Identification of mRNAs and lncRNAs Involved in the Regulation of Follicle Development in Goat

Follicular development and maturation has a significant impact on goat reproductive performance, and it is therefore important to understand the molecular basis of this process. The importance of long non-coding RNAs (lncRNAs) in mammalian reproduction has been established, but little is known about the roles of lncRNAs in different follicular stages, especially in goats. In this study, RNA sequencing (RNA-seq) of large follicles (>10 mm) and small follicles (<3 mm) of Chuanzhong black goats was performed to investigate the regulatory mechanisms of lncRNAs and mRNAs in follicular development and maturation. A total of 8 differentially expressed lncRNAs (DElncRNAs) and 1,799 DEmRNAs were identified, and the majority of these were upregulated in small follicles. MRO, TC2N, CDO1, and NTRK1 were potentially associated with follicular maturation. KEGG pathway analysis showed that the DEmRNAs involved in ovarian steroidogenesis (BMP6, CYP11A1, CYP19A1, 3BHSD, STAR, LHCGR, and CYP51A1) and cAMP signaling play roles in regulating follicular maturation and developmental inhibition respectively. Five target pairs of DElncRNA-DEmRNA, namely, ENSCHIT00000001255-OTX2, ENSCHIT00000006005-PEG3, ENSCHIT00000009455-PIWIL3, ENSCHIT00000007977-POMP, and ENSCHIT00000000834-ACTR3 in co-expression analysis provide a clue in follicular development and maturation of lncRNA-mRNA interaction. Our findings provide a valuable resource for lncRNA studies, and could potentially provide a deeper understanding of the genetic basis and molecular mechanisms of goat follicular development and maturation.

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Transcriptome Analysis of Bovine Ovarian Follicles at Predeviation and Onset of Deviation Stages of a Follicular Wave

International Journal of Genomics ◽

10.1155/2016/3472748 ◽

2016 ◽

Vol 2016 ◽

pp. 1-9 ◽

Cited By ~ 3

Author(s):

Pengfei Li ◽

Jinzhu Meng ◽

Wenzhong Liu ◽

George W. Smith ◽

Jianbo Yao ◽

...

Keyword(s):

Pathway Analysis ◽

Kegg Pathway ◽

Steroid Hormone ◽

Follicular Development ◽

Regulatory Mechanisms ◽

Biosynthesis Pathway ◽

Follicular Wave ◽

Kegg Pathway Analysis ◽

Hormone Biosynthesis ◽

Upregulated Genes

For two libraries (PDF1 and ODF1) using Illumina sequencing 44,082,301 and 43,708,132 clean reads were obtained, respectively. After being mapped to the bovine RefSeq database, 15,533 genes were identified to be expressed in both types of follicles (cut-off RPKM > 0.5), of which 719 were highly expressed in bovine follicles (cut-off RPKM > 100). Furthermore, 83 genes were identified as being differentially expressed in ODF1 versus PDF1, where 42 genes were upregulated and 41 genes were downregulated. KEGG pathway analysis revealed two upregulated genes in ODF1 versus PDF1, CYP11A1, and CYP19A1, which are important genes in the steroid hormone biosynthesis pathway. This study represents the first investigation of transcriptome of bovine follicles at predeviation and onset of deviation stages and provides a foundation for future investigation of the regulatory mechanisms involved in follicular development in cattle.

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LncTarD: a manually-curated database of experimentally-supported functional lncRNA–target regulations in human diseases

Nucleic Acids Research ◽

10.1093/nar/gkz985 ◽

2019 ◽

Cited By ~ 4

Author(s):

Hongying Zhao ◽

Jian Shi ◽

Yunpeng Zhang ◽

Aimin Xie ◽

Lei Yu ◽

...

