lncRNA-mRNA Interaction Networks Research Articles

Identification of key LncRNAs and mRNAs in fat deposition of Saba pigs based on comparative analysis of transcriptomics

ABSTRACT Long non-coding RNAs (LncRNAs) are gaining attention in the context of pork production due to their role in regulating fat deposition, a crucial economic trait. This study focused on profiling LncRNAs in back fat deposition in Saba and Yorkshire pigs, which exhibit significant differences in fat accumulation. Using transcriptome sequencing and bioinformatics, we identified 704 differentially expressed mRNAs and 50 LncRNAs. We employed cis-regulatory analysis to explore the function of LncRNAs. Gene Ontology (GO) enrichment revealed pathways and enzyme activity-related terms, indicating that LncRNAs may modulate gene expression to influence biological processes. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed enrichment in fat deposition pathways, underscoring the critical role of LncRNAs in this process. Further analysis and construction of LncRNA-mRNA interaction networks revealed 5 potential regulatory networks. Combining the data of differentially expressed LncRNAs and mRNAs, we identified candidate LncRNAs that regulate the expression of ACACA and FASN, which are functionally important genes affecting fat deposition. In summary, this study provides a theoretical foundation and valuable insights into the molecular mechanisms underlying LncRNA-mediated regulation of fat deposition in pigs. These findings are essential for advancing our understanding of porcine fat deposition and enhancing pork production.

Possible Involvement of Long Non-Coding RNAs GNAS-AS1 and MIR205HG in the Modulation of 5-Fluorouracil Chemosensitivity in Colon Cancer Cells through Increased Extracellular Release of Exosomes.

A growing number of studies have suggested the involvement of long non-coding RNAs as the key players in not just the initiation and progression of the tumor microenvironment, but also in chemotherapy tolerance. In the present study, generated 5-FU-resistant SW480/DR cells were analyzed via cDNA microarray for its aberrant lncRNAs and mRNAs expression in comparison with the 5-FU-susceptible SW480/DS cells. Among the 126 lncRNAs described, lncRNAs GNAS-AS1, MIR205HG, and LOC102723721 have been identified to be significantly upregulated, while lncRNs lnc-RP11-597K23.2.1-2, LOC100507639, and CCDC144NL-AS1 have been found to be significantly downregulated. In the meantime, bioinformatic analysis through gene ontology studies of aberrantly expressed mRNAs revealed "regulated exocytosis", among others, as the biological process most impacted in SW480/DR cells. To investigate, exosome purification was then carried out and its characterization were validated via transmission electron microscopy and nanoparticle tracking analysis. Interestingly, it was determined that the 5-FU-resistant SW480/DR cells secretes significantly higher concentration of extracellular vesicles, particularly, exosomes when compared to the 5-FU-susceptible SW480/DS cells. Based on the lncRNA-mRNA interaction network analysis generated, lncRNA GNAS-AS1 and MIR205HG have been identified to be potentially involved in the incidence of 5-FU resistance in SW480 colon cancer cells through promoting increased release of exosomes into the intercellular matrix. Our study hopes not only to provide insights on the list of involved candidate lncRNAs, but also to elucidate the role exosomes play in the initiation and development of 5-FU chemotherapy resistance in colon cancer cells.

Transcriptomic sequencing analysis of key long noncoding RNAs and mRNAs expression profiles in postoperative recurrence of hepatocellular carcinoma.

Recurrence is the main cause of death in hepatocellular carcinoma (HCC) patients after liver resection. The long non-coding RNAs (lncRNAs) have been reported participated in progression and prognosis of HCC, however, the vital role of lncRNA in postoperative recurrence of HCC has rarely been systematically identified. RNA-sequencing (RNA-seq) was performed between orthotopic model of HCC and hepatoma postoperative recurrent model to comprehensively analyze the integrated transcriptome expression profiles of lncRNA and mRNA. Quantitative Real-Time Polymerase Chain Reaction (qRT-PCR) was then conducted to quantify the expression levels of DElncRNAs and their target mRNAs. In our study, 211 lncRNAs (P-value < 0.05) and 1125 mRNAs (P-adjust < 0.05) were significantly differentially expressed (DE) between two groups. Moreover, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses showed that DElncRNAs and DEmRNAs were mainly enriched in lipid metabolism, including Arachidonic acid metabolism, PPAR signaling pathway, Steroid hormone biosynthesis, Linoleic acid metabolism, Inflammatory mediator regulation of TRP channels, and Fatty acid degradation. Furthermore, we constructed lncRNA-mRNA interaction networks and protein-protein interaction (PPI) network, and verified by qRT-PCR, suggesting that increased DEIncRNAs (XLOC_063499 and XLOC_042016) may prevent HCC recurrence after surgery by upregulating on targeted cytochrome P450 (CYP) family genes in the lipid metabolism pathway, such as cyp3a16, cyp3a44, cyp2c39, cyp2c40 and cyp2c68. Overall, Our findings provided new insights for further investigation of biological function in lncRNA related HCC recurrence.

