary conservation and covariation analyses support 153 of 194 helices in 51 mammalian MALAT1 homologs and 42 of 194 helices in 53 vertebrate MALAT1 homologs, thereby identifying an evolutionarily conserved core that likely has important functional roles in mammals and vertebrates. Data mining revealed that RNA modifications, somatic cancer-associated mutations, and single-nucleotide polymorphisms may induce structural rearrangements that sequester or expose binding sites for several cancer-associated microRNAs. Our findings reveal new mechanistic leads into the roles of MALAT1 by identifying several intriguing structure-function relationships in which the dynamic structure of MALAT1 underlies its biological functions.

Stability of an RNA•DNA-DNA triple helix depends on base triplet composition and length of the RNA third strand.

Recent studies suggest noncoding RNAs interact with genomic DNA, forming an RNA•DNA-DNA triple helix that regulates gene expression. However, base triplet composition of pyrimidine motif RNA•DNA-DNA triple helices is not well understood beyond the canonical U•A-T and C•G-C base triplets. Using native gel-shift assays, the relative stability of 16 different base triplets at a single position, Z•X-Y (where Z = C, U, A, G and X-Y = A-T, G-C, T-A, C-G), in an RNA•DNA-DNA triple helix was determined. The canonical U•A-T and C•G-C base triplets were the most stable, while three non-canonical base triplets completely disrupted triple-helix formation. We further show that our RNA•DNA-DNA triple helix can tolerate up to two consecutive non-canonical A•G-C base triplets. Additionally, the RNA third strand must be at least 19 nucleotides to form an RNA•DNA-DNA triple helix but increasing the length to 27 nucleotides does not increase stability. The relative stability of 16 different base triplets in DNA•DNA-DNA and RNA•RNA-RNA triple helices was distinctly different from those in RNA•DNA-DNA triple helices, showing that base triplet stability depends on strand composition being DNA and/or RNA. Multiple factors influence the stability of triple helices, emphasizing the importance of experimentally validating formation of computationally predicted triple helices.