Keyword(s):

Molecular Mechanisms ◽

Sequence Data ◽

Human Diseases ◽

Regulatory Mechanisms ◽

Biological Functions ◽

Functional Dynamics ◽

Disease Associations ◽

Non Coding Rnas ◽

User Friendly ◽

Pan Cancer

Abstract Long non-coding RNAs (lncRNAs) are associated with human diseases. Although lncRNA–disease associations have received significant attention, no online repository is available to collect lncRNA-mediated regulatory mechanisms, key downstream targets, and important biological functions driven by disease-related lncRNAs in human diseases. We thus developed LncTarD (http://biocc.hrbmu.edu.cn/LncTarD/ or http://bio-bigdata.hrbmu.edu.cn/LncTarD), a manually-curated database that provides a comprehensive resource of key lncRNA–target regulations, lncRNA-influenced functions, and lncRNA-mediated regulatory mechanisms in human diseases. LncTarD offers (i) 2822 key lncRNA–target regulations involving 475 lncRNAs and 1039 targets associated with 177 human diseases; (ii) 1613 experimentally-supported functional regulations and 1209 expression associations in human diseases; (iii) important biological functions driven by disease-related lncRNAs in human diseases; (iv) lncRNA–target regulations responsible for drug resistance or sensitivity in human diseases and (v) lncRNA microarray, lncRNA sequence data and transcriptome data of an 11 373 pan-cancer patient cohort from TCGA to help characterize the functional dynamics of these lncRNA–target regulations. LncTarD also provides a user-friendly interface to conveniently browse, search, and download data. LncTarD will be a useful resource platform for the further understanding of functions and molecular mechanisms of lncRNA deregulation in human disease, which will help to identify novel and sensitive biomarkers and therapeutic targets.

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Transcriptomic Analysis of mRNA-lncRNA-miRNA Interactions in Hepatocellular Carcinoma

Scientific Reports ◽

10.1038/s41598-019-52559-x ◽

2019 ◽

Vol 9 (1) ◽

Cited By ~ 14

Author(s):

Xia Tang ◽

Delong Feng ◽

Min Li ◽

Jinxue Zhou ◽

Xiaoyuan Li ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Molecular Mechanisms ◽

Expression Profiles ◽

Rna Seq ◽

Pairwise Interactions ◽

Micro Rnas ◽

Non Coding Rnas ◽

First Time

Abstract Fully elucidating the molecular mechanisms of non-coding RNAs (ncRNAs), including micro RNAs (miRNAs) and long non-coding RNAs (lncRNAs), underlying hepatocarcinogenesis is challenging. We characterized the expression profiles of ncRNAs and constructed a regulatory mRNA-lncRNA-miRNA (MLMI) network based on transcriptome sequencing (RNA-seq) of hepatocellular carcinoma (HCC, n = 9) patients. Of the identified miRNAs (n = 203) and lncRNAs (n = 1,090), we found 16 significantly differentially expressed (DE) miRNAs and three DE lncRNAs. The DE RNAs were highly enriched in 21 functional pathways implicated in HCC (p < 0.05), including p53, MAPK, and NAFLD signaling. Potential pairwise interactions between DE ncRNAs and mRNAs were fully characterized using in silico prediction and experimentally-validated evidence. We for the first time constructed a MLMI network of reciprocal interactions for 16 miRNAs, three lncRNAs, and 253 mRNAs in HCC. The predominant role of MEG3 in the MLMI network was validated by its overexpression in vitro that the expression levels of a proportion of MEG3-targeted miRNAs and mRNAs was changed significantly. Our results suggested that the comprehensive MLMI network synergistically modulated carcinogenesis, and the crosstalk of the network provides a new avenue to accurately describe the molecular mechanisms of hepatocarcinogenesis.

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Identification of key candidate genes and biological pathways in bladder cancer

PeerJ ◽

10.7717/peerj.6036 ◽

2018 ◽

Vol 6 ◽

pp. e6036 ◽

Cited By ~ 22

Author(s):

Xin Gao ◽

Yinyi Chen ◽

Mei Chen ◽

Shunlan Wang ◽

Xiaohong Wen ◽

...

