IsoSCM: improved and alternative 3' UTR annotation using multiple change-point inference

Identification and Characterization of the miRNA Transcriptome Controlling Green Pigmentation of Chicken Eggshells

Green eggs are mainly caused by inserting an avian endogenous retrovirus (EVA-HP) fragment into the SLCO1B3 gene. Although the genotypes for this insertion allele are consistent, eggshell color (ESC) may vary after a peak laying period; light-colored eggs are undesired by consumers and farmers and result in financial loss, so it is necessary to resolve this problem. miRNAs are small non-coding RNAs that exert essential functions in animal development and diseases. However, the regulatory miRNAs and detailed molecular mechanisms regulating eggshell greenness remain unclear. In the present study, we determined the genotype of green-eggshell hens through the detection of a homozygous allele insertion in the SLCO1B3 gene. The shell gland epithelium was obtained from green-eggshell hens that produced white and green shell eggs to perform transcriptome sequencing and investigate the important regulatory mechanisms that influence the ESC. Approximately 921 miRNAs were expressed in these two groups, which included 587 known miRNAs and 334 novel miRNAs, among which 44 were differentially expressed. There were 22 miRNAs that were significantly upregulated in the green and white groups, respectively, which targeted hundreds of genes, including KIT, HMOX2, and several solute carrier family genes. A Gene Ontology enrichment analysis of the target genes showed that the differentially expressed miRNA-targeted genes mainly belonged to the functional categories of homophilic cell adhesion, gland development, the Wnt signaling pathway, and epithelial tube morphogenesis. A KEGG enrichment analysis showed that the Hedgehog signaling pathway was significantly transformed in this study. The current study provides an overview of the miRNA expression profiles and the interaction between the miRNAs and their target genes. It provides valuable insights into the molecular mechanisms underlying green eggshell pigmentation, screening more effective hens to produce stable green eggs and obtaining higher economic benefits.

Efficient estimation of Cox model with random change point

In clinical studies, the risk of a disease may dramatically change when some biological indexes of the human body exceed some thresholds. Furthermore, the differences in individual characteristics of patients such as physical and psychological experience may lead to subject-specific thresholds or change points. Although a large literature has been established for regression analysis of failure time data with change points, most of the existing methods assume the same, fixed change point for all study subjects. In this paper, we consider the situation where there exists a subject-specific change point and two Cox type models are presented. The proposed models also offer a framework for subgroup analysis. For inference, a sieve maximum likelihood estimation procedure is proposed and the asymptotic properties of the resulting estimators are established. An extensive simulation study is conducted to assess the empirical performance of the proposed method and indicates that it works well in practical situations. Finally the proposed approach is applied to a set of breast cancer data.

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.

Full-length transcript alterations in human bronchial epithelial cells with U2AF1 S34F mutations

U2AF1 is one of the most recurrently mutated splicing factors in lung adenocarcinoma and has been shown to cause transcriptome-wide pre-mRNA splicing alterations; however, the full-length altered mRNA isoforms associated with the mutation are largely unknown. To better understand the impact U2AF1 has on full-length isoform fate and function, we conducted high-throughput long-read cDNA sequencing from isogenic human bronchial epithelial cells with and without a U2AF1 S34F mutation. We identified 49,366 multi-exon transcript isoforms, more than half of which did not match GENCODE or short-read-assembled isoforms. We found 198 transcript isoforms with significant expression and usage changes relative to WT, only 68% of which were assembled by short reads. Expression of isoforms from immune-related genes is largely down-regulated in mutant cells and without observed splicing changes. Finally, we reveal that isoforms likely targeted by nonsense-mediated decay are down-regulated in U2AF1 S34F cells, suggesting that isoform changes may alter the translational output of those affected genes. Altogether, our work provides a resource of full-length isoforms associated with U2AF1 S34F in lung cells.

Hormonal gatekeeping via the blood-brain barrier governs caste-specific behavior in ants

Here, we reveal an unanticipated role of the blood-brain barrier (BBB) in regulating complex social behavior in ants. Using scRNA-seq, we find localization in the BBB of a key hormone-degrading enzyme called juvenile hormone esterase (Jhe), and we show that this localization governs the level of juvenile hormone (JH3) entering the brain. Manipulation of the Jhe level reprograms the brain transcriptome between ant castes. Although ant Jhe is retained and functions intracellularly within the BBB, we show that Drosophila Jhe is naturally extracellular. Heterologous expression of ant Jhe into the Drosophila BBB alters behavior in fly to mimic what is seen in ants. Most strikingly, manipulation of Jhe levels in ants reprograms complex behavior between worker castes. Our study thus uncovers a remarkable, potentially conserved role of the BBB serving as a molecular gatekeeper for a neurohormonal pathway that regulates social behavior.

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.

Regulatory logic of endogenous RNAi in silencing de novo genomic conflicts

Although the biological utilities of endogenous RNAi (endo-RNAi) have been largely elusive, recent studies reveal its critical role in the non-model fruitfly Drosophila simulans to suppress selfish genes, whose unchecked activities can severely impair spermatogenesis. In particular, hairpin RNA (hpRNA) loci generate endo-siRNAs that suppress evolutionary novel, X-linked, meiotic drive loci. The consequences of deleting even a single hpRNA (Nmy) in males are profound, as such individuals are nearly incapable of siring male progeny. Here, comparative genomic analyses of D. simulans and D. melanogaster mutants of the core RNAi factor dcr-2 reveal a substantially expanded network of recently-emerged hpRNA-target interactions in the former species. The de novo hpRNA regulatory network in D. simulans provides insight into molecular strategies that underlie hpRNA emergence and their potential roles in sex chromosome conflict. In particular, our data support the existence of ongoing rapid evolution of Nmy/Dox-related networks, and recurrent targeting of testis HMG Box loci by hpRNAs. Importantly, the impact of the endo-RNAi network on gene expression flips the convention for regulatory networks, since we observe strong derepression of targets of the youngest hpRNAs, but only mild effects on the targets of the oldest hpRNAs. These data suggest that endo-RNAi are especially critical during incipient stages of intrinsic sex chromosome conflicts, and that continual cycles of distortion and resolution may contribute to speciation.

