Detection of Differentially Expressed Cleavage Site Intervals Within 3' Untranslated Regions Using CSI-UTR Reveals Regulated Interaction Motifs

Extensible benchmarking of methods that identify and quantify polyadenylation sites from RNA-seq data

The tremendous rate with which data is generated and analysis methods emerge makes it increasingly difficult to keep track of their domain of applicability, assumptions, limitations, and consequently, of the efficacy and precision with which they solve specific tasks. Therefore, there is an increasing need for benchmarks, and for the provision of infrastructure for continuous method evaluation. APAeval is an international community effort, organized by the RNA Society in 2021, to benchmark tools for the identification and quantification of the usage of alternative polyadenylation (APA) sites from short-read, bulk RNA-sequencing (RNA-seq) data. Here, we reviewed 17 tools and benchmarked eight on their ability to perform APA identification and quantification, using a comprehensive set of RNA-seq experiments comprising real, synthetic, and matched 3'-end sequencing data. To support continuous benchmarking, we have incorporated the results into the OpenEBench online platform, which allows for continuous extension of the set of methods, metrics, and challenges. We envisage that our analyses will assist researchers in selecting the appropriate tools for their studies, while the containers and reproducible workflows could easily be deployed and extended to evaluate new methods or data sets.

Members of the CUGBP Elav-like family of RNA-binding proteins are expressed in distinct populations of primary sensory neurons

Primary sensory dorsal root ganglia (DRG) neurons are diverse, with distinct populations that respond to specific stimuli. Previously, we observed that functionally distinct populations of DRG neurons express mRNA transcript variants with different 3' untranslated regions (3'UTRs). 3'UTRs harbor binding sites for interaction with RNA-binding proteins (RBPs) for transporting mRNAs to subcellular domains, modulating transcript stability, and regulating the rate of translation. In the current study, analysis of publicly available single-cell RNA-sequencing data generated from adult mice revealed that 17 3'UTR-binding RBPs were enriched in specific populations of DRG neurons. This included four members of the CUG triplet repeat (CUGBP) Elav-like family (CELF): CELF2 and CELF4 were enriched in peptidergic, CELF6 in both peptidergic and nonpeptidergic, and CELF3 in tyrosine hydroxylase-expressing neurons. Immunofluorescence studies confirmed that 60% of CELF4+ neurons are small-diameter C fibers and 33% medium-diameter myelinated (likely Aδ) fibers and showed that CELF4 is distributed to peripheral termini. Coexpression analyses using transcriptomic data and immunofluorescence revealed that CELF4 is enriched in nociceptive neurons that express GFRA3, CGRP, and the capsaicin receptor TRPV1. Reanalysis of published transcriptomic data from macaque DRG revealed a highly similar distribution of CELF members, and reanalysis of single-nucleus RNA-sequencing data derived from mouse and rat DRG after sciatic injury revealed differential expression of CELFs in specific populations of sensory neurons. We propose that CELF RBPs may regulate the fate of mRNAs in populations of nociceptors, and may play a role in pain and/or neuronal regeneration following nerve injury.

Extensible benchmarking of methods that identify and quantify polyadenylation sites from RNA-seq data

The tremendous rate with which data is generated and analysis methods emerge makes it increasingly difficult to keep track of their domain of applicability, assumptions, and limitations and consequently, of the efficacy and precision with which they solve specific tasks. Therefore, there is an increasing need for benchmarks, and for the provision of infrastructure for continuous method evaluation. APAeval is an international community effort, organized by the RNA Society in 2021, to benchmark tools for the identification and quantification of the usage of alternative polyadenylation (APA) sites from short-read, bulk RNA-sequencing (RNA-seq) data. Here, we reviewed 17 tools and benchmarked eight on their ability to perform APA identification and quantification, using a comprehensive set of RNA-seq experiments comprising real, synthetic, and matched 3'-end sequencing data. To support continuous benchmarking, we have incorporated the results into the OpenEBench online platform, which allows for seamless extension of the set of methods, metrics, and challenges. We envisage that our analyses will assist researchers in selecting the appropriate tools for their studies. Furthermore, the containers and reproducible workflows generated in the course of this project can be seamlessly deployed and extended in the future to evaluate new methods or datasets.

scMAPA: Identification of cell-type-specific alternative polyadenylation in complex tissues

Background

Alternative polyadenylation (APA) causes shortening or lengthening of the 3ʹ-untranslated region (3ʹ-UTR) of genes (APA genes) in diverse cellular processes such as cell proliferation and differentiation. To identify cell-type–specific APA genes in scRNA-Seq data, current bioinformatic methods have several limitations. First, they assume certain read coverage shapes in the scRNA-Seq data, which can be violated in multiple APA genes. Second, their identification is limited between 2 cell types and not directly applicable to the data of multiple cell types. Third, they do not control undesired source of variance, which potentially introduces noise to the cell-type–specific identification of APA genes.

Findings

We developed a combination of a computational change-point algorithm and a statistical model, single-cell Multi-group identification of APA (scMAPA). To avoid the assumptions on the read coverage shape, scMAPA formulates a change-point problem after transforming the 3ʹ biased scRNA-Seq data to represent the full-length 3ʹ-UTR signal. To identify cell-type–specific APA genes while adjusting for undesired source of variation, scMAPA models APA isoforms in consideration of the cell types and the undesired source. In our novel simulation data and data from human peripheral blood mononuclear cells, scMAPA outperforms existing methods in sensitivity, robustness, and stability. In mouse brain data consisting of multiple cell types sampled from multiple regions, scMAPA identifies cell-type–specific APA genes, elucidating novel roles of APA for dividing immune cells and differentiated neuron cells and in multiple brain disorders.

