scholarly journals Effective Biomarkers and Therapeutic Targets of Nerve-Immunity Interaction in The Treatment of Depression: A Integrated Analysis of miRNA-mRNA Regulatory Networks

2021 ◽  
Author(s):  
Zi-xuan Wu ◽  
Xuyan Huang ◽  
Min-jie Cai ◽  
Peidong Huang ◽  
Zunhui Guan
Keyword(s):  
Regulatory Networks ◽  
Target Genes ◽  
Therapeutic Targets ◽  
Enrichment Analysis ◽  
Integrated Analysis ◽  
Daily Lives ◽  
Gene Expression Matrix ◽  
Treatment Of Depression ◽  
Negative Effect ◽  
Core Genes

Abstract Background: Major depressive disorder (MDD) is an emotional disorder that has a negative effect on patients' studies and daily lives. A great number of studies have found that miRNAs play an important role in the development of MDD and that they can be used as a biomarker for the diagnosis and treatment of MDD. However, there have been few investigations on nerve-immunity interaction therapy for MMD patients' brains.Methods: We attempted to evaluate MDD in the gene expression matrix database and miRNAs in plasma samples from healthy controls using bioinformatics methods. Four plasma miRNAs (DE-miRNAs) samples were found from MDD patients. Funrich planned the transcription factors and target genes of miRNAs, and the enrichment of TF and GO was examined. The intersecting mRNAs were discovered by comparing the various expressions of the projected target genes and 5 mRNAs (DE-mRNAs) samples. In the end, 34 DE-miRNAs, 386 DE-mRNAs, and 17 intersecting mRNAs were detected. Intersecting core genes were then investigated using GO and KEGG enrichment analysis to find the intersecting mRNA. Identify particular candidate genes and pathways in neurology and immunology that may be associated with MDD for further investigation.Results: We discovered 17 important HUB genes by the advance of a miRNA-mRNA network, and 5 HUB DE-MRNAs were derived following CytoNCA topology.Conclusion: Our findings from a comprehensive bioinformatics analysis of miRNAs and mRNAs in MDD show that DE-miRNAs like miR-338-3P and miR-206 may be excellent biomarkers and potential therapeutic targets for the treatment of MDD via nerve-immunity interaction.

scholarly journals Identification of transcription factors and construction of a novel miRNA regulatory network in primary osteoarthritis by integrated analysis

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Ying Jiang ◽  
Yi Shen ◽  
Liyan Ding ◽  
Shengli Xia ◽  
Liying Jiang
Keyword(s):  
Regulatory Networks ◽  
Target Genes ◽  
Therapeutic Targets ◽  
Microarray Dataset ◽  
Integrated Analysis ◽  
Rna Seq ◽  
Hub Genes ◽  
Serum Samples ◽  
Regulatory Pathways ◽  
Novel Mirna

Abstract Backgrounds As osteoarthritis (OA) disease-modifying therapies are not available, novel therapeutic targets need to be discovered and prioritized. Here, we aim to identify miRNA signatures in patients to fully elucidate regulatory mechanism of OA pathogenesis and advance in basic understanding of the genetic etiology of OA. Methods Six participants (3 OA and 3 controls) were recruited and serum samples were assayed through RNA sequencing (RNA-seq). And, RNA-seq dataset was analysed to identify genes, pathways and regulatory networks dysregulated in OA. The overlapped differentially expressed microRNAs (DEMs) were further screened in combination with the microarray dataset GSE143514. The expression levels of candidate miRNAs were further validated by quantitative real-time PCR (qRT-PCR) based on the GEO dataset (GSE114007). Results Serum samples were sequenced interrogating 382 miRNAs. After screening of independent samples and GEO database, the two comparison datasets shared 19 overlapped candidate micRNAs. Of these, 9 up-regulated DEMs and 10 down-regulated DEMs were detected, respectively. There were 236 target genes for up-regulated DEMs and 400 target genes for those down-regulated DEMs. For up-regulated DEMs, the top 10 hub genes were KRAS, NRAS, CDC42, GDNF, SOS1, PIK3R3, GSK3B, IRS2, GNG12, and PRKCA; for down-regulated DEMs, the top 10 hub genes were NR3C1, PPARGC1A, SUMO1, MEF2C, FOXO3, PPP1CB, MAP2K1, RARA, RHOC, CDC23, and CREB3L2. Mir-584-5p-KRAS, mir-183-5p-NRAS, mir-4435-PIK3R3, and mir-4435-SOS1 were identified as four potential regulatory pathways by integrated analysis. Conclusions We have integrated differential expression data to reveal putative genes and detected four potential miRNA-target gene pathways through bioinformatics analysis that represent new mediators of abnormal gene expression and promising therapeutic targets in OA.

