Tracing Translational Footprint by Ribo-Seq: Principle, Workflow, and Applications to Understand the Mechanism of Human Diseases

Bagheri, Atefeh; Астафьев, А. А.; Al-Hashimy, Tara; Jiang, Peng

doi:10.3390/cells11192966

Cited by 6 publications

(3 citation statements)

References 57 publications

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“…The protein-coding or peptide-coding potential of lincRNAs of human chromosome 18 was examined using the LncBook 2.0 database linked with the SmProt database [ 59 ]. SmProt is an online repository with annotation of small proteins derived from ribosome profiling that is based on high-throughput sequencing of mRNAs interacting with active ribosomes in cells [ 60 ]. Table S18 shows a list of 28 potential smORF proteins encoded by six lincRNAs of chromosome 18, though records on their mass spectrometry identification are absent in the Peptide Atlas database [ 61 ].…”

Section: Interactomics Of Lincrnas Of Human Chromosome 18mentioning

confidence: 99%

Long Intergenic Non-Coding RNAs of Human Chromosome 18: Focus on Cancers

Ershov,

Yablokov,

Mezentsev

et al. 2024

Biomedicines

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Malignant neoplasms are characterized by high molecular heterogeneity due to multilevel deregulation of gene expression and cellular functions. It is known that non-coding RNAs, including long intergenic non-coding RNAs (lincRNAs), can play significant roles in cancer biology. The current review focuses on a systematical analysis of genomic, transcriptomic, epigenomic, interactomic, and literature data on 65 lincRNAs of human chromosome 18 in the context of pan-cancer studies. The entire group of lincRNAs can be conditionally divided into 4 subgroups depending on experimental evidence on direct or indirect involvement in cancers and the biological associations with cancers, which we found during the data-mining process: the most studied (5 lincRNAs), moderately or poorly studied (11 lincRNAs), and understudied (31 lincRNAs). For the remaining 18 lincRNAs, data for analysis were fragmentary or missing. Among the key findings were the following: Of the lincRNAs of human chromosome 18, 40% have tissue-specific expression patterns, 22% of lincRNAs are known to have gene fusions, 40% of lincRNAs are prone to gene amplifications and/or deletions in cancers at a frequency greater than 3%, and 23% of lincRNAs are differentially expressed across cancer types, whereas 7% have subtype-specific expression patterns. LincRNAs’ interactomes consist of ‘master’ microRNAs and 47 proteins (including cancer-associated proteins and microRNAs) that can interact with 3 or more lincRNAs. Functional enrichment analysis of a set of highly co-expressed genes retrieved for 17 lincRNAs in different cancer types indicated the potential associations of these lincRNAs with cellular signaling pathways. Six lincRNAs encoded small open-reading frame (smORF) proteins with emerging roles in cancers, and microRNAs as well as proteins with known functions in molecular carcinogenesis can bind to coding regions of smORFs. We identified seven transcriptomic signatures with potential prognostic value, consisting of two to seven different lincRNAs only. Taken together, the literature, biomedical, and molecular biology data analyzed indicated that only five of all lincRNAs of human chromosome 18 are cancer-associated, while eleven other lincRNAs have the tendency to be associated with cancers.

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Section: Interactomics Of Lincrnas Of Human Chromosome 18mentioning

confidence: 99%

Long Intergenic Non-Coding RNAs of Human Chromosome 18: Focus on Cancers

Ershov,

Yablokov,

Mezentsev

et al. 2024

Biomedicines

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“…Therefore, integrating multi-omics data has become a popular method nowadays. Ribo-seq is an emerging technology to study the translational footprint by analyzing mRNA fragments bound to ribosomes, and the combined analysis of Ribo-seq and RNA-seq will also allow us to get a clearer view of how genes change at the transcriptional level and the translational level [25].…”

Section: Introductionmentioning

confidence: 99%

Identification of genes associated with sperm storage capacity in hens at different times after insemination by RNA-seq and Ribo-seq

