Allele-specific SHAPE-MaP assessment of the effects of somatic variation and protein binding on mRNA structure

The plant noncoding transcriptome: a versatile environmental sensor

Plant noncoding RNA transcripts have gained increasing attention in recent years due to growing evidence that they can regulate developmental plasticity. In this review article, we comprehensively analyze the relationship between noncoding RNA transcripts in plants and their response to environmental cues. We first provide an overview of the various noncoding transcript types, including long and small RNAs, and how the environment modulates their performance. We then highlight the importance of noncoding RNA secondary structure for their molecular and biological functions. Finally, we discuss recent studies that have unveiled the functional significance of specific long noncoding transcripts and their molecular partners within ribonucleoprotein complexes during development and in response to biotic and abiotic stress. Overall, this review sheds light on the fascinating and complex relationship between dynamic noncoding transcription and plant environmental responses, and highlights the need for further research to uncover the underlying molecular mechanisms and exploit the potential of noncoding transcripts for crop resilience in the context of global warming.

Structural analysis of MALAT1 long noncoding RNA in cells and in evolution

Although not canonically polyadenylated, the long noncoding RNA MALAT1 (metastasis-associated lung adenocarcinoma transcript 1) is stabilized by a highly conserved 76-nt triple helix structure on its 3' end. The entire MALAT1 transcript is over 8000 nt long in humans. The strongest structural conservation signal in MALAT1 (as measured by covariation of base pairs) is in the triple helix structure. Primary sequence analysis of covariation alone does not reveal the degree of structural conservation of the entire full-length transcript, however. Furthermore, RNA structure is often context dependent; RNA binding proteins that are differentially expressed in different cell types may alter structure. We investigate here the in-cell and cell-free structures of the full-length human and green monkey (Chlorocebus sabaeus) MALAT1 transcripts in multiple tissue-derived cell lines using SHAPE chemical probing. Our data reveal levels of uniform structural conservation in different cell lines, in cells and cell-free, and even between species, despite significant differences in primary sequence. The uniformity of the structural conservation across the entire transcript suggests that, despite seeing covariation signals only in the triple helix junction of the lncRNA, the rest of the transcript's structure is remarkably conserved, at least in primates and across multiple cell types and conditions.

How does precursor RNA structure influence RNA processing and gene expression?

RNA is a fundamental biomolecule that has many purposes within cells. Due to its single-stranded and flexible nature, RNA naturally folds into complex and dynamic structures. Recent technological and computational advances have produced an explosion of RNA structural data. Many RNA structures have regulatory and functional properties. Studying the structure of nascent RNAs is particularly challenging due to their low abundance and long length, but their structures are important because they can influence RNA processing. Precursor RNA processing is a nexus of pathways that determines mature isoform composition and that controls gene expression. In this review, we examine what is known about human nascent RNA structure and the influence of RNA structure on processing of precursor RNAs. These known structures provide examples of how other nascent RNAs may be structured and show how novel RNA structures may influence RNA processing including splicing and polyadenylation. RNA structures can be targeted therapeutically to treat disease.

Selective Chemical Modification to the Higher-Order Structures of Nucleic Acids

DNA and RNA can adopt a variety of stable higher-order structural motifs, including G-quadruplex (G4 s), mismatches, and bulges. Many of these secondary structures are closely related to the regulation of gene expression. Therefore, the higher-order structure of nucleic acids is one of the candidate therapeutic targets, and the development of binding molecules targeting the higher-order structure of nucleic acids has been pursued vigorously. Furthermore, as one of the methodologies for detecting the higher-order structures of these nucleic acids, developing techniques for the selective chemical modification of the higher-order structures of nucleic acids is also underway. In this personal account, we focus on the following higher-order structures of nucleic acids, double-stranded DNA containing the abasic site, T-T/U-U mismatch structure, and G-quadruplex structure, and describe the development of molecules that bind to and chemically modify these structures.

RNAsmc: A integrated tool for comparing RNA secondary structure and evaluating allosteric effects

RNA structure plays a crucial role in gene regulation, in RNA stability and the essential biological processes. RNA secondary structure (RSS) motifs are the basic building blocks for investigating the biological mechanisms of structure. Here, we present a strategy for structural motif-based dynamic alignment, namely, RNA secondary-structural motif-comparing (RNAsmc), to identify structural motifs and quantitatively evaluate their underlying molecular functions. RNAsmc also has strong robustness to sequence length, folding protocol and RNA structural profile by chemical probing. Notably, it is also applicable to quantify structural variation in special RNA editing events (SNVs or SNPs, fragment insertion or deletion, etc.). The findings indicate that RNAsmc can uncover the heterogeneity of RNA secondary structure and score for similarities among components, which provides an impetus to cluster RNA families and evaluate allosteric effects. We find that RNAsmc exhibits remarkable detection efficiency for experimentally-derived RiboSNitches. Finally, the pipeline was assembled into an R software package to serve as an automated toolkit to explore, align, and cluster RSS. It is freely available for download at https://CRAN.R-project.org/package=RNAsmc.