scholarly journals Integrated Analysis of lncRNAs, mRNAs, and TFs to Identify Regulatory Networks Underlying MAP Infection in Cattle

2021 ◽  
Vol 12 ◽  
Author(s):  
Maryam Heidari ◽  
Abbas Pakdel ◽  
Mohammad Reza Bakhtiarizadeh ◽  
Fariba Dehghanian
Keyword(s):  
Regulatory Networks ◽  
Molecular Mechanisms ◽  
Enrichment Analysis ◽  
Johne's Disease ◽  
Johne’S Disease ◽  
Functional Enrichment ◽  
Integrated Analysis ◽  
Complex Nature ◽  
Hub Genes ◽  
Cis And Trans

Johne’s disease is a chronic infection of ruminants that burdens dairy herds with a significant economic loss. The pathogenesis of the disease has not been revealed clearly due to its complex nature. In order to achieve deeper biological insights into molecular mechanisms involved in MAP infection resulting in Johne’s disease, a system biology approach was used. As far as is known, this is the first study that considers lncRNAs, TFs, and mRNAs, simultaneously, to construct an integrated gene regulatory network involved in MAP infection. Weighted gene coexpression network analysis (WGCNA) and functional enrichment analysis were conducted to explore coexpression modules from which nonpreserved modules had altered connectivity patterns. After identification of hub and hub-hub genes as well as TFs and lncRNAs in the nonpreserved modules, integrated networks of lncRNA-mRNA-TF were constructed, and cis and trans targets of lncRNAs were identified. Both cis and trans targets of lncRNAs were found in eight nonpreserved modules. Twenty-one of 47 nonpreserved modules showed significant biological processes related to the immune system and MAP infection. Some of the MAP infection’s related pathways in the most important nonpreserved modules comprise “positive regulation of cytokine-mediated signaling pathway,” “negative regulation of leukocyte migration,” “T-cell differentiation,” “neutrophil activation,” and “defense response.” Furthermore, several genes were identified in these modules, including SLC11A1, MAPK8IP1, HMGCR, IFNGR1, CMPK2, CORO1A, IRF1, LDLR, BOLA-DMB, and BOLA-DMA, which are potentially associated with MAP pathogenesis. This study not only enhanced our knowledge of molecular mechanisms behind MAP infection but also highlighted several promising hub and hub-hub genes involved in macrophage-pathogen interaction.

Discussing the Mechanism of Dahuang Huanglian Xiexin Decoction in the Treatment of Type 2 Diabetes Mellitus via Network Pharmacology and Molecular Docking

2021 ◽  
Author(s):  
Xi Cen ◽  
Yan Wang ◽  
LeiLei Zhang ◽  
XiaoXiao Xue ◽  
Yan Wang ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Molecular Docking ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Overlapping Genes ◽  
Potential Mechanism ◽  
Active Components ◽  
The Core ◽  
Core Genes