Transcriptome Analysis of mRNA and lncRNA Related to Muscle Growth and Development in Gannan Yak and Jeryak

The production performance of Jeryak, resulting from the F1 generation of the cross between Gannan yak and Jersey cattle, exhibits a significantly superior outcome compared with that of Gannan yak. Therefore, we used an RNA-seq approach to identify differentially expressed mRNAs (DEMs) and differentially expressed lncRNAs (DELs) influencing muscle growth and development in Gannan yaks and Jeryaks. A total of 304 differentially expressed lncRNAs and 1819 differentially expressed mRNAs were identified based on the screening criteria of |log 2 FC| &gt; 1 and FDR &lt; 0.05. Among these, 132 lncRNAs and 1081 mRNAs were found to be down-regulated, while 172 lncRNAs and 738 mRNAs were up-regulated. GO and KEGG analyses showed that the identified DELs and DEMs were enriched in the entries of pathways associated with muscle growth and development. On this basis, we constructed an lncRNA–mRNA interaction network. Interestingly, two candidate DELs (MSTRG.16260.9 and MSTRG.22127.1) had targeting relationships with 16 (MYC, IGFBP5, IGFBP2, MYH4, FGF6, etc.) genes related to muscle growth and development. These results could provide a basis for further studies on the roles of lncRNAs and mRNAs in muscle growth in Gannan yaks and Jeryak breeds.

Genome-Wide Expression Analysis of Long Noncoding RNAs and Their Target Genes in Metafemale Drosophila.

Aneuploidy is usually more detrimental than altered ploidy of the entire set of chromosomes. To explore the regulatory mechanism of gene expression in aneuploidy, we analyzed the transcriptome sequencing data of metafemale Drosophila. The results showed that most genes on the X chromosome undergo dosage compensation, while the genes on the autosomal chromosomes mainly present inverse dosage effects. Furthermore, long noncoding RNAs (lncRNAs) have been identified as key regulators of gene expression, and they are more sensitive to dosage changes than mRNAs. We analyzed differentially expressed mRNAs (DEGs) and differentially expressed lncRNAs (DELs) in metafemale Drosophila and performed functional enrichment analyses of DEGs and the target genes of DELs, and we found that they are involved in several important biological processes. By constructing lncRNA-mRNA interaction networks and calculating the maximal clique centrality (MCC) value of each node in the network, we also identified two key candidate lncRNAs (CR43940 and CR42765), and two of their target genes, Sin3A and MED1, were identified as inverse dosage modulators. These results suggest that lncRNAs play an important role in the regulation of genomic imbalances. This study may deepen the understanding of the gene expression regulatory mechanisms in aneuploidy from the perspective of lncRNAs.

Integrated analysis of lncRNA and mRNA expression profiles in patients with unexplained recurrent spontaneous abortion.

Unexplained recurrent spontaneous abortion (URSA) is one of the most frustrating and confounding conditions in reproductive medicine, and its exact pathogenesis has not been clearly established. In this study, we used RNA sequencing to characterize the mRNA and lncRNA expression profiles in peripheral blood. Thereafter, enrichment analysis was performed to determine the functions of the differentially expressed genes, and Cytoscape was used to construct lncRNA-mRNA interaction networks. Our results showed that the peripheral blood of patients with URSA has distinct mRNA and lncRNA expression profiles, with a total of 359 mRNAs and 683 lncRNAs being differentially expressed. Moreover, the top hub genes, including IGF1, PPARG, CCL3, RETN, SERPINE1, HESX1, and PRL, were identified and further validated using real-time quantitative PCR. Furthermore, we demonstrated a lncRNA-mRNA interaction network that achieved 12 key lncRNAs and their targeted mRNAs are involved in systemic lupus erythematosus, allograft rejection, and complement and coagulation cascades. Finally, the correlation between immune cell subtypes and IGF1 expression was evaluated; a negative correlation was observed with the proportion of natural killer cells, which increased significantly in URSA. We identified seven top hub genes, constructed a lncRNA-related network and suggested that IGF1 plays a key role in regulating maternal immune response by affecting NK and T cells' function, which helps to identify the pathogenesis of URSA.

