scholarly journals Integrated Analysis of lncRNA, miRNA and mRNA Reveals Novel Insights into the Fertility Regulation of Large White Sows

2019 ◽  
Author(s):  
Huiyan Hu ◽  
Qing Jia ◽  
Jianzhong Xi ◽  
Bo Zhou ◽  
Zhiqiang Li
Keyword(s):  
Molecular Mechanisms ◽  
Ovarian Tissue ◽  
Length Distribution ◽  
Differentially Expressed ◽  
Integrated Analysis ◽  
Rna Seq ◽  
Large White ◽  
Reproductive Process ◽  
Mrna Targets ◽  
Micro Rnas

Abstract Background: Improving sow fertility is extremely important as it can lead to increased reproductive efficiency and thus profitability for swine producers. There are considerable differences in fertility rates among individual animals, but the underlying molecular mechanisms remain unclear. In this study, by using different types of RNA libraries, we investigated the complete transcriptome of ovarian tissue during the luteal (L) and follicular phases (F) of the estrous cycle in Large White pigs with high (H) and low fecundity (L), and performed a comprehensive analysis of long noncoding RNAs (lncRNAs), mRNAs and micro RNAs (miRNAs) from 16 samples by combining RNA sequencing (RNA-seq) with bioinformatics. Results: In total, 24,447 lncRNAs, 27,370 mRNAs, and 216 known miRNAs were identified in ovarian tissues. The genomic features of lncRNAs, such as length distribution and number of exons, were further analyzed. We selected a threshold of P < 0.05 and |log2 (fold change)| ≥ 1to obtain the differentially expressed lncRNAs, miRNAs and mRNAs by pairwise comparison (LH vs. LL, FH vs. FL). Bioinformatics analysis of these differentially expressed RNAs revealed multiple significantly enriched pathways (P < 0.05) that were closely involved in the reproductive process, such as ovarian steroidogenesis, lysosome, steroid biosynthesis, and the estrogen and GnRH signaling pathways. Moreover, bioinformatics screening of differentially expressed miRNAs that share common miRNA response elements (MREs) with lncRNAs and their downstream mRNA targets were performed. Finally, we constructed lncRNA–miRNA–mRNA regulation networks. The key genes in these networks were verified by Reverse Transcription Real-time Quantitative PCR (RT-qRCR), which were consistent with the results from RNA-Seq data.Conclusions: These results provide further insights into the fertility of pigs and can contribute to further experimental investigation of the functions of these genes.

scholarly journals Integrated analysis of lncRNA, miRNA and mRNA reveals novel insights into the fertility regulation of large white sows

BMC Genomics ◽  
2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Huiyan Hu ◽  
Qing Jia ◽  
Jianzhong Xi ◽  
Bo Zhou ◽  
Zhiqiang Li
Keyword(s):  
Molecular Mechanisms ◽  
Ovarian Tissue ◽  
Length Distribution ◽  
Differentially Expressed ◽  
Integrated Analysis ◽  
Rna Seq ◽  
Large White ◽  
Reproductive Process ◽  
Mrna Targets ◽  
Micro Rnas

Abstract Background Improving sow fertility is extremely important as it can lead to increased reproductive efficiency and thus profitability for swine producers. There are considerable differences in fertility rates among individual animals, but the underlying molecular mechanisms remain unclear. In this study, by using different types of RNA libraries, we investigated the complete transcriptome of ovarian tissue during the luteal (L) and follicular (F) phases of the estrous cycle in Large White pigs with high (H) and low (L) fecundity, and performed a comprehensive analysis of long noncoding RNAs (lncRNAs), mRNAs and micro RNAs (miRNAs) from 16 samples by combining RNA sequencing (RNA-seq) with bioinformatics. Results In total, 24,447 lncRNAs, 27,370 mRNAs, and 216 known miRNAs were identified in ovarian tissues. The genomic features of lncRNAs, such as length distribution and number of exons, were further analyzed. We selected a threshold of P < 0.05 and |log2 (fold change)| ≥ 1 to obtain the differentially expressed lncRNAs, miRNAs and mRNAs by pairwise comparison (LH vs. LL, FH vs. FL). Bioinformatics analysis of these differentially expressed RNAs revealed multiple significantly enriched pathways (P < 0.05) that were closely involved in the reproductive process, such as ovarian steroidogenesis, lysosome, steroid biosynthesis, and the estrogen and GnRH signaling pathways. Moreover, bioinformatics screening of differentially expressed miRNAs that share common miRNA response elements (MREs) with lncRNAs and their downstream mRNA targets were performed. Finally, we constructed lncRNA–miRNA–mRNA regulation networks. The key genes in these networks were verified by Reverse Transcription Real-time Quantitative PCR (RT-qRCR), which were consistent with the results from RNA-Seq data. Conclusions These results provide further insights into the fertility of pigs andcan contribute to further experimental investigation of the functions of these genes.

