Function and Regulation of Nucleotide Variants in RNA

RNA molecules harbor the information necessary for the synthesis of proteins and are essential to a wide variety of cellular processes. Variation of the RNA sequences results in significant phenotypic differences; however, the precise relationship between the two remains largely unknown. Thanks to the advent of high-throughput sequencing technologies, we now have the opportunity to study the transcriptome with unprecedented detail and characterize many different types of variants present in the RNA. In the present work, we developed novel computational approaches and performed in-depth analysis of RNA-sequencing (RNA-seq) data with the overarching goal of studying the function and regulations of nucleotide variants in RNA. We first aimed to understand the factors that regulate the most prevalent type of non-genetic nucleotide variant in human RNAs which is Adenosine-to-Inosine (A-to-I) editing. We analyzed bulk RNA-seq data obtained following the knockdown of over two hundred RNA Binding Proteins (RBPs) individually. This allowed us to study their role in the regulation of A-to-I editing at the transcriptome-wide scale. We identified several RBPs including DROSHA, ILF2/3, TROVE2, and TARDBP that significantly alter editing levels through various mechanisms including directly targeting the expression of ADAR1, protein-protein interaction, and direct binding to edited regions. Next, to study the effect of nucleotide variants, we made use of single-cell RNA-sequencing (scRNA-seq) data. This technology offers a unique glimpse of the transcriptome at the single cell-resolution. However, identification of nucleotide variants in scRNA-seq remains challenging and very few methods are available for this purpose. Here, we present scAllele, a novel method that detects both single nucleotide variants (SNVs) and microindels in scRNA-seq with high accuracy and sensitivity. In addition, scAllele identifies functional relationships between the identified variants and alternative RNA processing. We applied scAllele to scRNA-seq data derived from lung cancer patients (matched tumor and normal) and detected over 150 allele-specific splicing events that were unique to each condition or showed differential prevalence. Based on scAllele, we further developed a new method, namely T-Allele, to identify nucleotide variants and their linkage patterns in third-generation RNA-seq data. We demonstrated that the precision of variant calls by T-Allele is robust despite the relatively high sequencing error rate of this type of data. Using T-Allele, we identified up to 44 haplotype-specific alternative splicing events in each of the 8 cell lines included in our study. We also showed T-allele’s ability to segregate alternative splicing events regulated genetically from those whose regulation involved other factors

RNA editing in cancer impacts mRNA abundance in immune response pathways.

BackgroundRNA editing generates modifications to the RNA sequences, thereby increasing protein diversity and shaping various layers of gene regulation. Recent studies have revealed global shifts in editing levels across many cancer types, as well as a few specific mechanisms implicating individual sites in tumorigenesis or metastasis. However, most tumor-associated sites, predominantly in noncoding regions, have unknown functional relevance.ResultsHere, we carry out integrative analysis of RNA editing profiles between epithelial and mesenchymal tumors, since epithelial-mesenchymal transition is a key paradigm for metastasis. We identify distinct editing patterns between epithelial and mesenchymal tumors in seven cancer types using TCGA data, an observation further supported by single-cell RNA sequencing data and ADAR perturbation experiments in cell culture. Through computational analyses and experimental validations, we show that differential editing sites between epithelial and mesenchymal phenotypes function by regulating mRNA abundance of their respective genes. Our analysis of RNA-binding proteins reveals ILF3 as a potential regulator of this process, supported by experimental validations. Consistent with the known roles of ILF3 in immune response, epithelial-mesenchymal differential editing sites are enriched in genes involved in immune and viral processes. The strongest target of editing-dependent ILF3 regulation is the transcript encoding PKR, a crucial player in immune and viral response.ConclusionsOur study reports widespread differences in RNA editing between epithelial and mesenchymal tumors and a novel mechanism of editing-dependent regulation of mRNA abundance. It reveals the broad impact of RNA editing in cancer and its relevance to cancer-related immune pathways

RNA editing in nascent RNA affects pre-mRNA splicing.