Chai,

Xiao,

Yang

et al. 2024

BMC Genomics

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Background Sperm storage capacity (SSC) determines the duration of fertility in hens and is an important reproduction trait that cannot be ignored in production. Currently, the genetic mechanism of SSC is still unclear in hens. Therefore, to explore the genetic basis of SSC, we analyzed the uterus-vagina junction (UVJ) of hens with different SSC at different times after insemination by RNA-seq and Ribo-seq. Results Our results showed that 589, 596, and 527 differentially expressed genes (DEGs), 730, 783, and 324 differentially translated genes (DTGs), and 804, 625, and 467 differential translation efficiency genes (DTEGs) were detected on the 5th, 10th, and 15th days after insemination, respectively. In transcription levels, we found that the differences of SSC at different times after insemination were mainly reflected in the transmission of information between cells, the composition of intercellular adhesion complexes, the regulation of ion channels, the regulation of cellular physiological activities, the composition of cells, and the composition of cell membranes. In translation efficiency (TE) levels, the differences of SSC were mainly related to the physiological and metabolic activities in the cell, the composition of the organelle membrane, the physiological activities of oxidation, cell components, and cell growth processes. According to pathway analysis, SSC was related to neuroactive ligand-receptor interaction, histidine metabolism, and PPAR signaling pathway at the transcriptional level and glutathione metabolism, oxidative phosphorylation, calcium signaling pathway, cell adhesion molecules, galactose metabolism, and Wnt signaling pathway at the TE level. We screened candidate genes affecting SSC at transcriptional levels (COL4A4, MUC6, MCHR2, TACR1, AVPR1A, COL1A1, HK2, RB1, VIPR2, HMGCS2) and TE levels(COL4A4, MUC6, CYCS, NDUFA13, CYTB, RRM2, CAMK4, HRH2, LCT, GCK, GALT). Among them, COL4A4 and MUC6 were the key candidate genes differing in transcription, translation, and translation efficiency. Conclusions Our study used the combined analysis of RNA-seq and Ribo-seq for the first time to investigate the SSC and reveal the physiological processes associated with SSC. The key candidate genes affecting SSC were screened, and the theoretical basis was provided for the analysis of the molecular regulation mechanism of SSC.

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“…In this review, we focus on the methodological improvements and optimization of the sRNA library construction for the profiling of sRNAs with lengths (15–50 nt), summarize the advantages and drawbacks, and also discuss the challenges and the possible solutions underlying different treatment procedures. Moreover, the current widely‐exploited techniques, including RNA immunoprecipitation and sequencing (RIP‐seq) (Gagliardi & Matarazzo, 2016), cross‐linking and immunoprecipitation by sequencing (CLIP‐seq) (Markus Hafner et al, 2021; Y. Zhang et al, 2015), and ribosome profiling by sequencing (Ribo‐seq) (Bagheri et al, 2022), aim to globally interrogate the direct RNA binding sequences (i.e., the short mRNA fragments, hereafter referred to as RNA fragment footprinting). Therefore, these techniques are built on the short RNA sequencing strategies analogous to sRNA library construction, we thus also briefly discuss how the strategies of sRNA sequencing might inspire different aspects of RNA fragment footprinting.…”

Section: Introductionmentioning

confidence: 99%

Untacking small RNA profiling and RNA fragment footprinting: Approaches and challenges in library construction

Shen,

Naveed,

Bao

2024

WIREs RNA

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Small RNAs (sRNAs) with sizes ranging from 15 to 50 nucleotides (nt) are critical regulators of gene expression control. Prior studies have shown that sRNAs are involved in a broad range of biological processes, such as organ development, tumorigenesis, and epigenomic regulation; however, emerging evidence unveils a hidden layer of diversity and complexity of endogenously encoded sRNAs profile in eukaryotic organisms, including novel types of sRNAs and the previously unknown post‐transcriptional RNA modifications. This underscores the importance for accurate, unbiased detection of sRNAs in various cellular contexts. A multitude of high‐throughput methods based on next‐generation sequencing (NGS) are developed to decipher the sRNA expression and their modifications. Nonetheless, distinct from mRNA sequencing, the data from sRNA sequencing suffer frequent inconsistencies and high variations emanating from the adapter contaminations and RNA modifications, which overall skew the sRNA libraries. Here, we summarize the sRNA‐sequencing approaches, and discuss the considerations and challenges for the strategies and methods of sRNA library construction. The pros and cons of sRNA sequencing have significant implications for implementing RNA fragment footprinting approaches, including CLIP‐seq and Ribo‐seq. We envision that this review can inspire novel improvements in small RNA sequencing and RNA fragment footprinting in future.This article is categorized under: RNA Evolution and Genomics > Computational Analyses of RNA RNA Processing > Processing of Small RNAs Regulatory RNAs/RNAi/Riboswitches > Biogenesis of Effector Small RNAs

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Tracing Translational Footprint by Ribo-Seq: Principle, Workflow, and Applications to Understand the Mechanism of Human Diseases

Cited by 6 publications

References 57 publications

Long Intergenic Non-Coding RNAs of Human Chromosome 18: Focus on Cancers

Long Intergenic Non-Coding RNAs of Human Chromosome 18: Focus on Cancers

Identification of genes associated with sperm storage capacity in hens at different times after insemination by RNA-seq and Ribo-seq

Untacking small RNA profiling and RNA fragment footprinting: Approaches and challenges in library construction

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