scholarly journals Genome-Wide Transcriptional Changes of Rhodosporidium kratochvilovae at Low Temperature

2021 ◽  
Vol 12 ◽  
Author(s):  
Rui Guo ◽  
Meixia He ◽  
Xiaoqing Zhang ◽  
Xiuling Ji ◽  
Yunlin Wei ◽  
...  
Keyword(s):  
Low Temperature ◽  
Temperature Response ◽  
Sugar Metabolism ◽  
Enrichment Analysis ◽  
Amino Sugar ◽  
Mapk Signaling ◽  
Pathway Enrichment Analysis ◽  
Rna Seq ◽  
Deep Sequencing Technology ◽  
Rhodosporidium Kratochvilovae

Rhodosporidium kratochvilovae strain YM25235 is a cold-adapted oleaginous yeast strain that can grow at 15°C. It is capable of producing polyunsaturated fatty acids. Here, we used the Nanopore Platform to first assemble the R. kratochvilovae strain YM25235 genome into a 23.71 Mb size containing 46 scaffolds and 8,472 predicted genes. To explore the molecular mechanism behind the low temperature response of R. kratochvilovae strain YM25235, we analyzed the RNA transcriptomic data from low temperature (15°C) and normal temperature (30°C) groups using the next-generation deep sequencing technology (RNA-seq). We identified 1,300 differentially expressed genes (DEGs) by comparing the cultures grown at low temperature (15°C) and normal temperature (30°C) transcriptome libraries, including 553 significantly upregulated and 747 significantly downregulated DEGs. Gene ontology and pathway enrichment analysis revealed that DEGs were primarily related to metabolic processes, cellular processes, cellular organelles, and catalytic activity, whereas the overrepresented pathways included the MAPK signaling pathway, metabolic pathways, and amino sugar and nucleotide sugar metabolism. We validated the RNA-seq results by detecting the expression of 15 DEGs using qPCR. This study provides valuable information on the low temperature response of R. kratochvilovae strain YM25235 for further research and broadens our understanding for the response of R. kratochvilovae strain YM25235 to low temperature.

scholarly journals ­Transcriptome profiling of non-climacteric ‘Yellow’ melon during ripening: insights on sugar metabolism

2020 ◽  
Author(s):  
Michelle Orane Schemberger ◽  
Marília Aparecida Stroka ◽  
Letícia Reis ◽  
Kamila Karoline de Souza Los ◽  
Gillize Aparecida Telles de Araujo ◽  
...  
Keyword(s):  
Cucumis Melo ◽  
Sugar Content ◽  
Sugar Metabolism ◽  
Enrichment Analysis ◽  
Transcriptome Profiling ◽  
Sucrose Metabolism ◽  
Pathway Enrichment Analysis ◽  
Rna Seq ◽  
Pathway Enrichment ◽  
Maturation Stages

Abstract Background: The non-climacteric ‘Yellow’ melon ( Cucumis melo , inodorus group) is an economically important crop and its quality is mainly determined by the sugar content. Thus, knowledge of sugar metabolism and its related pathways can contribute to the development of new field management and post-harvest practices, making it possible to deliver better quality fruits to consumers. Results: The RNA-seq associated with RT-qPCR analyses of four maturation stages were performed to identify important enzymes and pathways that are involved in the ripening profile of non-climacteric ‘Yellow’ melon fruit focusing on sugar metabolism. We identified 895 genes 10 days after pollination (DAP)-biased and 909 genes 40 DAP-biased. The KEGG pathway enrichment analysis of these differentially expressed (DE) genes revealed that ‘hormone signal transduction’, ‘carbon metabolism’, ‘sucrose metabolism’, ‘protein processing in endoplasmic reticulum’ and ‘spliceosome’ were the most differentially regulated processes occurring during melon development. In the sucrose metabolism, five DE genes are up-regulated and twelve are down-regulated during fruit ripening. Conclusions: The results demonstrated important enzymes in the sugar pathway that are responsible for the sucrose content and maturation profile in non-climacteric ‘Yellow’ melon. New DE genes were first detected for melon in this study such as invertase inhibitor LIKE 3 ( CmINH3 ), trehalose phosphate phosphatase ( CmTPP1 ) and trehalose phosphate synthases ( CmTPS5 , CmTPS7 , CmTPS9 ). Furthermore, the results of the protein-protein network interaction demonstrated general characteristics of the transcriptome of young and full-ripe melon and provide new perspectives for the understanding of ripening.