scholarly journals Integrated Analysis of lncRNA, miRNA and mRNA Reveals Novel Insights into the Fertility Regulation of Large White Sows

2020 ◽  
Author(s):  
Huiyan Hu ◽  
Qing Jia ◽  
Jianzhong Xi ◽  
Bo Zhou ◽  
Zhiqiang Li
Keyword(s):  
Molecular Mechanisms ◽  
Ovarian Tissue ◽  
Length Distribution ◽  
Differentially Expressed ◽  
Integrated Analysis ◽  
Rna Seq ◽  
Large White ◽  
Reproductive Process ◽  
Mrna Targets ◽  
Micro Rnas

Abstract Background: Improving sow fertility is extremely important as it can lead to increased reproductive efficiency and thus profitability for swine producers. There are considerable differences in fertility rates among individual animals, but the underlying molecular mechanisms remain unclear. In this study, by using different types of RNA libraries, we investigated the complete transcriptome of ovarian tissue during the luteal (L) and follicular (F) phases of the estrous cycle in Large White pigs with high (H) and low (L) fecundity, and performed a comprehensive analysis of long noncoding RNAs (lncRNAs), mRNAs and micro RNAs (miRNAs) from 16 samples by combining RNA sequencing (RNA-seq) with bioinformatics.Results: In total, 24,447 lncRNAs, 27,370 mRNAs, and 216 known miRNAs were identified in ovarian tissues. The genomic features of lncRNAs, such as length distribution and number of exons, were further analyzed. We selected a threshold of P <0.05 and |log2 (fold change)| ≥ 1 to obtain the differentially expressed lncRNAs, miRNAs and mRNAs by pairwise comparison (LH vs. LL, FH vs. FL). Bioinformatics analysis of these differentially expressed RNAs revealed multiple significantly enriched pathways (P <0.05) that were closely involved in the reproductive process, such as ovarian steroidogenesis, lysosome, steroid biosynthesis, and the estrogen and GnRH signaling pathways. Moreover, bioinformatics screening of differentially expressed miRNAs that share common miRNA response elements (MREs) with lncRNAs and their downstream mRNA targets were performed. Finally, we constructed lncRNA–miRNA–mRNA regulation networks. The key genes in these networks were verified by Reverse Transcription Real-time Quantitative PCR (RT-qRCR), which were consistent with the results from RNA-Seq data.Conclusions: These results provide further insights into the fertility of pigs andcan contribute to further experimental investigation of the functions of these genes.

scholarly journals Integrated Analysis of lncRNA, miRNA and mRNA Reveals Novel Insights into the Fertility Regulation of Large White Sows

2020 ◽  
Author(s):  
Huiyan Hu ◽  
Qing Jia ◽  
Jianzhong Xi ◽  
Bo Zhou ◽  
Zhiqiang Li
Keyword(s):  
Molecular Mechanisms ◽  
Ovarian Tissue ◽  
Length Distribution ◽  
Differentially Expressed ◽  
Integrated Analysis ◽  
Rna Seq ◽  
Large White ◽  
Reproductive Process ◽  
Mrna Targets ◽  
Micro Rnas