Transcriptome analysis provides critical answers to the "variants of uncertain significance" conundrum

While whole-genome and exome sequencing have transformed our collective understanding of genetics' role in disease pathogenesis, there are certain conditions and populations for whom DNA-level data fails to identify the underlying genetic etiology. Specifically, patients of non-White race and non-European ancestry are disproportionately affected by "variants of unknown/uncertain significance" (VUS), limiting the scope of precision medicine for minority patients and perpetuating health disparities. VUS often include deep intronic and splicing variants which are difficult to interpret from DNA data alone. RNA analysis can illuminate the consequences of VUS, thereby allowing for their reclassification as pathogenic versus benign. Here we review the critical role transcriptome analysis plays in clarifying VUS in both neoplastic and non-neoplastic diseases.

ReadZS detects cell type-specific and developmentally regulated RNA processing programs in single-cell RNA-seq

RNA processing, including splicing and alternative polyadenylation, is crucial to gene function and regulation, but methods to detect RNA processing from single-cell RNA sequencing data are limited by reliance on pre-existing annotations, peak calling heuristics, and collapsing measurements by cell type. We introduce ReadZS, an annotation-free statistical approach to identify regulated RNA processing in single cells. ReadZS discovers cell type-specific RNA processing in human lung and conserved, developmentally regulated RNA processing in mammalian spermatogenesis-including global 3' UTR shortening in human spermatogenesis. ReadZS also discovers global 3' UTR lengthening in Arabidopsis development, highlighting the usefulness of this method in under-annotated transcriptomes.

A Survey on Methods for Predicting Polyadenylation Sites from DNA Sequences, Bulk RNA-seq, and Single-cell RNA-seq

Alternative polyadenylation (APA) plays important roles in modulating mRNA stability, translation, and subcellular localization, and contributes extensively to shaping eukaryotic transcriptome complexity and proteome diversity. Identification of poly(A) sites (pAs) on a genome-wide scale is a critical step toward understanding the underlying mechanism of APA-mediated gene regulation. A number of established computational tools have been proposed to predict pAs from diverse genomic data. Here we provided an exhaustive overview of computational approaches for predicting pAs from DNA sequences, bulk RNA sequencing (RNA-seq) data, and single-cell RNA sequencing (scRNA-seq) data. Particularly, we examined several representative tools using bulk RNA-seq and scRNA-seq data from peripheral blood mononuclear cells and put forward operable suggestions on how to assess the reliability of pAs predicted by different tools. We also proposed practical guidelines on choosing appropriate methods applicable to diverse scenarios. Moreover, we discussed in depth the challenges in improving the performance of pA prediction and benchmarking different methods. Additionally, we highlighted outstanding challenges and opportunities using new machine learning and integrative multi-omics techniques, and provided our perspective on how computational methodologies might evolve in the future for non-3' untranslated region, tissue-specific, cross-species, and single-cell pA prediction.

Diverse cell-specific patterns of alternative polyadenylation in Drosophila

Most genes in higher eukaryotes express isoforms with distinct 3' untranslated regions (3' UTRs), generated by alternative polyadenylation (APA). Since 3' UTRs are predominant locations of post-transcriptional regulation, APA can render such programs conditional, and can also alter protein sequences via alternative last exon (ALE) isoforms. We previously used 3'-sequencing from diverse Drosophila samples to define multiple tissue-specific APA landscapes. Here, we exploit comprehensive single nucleus RNA-sequencing data (Fly Cell Atlas) to elucidate cell-type expression of 3' UTRs across >250 adult Drosophila cell types. We reveal the cellular bases of multiple tissue-specific APA/ALE programs, such as 3' UTR lengthening in differentiated neurons and 3' UTR shortening in spermatocytes and spermatids. We trace dynamic 3' UTR patterns across cell lineages, including in the male germline, and discover new APA patterns in the intestinal stem cell lineage. Finally, we correlate expression of RNA binding proteins (RBPs), miRNAs and global levels of cleavage and polyadenylation (CPA) factors in several cell types that exhibit characteristic APA landscapes, yielding candidate regulators of transcriptome complexity. These analyses provide a comprehensive foundation for future investigations of mechanisms and biological impacts of alternative 3' isoforms across the major cell types of this widely-studied model organism.

Regulation of the Alternative Neural Transcriptome by ELAV/Hu RNA Binding Proteins

The process of alternative polyadenylation (APA) generates multiple 3' UTR isoforms for a given locus, which can alter regulatory capacity and on occasion change coding potential. APA was initially characterized for a few genes, but in the past decade, has been found to be the rule for metazoan genes. While numerous differences in APA profiles have been catalogued across genetic conditions, perturbations, and diseases, our knowledge of APA mechanisms and biology is far from complete. In this review, we highlight recent findings regarding the role of the conserved ELAV/Hu family of RNA binding proteins (RBPs) in generating the broad landscape of lengthened 3' UTRs that is characteristic of neurons. We relate this to their established roles in alternative splicing, and summarize ongoing directions that will further elucidate the molecular strategies for neural APA, the in vivo functions of ELAV/Hu RBPs, and the phenotypic consequences of these regulatory paradigms in neurons.