scholarly journals ­Transcriptome profiling of non-climacteric ‘Yellow’ melon during ripening: insights on sugar metabolism

2020 ◽  
Author(s):  
Michelle Orane Schemberger ◽  
Marília Aparecida Stroka ◽  
Letícia Reis ◽  
Kamila Karoline de Souza Los ◽  
Gillize Aparecida Telles de Araujo ◽  
...  
Keyword(s):  
Cucumis Melo ◽  
Sugar Content ◽  
Sugar Metabolism ◽  
Enrichment Analysis ◽  
Transcriptome Profiling ◽  
Sucrose Metabolism ◽  
Pathway Enrichment Analysis ◽  
Rna Seq ◽  
Pathway Enrichment ◽  
Maturation Stages

Abstract Background: The non-climacteric ‘Yellow’ melon ( Cucumis melo , inodorus group) is an economically important crop and its quality is mainly determined by the sugar content. Thus, knowledge of sugar metabolism and its related pathways can contribute to the development of new field management and post-harvest practices, making it possible to deliver better quality fruits to consumers. Results: The RNA-seq associated with RT-qPCR analyses of four maturation stages were performed to identify important enzymes and pathways that are involved in the ripening profile of non-climacteric ‘Yellow’ melon fruit focusing on sugar metabolism. We identified 895 genes 10 days after pollination (DAP)-biased and 909 genes 40 DAP-biased. The KEGG pathway enrichment analysis of these differentially expressed (DE) genes revealed that ‘hormone signal transduction’, ‘carbon metabolism’, ‘sucrose metabolism’, ‘protein processing in endoplasmic reticulum’ and ‘spliceosome’ were the most differentially regulated processes occurring during melon development. In the sucrose metabolism, five DE genes are up-regulated and twelve are down-regulated during fruit ripening. Conclusions: The results demonstrated important enzymes in the sugar pathway that are responsible for the sucrose content and maturation profile in non-climacteric ‘Yellow’ melon. New DE genes were first detected for melon in this study such as invertase inhibitor LIKE 3 ( CmINH3 ), trehalose phosphate phosphatase ( CmTPP1 ) and trehalose phosphate synthases ( CmTPS5 , CmTPS7 , CmTPS9 ). Furthermore, the results of the protein-protein network interaction demonstrated general characteristics of the transcriptome of young and full-ripe melon and provide new perspectives for the understanding of ripening.

Transcriptome analysis of castrated Bovine reveals the characters of protein accumulation

2017 ◽  
Author(s):  
Xi Wang ◽  
Yuanqing Zhang ◽  
Xizhong Zhang ◽  
Guang Jin ◽  
Dongcai Wang ◽  
...  
Keyword(s):  
Differential Expression ◽  
High Throughput Sequencing ◽  
Enrichment Analysis ◽  
Mapk Signaling ◽  
Receptor Interaction ◽  
Pathway Enrichment Analysis ◽  
Protein Accumulation ◽  
Rna Seq ◽  
Structure Information ◽  
New Genes