Abstract Background: Improving sow fertility is extremely important as it can lead to increased reproductive efficiency and thus profitability for swine producers. There are considerable differences in fertility rates among individual animals, but the underlying molecular mechanisms remain unclear. In this study, by using different types of RNA libraries, we investigated the complete transcriptome of ovarian tissue during the luteal (L) and follicular (F) phases of the estrous cycle in Large White pigs with high (H) and low (L) fecundity, and performed a comprehensive analysis of long noncoding RNAs (lncRNAs), mRNAs and micro RNAs (miRNAs) from 16 samples by combining RNA sequencing (RNA-seq) with bioinformatics.Results: In total, 24,447 lncRNAs, 27,370 mRNAs, and 216 known miRNAs were identified in ovarian tissues. The genomic features of lncRNAs, such as length distribution and number of exons, were further analyzed. We selected a threshold of P <0.05 and |log2 (fold change)| ≥ 1 to obtain the differentially expressed lncRNAs, miRNAs and mRNAs by pairwise comparison (LH vs. LL, FH vs. FL). Bioinformatics analysis of these differentially expressed RNAs revealed multiple significantly enriched pathways (P <0.05) that were closely involved in the reproductive process, such as ovarian steroidogenesis, lysosome, steroid biosynthesis, and the estrogen and GnRH signaling pathways. Moreover, bioinformatics screening of differentially expressed miRNAs that share common miRNA response elements (MREs) with lncRNAs and their downstream mRNA targets were performed. Finally, we constructed lncRNA–miRNA–mRNA regulation networks. The key genes in these networks were verified by Reverse Transcription Real-time Quantitative PCR (RT-qRCR), which were consistent with the results from RNA-Seq data.Conclusions: These results provide further insights into the fertility of pigs andcan contribute to further experimental investigation of the functions of these genes.

scholarly journals Integrated Analysis of lncRNA, miRNA and mRNA Reveals Novel Insights into the Fertility Regulation of Large White Sows

2020 ◽  
Author(s):  
Huiyan Hu ◽  
Qing Jia ◽  
Jianzhong Xi ◽  
Bo Zhou ◽  
Zhiqiang Li
Keyword(s):  
Molecular Mechanisms ◽  
Ovarian Tissue ◽  
Length Distribution ◽  
Differentially Expressed ◽  
Integrated Analysis ◽  
Rna Seq ◽  
Large White ◽  
Reproductive Process ◽  
Mrna Targets ◽  
Micro Rnas

Abstract Background: Improving sow fertility is extremely important as it can lead to increased reproductive efficiency and thus profitability for swine producers. There are considerable differences in fertility rates among individual animals, but the underlying molecular mechanisms remain unclear. In this study, by using different types of RNA libraries, we investigated the complete transcriptome of ovarian tissue during the luteal (L) and follicular (F) phases of the estrous cycle in Large White pigs withhigh (H) and low (L) fecundity, and performed a comprehensive analysis of long noncoding RNAs (lncRNAs), mRNAs and micro RNAs (miRNAs) from 16 samples by combining RNA sequencing (RNA-seq) with bioinformatics.Results: In total, 24,447 lncRNAs, 27,370 mRNAs, and 216 known miRNAs were identified in ovarian tissues. The genomic features of lncRNAs, such as length distribution and number of exons, were further analyzed. We selected a threshold of P<0.05 and |log2 (fold change)| ≥ 1 to obtain the differentially expressed lncRNAs, miRNAs and mRNAs by pairwise comparison (LH vs. LL, FH vs. FL).Bioinformatics analysis of these differentially expressed RNAs revealed multiple significantly enriched pathways (P< 0.05) that were closely involved in the reproductive process, such as ovarian steroidogenesis, lysosome, steroid biosynthesis, and the estrogen and GnRH signaling pathways. Moreover, bioinformatics screening of differentially expressed miRNAs that share common miRNA response elements (MREs) with lncRNAs and their downstream mRNA targets were performed. Finally, we constructed lncRNA–miRNA–mRNA regulation networks. The key genes in these networks were verified by Reverse Transcription Real-time Quantitative PCR (RT-qRCR), which were consistent with the results from RNA-Seq data.Conclusions: These results provide further insights into the fertility of pigs andcan contribute to further experimental investigation of the functions of these genes.

scholarly journals Comprehensive Analysis of Transcriptome and Metabolome Reveals the Flavonoid Metabolic Pathway Is Associated with Fruit Peel Coloration of Melon

Molecules ◽  
2021 ◽  
Vol 26 (9) ◽  
pp. 2830
Author(s):  
Aiai Zhang ◽  
Jing Zheng ◽  
Xuemiao Chen ◽  
Xueyin Shi ◽  
Huaisong Wang ◽  
...  
Keyword(s):  
Molecular Mechanisms ◽  
Comprehensive Analysis ◽  
Differentially Expressed ◽  
Integrated Analysis ◽  
Fruit Peel ◽  
External Quality ◽  
Color Formation ◽  
Peel Color ◽  
Dark Green