Polymorphism, Expression, and Structure Analysis of a Key Gene ARNT in Sheep (Ovis aries)

Growth traits are influential factors that significantly affects the development of the sheep industry. A previous TMT proteomic analysis found that a key protein in the HIF signaling pathway, ARNT, may influence embryonic skeletal muscle growth and development in sheep. The purpose of this study was to better understand the association between the polymorphisms of ARNT and growth traits of sheep, and the potential function of ARNT. Real-time qPCR (qRT-PCR) of ARNT was carried out to compare its expression in different developmental stages of the muscle tissues and primary myoblasts in the Hu, Chinese merino, and Gangba sheep. The genetic variance of ARNT was detected using the Illumina Ovine SNP 50 K and 600 K BeadChip in the Hu and Ujimqin sheep populations, respectively. The CDS sequence of the ARNT gene was cloned in the Hu sheep using PCR technology. Finally, bioinformatic analytical methods were applied to characterize the genes and their hypothetical protein products. The qRT-PCR results showed that the ARNT gene was expressed significantly in the Chinese merino embryo after 85 gestation days (D85) (p < 0.05). Additionally, after the sheep were born, the expression of ARNT was significant at the weaning stage of the Hu sheep (p < 0.01). However, there was no difference in the Gangba sheep.In addition, six SNP loci were screened using 50 K and 600 K BeadChip. We found a significant association between rs413597480 A > G and the Hu sheep weight at weaning and backfat thickness in the 5-month-old sheep (p < 0.05), and four SNP loci (rs162298018 G > C, rs159644025 G > A, rs421351865 G > A, and rs401758103 A > G) were also associated with growth traits in the Ujimqin sheep (p < 0.05). Interestingly, we found that a G > C mutation at 1948 bp in the cloned ARNT CDS sequence of the Hu sheep was the same locus mutation as rs162298018 G > C identified using the 600 K BeadChip, which resulted in a nonconservative missense point mutation, leading to a change from proline to alanine and altering the number of DNA, protein-binding sites, and the α-helix of the ARNT protein. There was a strong linkage disequilibrium between rs162298018 G > C and rs159644025 G > A, and the ARNT protein was conserved among the goat, Hu sheep, and Texel sheep. And, we propose that a putative molecular marker for growth and development in sheep may be the G > C mutation at 1948 bp in the CDS region of the ARNT gene. Our study systematically analyzed the expression, structure, and function of the ARNT gene and its encoded proteins in sheep. This provides a basis for future studies of the regulatory mechanisms of the ARNT gene.

Rotavirus RNA chaperone mediates global transcriptome-wide increase in RNA backbone flexibility

Due to genome segmentation, rotaviruses must co-package eleven distinct genomic RNAs. The packaging is mediated by virus-encoded RNA chaperones, such as the rotavirus NSP2 protein. While the activities of distinct RNA chaperones are well studied on smaller RNAs, little is known about their global effect on the entire viral transcriptome. Here, we used Selective 2'-hydroxyl Acylation Analyzed by Primer Extension and Mutational Profiling (SHAPE-MaP) to examine the secondary structure of the rotavirus transcriptome in the presence of increasing amounts of NSP2. SHAPE-MaP data reveals that despite the well-documented helix-unwinding activity of NSP2 in vitro, its incubation with cognate rotavirus transcripts does not induce a significant change in the SHAPE reactivities. However, a quantitative analysis of mutation rates measured by mutational profiling reveals a global 5-fold rate increase in the presence of NSP2. We demonstrate that the normalization procedure used in deriving SHAPE reactivities from mutation rates can mask an important global effect of an RNA chaperone. Analysis of the mutation rates reveals a larger effect on stems rather than loops. Together, these data provide the first experimentally derived secondary structure model of the rotavirus transcriptome and reveal that NSP2 acts by globally increasing RNA backbone flexibility in a concentration-dependent manner.

Predicting functional riboSNitches in the context of alternative splicing

RNAs are the major regulators of gene expression, and their secondary structures play crucial roles at different levels. RiboSNitches are disease-associated SNPs that cause changes in the pre-mRNA secondary structural ensemble. Several riboSNitches have been detected in the 5' and 3' untranslated regions and lncRNA. Although cases of secondary structural elements playing a regulatory role in alternative splicing are known, regions specific to splicing events, such as splice junctions have not received much attention. We tested splice-site mutations for their efficiency in disrupting the secondary structure and hypothesized that these could play a crucial role in alternative splicing. Multiple riboSNitch prediction methods were applied to obtain overlapping results that are potentially more reliable. Putative riboSNitches were identified from aberrant 5' and 3' splice site mutations, cancer-causing somatic mutations, and genes that harbor the regulatory RNA secondary structural elements. Our workflow for predicting riboSNitches associated with alternative splicing is novel and paves the way for subsequent experimental validation.

