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1. Structured 3′ UTRs destabilize mRNAs in plants

   https://doi.org/10.1186/s13059-024-03186-x  

   Zhang, Tianru ; Li, Changhao ; Zhu, Jiaying ; Li, Yanjun ; Wang, Zhiye ; Tong, Chun-Yip ; Xi, Yu ; Han, Yi ; Koiwa, Hisashi ; Peng, Xu ; et al ( February 2024 , Genome Biology)

   RNA secondary structure (RSS) can influence the regulation of transcription, RNA processing, and protein synthesis, among other processes. 3′ untranslated regions (3′ UTRs) of mRNA also hold the key for many aspects of gene regulation. However, there are often contradictory results regarding the roles of RSS in 3′ UTRs in gene expression in different organisms and/or contexts.

   Here, we incidentally observe that the primary substrate of miR159a (pri-miR159a), when embedded in a 3′ UTR, could promote mRNA accumulation. The enhanced expression is attributed to the earlier polyadenylation of the transcript within the hybrid pri-miR159a-3′ UTR and, resultantly, a poorly structured 3′ UTR. RNA decay assays indicate that poorly structured 3′ UTRs could promote mRNA stability, whereas highly structured 3′ UTRs destabilize mRNA in vivo. Genome-wide DMS-MaPseq also reveals the prevailing inverse relationship between 3′ UTRs’ RSS and transcript accumulation in the transcriptomes ofArabidopsis, rice, and even human. Mechanistically, transcripts with highly structured 3′ UTRs are preferentially degraded by 3′–5′ exoribonuclease SOV and 5′–3′ exoribonuclease XRN4, leading to decreased expression inArabidopsis. Finally, we engineer different structured 3′ UTRs to an endogenousFTgene and alter theFT-regulated flowering time inArabidopsis.

   We conclude that highly structured 3′ UTRs typically cause reduced accumulation of the harbored transcripts inArabidopsis. This pattern extends to rice and even mammals. Furthermore, our study provides a new strategy of engineering the 3′ UTRs’ RSS to modify plant traits in agricultural production and mRNA stability in biotechnology.

    

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2. Predicting gene structure changes resulting from genetic variants via exon definition features

   https://doi.org/10.1093/bioinformatics/bty324  

   Majoros, William H. ; Holt, Carson ; Campbell, Michael S. ; Ware, Doreen ; Yandell, Mark ; Reddy, Timothy E. ; Birol, ed., Inanc ( April 2018 , Bioinformatics)

   Genetic variation that disrupts gene function by altering gene splicing between individuals can substantially influence traits and disease. In those cases, accurately predicting the effects of genetic variation on splicing can be highly valuable for investigating the mechanisms underlying those traits and diseases. While methods have been developed to generate high quality computational predictions of gene structures in reference genomes, the same methods perform poorly when used to predict the potentially deleterious effects of genetic changes that alter gene splicing between individuals. Underlying that discrepancy in predictive ability are the common assumptions by reference gene finding algorithms that genes are conserved, well-formed and produce functional proteins.

   We describe a probabilistic approach for predicting recent changes to gene structure that may or may not conserve function. The model is applicable to both coding and non-coding genes, and can be trained on existing gene annotations without requiring curated examples of aberrant splicing. We apply this model to the problem of predicting altered splicing patterns in the genomes of individual humans, and we demonstrate that performing gene-structure prediction without relying on conserved coding features is feasible. The model predicts an unexpected abundance of variants that create de novo splice sites, an observation supported by both simulations and empirical data from RNA-seq experiments. While these de novo splice variants are commonly misinterpreted by other tools as coding or non-coding variants of little or no effect, we find that in some cases they can have large effects on splicing activity and protein products and we propose that they may commonly act as cryptic factors in disease.

   The software is available from geneprediction.org/SGRF.

   Supplementary information is available at Bioinformatics online.

    

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3. Emerging Roles for 3′ UTRs in Neurons

   https://doi.org/10.3390/ijms21103413  

   Bae, Bongmin ; Miura, Pedro ( May 2020 , International Journal of Molecular Sciences)

   The 3′ untranslated regions (3′ UTRs) of mRNAs serve as hubs for post-transcriptional control as the targets of microRNAs (miRNAs) and RNA-binding proteins (RBPs). Sequences in 3′ UTRs confer alterations in mRNA stability, direct mRNA localization to subcellular regions, and impart translational control. Thousands of mRNAs are localized to subcellular compartments in neurons—including axons, dendrites, and synapses—where they are thought to undergo local translation. Despite an established role for 3′ UTR sequences in imparting mRNA localization in neurons, the specific RNA sequences and structural features at play remain poorly understood. The nervous system selectively expresses longer 3′ UTR isoforms via alternative polyadenylation (APA). The regulation of APA in neurons and the neuronal functions of longer 3′ UTR mRNA isoforms are starting to be uncovered. Surprising roles for 3′ UTRs are emerging beyond the regulation of protein synthesis and include roles as RBP delivery scaffolds and regulators of alternative splicing. Evidence is also emerging that 3′ UTRs can be cleaved, leading to stable, isolated 3′ UTR fragments which are of unknown function. Mutations in 3′ UTRs are implicated in several neurological disorders—more studies are needed to uncover how these mutations impact gene regulation and what is their relationship to disease severity. 