Keyword(s):

Bladder Cancer ◽

Pathway Analysis ◽

Molecular Mechanisms ◽

Kegg Pathway ◽

Aurora Kinase ◽

Smooth Muscle Contraction ◽

Ppi Network ◽

Tissue Samples ◽

Kegg Pathway Analysis ◽

Key Genes

Background Bladder cancer is a malignant tumor in the urinary system with high mortality and recurrence rates. However, the causes and recurrence mechanism of bladder cancer are not fully understood. In this study, we used integrated bioinformatics to screen for key genes associated with the development of bladder cancer and reveal their potential molecular mechanisms. Methods The GSE7476, GSE13507, GSE37815 and GSE65635 expression profiles were downloaded from the Gene Expression Omnibus database, and these datasets contain 304 tissue samples, including 81 normal bladder tissue samples and 223 bladder cancer samples. The RobustRankAggreg (RRA) method was utilized to integrate and analyze the four datasets to obtain integrated differentially expressed genes (DEGs), and the gene ontology (GO) functional annotation and Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis were performed. Protein-protein interaction (PPI) network and module analyses were performed using Cytoscape software. The OncoLnc online tool was utilized to analyze the relationship between the expression of hub genes and the prognosis of bladder cancer. Results In total, 343 DEGs, including 111 upregulated and 232 downregulated genes, were identified from the four datasets. GO analysis showed that the upregulated genes were mainly involved in mitotic nuclear division, the spindle and protein binding. The downregulated genes were mainly involved in cell adhesion, extracellular exosomes and calcium ion binding. The top five enriched pathways obtained in the KEGG pathway analysis were focal adhesion (FA), PI3K-Akt signaling pathway, proteoglycans in cancer, extracellular matrix (ECM)-receptor interaction and vascular smooth muscle contraction. The top 10 hub genes identified from the PPI network were vascular endothelial growth factor A (VEGFA), TOP2A, CCNB1, Cell division cycle 20 (CDC20), aurora kinase B, ACTA2, Aurora kinase A, UBE2C, CEP55 and CCNB2. Survival analysis revealed that the expression levels of ACTA2, CCNB1, CDC20 and VEGFA were related to the prognosis of patients with bladder cancer. In addition, a KEGG pathway analysis of the top 2 modules identified from the PPI network revealed that Module 1 mainly involved the cell cycle and oocyte meiosis, while the analysis in Module 2 mainly involved the complement and coagulation cascades, vascular smooth muscle contraction and FA. Conclusions This study identified key genes and pathways in bladder cancer, which will improve our understanding of the molecular mechanisms underlying the development and progression of bladder cancer. These key genes might be potential therapeutic targets and biomarkers for the treatment of bladder cancer.

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Comprehensive Analysis of mRNAs and miRNAs in the Ovarian Follicles of Uniparous and Multiple Goats at Estrus Phase

10.21203/rs.2.15819/v1 ◽

2019 ◽

Author(s):

Xian Zou ◽

Tingting Lu ◽

Zhifeng Zhao ◽

Guangbin Liu ◽

Zhiquan Lian ◽

...

Keyword(s):

Molecular Mechanisms ◽

Steroid Hormone ◽

Follicular Development ◽

Interaction Network ◽

Ovarian Follicles ◽

Rna Seq ◽

Steroid Hormone Biosynthesis ◽

Hormone Biosynthesis ◽

Meat Goat ◽

Estrus Phase

Abstract Background Fertility is an important economic trait in production of meat goat, and follicular development plays an important role in fertility. Despite many mRNAs and microRNAs (miRNAs) have been found in playing critical roles in ovarian biological processes, the interactions between mRNAs and miRNAs in follicular development is not yet completely understood. In addition, less attention has been given to the single follicle (dominant or atretic follicle) in goat. The study was aimed to identify mRNAs, miRNAs and signaling pathways as well as their interaction networks in the ovarian follicles (large follicles and small follicles) of multiple and uniparous goats (Chuanzhong Black Goats) at estrus phase by using a deep RNA-sequencing (RNA-seq) method.Results The result showed that there were more large follicles in multiple than in uniparous goats ( P <0.05), while no difference was observed in small follicles between them ( P >0.05). For the small follicles of multiple and uniparous goats at estrus phase, 289 differentially expressed mRNAs (DEmRNAs) and 16 DEmiRNAs were identified; and for the large follicles, 195 DEmRNAs and 7 DEmiRNAs were identified. Ovarian steroidogenesis and steroid hormone biosynthesis were significantly enriched in small follicles, while ABC transporters and steroid hormone biosynthesis in large follicles. The results of qRT-PCR were generally consistent with the RNA-seq data. The mRNA-miRNA interaction network showed that CD36 (miR-122, miR-200a, miR-141), TNFAIP6 (miR-141, miR-200a, miR-182), CYP11A1 (miR-122), SERPINA5 (miR-1, miR-206, miR-133a-3p, miR-133b) and PTGFR (miR-182, miR-122) might be related to fertility, but need further verification.Conclusion This study provides the first identification of the DEmRNAs and DEmiRNAs as well as their interactions in the follicles of multiple and uniparous goats at estrus phase by using RNA-seq technology. These analyses provide new clues to uncover molecular mechanisms and signaling networks of goat reproduction which could be potentially used to increase ovulation rate and kidding rate in goat.