Genome annotation with long RNA reads reveals new patterns of gene expression and improves single-cell analyses in an ant brain

BACKGROUND

Functional genomic analyses rely on high-quality genome assemblies and annotations. Highly contiguous genome assemblies have become available for a variety of species, but accurate and complete annotation of gene models, inclusive of alternative splice isoforms and transcription start and termination sites, remains difficult with traditional approaches.

RESULTS

Here, we utilized full-length isoform sequencing (Iso-Seq), a long-read RNA sequencing technology, to obtain a comprehensive annotation of the transcriptome of the ant Harpegnathos saltator. The improved genome annotations include additional splice isoforms and extended 3' untranslated regions for more than 4000 genes. Reanalysis of RNA-seq experiments using these annotations revealed several genes with caste-specific differential expression and tissue- or caste-specific splicing patterns that were missed in previous analyses. The extended 3' untranslated regions afforded great improvements in the analysis of existing single-cell RNA-seq data, resulting in the recovery of the transcriptomes of 18% more cells. The deeper single-cell transcriptomes obtained with these new annotations allowed us to identify additional markers for several cell types in the ant brain, as well as genes differentially expressed across castes in specific cell types.

CONCLUSIONS

Our results demonstrate that Iso-Seq is an efficient and effective approach to improve genome annotations and maximize the amount of information that can be obtained from existing and future genomic datasets in Harpegnathos and other organisms.

Kr-h1 maintains distinct caste-specific neurotranscriptomes in response to socially regulated hormones

Behavioral plasticity is key to animal survival. Harpegnathos saltator ants can switch between worker and queen-like status (gamergate) depending on the outcome of social conflicts, providing an opportunity to study how distinct behavioral states are achieved in adult brains. Using social and molecular manipulations in live ants and ant neuronal cultures, we show that ecdysone and juvenile hormone drive molecular and functional differences in the brains of workers and gamergates and direct the transcriptional repressor Kr-h1 to different target genes. Depletion of Kr-h1 in the brain caused de-repression of "socially inappropriate" genes: gamergate genes were upregulated in workers, whereas worker genes were upregulated in gamergates. At the phenotypic level, loss of Kr-h1 resulted in the emergence of worker-specific behaviors in gamergates and gamergate-specific traits in workers. We conclude that Kr-h1 is a transcription factor that maintains distinct brain states established in response to socially regulated hormones.

The microRNA target site landscape is a novel molecular feature associating alternative polyadenylation with immune evasion activity in breast cancer

Alternative polyadenylation (APA) in breast tumor samples results in the removal/addition of cis-regulatory elements such as microRNA (miRNA) target sites in the 3'-untranslated region (3'-UTRs) of genes. Although previous computational APA studies focused on a subset of genes strongly affected by APA (APA genes), we identify miRNAs of which widespread APA events collectively increase or decrease the number of target sites [probabilistic inference of microRNA target site modification through APA (PRIMATA-APA)]. Using PRIMATA-APA on the cancer genome atlas (TCGA) breast cancer data, we found that the global APA events change the number of the target sites of particular microRNAs [target sites modified miRNA (tamoMiRNA)] enriched for cancer development and treatments. We also found that when knockdown (KD) of NUDT21 in HeLa cells induces a different set of widespread 3'-UTR shortening than TCGA breast cancer data, it changes the target sites of the common tamoMiRNAs. Since the NUDT21 KD experiment previously demonstrated the tumorigenic role of APA events in a miRNA dependent fashion, this result suggests that the APA-initiated tumorigenesis is attributable to the miRNA target site changes, not the APA events themselves. Further, we found that the miRNA target site changes identify tumor cell proliferation and immune cell infiltration to the tumor microenvironment better than the miRNA expression levels or the APA events themselves. Altogether, our computational analyses provide a proof-of-concept demonstration that the miRNA target site information indicates the effect of global APA events with a potential as predictive biomarker.

The Detection and Bioinformatic Analysis of Alternative 3' UTR Isoforms as Potential Cancer Biomarkers

Alternative transcript cleavage and polyadenylation is linked to cancer cell transformation, proliferation and outcome. This has led researchers to develop methods to detect and bioinformatically analyse alternative polyadenylation as potential cancer biomarkers. If incorporated into standard prognostic measures such as gene expression and clinical parameters, these could advance cancer prognostic testing and possibly guide therapy. In this review, we focus on the existing methodologies, both experimental and computational, that have been applied to support the use of alternative polyadenylation as cancer biomarkers.

Aptardi predicts polyadenylation sites in sample-specific transcriptomes using high-throughput RNA sequencing and DNA sequence

Annotation of polyadenylation sites from short-read RNA sequencing alone is a challenging computational task. Other algorithms rooted in DNA sequence predict potential polyadenylation sites; however, in vivo expression of a particular site varies based on a myriad of conditions. Here, we introduce aptardi (alternative polyadenylation transcriptome analysis from RNA-Seq data and DNA sequence information), which leverages both DNA sequence and RNA sequencing in a machine learning paradigm to predict expressed polyadenylation sites. Specifically, as input aptardi takes DNA nucleotide sequence, genome-aligned RNA-Seq data, and an initial transcriptome. The program evaluates these initial transcripts to identify expressed polyadenylation sites in the biological sample and refines transcript 3'-ends accordingly. The average precision of the aptardi model is twice that of a standard transcriptome assembler. In particular, the recall of the aptardi model (the proportion of true polyadenylation sites detected by the algorithm) is improved by over three-fold. Also, the model-trained using the Human Brain Reference RNA commercial standard-performs well when applied to RNA-sequencing samples from different tissues and different mammalian species. Finally, aptardi's input is simple to compile and its output is easily amenable to downstream analyses such as quantitation and differential expression.