Abstract BackgroundType 2 diabetes mellitus (T2DM) is regarded as Pi Dan disease in traditional Chinese medicine (TCM). Dahuang Huanglian Xiexin Decoction (DHXD), a classical TCM formula, has been used for treating Pi Dan disease in clinic, its pharmacological mechanism has not been elucidated. MethodsThis study used network pharmacological analysis and molecular docking approach to explore the mechanism of DHXD on T2DM. Firstly, the compounds in DHXD were obtained from TCMSP and TCMID databases, the potential targets were determined based on TCMSP and UniProt databases. Next, Genecards, Digenet and UniProt databases were used to identify the targets of T2DM. Then, the protein-protein interaction (PPI) network was established with overlapping genes of T2DM and compounds, and the core targets in the network were identified and analyzed. Then, the David database was used for GO and KEGG enrichment analysis. Finally, the target genes were selected and the molecular docking was completed by Autodock software to observe the binding level of active components with target genes.ResultsA total of 397 related components and 128 overlapping genes were identified. After enrichment analysis, it was found that HIF-1, TNF, IL-17 and other signaling pathways, as well as DNA transcription, gene expression, apoptosis and other cellular biological processes had the strongest correlation with the treatment of T2DM by DHXD, and most of them occurred in the extracellular space, plasma membrane and other places, which were related to enzyme binding and protein binding. In addition, 42 core genes of DHXD, such as VEGFA, TP53 and MAPK1, were considered as potential therapeutic targets, indicating the potential mechanism of DHXD on T2DM. Finally, the results of molecular docking showed that HIF-1 pathway had strong correlation with the target genes INSR and GLUT4, quercetin and berberine had the strongest binding power with them respectively.ConclusionThis study summarized the main components of DHXD in the treatment of T2DM, identified the core genes and pathways, and systematically analyzed the interaction of related targets, trying to lay the foundation for clarifying the potential mechanism of DHXD on T2DM, so as to carry out further research in the future.

scholarly journals DNA methylome signatures as epigenetic biomarkers of hexanal associated with lung toxicity

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e10779
Author(s):  
Yoon Cho ◽  
Mi-Kyung Song ◽  
Jae-Chun Ryu
Keyword(s):  
Dna Methylation ◽  
Intracellular Signaling ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Environmental Chemicals ◽  
Receptor Interaction ◽  
Integrated Analysis ◽  
Pathway Enrichment Analysis ◽  
Biological Processes ◽  
Epigenetic Biomarkers

Background Numerous studies have investigated the relationship of environmental exposure, epigenetic effects, and human diseases. These linkages may contribute to the potential toxicity mechanisms of environmental chemicals. Here, we investigated the epigenetic pulmonary response of hexanal, a major indoor irritant, following inhalation exposure in F-344 rats. Methods Based on DNA methylation profiling in gene promoter regions, we identified hexanal-characterized methylated sites and target genes using an unpaired t-test with a fold-change cutoff of ≥ 3.0 and a p-value < 0.05. We also conducted an integrated analysis of DNA methylation and mRNA expression data to identify core anti-correlated target genes of hexanal exposure. To further investigate the potential key biological processes and pathways of core DNA methylated target genes, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis were performed. Results Thirty-six dose-dependent methylated genes and anti-correlated target genes of DNA methylation and mRNA in lung tissue of hexanal exposed F-344 rats were identified. These genes were involved in diverse biological processes such as neuroactive ligand-receptor interaction, protein kinase cascade, and intracellular signaling cascade associated with pulmonary toxicity. These results suggest that novel DNA methylation-based epigenetic biomarkers of exposure to hexanal and elucidate the potential pulmonary toxicological mechanisms of action of hexanal.

scholarly journals Genome-wide identification and comparison of differentially expressed profiles of miRNAs and lncRNAs with associated ceRNA networks in the gonads of Chinese soft-shelled turtle, Pelodiscus sinensis

2019 ◽  
Author(s):  
Xiao Ma ◽  
Shuangshuang Cen ◽  
Luming Wang ◽  
Chao Zhang ◽  
Limin Wu ◽  
...  
Keyword(s):  
Messenger Rna ◽  
Regulatory Networks ◽  
Target Genes ◽  
Expression Profiles ◽  
Integrated Analysis ◽  
Regulation Mechanism ◽  
Pelodiscus Sinensis ◽  
Specific Expression ◽  
Protein Coding ◽  
Protein Coding Genes

