Towards a comprehensive pipeline to identify and functionally annotate long noncoding RNA (lncRNA)

LINC01094: A key long non-coding RNA in the regulation of cancer progression and therapeutic targets

LINC01094 is a long non-coding RNA that plays a crucial role in cancer progression by modulating key signaling pathways, such as PI3K/AKT, Wnt/β-catenin and TGF-β Signaling Pathway Feedback Loop. In this review we summarize the recent research on the functional mechanisms of LINC01094 in various cancers, including its impact on tumor growth, metastasis, and resistance to therapy. We also discuss the therapeutic potential of targeting LINC01094 and highlight the current strategies and challenges in this area. Perspectives on future development of LINC01094-based therapies are also provided.

Plant long non-coding RNAs: identification and analysis to unveil their physiological functions

Eukaryotic genomes encode thousands of RNA molecules; however, only a minimal fraction is translated into proteins. Among the non-coding elements, long non-coding RNAs (lncRNAs) play important roles in diverse biological processes. LncRNAs are associated mainly with the regulation of the expression of the genome; nonetheless, their study has just scratched the surface. This is somewhat due to the lack of widespread conservation at the sequence level, in addition to their relatively low and highly tissue-specific expression patterns, which makes their exploration challenging, especially in plant genomes where only a few of these molecules have been described completely. Recently published high-quality genomes of crop plants, along with new computational tools, are considered promising resources for studying these molecules in plants. This review briefly summarizes the characteristics of plant lncRNAs, their presence and conservation, the different protocols to find these elements, and the limitations of these protocols. Likewise, it describes their roles in different plant physiological phenomena. We believe that the study of lncRNAs can help to design strategies to reduce the negative effect of biotic and abiotic stresses on the yield of crop plants and, in the future, help create fruits and vegetables with improved nutritional content, higher amounts of compounds with positive effects on human health, better organoleptic characteristics, and fruits with a longer postharvest shelf life.

Linc2function: A Comprehensive Pipeline and Webserver for Long Non-Coding RNA (lncRNA) Identification and Functional Predictions Using Deep Learning Approaches

Long non-coding RNAs (lncRNAs), comprising a significant portion of the human transcriptome, serve as vital regulators of cellular processes and potential disease biomarkers. However, the function of most lncRNAs remains unknown, and furthermore, existing approaches have focused on gene-level investigation. Our work emphasizes the importance of transcript-level annotation to uncover the roles of specific transcript isoforms. We propose that understanding the mechanisms of lncRNA in pathological processes requires solving their structural motifs and interactomes. A complete lncRNA annotation first involves discriminating them from their coding counterparts and then predicting their functional motifs and target bio-molecules. Current in silico methods mainly perform primary-sequence-based discrimination using a reference model, limiting their comprehensiveness and generalizability. We demonstrate that integrating secondary structure and interactome information, in addition to using transcript sequence, enables a comprehensive functional annotation. Annotating lncRNA for newly sequenced species is challenging due to inconsistencies in functional annotations, specialized computational techniques, limited accessibility to source code, and the shortcomings of reference-based methods for cross-species predictions. To address these challenges, we developed a pipeline for identifying and annotating transcript sequences at the isoform level. We demonstrate the effectiveness of the pipeline by comprehensively annotating the lncRNA associated with two specific disease groups. The source code of our pipeline is available under the MIT licensefor local use by researchers to make new predictions using the pre-trained models or to re-train models on new sequence datasets. Non-technical users can access the pipeline through a web server setup.

ICAnnoLncRNA: A Snakemake Pipeline for a Long Non-Coding-RNA Search and Annotation in Transcriptomic Sequences

Long non-coding RNAs (lncRNAs) are RNA molecules longer than 200 nucleotides that do not encode proteins. Experimental studies have shown the diversity and importance of lncRNA functions in plants. To expand knowledge about lncRNAs in other species, computational pipelines that allow for standardised data-processing steps in a mode that does not require user control up until the final result were actively developed recently. These advancements enable wider functionality for lncRNA data identification and analysis. In the present work, we propose the ICAnnoLncRNA pipeline for the automatic identification, classification and annotation of plant lncRNAs in assembled transcriptomic sequences. It uses the LncFinder software for the identification of lncRNAs and allows the adjustment of recognition parameters using genomic data for which lncRNA annotation is available. The pipeline allows the prediction of lncRNA candidates, alignment of lncRNA sequences to the reference genome, filtering of erroneous/noise transcripts and probable transposable elements, lncRNA classification by genome location, comparison with sequences from external databases and analysis of lncRNA structural features and expression. We used transcriptomic sequences from 15 maize libraries assembled by Trinity and Hisat2/StringTie to demonstrate the application of the ICAnnoLncRNA pipeline.