Animal-APAdb: a comprehensive animal alternative polyadenylation database

Alternative polyadenylation (APA) is an important post-transcriptional regulatory mechanism that recognizes different polyadenylation signals on transcripts, resulting in transcripts with different lengths of 3′ untranslated regions and thereby influencing a series of biological processes. Recent studies have highlighted the important roles of APA in human. However, APA profiles in other animals have not been fully recognized, and there is no database that provides comprehensive APA information for other animals except human. Here, by using the RNA sequencing data collected from public databases, we systematically characterized the APA profiles in 9244 samples of 18 species. In total, we identified 342 952 APA events with a median of 17 020 per species using the DaPars2 algorithm, and 315 691 APA events with a median of 17 953 per species using the QAPA algorithm in these 18 species, respectively. In addition, we predicted the polyadenylation sites (PAS) and motifs near PAS of these species. We further developed Animal-APAdb, a user-friendly database (http://gong_lab.hzau.edu.cn/Animal-APAdb/) for data searching, browsing and downloading. With comprehensive information of APA events in different tissues of different species, Animal-APAdb may greatly facilitate the exploration of animal APA patterns and novel mechanisms, gene expression regulation and APA evolution across tissues and species.

Profiling Alternative 3' Untranslated Regions in Sorghum using RNA-seq Data

Sorghum is an important crop widely used for food, feed, and fuel. Transcriptome-wide studies of 3′ untranslated regions (3′UTR) using regular RNA-seq remain scarce in sorghum, while transcriptomes have been characterized extensively using Illumina short-read sequencing platforms for many sorghum varieties under various conditions or developmental contexts. 3′UTR is a critical regulatory component of genes, controlling the translation, transport, and stability of messenger RNAs. In the present study, we profiled the alternative 3′UTRs at the transcriptome level in three genetically related but phenotypically contrasting lines of sorghum: Rio, BTx406, and R9188. A total of 1,197 transcripts with alternative 3′UTRs were detected using RNA-seq data. Their categorization identified 612 high-confidence alternative 3′UTRs. Importantly, the high-confidence alternative 3′UTR genes significantly overlapped with the genesets that are associated with RNA N⁶-methyladenosine (m⁶A) modification, suggesting a clear indication between alternative 3′UTR and m⁶A methylation in sorghum. Moreover, taking advantage of sorghum genetics, we provided evidence of genotype specificity of alternative 3′UTR usage. In summary, our work exemplifies a transcriptome-wide profiling of alternative 3′UTRs using regular RNA-seq data in non-model crops and gains insights into alternative 3′UTRs and their genotype specificity.

ELAV and FNE Determine Neuronal Transcript Signatures through EXon-Activated Rescue

The production of alternative RNA variants contributes to the tissue-specific regulation of gene expression. In the animal nervous system, a systematic shift toward distal sites of transcription termination produces transcript signatures that are crucial for neuron development and function. Here, we report that, in Drosophila, the highly conserved protein ELAV globally regulates all sites of neuronal 3' end processing and directly binds to proximal polyadenylation sites of target mRNAs in vivo. We uncover an endogenous strategy of functional gene rescue that safeguards neuronal RNA signatures in an ELAV loss-of-function context. When not directly repressed by ELAV, the transcript encoding the ELAV paralog FNE acquires a mini-exon, generating a new protein able to translocate to the nucleus and rescue ELAV-mediated alternative polyadenylation and alternative splicing. We propose that exon-activated functional rescue is a more widespread mechanism that ensures robustness of processes regulated by a hierarchy, rather than redundancy, of effectors.

APAatlas: decoding alternative polyadenylation across human tissues

Alternative polyadenylation (APA) is an RNA-processing mechanism on the 3' terminus that generates distinct isoforms of mRNAs and/or other RNA polymerase II transcripts with different 3'UTR lengths. Widespread APA affects post-transcriptional gene regulation in mRNA translation, stability, and localization, and exhibits strong tissue specificity. However, no existing database provides comprehensive information about APA events in a large number of human normal tissues. Using the RNA-seq data from the Genotype-Tissue Expression project, we systematically identified APA events from 9475 samples across 53 human tissues and examined their associations with multiple traits and gene expression across tissues. We further developed APAatlas, a user-friendly database (https://hanlab.uth.edu/apa/) for searching, browsing and downloading related information. APAatlas will help the biomedical research community elucidate the functions and mechanisms of APA events in human tissues.

Long noncoding RNAs in lipid metabolism: literature review and conservation analysis across species

BACKGROUND

Lipids are important for the cell and organism life since they are major components of membranes, energy reserves and are also signal molecules. The main organs for the energy synthesis and storage are the liver and adipose tissue, both in humans and in more distant species such as chicken. Long noncoding RNAs (lncRNAs) are known to be involved in many biological processes including lipid metabolism.

RESULTS

In this context, this paper provides the most exhaustive list of lncRNAs involved in lipid metabolism with 60 genes identified after an in-depth analysis of the bibliography, while all "review" type articles list a total of 27 genes. These 60 lncRNAs are mainly described in human or mice and only a few of them have a precise described mode-of-action. Because these genes are still named in a non-standard way making such a study tedious, we propose a standard name for this list according to the rules dictated by the HUGO consortium. Moreover, we identified about 10% of lncRNAs which are conserved between mammals and chicken and 2% between mammals and fishes. Finally, we demonstrated that two lncRNA were wrongly considered as lncRNAs in the literature since they are 3' extensions of the closest coding gene.

CONCLUSIONS

Such a lncRNAs catalogue can participate to the understanding of the lipid metabolism regulators; it can be useful to better understand the genetic regulation of some human diseases (obesity, hepatic steatosis) or traits of economic interest in livestock species (meat quality, carcass composition). We have no doubt that this first set will be rapidly enriched in coming years.

What Are 3' UTRs Doing?