Integrated transcriptome analysis reveals roles of long non-coding RNAs (lncRNAs) in caprine skeletal muscle mass and meat quality.

Long non-coding RNAs (lncRNAs) play important roles in the growth and development of skeletal muscle. However, there is limited information on goats. In this study, expression profiles of lncRNAs in Longissimus dorsi muscle from Liaoning cashmere (LC) goats and Ziwuling black (ZB) goats with divergent meat yield and meat quality were compared using RNA-sequencing. Based on our previous microRNA (miRNA) and mRNA profiles obtained from the same tissues, the target genes and binding miRNAs of differentially expressed lncRNAs were obtained. Subsequently, lncRNA-mRNA interaction networks and a ceRNA network of lncRNA-miRNA-mRNA were constructed. A total of 136 differentially expressed lncRNAs were identified between the two breeds. Fifteen cis target genes and 143 trans target genes were found for differentially expressed lncRNAs, and they were enriched in muscle contraction, muscle system process, muscle cell differentiation, and p53 signaling pathway. A total of 69 lncRNA-trans target gene pairs were constructed, with close relationship with muscle development, intramuscular fat deposition, and meat tenderness. A total of 16 lncRNA-miRNA-mRNA ceRNA pairs were identified, of which some reportedly associated with skeletal muscle development and fat deposition were found. The study will provide an improved understanding of the roles of lncRNAs in caprine meat yield and meat quality.

Plant non-coding RNAs function in pollen development and male sterility.

Male sterility is classified as either cytoplasmic male sterility (CMS) or genic male sterility (GMS). Generally, CMS involves mitochondrial genomes interacting with the nuclear genome, while GMS is caused by nuclear genes alone. Male sterility is regulated by multilevel mechanisms in which non-coding RNAs (ncRNAs), including microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and phased small interfering RNAs (phasiRNAs), which have been proven to be critical elements. The development of high-throughput sequencing technology offers new opportunities to evaluate the genetic mechanism of ncRNAs in plant male sterility. In this review, we summarize the critical ncRNAs that regulate gene expression in ways dependent on or independent of hormones, which involve the differentiation of the stamen primordia, degradation of the tapetum, formation of microspores, and the release of pollen. In addition, the key mechanisms of the miRNA-lncRNA-mRNA interaction networks mediating male sterility in plants are elaborated. We present a different perspective on exploring the ncRNA-mediated regulatory pathways that control CMS in plants and create male-sterile lines through hormones or genome editing. A refined understanding of the ncRNA regulatory mechanisms in plant male sterility for the development of new sterile lines would be conducive to improve hybridization breeding.

Characterization of differentially expressed and lipid metabolism-related lncRNA-mRNA interaction networks during the growth of liver tissue through rabbit models.