Quantitative prediction of variant effects on alternative splicing in MAPT using endogenous pre-messenger RNA structure probing

Splicing is highly regulated and is modulated by numerous factors. Quantitative predictions for how a mutation will affect precursor mRNA (pre-mRNA) structure and downstream function are particularly challenging. Here, we use a novel chemical probing strategy to visualize endogenous precursor and mature MAPT mRNA structures in cells. We used these data to estimate Boltzmann suboptimal structural ensembles, which were then analyzed to predict consequences of mutations on pre-mRNA structure. Further analysis of recent cryo-EM structures of the spliceosome at different stages of the splicing cycle revealed that the footprint of the B^act complex with pre-mRNA best predicted alternative splicing outcomes for exon 10 inclusion of the alternatively spliced MAPT gene, achieving 74% accuracy. We further developed a β-regression weighting framework that incorporates splice site strength, RNA structure, and exonic/intronic splicing regulatory elements capable of predicting, with 90% accuracy, the effects of 47 known and 6 newly discovered mutations on inclusion of exon 10 of MAPT. This combined experimental and computational framework represents a path forward for accurate prediction of splicing-related disease-causing variants.

Experimental demonstration and pan-structurome prediction of climate-associated riboSNitches in Arabidopsis

Background

Genome-wide association studies (GWAS) aim to correlate phenotypic changes with genotypic variation. Upon transcription, single nucleotide variants (SNVs) may alter mRNA structure, with potential impacts on transcript stability, macromolecular interactions, and translation. However, plant genomes have not been assessed for the presence of these structure-altering polymorphisms or “riboSNitches.”

Results

We experimentally demonstrate the presence of riboSNitches in transcripts of two Arabidopsis genes, ZINC RIBBON 3 (ZR3) and COTTON GOLGI-RELATED 3 (CGR3), which are associated with continentality and temperature variation in the natural environment. These riboSNitches are also associated with differences in the abundance of their respective transcripts, implying a role in regulating the gene's expression in adaptation to local climate conditions. We then computationally predict riboSNitches transcriptome-wide in mRNAs of 879 naturally inbred Arabidopsis accessions. We characterize correlations between SNPs/riboSNitches in these accessions and 434 climate descriptors of their local environments, suggesting a role of these variants in local adaptation. We integrate this information in CLIMtools V2.0 and provide a new web resource, T-CLIM, that reveals associations between transcript abundance variation and local environmental variation.

Conclusion

We functionally validate two plant riboSNitches and, for the first time, demonstrate riboSNitch conditionality dependent on temperature, coining the term “conditional riboSNitch.” We provide the first pan-genome-wide prediction of riboSNitches in plants. We expand our previous CLIMtools web resource with riboSNitch information and with 1868 additional Arabidopsis genomes and 269 additional climate conditions, which will greatly facilitate in silico studies of natural genetic variation, its phenotypic consequences, and its role in local adaptation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13059-022-02656-4.

Footprinting SHAPE-eCLIP Reveals Transcriptome-wide Hydrogen Bonds at RNA-Protein Interfaces

Discovering the interaction mechanism and location of RNA-binding proteins (RBPs) on RNA is critical for understanding gene expression regulation. Here, we apply selective 2'-hydroxyl acylation analyzed by primer extension (SHAPE) on in vivo transcripts compared to protein-absent transcripts in four human cell lines to identify transcriptome-wide footprints (fSHAPE) on RNA. Structural analyses indicate that fSHAPE precisely detects nucleobases that hydrogen bond with protein. We demonstrate that fSHAPE patterns predict binding sites of known RBPs, such as iron response elements in both known loci and previously unknown loci in CDC34, SLC2A4RG, COASY, and H19. Furthermore, by integrating SHAPE and fSHAPE with crosslinking and immunoprecipitation (eCLIP) of desired RBPs, we interrogate specific RNA-protein complexes, such as histone stem-loop elements and their nucleotides that hydrogen bond with stem-loop-binding proteins. Together, these technologies greatly expand our ability to study and understand specific cellular RNA interactions in RNA-protein complexes.

Pan-cancer analysis of somatic mutations in miRNA genes

Background

miRNAs are considered important players in oncogenesis, serving either as oncomiRs or suppressormiRs. Although the accumulation of somatic alterations is an intrinsic aspect of cancer development and many important cancer-driving mutations have been identified in protein-coding genes, the area of functional somatic mutations in miRNA genes is heavily understudied.