3' untranslated regions (3' UTRs) of messenger RNAs (mRNAs) are best known to regulate mRNA-based processes, such as mRNA localization, mRNA stability, and translation. In addition, 3' UTRs can establish 3' UTR-mediated protein-protein interactions (PPIs), and thus can transmit genetic information encoded in 3' UTRs to proteins. This function has been shown to regulate diverse protein features, including protein complex formation or posttranslational modifications, but is also expected to alter protein conformations. Therefore, 3' UTR-mediated information transfer can regulate protein features that are not encoded in the amino acid sequence. This review summarizes both 3' UTR functions-the regulation of mRNA and protein-based processes-and highlights how each 3' UTR function was discovered with a focus on experimental approaches used and the concepts that were learned. This review also discusses novel approaches to study 3' UTR functions in the future by taking advantage of recent advances in technology.

mountainClimber Identifies Alternative Transcription Start and Polyadenylation Sites in RNA-Seq

Alternative transcription start (ATS) and alternative polyadenylation (APA) create alternative RNA isoforms and modulate many aspects of RNA expression and protein production. However, ATS and APA remain difficult to detect in RNA sequencing (RNA-seq). Here, we developed mountainClimber, a de novo cumulative-sum-based approach to identify ATS and APA as change points. Unlike many existing methods, mountainClimber runs on a single sample and identifies multiple ATS or APA sites anywhere in the transcript. We analyzed 2,342 GTEx samples (36 tissues, 215 individuals) and found that tissue type is the predominant driver of transcript end variations. 75% and 65% of genes exhibited differential APA and ATS across tissues, respectively. In particular, testis displayed longer 5' untranslated regions (UTRs) and shorter 3' UTRs, often in genes related to testis-specific biology. Overall, we report the largest study of transcript ends across human tissues to our knowledge. mountainClimber is available at github.com/gxiaolab/mountainClimber.

TAPAS: tool for alternative polyadenylation site analysis

Motivation

The length of the 3' untranslated region (3' UTR) of an mRNA is essential for many biological activities such as mRNA stability, sub-cellular localization, protein translation, protein binding and translation efficiency. Moreover, correlation between diseases and the shortening (or lengthening) of 3' UTRs has been reported in the literature. This length is largely determined by the polyadenylation cleavage site in the mRNA. As alternative polyadenylation (APA) sites are common in mammalian genes, several tools have been published recently for detecting APA sites from RNA-Seq data or performing shortening/lengthening analysis. These tools consider either up to only two APA sites in a gene or only APA sites that occur in the last exon of a gene, although a gene may generally have more than two APA sites and an APA site may sometimes occur before the last exon. Furthermore, the tools are unable to integrate the analysis of shortening/lengthening events with APA site detection.

Results

We propose a new tool, called TAPAS, for detecting novel APA sites from RNA-Seq data. It can deal with more than two APA sites in a gene as well as APA sites that occur before the last exon. The tool is based on an existing method for finding change points in time series data, but some filtration techniques are also adopted to remove change points that are likely false APA sites. It is then extended to identify APA sites that are expressed differently between two biological samples and genes that contain 3' UTRs with shortening/lengthening events. Our extensive experiments on simulated and real RNA-Seq data demonstrate that TAPAS outperforms the existing tools for APA site detection or shortening/lengthening analysis significantly.

Availability and implementation

https://github.com/arefeen/TAPAS.

Supplementary information

Supplementary data are available at Bioinformatics online.

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.

A survey on identification and quantification of alternative polyadenylation sites from RNA-seq data

Alternative polyadenylation (APA) has been implicated to play an important role in post-transcriptional regulation by regulating mRNA abundance, stability, localization and translation, which contributes considerably to transcriptome diversity and gene expression regulation. RNA-seq has become a routine approach for transcriptome profiling, generating unprecedented data that could be used to identify and quantify APA site usage. A number of computational approaches for identifying APA sites and/or dynamic APA events from RNA-seq data have emerged in the literature, which provide valuable yet preliminary results that should be refined to yield credible guidelines for the scientific community. In this review, we provided a comprehensive overview of the status of currently available computational approaches. We also conducted objective benchmarking analysis using RNA-seq data sets from different species (human, mouse and Arabidopsis) and simulated data sets to present a systematic evaluation of 11 representative methods. Our benchmarking study showed that the overall performance of all tools investigated is moderate, reflecting that there is still lot of scope to improve the prediction of APA site or dynamic APA events from RNA-seq data. Particularly, prediction results from individual tools differ considerably, and only a limited number of predicted APA sites or genes are common among different tools. Accordingly, we attempted to give some advice on how to assess the reliability of the obtained results. We also proposed practical recommendations on the appropriate method applicable to diverse scenarios and discussed implications and future directions relevant to profiling APA from RNA-seq data.

APAtrap: identification and quantification of alternative polyadenylation sites from RNA-seq data

Motivation

Alternative polyadenylation (APA) has been increasingly recognized as a crucial mechanism that contributes to transcriptome diversity and gene expression regulation. As RNA-seq has become a routine protocol for transcriptome analysis, it is of great interest to leverage such unprecedented collection of RNA-seq data by new computational methods to extract and quantify APA dynamics in these transcriptomes. However, research progress in this area has been relatively limited. Conventional methods rely on either transcript assembly to determine transcript 3' ends or annotated poly(A) sites. Moreover, they can neither identify more than two poly(A) sites in a gene nor detect dynamic APA site usage considering more than two poly(A) sites.