RNA-Seq, a new developing high-throughput sequencing technology in recent years, provides a new and more effective method for research in the genes’ expression. The technology has been used to further improve our understanding on the function of the gene structure information and excavate the new transcripts and new genes. In this study, RNA-seq was employed to study the changes of the proteins after castration in cattle. The results showed the differential expression proteins between castrated cattle and noncastrated cattle were mainly lied in immunity, lipid and fatty acid metabolism and protein synthesis. Through GO and KEGG pathway enrichment analysis, the differential expression proteins were enriched in PPAR pathway which involved in meat quality traits and lipid metabolism and immunity. In addition, the genes were mainly involved in metabolic pathways, such as ECM-receptor, interaction MAPK, signaling pathway PPAR, protein phosphorylation. The function of the proteins involved in castration were not clear and needed further researches.

scholarly journals ­Transcriptome profiling of non-climacteric ‘Yellow’ melon during ripening: insights on sugar metabolism

2020 ◽  
Author(s):  
Michelle Orane Schemberger ◽  
Marília Aparecida Stroka ◽  
Letícia Reis ◽  
Kamila Karoline de Souza Los ◽  
Gillize Aparecida Telles de Araujo ◽  
...  
Keyword(s):  
Cucumis Melo ◽  
Sugar Content ◽  
Sugar Metabolism ◽  
Enrichment Analysis ◽  
Transcriptome Profiling ◽  
Sucrose Metabolism ◽  
Pathway Enrichment Analysis ◽  
Rna Seq ◽  
Pathway Enrichment ◽  
Maturation Stages

Abstract Background: The non-climacteric ‘Yellow’ melon ( Cucumis melo , inodorus group) is an economically important crop and its quality is mainly determined by the sugar content. Thus, knowledge of sugar metabolism and its related pathways can contribute to the development of new field management and post-harvest practices, making it possible to deliver better quality fruits to consumers. Results: The RNA-seq associated with RT-qPCR analyses of four maturation stages were performed to identify important enzymes and pathways that are involved in the ripening profile of non-climacteric ‘Yellow’ melon fruit focusing on sugar metabolism. We identified 895 genes 10 days after pollination (DAP)-biased and 909 genes 40 DAP-biased. The KEGG pathway enrichment analysis of these differentially expressed (DE) genes revealed that ‘hormone signal transduction’, ‘carbon metabolism’, ‘sucrose metabolism’, ‘protein processing in endoplasmic reticulum’ and ‘spliceosome’ were the most differentially regulated processes occurring during melon development. In the sucrose metabolism, five DE genes are up-regulated and twelve are down-regulated during fruit ripening. Conclusions: The results demonstrated important enzymes in the sugar pathway that are responsible for the sucrose content and maturation profile in non-climacteric ‘Yellow’ melon. New DE genes were first detected for melon in this study such as invertase inhibitor LIKE 3 ( CmINH3 ), trehalose phosphate phosphatase ( CmTPP1 ) and trehalose phosphate synthases ( CmTPS5 , CmTPS7 , CmTPS9 ). Furthermore, the results of the protein-protein network interaction demonstrated general characteristics of the transcriptome of young and full-ripe melon and provide new perspectives for the understanding of ripening.

scholarly journals Comparative transcriptome analysis of the cold resistance of the sterile rice line 33S

PLoS ONE ◽  
2022 ◽  
Vol 17 (1) ◽  
pp. e0261822
Author(s):  
Hongjun Xie ◽  
Mingdong Zhu ◽  
Yaying Yu ◽  
Xiaoshan Zeng ◽  
Guohua Tang ◽  
...  
Keyword(s):  
Low Temperature ◽  
Cold Resistance ◽  
Temperature Response ◽  
Enrichment Analysis ◽  
Abiotic Factor ◽  
Comparative Transcriptome ◽  
Important Species ◽  
Expression Of Genes ◽  
Nutrient Reserve ◽  
Cold Tolerant