Abstract Abstract Background: Gonad is the major factor affecting the animal reproduction. The regulation mechanism of protein coding genes expression involved reproduction is still remains to be elucidated. Increasing evidence has shown that ncRNAs play key regulatory roles in gene expression in many life processes. The roles of microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) in reproduction had been investigated in some species. However, the regulation patterns of miRNA and lncRNA in sex biased expression of protein coding genes remains to be elucidated. In this study, we performed an integrated analysis of miRNA, messenger RNA (mRNA), and lncRNA expression profiles to explore their regulatory patterns in the female ovary and male testis of the soft-shelled turtle, Pelodiscus sinensis. Results: We identified 10 796 mature miRNAs, 44 678 mRNAs, and 58 923 lncRNAs in the testis and ovary. A total of 16 817 target genes were identified for miRNAs. Of these, 11 319 mRNAs, 10 495 lncRNAs, and 633 miRNAs were expressed differently. The predicted target genes of these differential expression (DE) miRNAs and lncRNAs included genes related to reproduction regulation. Furthermore, we found that 5 408 DElncRNAs and 186 DE miRNAs showed sex-specific expression. Of these, 3 miRNAs and 917 lncRNAs were testis specific and 186 DEmiRNAs and 4 491 DElncRNAs were ovary specific. We constructed compete endogenous lncRNA-miRNA-mRNA networks using bioinformatics, including 273 DEmRNAs, 5 730 DEmiRNAs, and 2 945 DElncRNAs. The target genes for the different expressed of miRNAs and lncRNAs included Wt1, Creb3l2, Gata4, Wnt2, Nr5a1, Hsd17, Igf2r, H2afz, Lin52, Trim71, Zar1, and Jazf1, etc. Conclusions: In animals, miRNA and lncRNA regulate the reproduction process, including the regulation of oocyte maturation and spermatogenesis. Considering their importance, the identified miRNAs, lncRNAs, and their targets in P. sinensis might be useful for genome editing to produce higher quality aquaculture animals. A thorough understanding of ncRNA-based cellular regulatory networks will aid in the improvement of P. sinensis reproduction traits for aquaculture.

scholarly journals Deciphering The Molecular Pathogenesis Behind Neurological Manifestations of SARS-CoV-2 And Drug Repurposing, A Systems Biology Approach

2021 ◽  
Author(s):  
maryam mozafar ◽  
Seyed Amir Mirmotalebisohi ◽  
Marzieh Sameni ◽  
Zeinab Dehghan ◽  
Yalda Khazaei-Poul ◽  
...  
Keyword(s):  
Systems Biology ◽  
Regulatory Networks ◽  
Target Genes ◽  
Viral Infections ◽  
Drug Repurposing ◽  
Enrichment Analysis ◽  
Neurological Complications ◽  
Functional Enrichment ◽  
Neurological Manifestations ◽  
Ppi Networks

Abstract Introduction: As the COVID-19 pandemic spreads worldwide, reports about the neurological complications of SARS-CoV-2 are excessively increasing. However, there is still insufficient high-throughput data on neuronal cells infected with SARS-CoV-2 to help predict its neural pathogenesis. HCoV-OC43 is another member of the beta coronavirus family that has confirmed neuro-invasive effects and has available neural omics data. This study predicts the critical genes, biological processes, and pathways mediating in SARS-CoV-2 neurological manifestations using a systems biology approach.Method: We retrieved raw data related to SARS-CoV-2 and HCoV-OC43 infections from gene expression omnibus datasets (GSE147507 and GSE13879 respectively). We constructed gene regulatory networks for both infections, detected significant regulatory motifs by FANMOD software, and created their subnetworks. We also constructed PPI networks and identified the MCODE clusters. In the intersection of merged subnetworks of two viruses, the most critical genes were verified in GRN & PPI networks. We drug-repurposed for the selected target genes and performed the functional enrichment analysis using DAVID and String databases.Results: Some of the top KEGG pathway results included NF-kappa B, Toll-like receptor, NOD-like receptor, MAPK, and Neurotrophin signaling pathways. The most essential identified genes included IL6, TNF, HOXA5, POU2F2, ITGB3, STAT1, YY1, E2F6, ESR1, FOXO3, FOXO1, MEF2A, ATF3, ATF4, DDIT3, TCF4, BCL2L2, and BMP4. These genes were also involved in mechanisms of other viral infections of the nervous system. This study repurposes nine medicines with effects on COVID-19 neurological complications. Some of the repurposed drugs were previously registered in clinical trials for COVID-19 treatment.Conclusion: We recommended some identified crucial genes and medications to investigate further their potential role in treating COVID-19 neurological complications.

scholarly journals Integrative analysis of miRNA–mRNA network in idiopathic membranous nephropathy by bioinformatics analysis

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e12271
Author(s):  
Wenfang He ◽  
Jinshi Zhang ◽  
Shizhu Yuan ◽  
Mingzhu Liang ◽  
Weidong Chen ◽  
...  
Keyword(s):  
Membranous Nephropathy ◽  
Regulatory Networks ◽  
Target Genes ◽  
Therapeutic Targets ◽  
Differentially Expressed ◽  
Idiopathic Membranous Nephropathy ◽  
Validation Dataset ◽  
Epidermal Growth ◽  
Specific Antigens