BackgroundCharacterization the long non-coding RNAs (lncRNAs) and their regulated mRNAs involved in lipid metabolism during liver growth and development is of great value for discovering new genomic biomarkers and therapeutic targets for fatty liver and metabolic syndrome.Materials and methodsLiver samples from sixteen rabbit models during the four growth stages (birth, weaning, sexual maturity, and somatic maturity) were used for RNA-seq and subsequent bioinformatics analyses. Differentially expressed (DE) lncRNAs and mRNAs were screened, and the cis/trans-regulation target mRNAs of DE lncRNAs were predicted. Then the function enrichment analyses of target mRNAs were performed through Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, respectively. The target protein interaction (PPI) and lncRNA-mRNA co-expression networks were constructed using string version 11.0 platform and R Stats. Finally, six lncRNAs and six mRNAs were verified taking RT-qPCR.ResultsLiver Oil Red O detection found that the liver showed time-dependent accumulation of lipid droplets. 41,095 lncRNAs, 30,744 mRNAs, and amount to 3,384 DE lncRNAs and 2980 DE mRNAs were identified from 16 cDNA sequencing libraries during the growth of liver. 689 out of all DE lncRNAs corresponded to 440 DE mRNAs by cis-regulation and all DE mRNAs could be regulated by DE lncRNAs by trans-regulation. GO enrichment analysis showed significant enrichment of 892 GO terms, such as protein binding, cytosol, extracellular exsome, nucleoplasm, and oxidation-reduction process. Besides, 52 KEGG pathways were significantly enriched, including 11 pathways of lipid metabolism were found, like Arachidonic acid metabolism, PPAR signaling pathway and Biosynthesis of unsaturated fatty acids. After the low expression DE mRNAs and lncRNAs were excluded, we further obtained the 54 mRNAs were regulated by 249 lncRNAs. 351 interaction pairs were produced among 38 mRNAs and 215 lncRNAs through the co-expression analysis. The PPI network analysis found that 10 mRNAs such as 3β-Hydroxysteroid-Δ24 Reductase (DHCR24), lathosterol 5-desaturase (SC5D), and acetyl-CoA synthetase 2 (ACSS2) were highly interconnected hub protein-coding genes. Except for MSTRG.43041.1, the expression levels of the 11 genes by RT-qPCR were the similar trends to the RNA-seq results.ConclusionThe study revealed lncRNA-mRNA interation networks that regulate lipid metabolism during liver growth, providing potential research targets for the prophylaxis and treatment of related diseases caused by liver lipid metabolism disorders.

LncRNA-mRNA modules involved in goat rumen development: Insights from genome-wide transcriptome profiling.

The rumen is an essential digestive and absorption organ of ruminants. During fetal life, lactation, and post-weaning period, goat rumen undergoes drastic morphological and metabolic-functional changes triggered by potential regulated genes and non-coding RNA molecules. As the essential regulatory factors, long non-coding RNAs (lncRNAs) have vital functions in various biological activities. However, their roles during rumen development are still poorly explored in ruminants. To explore the genome-wide expression profiles of lncRNAs and mRNAs in the goat rumens, we generated 5,007 lncRNAs and 19,738 mRNAs identified during the fetal and prepubertal stages by the high-throughput RNA sequencing. Notably, 365 lncRNAs and 2,877 mRNAs were considered to be differentially expressed. The weighted gene co-expression network analysis and functional analysis were performed to explore the regulatory roles of those differentially expressed molecules. The cis-and trans-target genes of differently expressed lncRNAs were enriched for pathways related to focal adhesion, cGMP-PKG signaling pathway, alpha-linolenic acid metabolism, arachidonic acid metabolism, and fat digestion and absorption. Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes analyses showed that the differently expressed genes mainly participated in mitotic cytokinesis, desmosome, fatty acid degradation, cell adhesion molecules, and fatty acid metabolism. The prediction of lncRNA-mRNA interaction networks further revealed transcripts potentially involved in rumen development. The present study profiles a global overview of lncRNAs and mRNAs during rumen development. Our findings provide valuable resources for genetic regulation and molecular mechanisms of rumen development in ruminants.

Transcriptome identification and characterization of long non-coding RNAs in the ovary of hens at four stages

Long non-coding RNAs (lncRNAs) play important roles in transcriptional and post-transcriptional regulation. LncRNAs, which are defined as non-coding RNAs more than 200 bp in length, are involved in key biological processes, such as cell proliferation and differentiation, epigenetic regulation, and gene transcriptional translation. Recent studies have shown that lncRNAs also play major regulatory roles in the reproduction of mammals. However, knowledge of the roles of lncRNAs in the chicken ovary lacking. In this study, we performed RNA-seq analyses of ovarian tissue from Hy-Line brown laying hens at four physiological stages [15, 20, 30, and 68 weeks of age (W)]. We identified 657 lncRNA transcripts that were differentially expressed during ovarian development, the number of down-regulated lncRNAs was higher than the number of up-regulated lncRNAs during development. We predicted the cis and trans target genes of the DE lncRNAs and constructed a lncRNA-mRNA interaction network, which indicated that the DE genes (DEGs) and the target genes of the DE lncRNAs are mainly involved in signaling pathways associated with ovarian development, including oocyte meiosis, calcium signaling pathways, ECM-receptor interactions, and ribosome and focal adhesion. Overall, we found that twelve lncRNAs were strongly involved in ovarian development: LNC_013443, LNC_001029, LNC_005713, LNC_016762, ENSGALT00000101857, LNC_003913, LNC_013692, LNC_012219, LNC_004140, ENSGALT00000096941, LNC_009356, and ENSGALT00000098716. In summary, our study utilized RNA-seq analysis of hen ovaries to explore key lncRNAs involved in ovarian development and function. Furthermore, the comprehensive analysis identified the target genes of these lncRNAs providing a better understanding of the mechanisms underlying ovarian development in hens and a theoretical basis for further research.