The peel color is an important external quality of melon fruit. To explore the mechanisms of melon peel color formation, we performed an integrated analysis of transcriptome and metabolome with three different fruit peel samples (grey-green ‘W’, dark-green ‘B’, and yellow ‘H’). A total of 40 differentially expressed flavonoids were identified. Integrated transcriptomic and metabolomic analyses revealed that flavonoid biosynthesis was associated with the fruit peel coloration of melon. Twelve differentially expressed genes regulated flavonoids synthesis. Among them, nine (two 4CL, F3H, three F3′H, IFS, FNS, and FLS) up-regulated genes were involved in the accumulation of flavones, flavanones, flavonols, and isoflavones, and three (2 ANS and UFGT) down-regulated genes were involved in the accumulation of anthocyanins. This study laid a foundation to understand the molecular mechanisms of melon peel coloration by exploring valuable genes and metabolites.

scholarly journals Comparative analysis of gene expression profiles in differentiated subcutaneous adipocytes between Jiaxing Black and Large White Pigs

2020 ◽  
Author(s):  
Dawei Zhang ◽  
Wenjing Wu ◽  
Xin Huang ◽  
Ke Xu ◽  
Cheng Zheng ◽  
...  
Keyword(s):  
Signaling Pathway ◽  
Expression Profiles ◽  
Mapk Signaling ◽  
Fat Deposition ◽  
Mapk Signaling Pathway ◽  
Differentially Expressed ◽  
Rna Seq ◽  
Domestic Pig ◽  
Large White ◽  
Pig Breeds

Abstract Background: Chinese domestic pig breeds are reputed for pork quality, but their low ratio of lean-to-fat carcass weight decreases production efficiency. A better understanding of the genetic regulation network of SC fat tissue is necessary for the rational selection of Chinese domestic pig breeds. In the present study, SC adipocytes were isolated from Jiaxing Black pigs (a Chinese indigenous pig breed with redundant SC fat deposition) and Large White pigs (a lean-type pig breed with relatively low SC fat deposition) and the expression profiles of mRNAs and lncRNAs were compared by RNA-seq analysis to identify biomarkers correlated with the differences of SC fat deposition between the two breeds.Results: A total of 3,371 differentially expressed genes (DEGs) and 1,182 differentially expressed lncRNAs (DELs) were identified in SC adipocytes between Jiaxing Black (JX) and Large White (LW) pigs, which included 797 upregulated mRNAs, 2,574 downregulated mRNAs, 461 upregulated lncRNAs and 721 downregulated lncRNAs. Gene Ontology and KEGG pathway analyses revealed that the DEGs and DELs were mainly involved in the immune response, cell fate determination, PI3K-Akt signaling pathway and MAPK signaling pathway, which are known to be related to adipogenesis and lipid metabolism. The expression levels of DEGs and DELs according to the RNA-seq data were verified by quantitative PCR, which showed 81.8% consistency. The differences in MAPK pathway activity between JX and LW pigs was confirmed by western blot analysis, with <100-fold elevated p38 phosphorylation in JX pigs.Conclusions: This study offers a detailed characterization of mRNAs and lncRNAs in fat- and lean-type pig breeds. The activity of the MAPK signaling pathway was found to be associated with subcutaneous adipogenesis. These results greatly enhance our understanding of the molecular mechanisms regulating SC fat deposition in pigs.

136. PROGESTERONE RECEPTOR-REGULATED GENES IN THE PREOVULATORY OVARIAN FOLLICLE AND OVIDUCT

2010 ◽  
Vol 22 (9) ◽  
pp. 54 ◽  
Author(s):  
L. Akison ◽  
D. Russell ◽  
R. Robker
Keyword(s):  
Progesterone Receptor ◽  
Molecular Mechanisms ◽  
Ovarian Follicle ◽  
Normal Growth ◽  
Cellular Adhesion ◽  
Differentially Expressed ◽  
Reproductive Process ◽  
Molecular Control ◽  
Cancer Migration ◽  
Preovulatory Follicles