Altered long non-coding RNAs expression in normal and diseased primary human airway epithelial cells exposed to diesel exhaust particles

BACKGROUND

Exposure to diesel exhaust particles (DEP) has been linked to a variety of adverse health effects, including increased morbidity and mortality from cardiovascular diseases, chronic obstructive pulmonary disease (COPD), metabolic syndrome, and lung cancer. The epigenetic changes caused by air pollution have been associated with increased health risks. However, the exact molecular mechanisms underlying the lncRNA-mediated pathogenesis induced by DEP exposure have not been revealed.

METHODS

Through RNA-sequencing and integrative analysis of both mRNA and lncRNA profiles, this study investigated the role of lncRNAs in altered gene expression in healthy and diseased human primary epithelial cells (NHBE and DHBE-COPD) exposed to DEP at a dose of 30 μg/cm2.

RESULTS

We identified 503 and 563 differentially expressed (DE) mRNAs and a total of 10 and 14 DE lncRNAs in NHBE and DHBE-COPD cells exposed to DEP, respectively. In both NHBE and DHBE-COPD cells, enriched cancer-related pathways were identified at mRNA level, and 3 common lncRNAs OLMALINC, AC069234.2, and LINC00665 were found to be associated with cancer initiation and progression. In addition, we identified two cis-acting (TMEM51-AS1 and TTN-AS1) and several trans-acting lncRNAs (e.g. LINC01278, SNHG29, AC006064.4, TMEM51-AS1) only differentially expressed in COPD cells, which could potentially play a role in carcinogenesis and determine their susceptibility to DEP exposure.

CONCLUSIONS

Overall, our work highlights the potential importance of lncRNAs in regulating DEP-induced gene expression changes associated with carcinogenesis, and individuals suffering from COPD are likely to be more vulnerable to these environmental triggers.

LncRNA-disease association identification using graph auto-encoder and learning to rank

Discovering the relationships between long non-coding RNAs (lncRNAs) and diseases is significant in the treatment, diagnosis and prevention of diseases. However, current identified lncRNA-disease associations are not enough because of the expensive and heavy workload of wet laboratory experiments. Therefore, it is greatly important to develop an efficient computational method for predicting potential lncRNA-disease associations. Previous methods showed that combining the prediction results of the lncRNA-disease associations predicted by different classification methods via Learning to Rank (LTR) algorithm can be effective for predicting potential lncRNA-disease associations. However, when the classification results are incorrect, the ranking results will inevitably be affected. We propose the GraLTR-LDA predictor based on biological knowledge graphs and ranking framework for predicting potential lncRNA-disease associations. Firstly, homogeneous graph and heterogeneous graph are constructed by integrating multi-source biological information. Then, GraLTR-LDA integrates graph auto-encoder and attention mechanism to extract embedded features from the constructed graphs. Finally, GraLTR-LDA incorporates the embedded features into the LTR via feature crossing statistical strategies to predict priority order of diseases associated with query lncRNAs. Experimental results demonstrate that GraLTR-LDA outperforms the other state-of-the-art predictors and can effectively detect potential lncRNA-disease associations. Availability and implementation: Datasets and source codes are available at http://bliulab.net/GraLTR-LDA.