In eukaryotes, nascent RNA transcripts undergo an intricate series of RNA processing steps to achieve mRNA maturation. RNA editing and alternative splicing are two major RNA processing steps that can introduce significant modifications to the final gene products. By tackling these processes in isolation, recent studies have enabled substantial progress in understanding their global RNA targets and regulatory pathways. However, the interplay between individual steps of RNA processing, an essential aspect of gene regulation, remains poorly understood. By sequencing the RNA of different subcellular fractions, we examined the timing of adenosine-to-inosine (A-to-I) RNA editing and its impact on alternative splicing. We observed that >95% A-to-I RNA editing events occurred in the chromatin-associated RNA prior to polyadenylation. We report about 500 editing sites in the 3' acceptor sequences that can alter splicing of the associated exons. These exons are highly conserved during evolution and reside in genes with important cellular function. Furthermore, we identified a second class of exons whose splicing is likely modulated by RNA secondary structures that are recognized by the RNA editing machinery. The genome-wide analyses, supported by experimental validations, revealed remarkable interplay between RNA editing and splicing and expanded the repertoire of functional RNA editing sites

RNA editing in cancer impacts mRNA abundance in immune response pathways.

BackgroundRNA editing generates modifications to the RNA sequences, thereby increasing protein diversity and shaping various layers of gene regulation. Recent studies have revealed global shifts in editing levels across many cancer types, as well as a few specific mechanisms implicating individual sites in tumorigenesis or metastasis. However, most tumor-associated sites, predominantly in noncoding regions, have unknown functional relevance.ResultsHere, we carry out integrative analysis of RNA editing profiles between epithelial and mesenchymal tumors, since epithelial-mesenchymal transition is a key paradigm for metastasis. We identify distinct editing patterns between epithelial and mesenchymal tumors in seven cancer types using TCGA data, an observation further supported by single-cell RNA sequencing data and ADAR perturbation experiments in cell culture. Through computational analyses and experimental validations, we show that differential editing sites between epithelial and mesenchymal phenotypes function by regulating mRNA abundance of their respective genes. Our analysis of RNA-binding proteins reveals ILF3 as a potential regulator of this process, supported by experimental validations. Consistent with the known roles of ILF3 in immune response, epithelial-mesenchymal differential editing sites are enriched in genes involved in immune and viral processes. The strongest target of editing-dependent ILF3 regulation is the transcript encoding PKR, a crucial player in immune and viral response.ConclusionsOur study reports widespread differences in RNA editing between epithelial and mesenchymal tumors and a novel mechanism of editing-dependent regulation of mRNA abundance. It reveals the broad impact of RNA editing in cancer and its relevance to cancer-related immune pathways

Additional file 1 of L-GIREMI uncovers RNA editing sites in long-read RNA-seq

Additional file 1: Fig. S1. Overview of the Alzheimer’s disease (AD) data. Fig. S2. Summary of mismatches observed in the AD dataset. Fig. S3. The data quality and RNA editing sites in the GM12878 long-read RNA-seq datasets generated by the Sequel II platform. Fig. S4. The data quality and RNA editing sites in the GM12878 long-read RNA-seq datasets generated by the Sequel platform. Fig. S5. Comparison of RNA editing sites identified in the short- and long-read data of GM12878. Fig. S6. Cumulative distribution of mutual information of pairs of REDIportal editing sites or pairs of SNPs in the same gene. Fig. S7. Histogram of the MI for the editing site. Fig. S8. Histograms of the read coverage of detected dsRNAs in two datasets. Fig. S9. Pattern of region-skipping and editing index of inverted Alu repeats

Additional file 2 of L-GIREMI uncovers RNA editing sites in long-read RNA-seq

Additional file 2: Table S1. Performance of L-GIREMI in different types of regions of the Alzheimer's Disease Brain dataset. Table S2. Performance of L-GIREMI in different types of regions of the GM12878 dataset. Table S3. Primer sequences of validated sites

Additional file 3 of L-GIREMI uncovers RNA editing sites in long-read RNA-seq

Additional file 3: Peer review history