ABSTRACT
BACKGROUND: The significance of A-to-I RNA editing in nervous system development is widely recognized; however, its influence on retina development remains to be thoroughly understood. RESULTS: In this study, we performed RNA sequencing and ribosome profiling experiments on developing mouse retinas to characterize the temporal landscape of A-to-I editing. Our findings revealed temporal changes in A-to-I editing, with distinct editing patterns observed across different developmental stages. Further analysis showed the interplay between A-to-I editing and alternative splicing, with A-to-I editing influencing splicing efficiency and the quantity of splicing events. A-to-I editing held the potential to enhance translation diversity, but this came at the expense of reduced translational efficiency. When coupled with splicing, it could produce a coordinated effect on gene translation. CONCLUSIONS: Overall, this study presents a temporally resolved atlas of A-to-I editing, connecting its changes with the impact on alternative splicing and gene translation in retina development.
Subject(s)
Protein Biosynthesis , RNA Editing , Retina , Animals , Mice , Retina/metabolism , Retina/embryology , Alternative Splicing , Inosine/metabolism , Inosine/genetics , Adenosine/metabolismABSTRACT
The increasing volume of ribosome profiling (Ribo-seq) data, computational complexity of its data processing and operational handicap of related analytical procedures present a daunting set of informatics challenges. These impose a substantial barrier to researchers particularly with no or limited bioinformatics expertise in analyzing and decoding translation information from Ribo-seq data, thus driving the need for a new research paradigm for data computation and information extraction. In this knowledge base, we herein present a novel interactive web platform, RiboChat (https://db.cngb.org/ribobench/chat.html), for direct analyzing and annotating Ribo-seq data in the form of a chat conversation. It consists of a user-friendly web interface and a backend cloud-computing service. When typing a data analysis question into the chat window, the object-text detection module will be run to recognize relevant keywords from the input text. Based on the features identified in the input, individual analytics modules are then scored to find the perfect-matching candidate. The corresponding analytics module will be further executed after checking the completion status of the uploading of datasets and configured parameters. Overall, RiboChat represents an important step forward in the emerging direction of next-generation data analytics and will enable the broad research community to conveniently decipher translation information embedded within Ribo-seq data.
Subject(s)
Protein Biosynthesis , Ribosomes , Computational Biology/methods , RNA, Messenger/metabolism , Ribosomes/genetics , Ribosomes/metabolism , SoftwareABSTRACT
RPFdb (http://www.rpfdb.org or http://sysbio.sysu.edu.cn/rpfdb) is a public database for hosting, analyzing and visualizing ribosome profiling (ribo-seq) data. Since its initial release in 2015, the amount of new ribo-seq data has been considerably enlarged with the increasing popularity of ribo-seq technique. Here, we describe an updated version, RPFdb v2.0, which brings significant data expansion, feature improvements, and functionality optimization: (i) RPFdb v2.0 currently hosts 2884 ribo-seq datasets from 293 studies, covering 29 different species, in comparison with 777 datasets from 82 studies and 8 species in the previous version; (ii) A refined analysis pipeline with multi-step quality controls has been applied to improve the pre-processing and alignment of ribo-seq data; (iii) New functional modules have been added to provide actively translated open reading frames (ORFs) information for each ribo-seq data; (iv) More features have been made available to increase database usability. With these additions and enhancements, RPFdb v2.0 will represent a more valuable and comprehensive database for the gene regulation community.
Subject(s)
Computational Biology/methods , Databases, Genetic , Genome-Wide Association Study , Protein Biosynthesis , RNA, Messenger/genetics , Ribosomes/metabolism , Humans , Web BrowserABSTRACT
As a common pathology of many ocular disorders such as diabetic retinopathy and glaucoma, retinal ischemia/reperfusion (IR) triggers inflammation and microglia activation that lead to irreversible retinal damage. The detailed molecular mechanism underlying retinal IR injury, however, remains poorly understood at present. Here we report the bioinformatic identification of a lncRNA 1810058I24Rik (181-Rik) that was shown to encode a mitochondrion-located micropeptide Stmp1. Its deficiency in mice protected retinal ganglion cells from retinal IR injury by attenuating the activation of microglia and the Nlrp3 inflammasome pathway. Moreover, its genetic knockout in mice or knockdown in primary microglia promoted mitochondrial fusion, impaired mitochondrial membrane potential, and reactive oxygen species (ROS) production, diminished aerobic glycolysis, and ameliorated inflammation. It appears that 181-Rik may trigger the Nlrp3 inflammasome activation by controlling mitochondrial functions through inhibiting expression of the metabolic sensor uncoupling protein 2 (Ucp2) and activating expression of the Ca2+ sensors S100a8/a9. Together, our findings shed new light on the molecular pathogenesis of retinal IR injury and may provide a fresh therapeutic target for IR-associated neurodegenerative diseases.
Subject(s)
RNA, Long Noncoding , Reperfusion Injury , Mice , Animals , Microglia/metabolism , Inflammasomes/metabolism , NLR Family, Pyrin Domain-Containing 3 Protein/genetics , NLR Family, Pyrin Domain-Containing 3 Protein/metabolism , RNA, Long Noncoding/metabolism , Neuroinflammatory Diseases , Mitochondria/metabolism , Inflammation/genetics , Inflammation/metabolism , Reperfusion Injury/metabolism , Ischemia/metabolism , MicropeptidesABSTRACT
riboCIRC is a translatome data-oriented circRNA database specifically designed for hosting, exploring, analyzing, and visualizing translatable circRNAs from multi-species. The database provides a comprehensive repository of computationally predicted ribosome-associated circRNAs; a manually curated collection of experimentally verified translated circRNAs; an evaluation of cross-species conservation of translatable circRNAs; a systematic de novo annotation of putative circRNA-encoded peptides, including sequence, structure, and function; and a genome browser to visualize the context-specific occupant footprints of circRNAs. It represents a valuable resource for the circRNA research community and is publicly available at http://www.ribocirc.com .