Rice (Oryza sativa L.) is one of the most important species for food production worldwide. Low temperature is a major abiotic factor that affects rice germination and reproduction. Here, the underlying regulatory mechanism in seedlings of a TGMS variety (33S) and a cold-sensitive variety (Nipponbare) was investigated by comparative transcriptome. There were 795 differentially expressed genes (DEGs) identified only in cold-treated 33S, suggesting that 33S had a unique cold-resistance system. Functional and enrichment analysis of these DEGs revealed that, in 33S, several metabolic pathways, such as photosynthesis, amino acid metabolism, secondary metabolite biosynthesis, were significantly repressed. Moreover, pathways related to growth and development, including starch and sucrose metabolism, and DNA biosynthesis and damage response/repair, were significantly enhanced. The expression of genes related to nutrient reserve activity were significantly up-regulated in 33S. Finally, three NAC and several ERF transcription factors were predicted to be important in this transcriptional reprogramming. This present work provides valuable information for future investigations of low-temperature response mechanisms and genetic improvement of cold-tolerant rice seedlings.

scholarly journals Differential Expression Profiling of Long Noncoding RNA and mRNA during Osteoblast Differentiation in Mouse

2018 ◽  
Vol 2018 ◽  
pp. 1-13
Author(s):  
Minjung Kim ◽  
Youngseok Yu ◽  
Ji-Hoi Moon ◽  
InSong Koh ◽  
Jae-Hyung Lee
Keyword(s):  
Noncoding Rna ◽  
Osteoblast Differentiation ◽  
Enrichment Analysis ◽  
Osteoblastic Differentiation ◽  
Pathway Enrichment Analysis ◽  
Rna Seq ◽  
Fuzzy C Means Clustering ◽  
Differentiation Stage ◽  
And Function ◽  
Differential Expression Profiling

Long noncoding RNAs (lncRNAs) are emerging as an important controller affecting metabolic tissue development, signaling, and function. However, little is known about the function and profile of lncRNAs in osteoblastic differentiation in mice. Here, we analyzed the RNA-sequencing (RNA-Seq) datasets obtained for 18 days in two-day intervals from neonatal mouse calvarial pre-osteoblast-like cells. Over the course of osteoblast differentiation, 4058 mRNAs and 3948 lncRNAs were differentially expressed, and they were grouped into 12 clusters according to the expression pattern by fuzzy c-means clustering. Using weighted gene coexpression network analysis, we identified 9 modules related to the early differentiation stage (days 2–8) and 7 modules related to the late differentiation stage (days 10–18). Gene ontology and KEGG pathway enrichment analysis revealed that the mRNA and lncRNA upregulated in the late differentiation stage are highly associated with osteogenesis. We also identified 72 mRNA and 89 lncRNAs as potential markers including several novel markers for osteoblast differentiation and activation. Our findings provide a valuable resource for mouse lncRNA study and improves our understanding of the biology of osteoblastic differentiation in mice.

scholarly journals Comprehensive circRNA Expression Profile and Construction of circRNAs-Related ceRNA Network in a Mouse Model of Autism

2021 ◽  
Vol 11 ◽  
Author(s):  
Ji Wang ◽  
Zhongxiu Yang ◽  
Canming Chen ◽  
Yang Xu ◽  
Hongguang Wang ◽  
...  
Keyword(s):  
Signaling Pathway ◽  
Expression Profile ◽  
Enrichment Analysis ◽  
Notch Signaling Pathway ◽  
Mapk Signaling ◽  
Circular Rnas ◽  
Pathway Enrichment Analysis ◽  
Common Disease ◽  
Cerna Network

Autism is a common disease that seriously affects the quality of life. The role of circular RNAs (circRNAs) in autism remains largely unexplored. We aimed to detect the circRNA expression profile and construct a circRNA-based competing endogenous RNA (ceRNA) network in autism. Valproate acid was used to establish an in vivo model of autism in mice. A total of 1,059 differentially expressed circRNAs (477 upregulated and 582 downregulated) in autism group was identified by RNA sequencing. The expression of novel_circ_015779 and novel_circ_035247 were detected by real-time PCR. A ceRNA network based on altered circRNAs was established, with 9,715 nodes and 150,408 edges. Module analysis was conducted followed by GO and KEGG pathway enrichment analysis. The top three modules were all correlated with autism-related pathways involving “TGF-beta signaling pathway,” “Notch signaling pathway,” “MAPK signaling pathway,” “long term depression,” “thyroid hormone signaling pathway,” etc. The present study reveals a novel circRNA involved mechanisms in the pathogenesis of autism.