Testing lncRNAs signature as clinical stage-related prognostic markers in gastric cancer progression using TCGA database.

LncRNA expression can be conducive to gastric cancer (GC) prognosis. The objective of this study is to ascertain five specific lncRNAs involved in tumor progression of GC and their role as prognostic markers to diagnose clinical stage-wise GC. High-throughput RNA sequencing data were obtained from The Cancer Genome Atlas (TCGA) database and performed genome-wide lncRNA expression analysis using edgeR package, Bioconductor.org, and R-statistical computing to analyze differentially expressed lncRNA analysis. Cutoff parameters were FDR < 0.05 and |Log2FC| > 2. Total 351 tumor samples with differentially expressed lncRNAs were divided into group-1 lncRNAs such as AC019117.2 and LINC00941, and group-2 lncRNAs such as LINC02410, AC012317.2, and AC141273.1 by 2:1. The Spearman correlation coefficients (p < 0.05) and correlation test function (cor.test ()) were performed for lncRNAs as per clinical stage. Cytoscape software was used to construct lncRNA-mRNA interaction networks. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway (p < 0.05) analysis were conducted using the clusterProfiler package. Kaplan-Meier survival analysis was performed to determine the overall survival of patients based on the expression of five lncRNAs in different clinical stages of GC. AC019117.2 and LINC00941 of group 1 inferred a positive correlation with clinical stages of stage I to stage IV, and their expressions were higher in tumor tissues than normal tissues. On the contrary, LINC02410, AC012317.2, and AC141273.1 of group 2 exhibited a negative correlation with clinical stage, and they exhibited more expression in normal tissues compared to tumor tissues. GO and KEGG pathway analysis reported that AC019117.2 may interact with LINC00941 via ITGA3 and trophoblast glycoprotein (TPBG) to foster tumor progression. Tumor-specific group-1 lncRNAs were conducive to the poor overall survival and exhibited a positive correlation with the clinical stages of stage I to stage IV in GC as per the lncRNA-mRNA networking analysis. These five lncRNAs could be considered as clinically useful lncRNA-based prognostic markers to predict clinical stage-wise GC progression.

WAFNRLTG: A Novel Model for Predicting LncRNA Target Genes Based on Weighted Average Fusion Network Representation Learning Method.

Long non-coding RNAs (lncRNAs) do not encode proteins, yet they have been well established to be involved in complex regulatory functions, and lncRNA regulatory dysfunction can lead to a variety of human complex diseases. LncRNAs mostly exert their functions by regulating the expressions of target genes, and accurate prediction of potential lncRNA target genes would be helpful to further understanding the functional annotations of lncRNAs. Considering the limitations in traditional computational methods for predicting lncRNA target genes, a novel model which was named Weighted Average Fusion Network Representation learning for predicting LncRNA Target Genes (WAFNRLTG) was proposed. First, a novel heterogeneous network was constructed by integrating lncRNA sequence similarity network, mRNA sequence similarity network, lncRNA-mRNA interaction network, lncRNA-miRNA interaction network and mRNA-miRNA interaction network. Next, four popular network representation learning methods were utilized to gain the representation vectors of lncRNA and mRNA nodes. Then, the representations of lncRNAs and target genes in the heterogeneous network were obtained with the weighted average fusion network representation learning method. Finally, we merged the representations of lncRNAs and related target genes to form lncRNA-gene pairs, trained the XGBoost classifier and predicted potential lncRNA target genes. In five-cross validations on the training and independent datasets, the experimental results demonstrated that WAFNRLTG obtained better AUC scores (0.9410, 0.9350) and AUPR scores (0.9391, 0.9350). Moreover, case studies of three common lncRNAs were performed for predicting their potential lncRNA target genes and the results confirmed the effectiveness of WAFNRLTG. The source codes and all data of WAFNRLTG can be freely downloaded at https://github.com/HGDYZW/WAFNRLTG.