Ovulation is a highly regulated and precisely timed reproductive process but the underlying molecular mechanisms are not well understood. Progesterone receptor (PGR) is a transcription factor highly yet transiently expressed in granulosa cells (GCs) of preovulatory follicles; has low expression in cumulus-oocyte-complexes (COCs); and is abundantly expressed in the oviduct. PR–/– mice validate its essential role in ovulation as they are anovulatory, despite normal growth and development of ovarian follicles and oocytes. Our aim was to use microarray to identify differentially expressed genes in GCs, COCs and oviducts from PR–/– and PR+/– mice, specifically genes potentially involved in oocyte release and transport. GCs, COCs and oviducts were collected from 21d-old mice (n = 5; 3 mice/replicate) at 8h post-hCG/44h post-eCG. Extracted RNA samples were hybridized to Affymetrix Mouse Gene 1.0 ST Arrays and post-experiment processing/analysis performed using Partek Genomics Suite. Gene ontology analysis was performed using Ingenuity Pathway Analysis (IPA). In GCs, 296 genes were differentially expressed (P < 0.05); 78% down-regulated in PR–/–. IPA identified genes involved in cancer migration/invasion, chemotaxis, and adhesion; the chemokine receptor Cxcr4, was >3-fold down-regulated in PR–/–. Proteases were also decreased; Adam8 (3.5-fold) and Adamts1 (2.6-fold) in PR–/–. In oviducts, 1003 genes were differentially expressed at P < 0.05 and 266 genes at P < 0.01; 93% were down-regulated in PR–/–. IPA identified genes involved in cell adhesion, movement/migration, invasion and chemotaxis as well as muscle contraction and vasoconstriction. The most highly down-regulated was Itga8 (>9-fold), one of 11 integrins, well known cellular adhesion receptors, differentially expressed. In COCs, 44 genes were differentially expressed (P < 0.05); 52% down-regulated in PR–/–. IPA identified 18 genes (41%) involved in cancer invasion/migration or adhesion. Thus, this study has identified novel gene targets for PGR regulation, which may have essential roles in the molecular control of oocyte release into the oviduct at ovulation.

scholarly journals Integration of mRNA and miRNA Analysis Reveals the Molecular Mechanism Underlying Salt and Alkali Stress Tolerance in Tobacco

2019 ◽  
Vol 20 (10) ◽  
pp. 2391 ◽  
Author(s):  
Jiayang Xu ◽  
Qiansi Chen ◽  
Pingping Liu ◽  
Wei Jia ◽  
Zheng Chen ◽  
...  
Keyword(s):  
Salinity Stress ◽  
Regulatory Networks ◽  
Molecular Mechanisms ◽  
Crop Yields ◽  
Antioxidant Activities ◽  
Expression Patterns ◽  
Differentially Expressed ◽  
Alkali Stress ◽  
Rna Seq ◽  
Alkali Tolerance

Salinity is one of the most severe forms of abiotic stress and affects crop yields worldwide. Plants respond to salinity stress via a sophisticated mechanism at the physiological, transcriptional and metabolic levels. However, the molecular regulatory networks involved in salt and alkali tolerance have not yet been elucidated. We developed an RNA-seq technique to perform mRNA and small RNA (sRNA) sequencing of plants under salt (NaCl) and alkali (NaHCO3) stress in tobacco. Overall, 8064 differentially expressed genes (DEGs) and 33 differentially expressed microRNAs (DE miRNAs) were identified in response to salt and alkali stress. A total of 1578 overlapping DEGs, which exhibit the same expression patterns and are involved in ion channel, aquaporin (AQP) and antioxidant activities, were identified. Furthermore, genes involved in several biological processes, such as “photosynthesis” and “starch and sucrose metabolism,” were specifically enriched under NaHCO3 treatment. We also identified 15 and 22 miRNAs that were differentially expressed in response to NaCl and NaHCO3, respectively. Analysis of inverse correlations between miRNAs and target mRNAs revealed 26 mRNA-miRNA interactions under NaCl treatment and 139 mRNA-miRNA interactions under NaHCO3 treatment. This study provides new insights into the molecular mechanisms underlying the response of tobacco to salinity stress.

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

2019 ◽  
Vol 9 (1) ◽  
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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