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4. The choice of sequence homologs included in multiple sequence alignments has a dramatic impact on evolutionary conservation analysis

   https://doi.org/10.1093/bioinformatics/bty523  

   Gil, Nelson ; Fiser, Andras ; Hancock, ed., John ( June 2018 , Bioinformatics)

   The analysis of sequence conservation patterns has been widely utilized to identify functionally important (catalytic and ligand-binding) protein residues for over a half-century. Despite decades of development, on average state-of-the-art non-template-based functional residue prediction methods must predict ∼25% of a protein’s total residues to correctly identify half of the protein’s functional site residues. The overwhelming proportion of false positives results in reported ‘F-Scores’ of ∼0.3. We investigated the limits of current approaches, focusing on the so-far neglected impact of the specific choice of homologs included in multiple sequence alignments (MSAs).

   The limits of conservation-based functional residue prediction were explored by surveying the binding sites of 1023 proteins. A straightforward conservation analysis of MSAs composed of randomly selected homologs sampled from a PSI-BLAST search achieves average F-Scores of ∼0.3, a performance matching that reported by state-of-the-art methods, which often consider additional features for the prediction in a machine learning setting. Interestingly, we found that a simple combinatorial MSA sampling algorithm will in almost every case produce an MSA with an optimal set of homologs whose conservation analysis reaches average F-Scores of ∼0.6, doubling state-of-the-art performance. We also show that this is nearly at the theoretical limit of possible performance given the agreement between different binding site definitions. Additionally, we showcase the progress in this direction made by Selection of Alignment by Maximal Mutual Information (SAMMI), an information-theory-based approach to identifying biologically informative MSAs. This work highlights the importance and the unused potential of optimally composed MSAs for conservation analysis.

   Supplementary data are available at Bioinformatics online.

    

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5. APA-Scan: detection and visualization of 3′-UTR alternative polyadenylation with RNA-seq and 3′-end-seq data

   https://doi.org/10.1186/s12859-022-04939-w  

   Fahmi, Naima Ahmed ; Ahmed, Khandakar Tanvir ; Chang, Jae-Woong ; Nassereddeen, Heba ; Fan, Deliang ; Yong, Jeongsik ; Zhang, Wei ( September 2022 , BMC Bioinformatics)

   The eukaryotic genome is capable of producing multiple isoforms from a gene by alternative polyadenylation (APA) during pre-mRNA processing. APA in the 3′-untranslated region (3′-UTR) of mRNA produces transcripts with shorter or longer 3′-UTR. Often, 3′-UTR serves as a binding platform for microRNAs and RNA-binding proteins, which affect the fate of the mRNA transcript. Thus, 3′-UTR APA is known to modulate translation and provides a mean to regulate gene expression at the post-transcriptional level. Current bioinformatics pipelines have limited capability in profiling 3′-UTR APA events due to incomplete annotations and a low-resolution analyzing power: widely available bioinformatics pipelines do not reference actionable polyadenylation (cleavage) sites but simulate 3′-UTR APA only using RNA-seq read coverage, causing false positive identifications. To overcome these limitations, we developed APA-Scan, a robust program that identifies 3′-UTR APA events and visualizes the RNA-seq short-read coverage with gene annotations.

   APA-Scan utilizes either predicted or experimentally validated actionable polyadenylation signals as a reference for polyadenylation sites and calculates the quantity of long and short 3′-UTR transcripts in the RNA-seq data. APA-Scan works in three major steps: (i) calculate the read coverage of the 3′-UTR regions of genes; (ii) identify the potential APA sites and evaluate the significance of the events among two biological conditions; (iii) graphical representation of user specific event with 3′-UTR annotation and read coverage on the 3′-UTR regions. APA-Scan is implemented in Python3. Source code and a comprehensive user’s manual are freely available athttps://github.com/compbiolabucf/APA-Scan.

   APA-Scan was applied to both simulated and real RNA-seq datasets and compared with two widely used baselines DaPars and APAtrap. In simulation APA-Scan significantly improved the accuracy of 3′-UTR APA identification compared to the other baselines. The performance of APA-Scan was also validated by 3′-end-seq data and qPCR on mouse embryonic fibroblast cells. The experiments confirm that APA-Scan can detect unannotated 3′-UTR APA events and improve genome annotation.

   APA-Scan is a comprehensive computational pipeline to detect transcriptome-wide 3′-UTR APA events. The pipeline integrates both RNA-seq and 3′-end-seq data information and can efficiently identify the significant events with a high-resolution short reads coverage plots.

    

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