Identification of lncRNA-mRNA regulatory network associated with isolated systolic hypertension and atherosclerotic cerebral infarction.

BackgroundIncreasingly, evidence has shown that long non-coding RNAs (lncRNAs) play an important role in isolated systolic hypertension (ISH). However, a systematic lncRNA-messenger RNA (mRNA) regulatory network is still absent in isolated systolic hypertension and atherosclerotic cerebral infarction patients (ISH & ACI). This research aimed to establish a lncRNA-mRNA co-expression network in patients with ISH & ACI, to probe into the potential functions of lncRNA in such patients.MethodsExpression profiles of lncRNA and mRNAs were collected and compared, from 8 patients with ISH and 8 patients with ISH & ACI by RNA-seq data. Differentially expressed lncRNAs and mRNAs were screened out via high-throughput sequencing in the plasma of ISH/ACI patients and control ISH patients. Then, a lncRNA-mRNA interaction network was built using the Pearson correlation coefficient by Cytoscape software. The expression levels of the hub genes and lncRNAs were verified by quantitative reverse transcription-polymerase chain reaction (qRT-PCR) in another 10 ISH/ACI patients and 10 control patients. This study was approved by the responsible institutional review board (IRB) and informed consent was provided by participants.ResultsA total of 2,768 differentially expressed lncRNAs and 747 differentially expressed mRNAs were identified. We identified two hub genes (CD226 and PARVB) and 11 lncRNAs in the lncRNA-mRNA interaction network. The results of qRT-PCR and cell assay verified that lncRNAs ENST00000590604 and CD226 are highly expressed in patients of ISH & ACI. Further, CD226 was associated with vascular endothelial cells growth and stability through the platelet activation and focal adhesion pathway.ConclusionsWe established a novel mRNA-lncRNA interaction network. The lncRNAs ENST00000590604 and CD226 might be the potential biomarkers of ISH & ACI.

Transcriptome Analysis Revealed Potential Mechanisms of Resistance to Trichomoniasis gallinae Infection in Pigeon (Columba livia).

Trichomoniasis gallinae (T. gallinae) is one of the most pathogenic parasites in pigeon, particularly in squabs. Oral cavity is the main site for the host-parasite interaction. Herein, we used RNA-sequencing technology to characterize lncRNA and mRNA profiles and compared transcriptomic dynamics of squabs, including four susceptible birds (S) from infected group, four tolerant birds (T) without parasites after T. gallinae infection, and three birds from uninfected group (N), to understand molecular mechanisms underlying host resistance to this parasite. We identified 29,809 putative lncRNAs and characterized their genomic features subsequently. Differentially expressed (DE) genes, DE-lncRNAs and cis/trans target genes of DE-lncRNAs were further compared among the three groups. The KEGG analysis indicated that specific intergroup DEGs were involved in carbon metabolism (S vs. T), metabolic pathways (N vs. T) and focal adhesion pathway (N vs. S), respectively. Whereas, the cis/trans genes of DE-lncRNAs were enriched in cytokine-cytokine receptor interaction, toll-like receptor signaling pathway, p53 signaling pathway and insulin signaling pathway, which play crucial roles in immune system of the host animal. This suggests T. gallinae invasion in pigeon mouth may modulate lncRNAs expression and their target genes. Moreover, co-expression analysis identified crucial lncRNA-mRNA interaction networks. Several DE-lncRNAs including MSTRG.82272.3, MSTRG.114849.42, MSTRG.39405.36, MSTRG.3338.5, and MSTRG.105872.2 targeted methylation and immune-related genes, such as JCHAIN, IL18BP, ANGPT1, TMRT10C, SAMD9L, and SOCS3. This implied that DE-lncRNAs exert critical influence on T. gallinae infections. The quantitative exploration of host transcriptome changes induced by T. gallinae infection broaden both transcriptomic and epigenetic insights into T. gallinae resistance and its pathological mechanism.