Results

We developed an approach called APAtrap based on the mean squared error model to identify and quantify APA sites from RNA-seq data. APAtrap is capable of identifying novel 3' UTRs and 3' UTR extensions, which contributes to locating potential poly(A) sites in previously overlooked regions and improving genome annotations. APAtrap also aims to tally all potential poly(A) sites and detect genes with differential APA site usages between conditions. Extensive comparisons of APAtrap with two other latest methods, ChangePoint and DaPars, using various RNA-seq datasets from simulation studies, human and Arabidopsis demonstrate the efficacy and flexibility of APAtrap for any organisms with an annotated genome.

Availability and implementation

Freely available for download at https://apatrap.sourceforge.io.

Contact

liqq@xmu.edu.cn or xhuister@xmu.edu.cn.

Supplementary information

Supplementary data are available at Bioinformatics online.

Computational Methods for Mapping, Assembly and Quantification for Coding and Non-coding Transcripts

The measurement of gene expression has long provided significant insight into biological functions. The development of high-throughput short-read sequencing technology has revealed transcriptional complexity at an unprecedented scale, and informed almost all areas of biology. However, as researchers have sought to gather more insights from the data, these new technologies have also increased the computational analysis burden. In this review, we describe typical computational pipelines for RNA-Seq analysis and discuss their strengths and weaknesses for the assembly, quantification and analysis of coding and non-coding RNAs. We also discuss the assembly of transposable elements into transcripts, and the difficulty these repetitive elements pose. In summary, RNA-Seq is a powerful technology that is likely to remain a key asset in the biologist's toolkit.

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

The length of untranslated regions at the 3' end of transcripts (3'UTRs) is regulated by alternate polyadenylation (APA). 3'UTRs contain regions that harbor binding motifs for regulatory molecules. However, the mechanisms that coordinate the 3'UTR length of specific groups of transcripts are not well-understood. We therefore developed a method, CSI-UTR, that models 3'UTR structure as tandem segments between functional alternative-polyadenylation sites (termed cleavage site intervals-CSIs). This approach facilitated (1) profiling of 3'UTR isoform expression changes and (2) statistical enrichment of putative regulatory motifs. CSI-UTR analysis is UTR-annotation independent and can interrogate legacy data generated from standard RNA-Seq libraries. CSI-UTR identified a set of CSIs in human and rodent transcriptomes. Analysis of RNA-Seq datasets from neural tissue identified differential expression events within 3'UTRs not detected by standard gene-based differential expression analyses. Further, in many instances 3'UTR and CDS from the same gene were regulated differently. This modulation of motifs for RNA-interacting molecules with potential condition-dependent and tissue-specific RNA binding partners near the polyA signal and CSI junction may play a mechanistic role in the specificity of alternative polyadenylation. Source code, CSI BED files and example datasets are available at: https://github.com/UofLBioinformatics/CSI-UTR.

Bioinformatic analysis of Chinese hamster ovary host cell protein lipases

Complete, accurate genome assemblies are necessary to design targets for genetic engineering strategies. Successful gene knockdowns and knockouts in Chinese hamster ovary (CHO) cells may prevent the expression of difficult-to-remove host cell proteins (HCPs). HCPs, if not removed, can cause problems in stability, safety, and efficacy of the biotherapeutic. A significantly improved Chinese hamster (CH) reference genome was used to identify new knockout targets with similar predicted functions and characteristics as the difficult-to-remove host cell lipases, LPL, PLBL2, and LPLA2. The CHO-K1 gene and protein sequences of several of these lipases were corrected using the updated CH genome. Sequence alignments were then used to identify conserved regions that may serve as possible targets for multiple simultaneous gene knockouts. Finally, comparison of the CHO-K1 lipase protein sequences to their human orthologs provided insight into which lipases, if persistent in the drug product, could possibly cause immunogenic responses in patients.

An integrative model for alternative polyadenylation, IntMAP, delineates mTOR-modulated endoplasmic reticulum stress response

3'-untranslated regions (UTRs) can vary through the use of alternative polyadenylation sites during pre-mRNA processing. Multiple publically available pipelines combining high profiling technologies and bioinformatics tools have been developed to catalog changes in 3'-UTR lengths. In our recent RNA-seq experiments using cells with hyper-activated mammalian target of rapamycin (mTOR), we found that cellular mTOR activation leads to transcriptome-wide alternative polyadenylation (APA), resulting in the activation of multiple cellular pathways. Here, we developed a novel bioinformatics algorithm, IntMAP, which integrates RNA-Seq and PolyA Site (PAS)-Seq data for a comprehensive characterization of APA events. By applying IntMAP to the datasets from cells with hyper-activated mTOR, we identified novel APA events that could otherwise not be identified by either profiling method alone. Several transcription factors including Cebpg (CCAAT/enhancer binding protein gamma) were among the newly discovered APA transcripts, indicating that diverse transcriptional networks may be regulated by mTOR-coordinated APA. The prevention of APA in Cebpg using the CRISPR/cas9-mediated genome editing tool showed that mTOR-driven 3'-UTR shortening in Cebpg is critical in protecting cells from endoplasmic reticulum (ER) stress. Taken together, we present IntMAP as a new bioinformatics algorithm for APA analysis by which we expand our understanding of the physiological role of mTOR-coordinated APA events to ER stress response. IntMAP toolbox is available at http://compbio.cs.umn.edu/IntMAP/.

Genic C-Methylation in Soybean Is Associated with Gene Paralogs Relocated to Transposable Element-Rich Pericentromeres

Most plants are polyploid due to whole-genome duplications (WGD) and can thus have duplicated genes. Following a WGD, paralogs are often fractionated (lost) and few duplicate pairs remain. Little attention has been paid to the role of DNA methylation in the functional divergence of paralogous genes. Using high-resolution methylation maps of accessions of domesticated and wild soybean, we show that in soybean, a recent paleopolyploid with many paralogs, DNA methylation likely contributed to the elimination of genetic redundancy of polyploidy-derived gene paralogs. Transcriptionally silenced paralogs exhibit particular genomic features as they are often associated with proximal transposable elements (TEs) and are preferentially located in pericentromeres, likely due to gene movement during evolution. Additionally, we provide evidence that gene methylation associated with proximal TEs is implicated in the divergence of expression profiles between orthologous genes of wild and domesticated soybean, and within populations.