Methods

Here, based on the analysis of large genomic datasets, mostly the whole-exome sequencing of over 10,000 cancer/normal sample pairs deposited within the TCGA repository, we undertook an analysis of somatic mutations in miRNA genes.

Findings

We identified and characterized over 10,000 somatic mutations and showed that some of the miRNA genes are overmutated in Pan-Cancer and/or specific cancers. Nonrandom occurrence of the identified mutations was confirmed by a strong association of overmutated miRNA genes with KEGG pathways, most of which were related to specific cancer types or cancer-related processes. Additionally, we showed that mutations in some of the overmutated genes correlate with miRNA expression, cancer staging, and patient survival.

Interpretation

Our study is the first comprehensive Pan-Cancer study of cancer somatic mutations in miRNA genes. It may help to understand the consequences of mutations in miRNA genes and the identification of miRNA functional mutations. The results may also be the first step (form the basis and provide the resources) in the development of computational and/or statistical approaches/tools dedicated to the identification of cancer-driver miRNA genes.

Funding

This work was supported by research grants from the Polish National Science Centre 2016/22/A/NZ2/00184 and 2015/17/N/NZ3/03629.

Dysregulation of TCTP in Biological Processes and Diseases

Translationally controlled tumor protein (TCTP), also called histamine releasing factor (HRF) or fortilin, is a multifunctional protein present in almost all eukaryotic organisms. TCTP is involved in a range of basic cell biological processes, such as promotion of growth and development, or cellular defense in response to biological stresses. Cellular TCTP levels are highly regulated in response to a variety of physiological signals, and regulatory mechanism at various levels have been elucidated. Given the importance of TCTP in maintaining cellular homeostasis, it is not surprising that dysregulation of this protein is associated with a range of disease processes. Here, we review recent progress that has been made in the characterisation of the basic biological functions of TCTP, in the description of mechanisms involved in regulating its cellular levels and in the understanding of dysregulation of TCTP, as it occurs in disease processes such as cancer.

HiPR: High-throughput probabilistic RNA structure inference

Recent high-throughput structure-sensitive genome-wide sequencing-based assays have enabled large-scale studies of RNA structure, and robust transcriptome-wide computational prediction of individual RNA structures across RNA classes from these assays has potential to further improve the prediction accuracy. Here, we describe HiPR, a novel method for RNA structure prediction at single-nucleotide resolution that combines high-throughput structure probing data (DMS-seq, DMS-MaPseq) with a novel probabilistic folding algorithm. On validation data spanning a variety of RNA classes, HiPR often increases accuracy for predicting RNA structures, giving researchers new tools to study RNA structure.

High-throughput determination of RNA structures

RNA performs and regulates a diverse range of cellular processes, with new functional roles being uncovered at a rapid pace. Interest is growing in how these functions are linked to RNA structures that form in the complex cellular environment. A growing suite of technologies that use advances in RNA structural probes, high-throughput sequencing and new computational approaches to interrogate RNA structure at unprecedented throughput are beginning to provide insights into RNA structures at new spatial, temporal and cellular scales.

dStruct: identifying differentially reactive regions from RNA structurome profiling data

RNA biology is revolutionized by recent developments of diverse high-throughput technologies for transcriptome-wide profiling of molecular RNA structures. RNA structurome profiling data can be used to identify differentially structured regions between groups of samples. Existing methods are limited in scope to specific technologies and/or do not account for biological variation. Here, we present dStruct which is the first broadly applicable method for differential analysis accounting for biological variation in structurome profiling data. dStruct is compatible with diverse profiling technologies, is validated with experimental data and simulations, and outperforms existing methods.

Revealing lncRNA Structures and Interactions by Sequencing-Based Approaches

Long noncoding RNAs (lncRNAs) have emerged as significant players in almost every level of gene function and regulation. Thus, characterizing the structures and interactions of lncRNAs is essential for understanding their mechanistic roles in cells. Through a combination of (bio)chemical approaches and automated capillary and high-throughput sequencing (HTS), the complexity and diversity of RNA structures and interactions has been revealed in the transcriptomes of multiple species. These methods have uncovered important biological insights into the mechanistic and functional roles of lncRNA in gene expression and RNA metabolism, as well as in development and disease. In this review, we summarize the latest sequencing strategies to reveal RNA structure, RNA-RNA, RNA-DNA, and RNA-protein interactions, and highlight the recent applications of these approaches to map functional lncRNAs. We discuss the advantages and limitations of these strategies, and provide recommendations to further advance methodologies capable of mapping RNA structure and interactions in order to discover new biology of lncRNAs and decipher their molecular mechanisms and implication in diseases.