Bioinformatics analysis for the identification of key genes and long non-coding RNAs related to bone metastasis in breast cancer.

The molecular mechanism of bone metastasis in breast cancer is largely unknown. Herein, we aimed to identify the key genes and long non-coding RNAs (lncRNAs) related to the bone metastasis of breast cancer using a bioinformatics approach. We screened differentially expressed genes and lncRNAs between normal breast and breast cancer bone metastasis samples using the GSE66206 dataset from the Gene Expression Omnibus. We also constructed a differentially expressed lncRNA-mRNA interaction network and analyzed the node degrees to identify the driving genes. After finding potential pathogenic modules of breast cancer bone metastasis, we identified breast cancer bone metastasis-related modules and functional enrichment analysis of the genes and lncRNAs in the modules. Based on the above analysis, we constructed a differentially expressed lncRNA-mRNA network related to bone metastasis in breast cancer and identified core driver genes, including BNIP3 and the lncRNA RP11-317-J19.1. The role of core driver genes and lncRNAs in the network implies their biological functions in regulating bone development and remodeling. Thus, targeting the core driver genes and lncRNAs in the network may be a promising therapeutic strategy to manage bone metastasis.

Differential lncRNA expression profiling of cognitive function in middle and old aged monozygotic twins using generalized association analysis

Cognitive impairment is the most prominent symptom in neurodegenerative disorders affecting quality of life and mortality. However, despite years of research, the molecular mechanism underlying the regulation of cognitive function and its impairment is poorly understood. This study aims to elucidate the role of long non-coding RNAs (lncRNAs) expression and lncRNA-mRNA interaction networks, by analyzing lncRNA expression in whole blood samples of 400 middle and old aged monozygotic twins in association with cognitive function using both linear models and a generalized correlation coefficient (GCC) to capture the diverse patterns of correlation. We detected 13 probes (p < 1e-03) displaying nonlinear and 7 probes (p < 1e-03) showing linear correlations. After combining the results, we identified 20 lncRNA probes with p < 1e-03. The top lncRNA probes were annotated to genes, along with the non-coding MALAT1, that play roles in neurodegenerative diseases. The top lncRNAs were linked to functional clusters including peptidyl-glycine modification, vascular smooth muscle cells, mitotic spindle organization and protein tyrosine phosphatase. In addition, mapping of the top significant lncRNAs to the lncRNA-mRNA interaction network detected significantly enriched biological pathways involving neuroactive ligand-receptor interaction, proteasome and chemokines. We show that GCC served as a complementary approach in detecting lncRNAs missed by the conventional linear models. A combination of GCC and linear models identified lncRNAs of diverse patterns of association enriched for GO biological and molecular functions meaningful in cognitive performance and cognitive decline. The novel lncRNA regulatory network further contributed to detect significant pathways implicated in cognition.

Intersectional analysis of chronic mild stress-induced lncRNA-mRNA interaction networks in rat hippocampus reveals potential anti-depression/anxiety drug targets

Despite studies providing insight into the neurobiology of chronic stress, depression and anxiety, long noncoding RNA (lncRNA)-mediated mechanisms underlying the common and distinct pathophysiology of these stress-induced disorders remain nonconclusive. In a previous study, we used the chronic mild stress paradigm to separate depression-susceptible, anxiety-susceptible and insusceptible rat subpopulations. In the current study, lncRNA and messenger RNA (mRNA) expression was comparatively profiled in the hippocampus of the three stress groups using microarray technology. Groupwise comparisons identified distinct sets of lncRNAs and mRNAs associated with the three different behavioral phenotypes of the stressed rats. To investigate the regulatory roles of the dysregulated lncRNAs upon mRNA expression, correlations between the differential lncRNAs and mRNAs were first analyzed by combined use of weighted gene coexpression network analysis and ceRNA theory-based methods. Subsequent functional analysis of strongly correlated mRNAs indicated that the dysregulated lncRNAs were involved in various biological pathways and processes to specifically induce rat susceptibility or resiliency to depression or anxiety. Further intersectional analysis of phenotype-associated and drug-associated lncRNA-mRNA networks and subnetworks assisted in identifying 16 hub lncRNAs as potential targets of anti-depression/anxiety drugs. Collectively, our study established the molecular basis for understanding the similarities and differences in pathophysiological mechanisms underlying stress-induced depression or anxiety and stress resiliency, revealing several important lncRNAs that represent potentially new therapeutic drug targets for depression and anxiety disorders.