Differential expression of mRNA isoforms in the skeletal muscle of pigs with distinct growth and fatness profiles

Background

The identification of genes differentially expressed in the skeletal muscle of pigs displaying distinct growth and fatness profiles might contribute to identify the genetic factors that influence the phenotypic variation of such traits. So far, the majority of porcine transcriptomic studies have investigated differences in gene expression at a global scale rather than at the mRNA isoform level. In the current work, we have investigated the differential expression of mRNA isoforms in the gluteus medius (GM) muscle of 52 Duroc HIGH (increased backfat thickness, intramuscular fat and saturated and monounsaturated fatty acids contents) and LOW pigs (opposite phenotype, with an increased polyunsaturated fatty acids content).

Results

Our analysis revealed that 10.9% of genes expressed in the GM muscle generate alternative mRNA isoforms, with an average of 2.9 transcripts per gene. By using two different pipelines, one based on the CLC Genomics Workbench and another one on the STAR, RSEM and DESeq2 softwares, we have identified 10 mRNA isoforms that both pipelines categorize as differentially expressed in HIGH vs LOW pigs (P-value < 0.01 and ±0.6 log₂fold-change). Only five mRNA isoforms, produced by the ITGA5, SEMA4D, LITAF, TIMP1 and ANXA2 genes, remain significant after correction for multiple testing (q-value < 0.05 and ±0.6 log₂fold-change), being upregulated in HIGH pigs.

Conclusions

The increased levels of specific ITGA5, LITAF, TIMP1 and ANXA2 mRNA isoforms in HIGH pigs is consistent with reports indicating that the overexpression of these four genes is associated with obesity and metabolic disorders in humans. A broader knowledge about the functional attributes of these mRNA variants would be fundamental to elucidate the consequences of transcript diversity on the determinism of porcine phenotypes of economic interest.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-4515-2) contains supplementary material, which is available to authorized users.

Analyses of alternative polyadenylation: from old school biochemistry to high-throughput technologies

Alternations in usage of polyadenylation sites during transcription termination yield transcript isoforms from a gene. Recent findings of transcriptome-wide alternative polyadenylation (APA) as a molecular response to changes in biology position APA not only as a molecular event of early transcriptional termination but also as a cellular regulatory step affecting various biological pathways. With the development of high-throughput profiling technologies at a single nucleotide level and their applications targeted to the 3'-end of mRNAs, dynamics in the landscape of mRNA 3'-end is measureable at a global scale. In this review, methods and technologies that have been adopted to study APA events are discussed. In addition, various bioinformatics algorithms for APA isoform analysis using publicly available RNA-seq datasets are introduced. [BMB Reports 2017; 50(4): 201-207].

Landscape and evolution of tissue-specific alternative polyadenylation across Drosophila species

BACKGROUND

Drosophila melanogaster has one of best-described transcriptomes of any multicellular organism. Nevertheless, the paucity of 3'-sequencing data in this species precludes comprehensive assessment of alternative polyadenylation (APA), which is subject to broad tissue-specific control.

RESULTS

Here, we generate deep 3'-sequencing data from 23 developmental stages, tissues, and cell lines of D. melanogaster, yielding a comprehensive atlas of ~ 62,000 polyadenylated ends. These data broadly extend the annotated transcriptome, identify ~ 40,000 novel 3' termini, and reveal that two-thirds of Drosophila genes are subject to APA. Furthermore, we dramatically expand the numbers of genes known to be subject to tissue-specific APA, such as 3' untranslated region (UTR) lengthening in head and 3' UTR shortening in testis, and characterize new tissue and developmental 3' UTR patterns. Our thorough 3' UTR annotations permit reassessment of post-transcriptional regulatory networks, via conserved miRNA and RNA binding protein sites. To evaluate the evolutionary conservation and divergence of APA patterns, we generate developmental and tissue-specific 3'-seq libraries from Drosophila yakuba and Drosophila virilis. We document broadly analogous tissue-specific APA trends in these species, but also observe significant alterations in 3' end usage across orthologs. We exploit the population of functionally evolving poly(A) sites to gain clear evidence that evolutionary divergence in core polyadenylation signal (PAS) and downstream sequence element (DSE) motifs drive broad alterations in 3' UTR isoform expression across the Drosophila phylogeny.

CONCLUSIONS

These data provide a critical resource for the Drosophila community and offer many insights into the complex control of alternative tissue-specific 3' UTR formation and its consequences for post-transcriptional regulatory networks.

Untranslated Parts of Genes Interpreted: Making Heads or Tails of High-Throughput Transcriptomic Data via Computational Methods: Computational methods to discover and quantify isoforms with alternative untranslated regions

In this review we highlight the importance of defining the untranslated parts of transcripts, and present a number of computational approaches for the discovery and quantification of alternative transcription start and poly-adenylation events in high-throughput transcriptomic data. The fate of eukaryotic transcripts is closely linked to their untranslated regions, which are determined by the position at which transcription starts and ends at a genomic locus. Although the extent of alternative transcription starts and alternative poly-adenylation sites has been revealed by sequencing methods focused on the ends of transcripts, the application of these methods is not yet widely adopted by the community. We suggest that computational methods applied to standard high-throughput technologies are a useful, albeit less accurate, alternative to the expertise-demanding 5' and 3' sequencing and they are the only option for analysing legacy transcriptomic data. We review these methods here, focusing on technical challenges and arguing for the need to include better normalization of the data and more appropriate statistical models of the expected variation in the signal.