Conclusions

scMAPA elucidates the cell-type–specific function of APA events and sheds novel insights into the functional roles of APA events in complex tissues.

Understanding small ORF diversity through a comprehensive transcription feature classification

Small open reading frames (small ORFs/sORFs/smORFs) are potentially coding sequences smaller than 100 codons that have historically been considered junk DNA by gene prediction software and in annotation screening; however, the advent of next-generation sequencing has contributed to the deeper investigation of junk DNA regions and their transcription products, resulting in the emergence of smORFs as a new focus of interest in systems biology. Several smORF peptides were recently reported in noncanonical mRNAs as new players in numerous biological contexts; however, their relevance is still overlooked in coding potential analysis. Hence, this review proposes a smORF classification based on transcriptional features, discussing the most promising approaches to investigate smORFs based on their different characteristics. First, smORFs were divided into nonexpressed (intergenic) and expressed (genic) smORFs. Second, genic smORFs were classified as smORFs located in noncoding RNAs (ncRNAs) or canonical mRNAs. Finally, smORFs in ncRNAs were further subdivided into sequences located in small or long RNAs, whereas smORFs located in canonical mRNAs were subdivided into several specific classes depending on their localization along the gene. We hope that this review provides new insights into large-scale annotations and reinforces the role of smORFs as essential components of a hidden coding DNA world.

Streamlining differential exon and 3' UTR usage with diffUTR

Background

Despite the importance of alternative poly-adenylation and 3′ UTR length for a variety of biological phenomena, there are limited means of detecting UTR changes from standard transcriptomic data.

Results

We present the diffUTR Bioconductor package which streamlines and improves upon differential exon usage (DEU) analyses, and leverages existing DEU tools and alternative poly-adenylation site databases to enable differential 3′ UTR usage analysis. We demonstrate the diffUTR features and show that it is more flexible and more accurate than state-of-the-art alternatives, both in simulations and in real data.

Conclusions

diffUTR enables differential 3′ UTR analysis and more generally facilitates DEU and the exploration of their results.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04114-7.

Genome-to-phenome research in rats: progress and perspectives

Because of their relatively short lifespan (<4 years), rats have become the second most used model organism to study health and diseases in humans who may live for up to 120 years. First-, second- and third-generation sequencing technologies and platforms have produced increasingly greater sequencing depth and accurate reads, leading to significant advancements in the rat genome assembly during the last 20 years. In fact, whole genome sequencing (WGS) of 47 strains have been completed. This has led to the discovery of genome variants in rats, which have been widely used to detect quantitative trait loci underlying complex phenotypes based on gene, haplotype, and sweep association analyses. DNA variants can also reveal strain, chromosome and gene functional evolutions. In parallel, phenome programs have advanced significantly in rats during the last 15 years and more than 10 databases host genome and/or phenome information. In order to discover the bridges between genome and phenome, systems genetics and integrative genomics approaches have been developed. On the other hand, multiple level information transfers from genome to phenome are executed by differential usage of alternative transcriptional start (ATS) and polyadenylation (APA) sites per gene. We used our own experiments to demonstrate how alternative transcriptome analysis can lead to enrichment of phenome-related causal pathways in rats. Development of advanced genome-to-phenome assays will certainly enhance rats as models for human biomedical research.

Alternative polyadenylation produces multiple 3' untranslated regions of odorant receptor mRNAs in mouse olfactory sensory neurons

BACKGROUND

Odorant receptor genes constitute the largest gene family in mammalian genomes and this family has been extensively studied in several species, but to date far less attention has been paid to the characterization of their mRNA 3' untranslated regions (3'UTRs). Given the increasing importance of UTRs in the understanding of RNA metabolism, and the growing interest in alternative polyadenylation especially in the nervous system, we aimed at identifying the alternative isoforms of odorant receptor mRNAs generated through 3'UTR variation.

RESULTS

We implemented a dedicated pipeline using IsoSCM instead of Cufflinks to analyze RNA-Seq data from whole olfactory mucosa of adult mice and obtained an extensive description of the 3'UTR isoforms of odorant receptor mRNAs. To validate our bioinformatics approach, we exhaustively analyzed the 3'UTR isoforms produced from 2 pilot genes, using molecular approaches including northern blot and RNA ligation mediated polyadenylation test. Comparison between datasets further validated the pipeline and confirmed the alternative polyadenylation patterns of odorant receptors. Qualitative and quantitative analyses of the annotated 3' regions demonstrate that 1) Odorant receptor 3'UTRs are longer than previously described in the literature; 2) More than 77% of odorant receptor mRNAs are subject to alternative polyadenylation, hence generating at least 2 detectable 3'UTR isoforms; 3) Splicing events in 3'UTRs are restricted to a limited subset of odorant receptor genes; and 4) Comparison between male and female data shows no sex-specific differences in odorant receptor 3'UTR isoforms.

CONCLUSIONS

We demonstrated for the first time that odorant receptor genes are extensively subject to alternative polyadenylation. This ground-breaking change to the landscape of 3'UTR isoforms of Olfr mRNAs opens new avenues for investigating their respective functions, especially during the differentiation of olfactory sensory neurons.