scholarly journals Identification, annotation and visualisation of extreme changes in splicing from RNA-seq experiments with SwitchSeq

2014 ◽  
Author(s):  
Mar Gonzàlez-Porta ◽  
Alvis Brazma
Keyword(s):  
Enrichment Analysis ◽  
R Package ◽  
Third Party ◽  
Pathway Enrichment Analysis ◽  
Rna Seq ◽  
Differential Splicing ◽  
Protein Coding ◽  
Downstream Analysis ◽  
Intuitive Manner ◽  
Abundant Transcript

In the past years, RNA sequencing has become the method of choice for the study of transcriptome composition. When working with this type of data, several tools exist to quantify differences in splicing across conditions and to address the significance of those changes. However, the number of genes predicted to undergo differential splicing is often high, and further interpretation of the results becomes a challenging task. Here we present SwitchSeq, a novel set of tools designed to help the users in the interpretation of differential splicing events that affect protein coding genes. More specifically, we provide a framework to identify switch events, i.e., cases where, for a given gene, the identity of the most abundant transcript changes across conditions. The identified events are then annotated by incorporating information from several public databases and third-party tools, and are further visualised in an intuitive manner with the independent R package tviz. All the results are displayed in a self-contained HTML document, and are also stored in txt and json format to facilitate the integration with any further downstream analysis tools. Such analysis approach can be used complementarily to Gene Ontology and pathway enrichment analysis, and can also serve as an aid in the validation of predicted changes in mRNA and protein abundance. The latest version of SwitchSeq, including installation instructions and use cases, can be found at https://github.com/mgonzalezporta/SwitchSeq. Additionally, the plot capabilities are provided as an independent R package at https://github.com/mgonzalezporta/tviz.

scholarly journals Uncovering the Mechanisms and Molecular Targets of Weibing Formula 1 against Gastritis: Coupling Network Pharmacology with GEO Database

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Ke Chen ◽  
Luojian Zhang ◽  
Zhen Qu ◽  
Feng Wan ◽  
Jia Li ◽  
...  
Keyword(s):  
Real Time ◽  
Signaling Pathway ◽  
Quantitative Pcr ◽  
Enrichment Analysis ◽  
Mapk Signaling ◽  
Gene Expression Omnibus ◽  
Network Pharmacology ◽  
Receptor Interaction ◽  
Pathway Enrichment Analysis ◽  
Real Time Quantitative Pcr

Weibing Formula 1, a classic traditional formula, has been widely used clinically to treat gastritis in recent years. However, the potential pharmacological mechanism of Weibing Formula 1 is still unclear to date. A network pharmacology-based strategy was performed to uncover the underlying mechanisms of Weibing Formula 1 against gastritis. Furthermore, we structured the drug-active ingredients-genes–disease network and PPI network of shared targets, and function enrichment analysis of these targets was carried out. Ultimately, Gene Expression Omnibus (GEO) datasets and real-time quantitative PCR were used to verify the related genes. We found 251 potential targets corresponding to 135 bioactive components of Weibing Formula 1. Then, 327 gastritis-related targets were known gastritis-related targets. Among which, 60 common targets were shared between potential targets of Weibing Formula 1 and known gastritis-related targets. The results of pathway enrichment analysis displayed that 60 common targets mostly participated in various pathways related to Toll-like receptor signaling pathway, MAPK signaling pathway, cytokine-cytokine receptor interaction pathway, chemokine signaling pathway, and apoptosis. Based on the GSE60427 dataset, 15 common genes were shared between differentially expressed genes and 60 candidate targets. The verification results of the GSE5081 dataset showed that except for DUOX2 and VCAM1, the other 13 genes were significantly upregulated in gastritis, which was consistent with the results in the GSE60427 dataset. More importantly, real-time quantitative PCR results showed that the expressions of PTGS2, MMP9, CXCL2, and CXCL8 were significantly upregulated and NOS2, EGFR, and IL-10 were downregulated in gastritis patients, while the expressions of PTGS2, MMP9, CXCL2, and CXCL8 were significantly downregulated and NOS2, EGFR, and IL-10 were upregulated after the treatment of Weibing Formula 1. PTGS2, NOS2, EGFR, MMP9, CXCL2, CXCL8, and IL-10 may be the important direct targets of Weibing Formula 1 in gastritis treatment. Our study revealed the mechanism of Weibing Formula 1 in gastritis from an overall and systematic perspective, providing a theoretical basis for further knowing and application of this formula in the future.