Genome-wide profiling of the 3' ends of polyadenylated RNAs

Alternative polyadenylation (APA) diversifies the 3' termini of a majority of mRNAs in most eukaryotes, and is consequently inferred to have substantial consequences for the utilization of post-transcriptional regulatory mechanisms. Since conventional RNA-sequencing methods do not accurately define mRNA termini, a number of protocols have been developed that permit sequencing of the 3' ends of polyadenylated transcripts (3'-seq). We present here our experimental protocol to generate 3'-seq libraries using a dT-priming approach, including extensive details on considerations that will enable successful library cloning. We pair this with a set of computational tools that allow the user to process the raw sequence data into a filtered set of clusters that represent high-confidence functional polyadenylation sites. The data are single-nucleotide resolution and quantitative, and can be used for downstream analyses of APA.

Genome-wide identification of microRNA targets in the neglected disease pathogens of the genus Echinococcus

MicroRNAs (miRNAs), a class of small non-coding RNAs, are key regulators of gene expression at post-transcriptional level and play essential roles in biological processes such as development. MiRNAs silence target mRNAs by binding to complementary sequences in the 3'untranslated regions (3'UTRs). The parasitic helminths of the genus Echinococcus are the causative agents of echinococcosis, a zoonotic neglected disease. In previous work, we performed a comprehensive identification and characterization of Echinococcus miRNAs. However, current knowledge about their targets is limited. Since target prediction algorithms rely on complementarity between 3'UTRs and miRNA sequences, a major limitation is the lack of accurate sequence information of 3'UTR for most species including parasitic helminths. We performed RNA-seq and developed a pipeline that integrates the transcriptomic data with available genomic data of this parasite in order to identify 3'UTRs of Echinococcus canadensis. The high confidence set of 3'UTRs obtained allowed the prediction of miRNA targets in Echinococcus through a bioinformatic approach. We performed for the first time a comparative analysis of miRNA targets in Echinococcus and Taenia. We found that many evolutionarily conserved target sites in Echinococcus and Taenia may be functional and under selective pressure. Signaling pathways such as MAPK and Wnt were among the most represented pathways indicating miRNA roles in parasite growth and development. Genome-wide identification and characterization of miRNA target genes in Echinococcus provide valuable information to guide experimental studies in order to understand miRNA functions in the parasites biology. miRNAs involved in essential functions, especially those being absent in the host or showing sequence divergence with respect to host orthologs, might be considered as novel therapeutic targets for echinococcosis control.

RNA surveillance via nonsense-mediated mRNA decay is crucial for longevity in daf-2/insulin/IGF-1 mutant C. elegans

Long-lived organisms often feature more stringent protein and DNA quality control. However, whether RNA quality control mechanisms, such as nonsense-mediated mRNA decay (NMD), which degrades both abnormal as well as some normal transcripts, have a role in organismal aging remains unexplored. Here we show that NMD mediates longevity in C. elegans strains with mutations in daf-2/insulin/insulin-like growth factor 1 receptor. We find that daf-2 mutants display enhanced NMD activity and reduced levels of potentially aberrant transcripts. NMD components, including smg-2/UPF1, are required to achieve the longevity of several long-lived mutants, including daf-2 mutant worms. NMD in the nervous system of the animals is particularly important for RNA quality control to promote longevity. Furthermore, we find that downregulation of yars-2/tyrosyl-tRNA synthetase, an NMD target transcript, by daf-2 mutations contributes to longevity. We propose that NMD-mediated RNA surveillance is a crucial quality control process that contributes to longevity conferred by daf-2 mutations.

Characterization of genetic loss-of-function of Fus in zebrafish

The RNA-binding protein FUS is implicated in transcription, alternative splicing of neuronal genes and DNA repair. Mutations in FUS have been linked to human neurodegenerative diseases such as ALS (amyotrophic lateral sclerosis). We genetically disrupted fus in zebrafish (Danio rerio) using the CRISPR-Cas9 system. The fus knockout animals are fertile and did not show any distinctive phenotype. Mutation of fus induces mild changes in gene expression on the transcriptome and proteome level in the adult brain. We observed a significant influence of genetic background on gene expression and 3'UTR usage, which could mask the effects of loss of Fus. Unlike published fus morphants, maternal zygotic fus mutants do not show motoneuronal degeneration and exhibit normal locomotor activity.

Roar: detecting alternative polyadenylation with standard mRNA sequencing libraries

BACKGROUND

Post-transcriptional regulation is a complex mechanism that plays a central role in defining multiple cellular identities starting from a common genome. Modifications in the length of 3'UTRs have been found to play an important role in this context, since alternative 3' UTRs could lead to differences for example in regulation by microRNAs and cellular localization of the transcripts thus altering their fate.

RESULTS

We propose a strategy to identify the genes undergoing regulation of 3' UTR length using RNA sequencing data obtained from standard libraries, thus widely applicable to data originally obtained to perform classical differential expression analyses. We decided to exploit previously annotated APA sites from public databases, in contrast with other approaches recently proposed in which the location of the APA site is inferred from the data together with the relative abundance of the isoforms. We demonstrate the reliability of our method by comparing it to the results of other microarray based or specific RNA-seq libraries methods and show that using APA sites databases results in higher sensitivity compared to de novo site prediction approach.

CONCLUSIONS

We implemented the algorithm in a Bioconductor package to facilitate its broad usage in the scientific community. The ability of this approach to detect shortening from libraries with a number of reads comparable to that needed for differential expression analyses makes it useful for investigating if alternative polyadenylation is relevant in a certain biological process without requiring specific experimental assays.