Integrated analysis of long noncoding RNAs and mRNA expression profiles reveals the potential role of lncRNAs in early stage of post-peripheral nerve injury in Sprague-Dawley rats.

The regulatory role of lncRNAs in the early stage post peripheral nerve injury (PNI) is not yet clear. In this study, next-generation sequencing was used to perform deep sequencing on normal sciatic nerves (control) and lesional tissues derived on the 4th (D4) and 7th days (D7) after sciatic nerve injury in rats. Time-point unique differentially expressed lncRNAs (DElncRNAs) were analyzed for functional enrichment. The results showed that 776 DElncRNAs were unique to D4, and their functions were mainly enriched in wound healing, phosphatase binding and MAPK signaling pathways; 317 DElncRNAs were unique to D7, and their functions were mainly enriched in ion transmembrane transporter channel activity; 579 DElncRNAs were shared by these two days, and their functions were mainly enriched in axongenesis, the PI3K-Akt signaling pathway and cell cycle. Furthermore, lncRNA-mRNA interaction networks were constructed in functions or pathways with a high enrichment rate. Finally, 3 mRNAs and 4 lncRNAs in the axongenesis interaction network were selected, and their expression levels were verified by RT-qPCR. This study preliminarily revealed the regulatory role of lncRNAs at different time points in the early stage post PNI, which provides potential targets for basic research and clinical treatment of PNI.

Using lncRNA Sequencing to Reveal a Putative lncRNA-mRNA Correlation Network and the Potential Role of PCBP1-AS1 in the Pathogenesis of Cervical Cancer.

Background/AimsLong non-coding RNAs (lncRNAs) play important roles in many diseases and participate in posttranscriptional regulatory networks in tumors. However, the functions of major lncRNAs in cervical cancer are unclear. Therefore, the aim of this study was to construct a lncRNA-mRNA coexpression functional network and analyze lncRNAs that might contribute to the pathogenesis of cervical cancer.MethodsDifferentially expressed lncRNAs (DElncRNAs) and mRNAs (DEmRNAs) between three pairs of cervical cancer tissues and adjacent mucosa were identified by lncRNA microarray analysis. LncRNA-mRNA correlation analysis and functional enrichment were performed on the DEGs. From the correlation network, PCBP1-AS1 was selected as a candidate for further analysis. PCBP1-AS1 expression was examined by qPCR, and Kaplan–Meier survival, clinicopathology, GSEA, and immune infiltration analysis of PCBP1-AS1 were performed. The immune responses of PCBP1-AS1 expression in cervical cancer were analyzed using TIMER and western blot. PCBP1-AS1 was knocked down and overexpressed to evaluate its role in cell proliferation, migration, and invasion.ResultsA total of 130 lncRNAs were significantly differentially expressed in cervical cancer patient samples compared with control samples. Differentially expressed mRNAs in the lncRNA-mRNA interaction network were involved in the EMT process. Combined with the Kaplan–Meier survival analyses, the coexpression network revealed that PCBP1-AS1 was significantly associated with OS and clinicopathological parameters in cervical cancer patients. Moreover, PCBP1-AS1 expression was not only significantly increased in cervical cancer specimens but also associated with tumor stage, TNM, and invasion. GSEA revealed that PCBP1-AS1 is closely correlated with cell biological function via the p53 and notch signaling pathways. TIMER analysis revealed that the numbers of NK cells and M2 macrophages decreased when PCBP1-AS1 expression was high, which was consistent with the western blot results in clinical samples. Furthermore, in vitro experiments showed that high expression of PCBP1-AS1 promoted cell proliferation, migration, and invasion.ConclusionsTranscriptomic and lncRNA-mRNA correlation analyses revealed that PCBP1-AS1 plays a key role as an independent prognostic factor in patients with cervical cancer. The identification of PCBP1-AS1 as a new biomarker for cervical cancer could help explain how changes in the immune environment promote cervical cancer development.