Background Currently, several specific antigens, M-type receptor for secretory phospholipase A2(PLA2R1), thrombospondin type-1 domain-containing 7A(THSD7A), and neural epidermal growth factor-like 1 protein (NELL-1), are discovered associated with the onset of idiopathic membranous nephropathy (IMN). But the pathomechanisms of IMN still need to be further claried. Understanding the mechanisms of IMN is required to improve its diagnosis and treatment. Methods In this study, we constructed miRNA regulatory networks to investigate IMN development. Moreover, miRNAs and mRNAs that were differentially expressed between Idiopathic Membranous Nephropathy (IMN) patients and normal controls were examined using the GSE115857 dataset and our previous sequence study. DE miRNA target genes were determined based on the FUNRICH software, starBase, miRDB, and miRWalk, and an miRNA-mRNA network was designed using DE-mRNAs that were negatively correlated with DE-miRNAs. The miRNA-mRNA network contained 228 miRNA-mRNA pairs. Thereafter, we conducted KEGG pathway, GO functional annotation, immune-related gene screening, protein interaction networks, and potential hub gene analyses. Furthermore, 10 miRNAs and 10 genes were determined and preliminarily validated using the validation dataset from GEO. Finally, we identified which pair may offer more accurate diagnosis and therapeutic targets for IMN. Results Two miRNA-mRNA pairs, miR-155-5p-FOS and miR-146a-5p-BTG2, were differentially expressed in IMN, indicating that these genes may affect IMN through immune processes. These findings may offer more accurate diagnoses and therapeutic targets for IMN.

scholarly journals Screening of Osteoarthritis-Related Genes and Function Determination Based on Bioinformatics Tools

2021 ◽  
Author(s):  
Zheng Fu ◽  
Weiqian Jiang ◽  
Wenlong Yan ◽  
Fei Xie ◽  
Yu Chen ◽  
...  
Keyword(s):  
Regulatory Networks ◽  
Bioinformatics Analysis ◽  
Kegg Pathway ◽  
Experimental Studies ◽  
Therapeutic Targets ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Ppi Network ◽  
Pathway Enrichment ◽  
Early Diagnostic

Abstract Background:Osteoarthritis(OA), commonly seen in the middle-aged and elderly population, imposes a heavy burden on patients from the clinical, humanistic and economic aspects. Our work aims at the discovery of early diagnostic and therapeutic targets for OA and new candidate biomarkers for experimental studies on OA via bioinformatics analysis.Methods:The dataset GSE114007 was downloaded from GEO to identify differentially expressed genes(DEGs) in R using 3 different algorithms. Overlapping DEGs were subject to GO and KEGG pathway enrichment analysis and functional annotation. Following the identification of DEGs, a protein-protein interaction(PPI) network was established and imported into Cytoscape to screen for hubgenes. The expression of each hubgene was verified in two other datasets and create miRNA-mRNA regulatory networks.Results:174 upregulated genes and 117 downregulated genes were identified among the overlapping DEGs. According to the results of GO enrichment analysis,MF enrichment was basically found in ECM degradation and collagen breakdown; enrichment was also present in the development, ossification, and differentiation of cells. The KEGG pathway enrichment analysis suggested significant enrichment in such pathways as PI3K-AKT, P53, TNF, and FoxO. 23 hubgenes were obtained from the PPI network, and 11 genes were identified as DEGs through verification. 8 genes were used for the establishment of miRNA-mRNA regulatory networks.Conclusion:OA-related genes, proteins, pathways and miRNAs that were identified through bioinformatics analysis may provide a reference for the discovery of early diagnostic and therapeutic targets for OA, as well as candidate biomarkers for experimental studies on OA.

scholarly journals Integrated Analysis of Microarray and RNA-Seq Data for the Identification of Hub Genes and Networks Involved in the Pancreatic Cancer