scholarly journals Transcriptome Analyses Revealed Adaptive-Responses in Livers of Mice Treated With Hua-Feng-Dan and Its “Guide Drug” Yaomu

2021 ◽  
Author(s):  
Jia-Jia Liu ◽  
Ya Zhang ◽  
Shang-Fu Xu ◽  
Feng Zhang ◽  
Jing-Shan Shi ◽  
...  
Keyword(s):  
Gene Expression ◽  
Liver Toxicity ◽  
Cholesterol Metabolism ◽  
Enrichment Analysis ◽  
Stroke Recovery ◽  
Pathway Enrichment Analysis ◽  
High Dose ◽  
Hepatic Gene Expression ◽  
Rna Seq ◽  
Adaptive Responses

Abstract BackgroundHua-Feng-Dan is a patent Chinese medicine for stroke recovery and is effective against Parkinson’s disease models with modulatory effects on gut microbiota, but its effects on hepatic gene expression are unknown. This study used RNA-Seq to profile hepatic gene expression by Hua-Feng-Dan and its “Guide Drug” Yaomu.MethodsMice received orally Hua-Feng-Dan 1.2 g/kg, Yaomu 0.1-0.3 g/kg, or vehicle for 7 days. Liver pathology was examined, and total RNA was isolated for RNA-Seq. The bioinformatics, including GO and KEGG pathway enrichment analysis, two-dimensional clustering, Ingenuity Pathways Analysis (IPA), and Illumina BaseSpace Correlation Engine were used to analyze differentially expressed genes (DEGs). qPCR was performed to verify selected genes.ResultsHua-Feng-Dan and Yaomu did not produce liver toxicity as evidenced by histopathology and serum ALT and AST. GO Enrichment revealed Hua-Feng-Dan affected lipid homeostasis, protein folding and cell adhesion. KEGG showed activated cholesterol metabolism, bile secretion and PPAR signaling pathways. DEGs were identified by DESeq2 with p < 0.05 compared to controls. Hua-Feng-Dan produced 806 DEGs, Yaomu-0.1 had 235, and Yaomu-0.3 had 92 DEGs. qPCR on selected genes largely verified RNA-Seq results. IPA upstream regulator analysis revealed activation of MAPK and adaptive responses. Yaomu-0.1 had similar effects, but Yaomu-0.3 had little effects. Hua-Feng-Dan-induced DEGs were highly correlated with the GEO database of chemical-induced adaptive transcriptome changes in the liver. ConclusionHua-Feng-Dan at clinical dose did not produce liver pathological changes but induced metabolic and signaling pathway activations. Low dose of its Guide Drug Yaomu produced similar changes to a lesser extent, but high dose of Yaomu had little effects. The effects of Hua-Feng-Dan on liver transcriptome changes may produce adaptive responses to program the liver to produce beneficial or detrimental (over-dosed) pharmacological effects.

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