LncRNA-miRNA axis in tumor progression and therapy response: An emphasis on molecular interactions and therapeutic interventions

Epigenetic factors are critical regulators of biological and pathological mechanisms and they could interact with different molecular pathways. Targeting epigenetic factors has been an idea approach in disease therapy, especially cancer. Accumulating evidence has highlighted function of long non-coding RNAs (lncRNAs) as epigenetic factors in cancer initiation and development and has focused on their association with downstream targets. microRNAs (miRNAs) are the most well-known targets of lncRNAs and present review focuses on lncRNA-miRNA axis in malignancy and therapy resistance of tumors. LncRNA-miRNA regulates cell death mechanisms such as apoptosis and autophagy in cancers. This axis affects tumor metastasis via regulating EMT and MMPs. Besides, lncRNA-miRNA axis determines sensitivity of tumor cells to chemotherapy, radiotherapy and immunotherapy. Based on the studies, lncRNAs can be affected by drugs and genetic tools in cancer therapy and this may affect expression level of miRNAs as their downstream targets, leading to cancer suppression/progression. LncRNAs have both tumor-promoting and tumor-suppressor functions in cancer and this unique function of lncRNAs has complicated their implication in tumor therapy. LncRNA-miRNA axis can also affect other signaling networks in cancer such as PI3K/Akt, STAT3, Wnt/β-catenin and EZH2 among others. Notably, lncRNA/miRNA axis can be considered as a signature for diagnosis and prognosis in cancers.

RASSF8-AS1 displays low expression in colorectal cancer and up-regulates RASSF8 to suppress cell invasion and migration

BACKGROUND

Colorectal cancer (CRC) is among the most prevalent cancers. Long non-coding RNAs (lncRNAs) are important participant in various cancers. Based on the literature, lncRNA RASSF8-AS1 inhibits laryngeal squamous cell carcinoma (LSCC) malignant progression. However, the role of RASSF8-AS1 in CRC remains unclear.

PURPOSE

This study centered on uncovering the role of RASSF8-AS1 and its related regulatory mechanisms in CRC cells.

METHODS

RT-qPCR and western blot were performed to examine the expression of target genes. Functional assays were conducted to determine the effect of target genes on the migration and invasion of CRC cells. Mechanism assays were also carried out to figure out the specific downstream mechanisms of RASSF8-AS1. In vivo assays were also involved.

RESULTS

The expression of RASSF8-AS1 and RASSF8 was positively correlated in CRC, and the two genes were down-regulated in CRC cells and tissues. Moreover, CRC cell invasion and migration as well as xenograft CRC tumor growth suppressed by RASSF8-AS1 overexpression were entirely recovered by RASSF8 knockdown or partially rescued by miR-33a-5p augment. As for the downstream mechanism, RASSF8-AS1 sponged miR-33a-5p to up-regulate RASSF8, or recruited HNRNPC to stabilize RASSF8 mRNA.

CONCLUSION

RASSF8-AS1 modulates miR-33a-5p/HNRNPC/RASSF8 axis to further impede CRC cell invasion and migration.

AVAILABILITY OF DATA

The research data is confidential.

Analysis of lncRNAs and mRNA Expression in the ZBTB1 Knockout Monoclonal EL4 Cell Line and Combined Analysis With miRNAs and circRNAs

In previous experiments, we identified the effect of deletion of the Zbtb1 gene on circRNAs and microRNAs. In this study, we examined the expression profiles of lncRNAs and mRNAs using the RNA-seq method for Zbtb1-deficient EL4 cells and performed a clustering analysis of differentially expressed lncRNAs and mRNAs. GO term histograms and KEGG scatter plots were drawn. For the experimental results, a joint analysis was performed, which predicted the regulatory relationships among lncRNAs, mRNAs, microRNAs and circRNAs. For the regulatory relationship between lncRNAs and target genes, the chromatin structure and the degree of openness were verified for the possible target gene locations regulated by lncRNA using experimental methods such as Hi-C and ATAC-seq. Ultimately, the possible differential regulation of the Brcal and Dennd5d genes by lncRNAs and the differential changes in transcription factor binding sites in the promoter region were identified. For neRNA-regulated target genes with significantly differentially expressed mRNAs, a combined screen was performed, and the final obtained candidate target genes were subjected to GO and KEGG term enrichment analyses. Our results illustrate that the Zbtb1 gene can not only function as a regulatory factor but also regulate EL4 cells from multiple perspectives based on ceRNA theory.