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Identification and characterization of circRNAs in the skin during the wool follicle development of Aohan fine wool sheep

10.21203/rs.2.15954/v1 ◽

2019 ◽

Author(s):

Ranran Zhao ◽

Nan Liu ◽

Fuhui Han ◽

Hegang Li ◽

Jifeng Liu ◽

...

Keyword(s):

Molecular Mechanisms ◽

Circular Rnas ◽

Follicle Development ◽

Rna Seq ◽

Ampk Signaling ◽

Wool Follicle ◽

Solid Foundation ◽

Sheep Shoulder ◽

Competitive Endogenous Rna

Abstract Background Aohan fine wool sheep (AFWS) is an early fine wool variety breed cultivated in China. The wool has excellent quality and good textile performance. Investigating the molecular mechanisms that regulate wool growth is important for improving wool quality and yield. Circular RNAs (circRNAs) are non-coding RNAs which are widely expressed and can act as a competitive endogenous RNA (ceRNA) to bind to miRNA. Although circRNA has been studied in many fields, research in sheep wool follicles is limited. To understand the regulation of circRNA in the growth of fine wool sheep, we used RNA-seq to identify circRNAs in sheep shoulder skin at three stages, embryonic day 90 (E90d), embryonic day 120 (E120d), and Birth.Results We identified 8,753circRNAs and found that 1,351 were differentially expressed. We also analyzed the classification and characteristic of the circRNAs in sheep shoulder skin. GO and KEGG were used for source genes of circRNAs, and these were mainly enriched in cellular component organization, regulation of primary metabolic process, tight junctions, and the cGMP-PKG and AMPK signaling pathways. In addition, we predicted interactions between 17 circRNAs and 8 miRNAs using miRanda ( http://www.microrna.org/microrna/home.do ). Based on the significant pathways, we speculate the circ-0005720, circ-0001754, circ-0008036, circ-0004032, circ-0005174, circ-0005519, circ-0007826 may play an important role in regulating wool follicle growth in AFWS. 5 circRNAs were randomly selected to validate the results of the RNA-seq by qRT-PCR.Conclusion Our results provide more information about circRNAs in regulating wool follicle development in AFWS and provide a solid foundation for future experiments.

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Identification of a Novel Gene Correlated With Vascular Smooth Muscle Cells Proliferation and Migration in Chronic Thromboembolic Pulmonary Hypertension

Frontiers in Physiology ◽

10.3389/fphys.2021.744219 ◽

2021 ◽

Vol 12 ◽

Author(s):

Feng Wang ◽

Congrui Sun ◽

Xiaoshuo Lv ◽

Mingsheng Sun ◽

Chaozeng Si ◽

...

Keyword(s):