2021 ◽  
Vol 12 ◽  
Author(s):  
Maryum Nisar ◽  
Rehan Zafar Paracha ◽  
Iqra Arshad ◽  
Sidra Adil ◽  
Sabaoon Zeb ◽  
...  
Keyword(s):  
Gene Expression ◽  
Pancreatic Cancer ◽  
Early Stage ◽  
Therapeutic Targets ◽  
Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Receptor Interaction ◽  
Integrated Analysis ◽  
Rna Seq ◽  
Hub Genes

Pancreatic cancer (PaCa) is the seventh most fatal malignancy, with more than 90% mortality rate within the first year of diagnosis. Its treatment can be improved the identification of specific therapeutic targets and their relevant pathways. Therefore, the objective of this study is to identify cancer specific biomarkers, therapeutic targets, and their associated pathways involved in the PaCa progression. RNA-seq and microarray datasets were obtained from public repositories such as the European Bioinformatics Institute (EBI) and Gene Expression Omnibus (GEO) databases. Differential gene expression (DE) analysis of data was performed to identify significant differentially expressed genes (DEGs) in PaCa cells in comparison to the normal cells. Gene co-expression network analysis was performed to identify the modules co-expressed genes, which are strongly associated with PaCa and as well as the identification of hub genes in the modules. The key underlaying pathways were obtained from the enrichment analysis of hub genes and studied in the context of PaCa progression. The significant pathways, hub genes, and their expression profile were validated against The Cancer Genome Atlas (TCGA) data, and key biomarkers and therapeutic targets with hub genes were determined. Important hub genes identified included ITGA1, ITGA2, ITGB1, ITGB3, MET, LAMB1, VEGFA, PTK2, and TGFβ1. Enrichment analysis characterizes the involvement of hub genes in multiple pathways. Important ones that are determined are ECM–receptor interaction and focal adhesion pathways. The interaction of overexpressed surface proteins of these pathways with extracellular molecules initiates multiple signaling cascades including stress fiber and lamellipodia formation, PI3K-Akt, MAPK, JAK/STAT, and Wnt signaling pathways. Identified biomarkers may have a strong influence on the PaCa early stage development and progression. Further, analysis of these pathways and hub genes can help in the identification of putative therapeutic targets and development of effective therapies for PaCa.

scholarly journals Integrated Analysis of lncRNA and mRNA Reveals Novel Insights into Wool Bending in Zhongwei Goat

Animals ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. 3326
Author(s):  
Xiaobo Li ◽  
Zhanfa Liu ◽  
Shaohui Ye ◽  
Yue Liu ◽  
Qian Chen ◽  
...  
Keyword(s):  
Signaling Pathway ◽  
Target Genes ◽  
Economic Value ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Hair Follicles ◽  
Functional Enrichment ◽  
Integrated Analysis ◽  
Rna Seq ◽  
Camp Signaling Pathway

Chinese Zhongwei goat is a rare and precious fur breed as its lamb fur is a well-known fur product. Wool bending of lamb fur of the Zhongwei goat is its most striking feature. However, the curvature of the wool decreases gradually with growth, which significantly affects its quality and economic value. The mechanism regulating the phenotypic changes of hair bending is still unclear. In the present study, the skin tissues of Zhongwei goats at 45 days (curving wool) and 108 days (slight-curving wool) after birth were taken as the research objects, and the expression profiling of long non-coding RNAs (lncRNAs) and mRNAs were analyzed based on the Ribo Zero RNA sequencing (RNA-seq) method. In total, 46,013 mRNAs and 13,549 lncRNAs were identified, of which 352 were differentially expressed mRNAs and 60 were. lncRNAs. Functional enrichment analysis of the target genes of lncRNAs were mainly enriched in PI3K-Akt, Arachidonic acid metabolic, cAMP, Wnt, and other signaling pathways. The qRT-PCR results of eight selected lncRNAs and target genes were consistent with the sequencing result, which indicated our data were reliable. Through the analysis of the weighted gene co-expression network, 13 co-expression modules were identified. The turquoise module contained a large number of differential expressed lncRNAs, which were mainly enriched in the PI3K-Akt signaling pathway and cAMP signaling pathway. The predicted LOC102172600 and LOC102191729 might affect the development of hair follicles and the curvature of wool by regulating the target genes. Our study provides novel insights into the potential roles of lncRNAs in the regulation of wool bending. In addition, the study offers a theoretical basis for further study of goat wool growth, so as to be a guidance and reference for breeding and improvement in the future.

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