Linc00467 promotion of gastric cancer development by directly regulating miR-7-5p expression and downstream epidermal growth factor receptor

Linc00467 is a vital regulator in tumor progression. This study explores the molecular mechanisms of linc00467 in gastric cancer (GC). Linc00467 expression was obtained and analyzed in GC tissue through exploration in the cancer genome atlas database. Then, real-time quantitative polymerase chain reaction was used to detect linc000467 expression in GC cells. Cell functions were observed using cell counting Kit-8, Transwell assay, Western blotting to testify the proliferation, migration, invasion, and the relative expression of epidermal growth factor receptor (EGFR) in GC cells. Moreover, a dual-luciferase reporter gene assay was used to verify the relationship between linc00467 and miR-7-5p. Results showed that the expression of linc00467 was overexpressed in GC. Linc00467 silencing decreased the GC cell proliferation, migration, and invasion. With mRNA verification and combined previous research, linc00467 directly regulated the miR-7-5p expression and downstream EGFR expression. Inhibited miR-7-5p could restore cell function, EGFR expression of GC cells when linc00467 knockdown occurs. Altogether, linc00467 directly regulates the miR-7-5p and EGFR signaling pathway to promote GC proliferation, migration, and invasion.

Genome-wide in silico analysis of long intergenic non-coding RNAs from rice peduncles at the heading stage

Long intergenic non-coding RNAs (lincRNAs) belong to the category of long non-coding RNAs (lncRNAs), originated from intergenic regions, which do not code for proteins. LincRNAs perform prominent role in regulation of gene expression during plant development and stress response by directly interacting with DNA, RNA, or proteins, or triggering production of small RNA regulatory molecules. Here, we identified 2973 lincRNAs and investigated their expression dynamics during peduncle elongation in two Indian rice cultivars, Pokkali and Swarna, at the time of heading. Differential expression analysis revealed common and cultivar-specific expression patterns, which we utilized to infer the lincRNA candidates with potential involvement in peduncle elongation and panicle exsertion. Their putative targets were identified using in silico prediction methods followed by pathway mapping and literature-survey based functional analysis. Further, to infer the mechanism of action, we identified the lincRNAs which potentially act as miRNA precursors or target mimics.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s12298-021-01059-2.

Alteration of long non-coding RNAs and mRNAs expression profiles by compound heterozygous ASXL3 mutations in the mouse brain

Compound mutations in the additional sex combs-like 3 (ASXL3) gene greatly impact the expression of long non-coding RNAs (lncRNAs) and messenger RNAs (mRNAs) in mouse myocardial tissues. Little is known about ASXL3 mutation effects on lncRNAs and mRNAs expression in the cerebrum and cerebellum. This study aims to clarify this point using quantitative real-time polymerase chain reaction and Western blotting. Transcriptome analysis based on RNA-seq followed by bioinformatics analysis were used to compare lncRNA and mRNA expression profiles. Cell proliferation, cell cycle progression, and apoptosis were evaluated after silencing of ASXL3 expression using the 3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4- sulfophenyl)-2 H-tetrazolium method and flow cytometry. Results showed that ASXL3 gene expression was decreased in the cerebrum and cerebellum of mice with ASXL3 P723R*P1817A mutations. We identified 319 lncRNAs and 252 mRNAs differentially expressed in the cerebrum of ASXL3 P723R*P1817A mutant mice. In the cerebellum of ASXL3 P723R*P1817A mutant mice, 5330 lncRNAs and 2204 mRNAs were differentially expressed. Differentially expressed lncRNAs and mRNAs were widely distributed across the mouse genome and were associated with various biological processes and pathways. ASXL3 silencing by siRNA transfection affected the proliferation, cell cycle progression, and apoptosis of neural cells. Therefore, the ASXL3 P723R*P1817A mutations greatly modify the lncRNA and mRNA expression profiles in the mouse cerebrum and cerebellum.

