Circular RNAs, mRNAs and lncRNAs associated with castration-related fat deposition
Ontology highlight
ABSTRACT:
ORGANISM(S): Sus scrofa
PROVIDER: GSE87680 | GEO | 2019/10/04
REPOSITORIES: GEO
Similar Datasets
Project description:We firstly compared the expression file of circRNAs, mRNAs and lncRNAs in backfat between the castrated and intact Huainan male pigs to identify the key circRNAs, mRNAs and lncRNAs involved in the genetic basis of castration associated fat deposition.
2019-10-08 | GSE87846 | GEO
Project description:We firstly compared the expression file of circRNAs in longissimus muscle (LM) between the Chinese indigenous Huainan (HN, the fat type line ) and the Western commercial Duroc×(Landrace×Yorkshire) (DLY, the thin type line) to identify the key circRNAs involved in the genetic basis of pork quality traits.
2019-03-27 | GSE86919 | GEO
Project description:To understand the role of message RNA (mRNAs, lncRNAs and circRNAs) in regulation of intramuscular fat deposition, the expression profiles of longissimus dorsi muscle from six Laiwu pigs were sequenced based on rRNA-depleted library construction. We then performed gene expression profiling analysis using data obtained from RNA-seq.
2022-08-31 | GSE207279 | GEO
Project description:Background: Intramuscular fat (IMF) content is highly valued as it improves meat product quality by enhancing taste, juiciness, and tenderness. IMF content can be significantly different between breeds. Thought many lipid metabolism-related genes are stated to be associated with IMF deposition, the molecular mechanism of IMF deposition is still poorly understood. To date, no gene or mutation loci responsible for the difference of IMF content among cattle breeds has been identified. To identify transcripts with potential regulatory role in lipid accumulated in muscle tissue, RNA sequencing was performed to compare the mRNAs, lncRNAs, and circRNAs expression patterns in the longissimus dorsi muscle and back fat between Chinese buffalo and cattle. Results: A total of 12 cDNA libraries were constructed. A total of 925,441,106 and 512,507,068 raw reads were obtained from buffalo and cattle, respectively. After filtering the adaptor and low quality reads, 909,040,352 and 491,967,820 clean reads were retained. In total, 19,917 mRNAs, 43,975 lncRNAs, and 10,701 circRNAs were identified in buffalo and 19,383 mRNAs, 8,265 lncRNAs, and 18,535 circRNAs were identified in cattle.
2020-10-20 | GSE139102 | GEO
Project description:Background: Background: In bovines, the development and growth of adipose involves many physiological processes and plays an extremely important role in the quality of beef, however, the regulatory mechanisms underlying the differences in meat quality are largely unknown. Therefore, a buffalo adipose transcriptome analysis was performed to compare gene expression profiles between different growth stages. Results: Finally, a total of 21,693 mRNAs were obtained, of which 2506 were significantly differentially expressed mRNAs in the two groups, 9494 lncRNAs, a total of 281 lncRNAs and 2506 mRNAs showed significant differential expression patterns and 14990 between the two buffaloes CircRNA, 252 circRNAs were significantly differentially expressed between young and adult buffalo.
2019-08-21 | GSE112744 | GEO
Project description:Background: Cryptosporidium baileyi is the most common Cryptosporidium species in birds. However, effective prevention measures and treatment for C. baileyi infection were less understood. Long non-coding RNA (lncRNA) and circular RNA (circRNA) were discovered to play an important role in regulating occurrence and progression of many diseases and identified as effective biomarkers for diagnosis and prognosis of several diseases. In the present study, the expression profiles of mRNA, lncRNA and circRNA associated with C. baileyi infection were investigated for the first time. Results: The tracheal tissues of experimental (C. baileyi infection) and control chickens were collected for deep RNA sequencing, and 545,479,934 clean reads were obtained. Of them, 1376 novel lncRNAs were identified, including 1161 long intergenic non-coding RNAs (lincRNAs) and 215 anti-sense lncRNAs. 124 lncRNAs were found to be significantly differentially expressed between experimental and control groups. Additionally, 14,698 mRNAs and 9085 circRNAs were identified, and significantly different expressions were observed for 1317 mRNAs and 104 circRNAs between two groups. The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of their targets and background genes suggested that these dysregulated genes would be involved in the interaction between host and C. baileyi. Conclusions: The present study firstly provides the expression profiles of mRNAs, lncRNAs and circRNAs during C. baileyi infection, and describes a novel perspective on the potential roles of lncRNAs and circRNAs underlying the pathogenesis mechanism of Cryptosporidium infection.