Vascular Remodeling ◽

Molecular Mechanisms ◽

Kegg Pathway ◽

Chronic Thromboembolic Pulmonary Hypertension ◽

Vsmc Proliferation ◽

Kegg Pathway Analysis ◽

Tnf Α ◽

Thromboembolic Pulmonary Hypertension ◽

And Migration ◽

Proliferation And Migration

Objective: Chronic thromboembolic pulmonary hypertension (CTEPH) is characterized by thrombofibrotic obstruction of the proximal pulmonary arteries, which result in vascular remodeling of the distal pulmonary artery. While the cellular and molecular mechanisms underlying CTEPH pathogenesis remain incompletely understood, recent evidence implicates vascular remodeling. Here, we identify the molecular mechanisms that contribute to vascular remodeling in CTEPH.Methods: Microarray data (GSE130391) for patients with CTEPH and healthy controls were downloaded from the Gene Expression Omnibus (GEO) and screened for differentially expressed genes (DEGs). DEGs were functionally annotated using Gene Ontology (GO) functional analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. A protein–protein interaction (PPI) network was constructed to identify hub genes. Finally, pulmonary artery samples were harvested from patients with CTEPH (n = 10) and from controls (n = 10) and primary vascular smooth muscle cells (VSMCs) were cultured. Effects of the proto-oncogene FOS on VSMC proliferation and migration were assessed using expression and knockdown studies.Results: We detected a total of 292 DEGs, including 151 upregulated and 141 downregulated genes. GO analysis revealed enrichment of DEGs in biological processes of signal transduction, response to lipopolysaccharide, signal transduction, and myeloid dendritic cell differentiation. Molecular function analysis revealed enrichment in tumor necrosis factor (TNF)-activated receptor activity, transcriptional activator activity, and protein homodimerization activity. The expression of TNF-α and its receptor (sTNFR1 and sTNFR2) were significantly higher in CTEPH group, compared with control group. KEGG pathway analysis revealed enrichment in salmonella infection, pathways in cancer, osteoclast differentiation, and cytokine-cytokine receptor interaction. Hub genes in the PPI included FOS, suggesting an important role for this gene in vascular remodeling in CTEPH. Primary VSMCs derived from patients with CTEPH showed increased FOS expression and high proliferation and migration, which was attenuated by FOS inhibition. In control VSMCs, TNF-α treatment increased proliferation and migration, which FOS inhibition likewise attenuated.Conclusion: TNF-α drives CTEPH pathogenesis by promoting VSMC proliferation and migration via increased FOS expression. These results advance our understanding of the molecular mechanisms of vascular remodeling in CTEPH, and may inform the development of new therapeutic targets.

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Mapping eQTLs With RNA-Seq Reveals Novel SLE Susceptibility Genes, Non-Coding RNAs, and Alternative-Splicing Events That Are Concealed Using Microarrays

10.1101/076026 ◽

2016 ◽

Author(s):

Christopher A. Odhams ◽

Andrea Cortini ◽

Lingyan Chen ◽

Amy L. Roberts ◽

Ana Vinuela ◽

...

Keyword(s):

Gene Expression ◽

Lupus Erythematosus ◽

Molecular Mechanisms ◽

Complex Disease ◽

Splice Junction ◽

Susceptibility Genes ◽

Eqtl Analysis ◽

Rna Seq ◽

Control Of Gene Expression ◽

Non Coding Rnas

AbstractStudies attempting to functionally interpret complex-disease susceptibility loci by GWAS and eQTL integration have predominantly employed microarrays to quantify gene-expression. RNA-Seq has the potential to discover a more comprehensive set of eQTLs and illuminate the underlying molecular consequence. We examine the functional outcome of 39 variants associated with Systemic Lupus Erythematosus (SLE) through integration of GWAS and eQTL data from the TwinsUK microarray and RNA-Seq cohort in lymphoblastoid cell lines. We use conditional analysis and a Bayesian colocalisation method to provide evidence of a shared causal-variant, then compare the ability of each quantification type to detect disease relevant eQTLs and eGenes. We discovered a greater frequency of candidate-causal eQTLs using RNA-Seq, and identified novel SLE susceptibility genes that were concealed using microarrays (e.g. NADSYN1, SKP1, and TCF7). Many of these eQTLs were found to influence the expression of several genes, suggesting risk haplotypes may harbour multiple functional effects. We pinpointed eQTLs modulating expression of four non-coding RNAs; three of which were replicated in whole-blood. Novel SLE associated splicing events were identified in the T-reg restricted transcription factor, IKZF2, the autophagy-related gene WDFY4, and the redox coenzyme NADSYN1, through asQTL mapping using the Geuvadis cohort. We have significantly increased our understanding of the genetic control of gene-expression in SLE by maximising the leverage of RNA-Seq and performing integrative GWAS-eQTL analysis against gene, exon, and splice-junction quantifications. In doing so, we have identified novel SLE candidate genes and specific molecular mechanisms that will serve as the basis for targeted follow-up studies.

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Unraveling proteome changes and potential regulatory proteins of bovine follicular Granulosa cells by mass spectrometry and multi-omics analysis

Proteome Science ◽

10.1186/s12953-019-0152-1 ◽

2019 ◽

Vol 17 (1) ◽

Cited By ~ 1

Author(s):

Shuning Hou ◽

Qingling Hao ◽

Zhiwei Zhu ◽

Dongmei Xu ◽

Wenzhong Liu ◽

...