A Survey of Current Resources to Study lncRNA-Protein Interactions

Phenotypes are driven by regulated gene expression, which in turn are mediated by complex interactions between diverse biological molecules. Protein-DNA interactions such as histone and transcription factor binding are well studied, along with RNA-RNA interactions in short RNA silencing of genes. In contrast, lncRNA-protein interaction (LPI) mechanisms are comparatively unknown, likely directed by the difficulties in studying LPI. However, LPI are emerging as key interactions in epigenetic mechanisms, playing a role in development and disease. Their importance is further highlighted by their conservation across kingdoms. Hence, interest in LPI research is increasing. We therefore review the current state of the art in lncRNA-protein interactions. We specifically surveyed recent computational methods and databases which researchers can exploit for LPI investigation. We discovered that algorithm development is heavily reliant on a few generic databases containing curated LPI information. Additionally, these databases house information at gene-level as opposed to transcript-level annotations. We show that early methods predict LPI using molecular docking, have limited scope and are slow, creating a data processing bottleneck. Recently, machine learning has become the strategy of choice in LPI prediction, likely due to the rapid growth in machine learning infrastructure and expertise. While many of these methods have notable limitations, machine learning is expected to be the basis of modern LPI prediction algorithms.

Long non‑coding RNA LINC01006 exhibits oncogenic properties in cervical cancer by functioning as a molecular sponge for microRNA‑28‑5p and increasing PAK2 expression

As previously reported, long intergenic non‑protein‑coding RNA 1006 (LINC01006) plays crucial roles in prostate, pancreatic and gastric cancers. However, whether it plays important roles in cervical cancer remains unclear. The present study thus aimed to determine the precise role of LINC01006 in cervical cancer and elucidate its regulatory mechanisms. The expression of LINC01006 in cervical cancer was examined by reverse transcription‑quantitative polymerase chain reaction. Cell proliferation assay, flow cytometric analysis, Transwell migration and invasion assays, and tumor xenograft model experiments were performed to elucidate the roles of LINC01006 in cervical cancer. Bioinformatics analysis, luciferase reporter assay, RNA immunoprecipitation and rescue experiments were performed for mechanistic analyses. The expression of LINC01006 was found to be upregulated in cervical cancer and to be associated with a poor prognosis. The absence of LINC01006 inhibited the proliferation, migration and invasion of cervical cancer cells, whereas it promoted cell apoptosis in vitro. The downregulation of LINC01006 impeded tumor growth in vivo. LINC01006 was verified as an endogenous 'sponge' that competed for microRNA‑28‑5p (miR‑28‑5p), which resulted in the upregulation of the miR‑28‑5p target P21‑activated kinase 2 (PAK2). Rescue experiments revealed that the suppression of miR‑28‑5p expression or the overexpression of PAK2 abrogated the effects of LINC01006 downregulation on malignant cellular functions in cervical cancer. On the whole, the present study demonstrates that LINC01006 exhibits tumor‑promoting functions in cervical cancer via the regulation of the miR‑28‑5p/PAK2 axis. These findings may provide the basis for the identification of LINC01006‑targeted clinical therapy.

Role of Transposable Elements in Gene Regulation in the Human Genome

Transposable elements (TEs), also known as mobile elements (MEs), are interspersed repeats that constitute a major fraction of the genomes of higher organisms. As one of their important functional impacts on gene function and genome evolution, TEs participate in regulating the expression of genes nearby and even far away at transcriptional and post-transcriptional levels. There are two known principal ways by which TEs regulate the expression of genes. First, TEs provide cis-regulatory sequences in the genome with their intrinsic regulatory properties for their own expression, making them potential factors for regulating the expression of the host genes. TE-derived cis-regulatory sites are found in promoter and enhancer elements, providing binding sites for a wide range of trans-acting factors. Second, TEs encode for regulatory RNAs with their sequences showed to be present in a substantial fraction of miRNAs and long non-coding RNAs (lncRNAs), indicating the TE origin of these RNAs. Furthermore, TEs sequences were found to be critical for regulatory functions of these RNAs, including binding to the target mRNA. TEs thus provide crucial regulatory roles by being part of cis-regulatory and regulatory RNA sequences. Moreover, both TE-derived cis-regulatory sequences and TE-derived regulatory RNAs have been implicated in providing evolutionary novelty to gene regulation. These TE-derived regulatory mechanisms also tend to function in a tissue-specific fashion. In this review, we aim to comprehensively cover the studies regarding these two aspects of TE-mediated gene regulation, mainly focusing on the mechanisms, contribution of different types of TEs, differential roles among tissue types, and lineage-specificity, based on data mostly in humans.