2018-04-28 | GSE108147 | GEO
Project description:F. nucleatum is an opportunistic pathogen that usually colonize in oral cavity, thereby closely associated with the development of periodontitis.However, the immune regulation mechanism of F. nucleatum to macrophage’s function in disease progress has not been clearly elucidated.Long non-coding RNA (lncRNA) and circular RNA (circRNA) were discovered to play an important role in regulating occurrence and progression of many diseases and identified as effective biomarkers for diagnosis and prognosis of several diseases. In the present study, the expression profiles of mRNA, lncRNA and circRNA associated with F. nucleatum infection were investigated for the first time. The results revealed that the expressions of 375 mRNAs, 64 lncRNAs, and 180 circRNAs were altered during F. nucleatum infection. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) biological pathway analysis showed that the target genes were mainly involved in the MAPK signaling pathway, Toll-like receptor signaling pathway, NF-kappa B signaling pathway and apoptosis. Conclusions: The present study firstly provides the expression profiles of mRNAs, lncRNAs and circRNAs during F. nucleatum infection, and describes a novel perspective on the potential roles of lncRNAs and circRNAs underlying the pathogenesis mechanism of F. nucleatum infection.
2021-12-13 | GSE190606 | GEO
Project description:To identify the mRNAs, long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs) involved in the pathogenesis of breast cancer, we performed the whole transcriptome sequencing. The whole transcriptome sequencing was performed with three breast cancer tissues with or without lymph node metastasis in each group, respectively. The results showed that 728 mRNAs, 131 lncRNAs, and 144 circRNAs were differentially expressed in lymph node metastasis group and no lymph node metastasis group (fold change≥2, p<0.05). These data indicate that dysregulation of mRNAs, lncRNAs, and circRNAs may contribute to breast cancer progression.
2021-12-31 | GSE163346 | GEO
Project description:The location of nasophryngeal cancer is hidden,so ti is difficult to diagnose at an early stage.In this study,we aimed to investigate expression profiles of circRNAs,mRNAs and IncRNAs and to provide some basis for further study.The expression profiles of circRNAs, mRNAs and lncRNAs were analyzed by microarray technology. The differentially expressed ncRNA was calculated by bioinformatics. Our study characterized the landscape of circRNAs, mRNAs and lncRNAs in NPC tissue and provided novel insights into the molecular mechanisms of NPC.
2023-12-01 | GSE218847 | GEO
Project description:LncRNA expression profiling for liver tissues of mice fed for NFD, LSF and HSF groups Summary: An abstract of the experiment and the data analysis. Experiment Workflow: A workflow of the experiment and the data analysis. Project Description: Sample and experiment information. Array Information: Mouse 8 x 60K LncRNA expression array information. Summary Table of Files for Data Delivery: Contains summary table of files for data delivery and the recommended software programs for viewing the data. Data Analysis for LncRNAs 1. Raw LncRNA data normalization and low intensity filtering: Raw signal intensities were normalized in quantile method by GeneSpring GX v11.5.1, and low intensity LncRNAs were filtered (LncRNAs that at least 6 out of 9 samples have flags in Present or Marginal were chosen for further analysis, these LncRNAs can be found from the LncRNA Expression Profiling Data.xls file). 2. Quality assessment of LncRNA data after filtering: Contains Box Plot and Scatter Plot for LncRNAs after filtering (This data can be found from the LncRNA Expression Profiling Data.xls file). 3. Differentially expressed LncRNAs screening: Contains differentially expressed genes with statistical significance that passed Volcano Plot filtering (Fold Change >= 2.0, P-value <= 0.05) (This data can be found from the Differentially Expressed LncRNAs.xls file). 4. Heat Map and Hierarchical Clustering: Hierarchical Clustering of Differentially Expressed LncRNAs (The heat map can be found from the LncRNA Expression Profiling Data.xls file). Data Analysis for mRNAs 1. Raw mRNA data normalization and low intensity filtering: Raw signal intensities were normalized in quantile method by GeneSpring GX v11.5.1, and low intensity mRNAs were filtered (mRNAs that at least 6 out of 9 samples have flags in Present or Marginal were chosen for further analysis, these mRNAs can be found from the mRNA Expression Profiling Data.xls file). 2. Quality assessment of mRNA data after filtering: Contains Box Plot and Scatter Plot for mRNAs after filtering (This data can be found from the mRNA Expression Profiling Data.xls file). 3. Differentially expressed mRNAs screening: Contains differentially expressed genes with statistical significance that passed Volcano Plot filtering (Fold Change >= 2.0, P-value <= 0.05) (This data can be found from the Differentially Expressed mRNAs.xls file). 4. Heat Map and Hierarchical Clustering: Hierarchical Clustering of Differentially Expressed mRNAs (The heat map can be found from the mRNA Expression Profiling Data.xls file). 5. Pathway analysis: Pathway analysis of the differentially expressed mRNAs. 6. GO analysis: GO term analysis of the differentially expressed mRNAs. LncRNA Classification and Subgroup Analysis 1. Rinn lincRNAs profiling: Contains profiling data of all lincRNAs based on John Rinn's papers (This data can be found from the Rinn lincRNAs profiling.xls file). 2. LincRNAs nearby coding gene data table: Contains the differentially expressed lincRNAs and nearby coding gene pairs (distance < 300 kb) (This data can be found from the LincRNAs nearby coding gene data table.xls file). Sample RNA Quality Control: Sample quality control data file from NanoDrop ND-1000 spectrophotometer and standard denaturing agarose gel electrophoresis. Methods: A brief introduction of methods for sample preparation, microarray design, experiment, and data analysis.
2022-11-24 | E-MTAB-9167 | biostudies-arrayexpress