Keyword(s):

Mass Spectrometry ◽

Data Analysis ◽

Pathway Analysis ◽

Kegg Pathway ◽

Follicular Development ◽

Regulatory Proteins ◽

Differentially Expressed ◽

Omics Data ◽

Kegg Pathway Analysis ◽

Omics Data Analysis

Abstract Background In previous study, we performed next-gene sequencing to investigate the differentially expressed transcripts of bovine follicular granulosa cells (GCs) at dominant follicle (DF) and subordinate follicle (SF) stages during first follicular wave. Present study is designed to further identify the key regulatory proteins and signaling pathways associated with follicular development using label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS) and multi-omics data analysis approach. Methods DF and SF from three cattle were collected by daily ultrasonography. The GCs were isolated from each follicle, total proteins were digested by trypsin, and then proteomic analyzed via LC-MS/MS, respectively. Proteins identified were retrieved from Uniprot-COW fasta database, and differentially expressed proteins were used to functional enrichment and KEGG pathway analysis. Proteome data and transcriptome data obtained from previous studies were integrated. Results Total 3409 proteins were identified from 30,321 peptides (FDR ≤0.01) obtained from LC-MS/MS analysis and 259 of them were found to be differentially expressed at different stage of follicular development (fold Change > 2, P < 0.05). KEGG pathway analysis of proteome data revealed important signaling pathways associated with follicular development, multi-omics data analysis results showed 13 proteins were identified as being differentially expressed in DF versus SF. Conclusions This study represents the first investigation of transcriptome and proteome of bovine follicles and offers essential information for future investigation of DF and SF in cattle. It also will enrich the theory of animal follicular development.

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Lnc2Cancer 3.0: an updated resource for experimentally supported lncRNA/circRNA cancer associations and web tools based on RNA-seq and scRNA-seq data

Nucleic Acids Research ◽

10.1093/nar/gkaa1006 ◽

2020 ◽

Vol 49 (D1) ◽

pp. D1251-D1258

Author(s):

Yue Gao ◽

Shipeng Shang ◽

Shuang Guo ◽

Xin Li ◽

Hanxiao Zhou ◽

...

Keyword(s):

Genetic Variants ◽

Regulatory Mechanisms ◽

Circular Rnas ◽

Rna Seq ◽

Biological Functions ◽

Cancer Subtypes ◽

Web Tools ◽

Online Tools ◽

Non Coding Rnas ◽

Mesenchymal Transformation

Abstract An updated Lnc2Cancer 3.0 (http://www.bio-bigdata.net/lnc2cancer or http://bio-bigdata.hrbmu.edu.cn/lnc2cancer) database, which includes comprehensive data on experimentally supported long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs) associated with human cancers. In addition, web tools for analyzing lncRNA expression by high-throughput RNA sequencing (RNA-seq) and single-cell RNA-seq (scRNA-seq) are described. Lnc2Cancer 3.0 was updated with several new features, including (i) Increased cancer-associated lncRNA entries over the previous version. The current release includes 9254 lncRNA-cancer associations, with 2659 lncRNAs and 216 cancer subtypes. (ii) Newly adding 1049 experimentally supported circRNA-cancer associations, with 743 circRNAs and 70 cancer subtypes. (iii) Experimentally supported regulatory mechanisms of cancer-related lncRNAs and circRNAs, involving microRNAs, transcription factors (TF), genetic variants, methylation and enhancers were included. (iv) Appending experimentally supported biological functions of cancer-related lncRNAs and circRNAs including cell growth, apoptosis, autophagy, epithelial mesenchymal transformation (EMT), immunity and coding ability. (v) Experimentally supported clinical relevance of cancer-related lncRNAs and circRNAs in metastasis, recurrence, circulation, drug resistance, and prognosis was included. Additionally, two flexible online tools, including RNA-seq and scRNA-seq web tools, were developed to enable fast and customizable analysis and visualization of lncRNAs in cancers. Lnc2Cancer 3.0 is a valuable resource for elucidating the associations between lncRNA, circRNA and cancer.

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