An integrative proteogenomics approach reveals peptides encoded by annotated lincRNA in the mouse kidney inner medulla

CircRNA and lncRNA-encoded peptide in diseases, an update review

Non-coding RNAs (ncRNAs), including circular RNAs (circRNAs) and long non-coding RNAs (lncRNAs), are unique RNA molecules widely identified in the eukaryotic genome. Their dysregulation has been discovered and played key roles in the pathogenesis of numerous diseases, including various cancers. Previously considered devoid of protein-coding ability, recent research has revealed that a small number of open reading frames (ORFs) within these ncRNAs endow them with the potential for protein coding. These ncRNAs-derived peptides or proteins have been proven to regulate various physiological and pathological processes through diverse mechanisms. Their emerging roles in disease diagnosis and targeted therapy underscore their potential utility in clinical settings. This comprehensive review aims to provide a systematic overview of proteins or peptides encoded by lncRNAs and circRNAs, elucidate their production and functional mechanisms, and explore their promising applications in cancer diagnosis, disease prediction, and targeted therapy.

Long noncoding RNA study: Genome-wide approaches

Long noncoding RNAs (lncRNAs) have been confirmed to play a crucial role in various biological processes across several species. Though many efforts have been devoted to the expansion of the lncRNAs landscape, much about lncRNAs is still unknown due to their great complexity. The development of high-throughput technologies and the constantly improved bioinformatic methods have resulted in a rapid expansion of lncRNA research and relevant databases. In this review, we introduced genome-wide research of lncRNAs in three parts: (i) novel lncRNA identification by high-throughput sequencing and computational pipelines; (ii) functional characterization of lncRNAs by expression atlas profiling, genome-scale screening, and the research of cancer-related lncRNAs; (iii) mechanism research by large-scale experimental technologies and computational analysis. Besides, primary experimental methods and bioinformatic pipelines related to these three parts are summarized. This review aimed to provide a comprehensive and systemic overview of lncRNA genome-wide research strategies and indicate a genome-wide lncRNA research system.

A peptide encoded by lncRNA MIR7-3 host gene (MIR7-3HG) alleviates dexamethasone-induced dysfunction in pancreatic β-cells through the PI3K/AKT signaling pathway

BACKGROUND

Dysfunction of pancreatic β-cells induced by glucocorticoids contributes to diabetes mellitus development. Long noncoding RNAs (lncRNAs) have been recognized to contain short open reading frames (ORFs) that can be translated into functional small peptides. Here, we investigated whether the short peptide encoded by the lncRNA MIR7-3 host gene (MIR7-3HG) can affect dexamethasone (DEX)-induced β-cell dysfunction.

METHODS

Bioinformatics analysis was used for selection of MIR7-3HG and prediction of its protein encoding potential. The small peptide was identified by a western blot method. The cell-permeable TAT was fused into MIR7-3HG ORF to produce the cell-permeable fusion peptide (TAT-MIR7-3HG-ORF). The effects of TAT-MIR7-3HG-ORF on DEX-induced β-cell dysfunction were evaluated by examining cell viability, apoptosis, insulin secretion, and reactive oxygen species (ROS) generation.

RESULTS

DEX induced β-TC6 cell dysfunction by impairing cell viability, insulin secretion and promoting cell apoptosis and ROS generation. The MIR7-3HG ORF could encode a 125-amino-acid-long short peptide. TAT-MIR7-3HG-ORF effectively transduced into β-TC6 cells and attenuated DEX-induced dysfunction in β-TC6 cells. Moreover, transduced TAT-MIR7-3HG-ORF reversed DEX-mediated inhibition of the activation of the PI3K/AKT signaling pathway. The inhibitor of the PI3K/AKT pathway partially abolished the alleviative effect of transduced TAT-MIR7-3HG-ORF on DEX-induced β-TC6 cell dysfunction.

CONCLUSION

The lncRNA MIR7-3HG encodes a short peptide, which can protect pancreatic β-cells from DEX-induced dysfunction by activating the PI3K/AKT pathway. Our study broadens the diversity and breadth of lncRNAs in human disorders.

Peptidomics Methods Applied to the Study of Flower Development

Understanding the global and dynamic nature of plant developmental processes requires not only the study of the transcriptome, but also of the proteome, including its largely uncharacterized peptidome fraction. Recent advances in proteomics and high-throughput analyses of translating RNAs (ribosome profiling) have begun to address this issue, evidencing the existence of novel, uncharacterized, and possibly functional peptides. To validate the accumulation in tissues of sORF-encoded polypeptides (SEPs), the basic setup of proteomic analyses (i.e., LC-MS/MS) can be followed. However, the detection of peptides that are small (up to ~100 aa, 6-7 kDa) and novel (i.e., not annotated in reference databases) presents specific challenges that need to be addressed both experimentally and with computational biology resources. Several methods have been developed in recent years to isolate and identify peptides from plant tissues. In this chapter, we outline two different peptide extraction protocols and the subsequent peptide identification by mass spectrometry using the database search or the de novo identification methods.

Proteomic-driven identification of short open reading frame-encoded peptides

Accumulating evidence has shown that a large number of short open reading frames (sORFs) also have the ability to encode proteins. The discovery of sORFs opens up a new research area, leading to the identification and functional study of sORF encoded peptides (SEPs) at the omics level. Besides bioinformatics prediction and ribosomal profiling, mass spectrometry (MS) has become a significant tool as it directly detects the sequence of SEPs. Though MS-based proteomics methods have proved to be effective for qualitative and quantitative analysis of SEPs, the detection of SEPs is still a great challenge due to their low abundance and short sequence. To illustrate the progress in method development, we described and discussed the main steps of large-scale proteomics identification of SEPs, including SEP extraction and enrichment, MS detection, data processing and quality control, quantification, and function prediction and validation methods. This article is protected by copyright. All rights reserved.

CALINCA-A Novel Pipeline for the Identification of lncRNAs in Podocyte Disease

Diseases of the renal filtration unit-the glomerulus-are the most common cause of chronic kidney disease. Podocytes are the pivotal cell type for the function of this filter and focal-segmental glomerulosclerosis (FSGS) is a classic example of a podocytopathy leading to proteinuria and glomerular scarring. Currently, no targeted treatment of FSGS is available. This lack of therapeutic strategies is explained by a limited understanding of the defects in podocyte cell biology leading to FSGS. To date, most studies in the field have focused on protein-coding genes and their gene products. However, more than 80% of all transcripts produced by mammalian cells are actually non-coding. Here, long non-coding RNAs (lncRNAs) are a relatively novel class of transcripts and have not been systematically studied in FSGS to date. The appropriate tools to facilitate lncRNA research for the renal scientific community are urgently required due to a row of challenges compared to classical analysis pipelines optimized for coding RNA expression analysis. Here, we present the bioinformatic pipeline CALINCA as a solution for this problem. CALINCA automatically analyzes datasets from murine FSGS models and quantifies both annotated and de novo assembled lncRNAs. In addition, the tool provides in-depth information on podocyte specificity of these lncRNAs, as well as evolutionary conservation and expression in human datasets making this pipeline a crucial basis to lncRNA studies in FSGS.