• Title/Summary/Keyword: pathway database

Search Result 144, Processing Time 0.022 seconds

Identification and functional prediction of long noncoding RNAs related to intramuscular fat content in Laiwu pigs

  • Wang, Lixue;Xie, Yuhuai;Chen, Wei;Zhang, Yu;Zeng, Yongqing
    • Animal Bioscience
    • /
    • v.35 no.1
    • /
    • pp.115-125
    • /
    • 2022
  • Objective: Intramuscular fat (IMF) is a critical economic indicator of pork quality. Studies on IMF among different pig breeds have been performed via high-throughput sequencing, but comparisons within the same pig breed remain unreported. Methods: This study was performed to explore the gene profile and identify candidate long noncoding RNA (lncRNAs) and mRNAs associated with IMF deposition among Laiwu pigs with different IMF contents. Based on the longissimus dorsi muscle IMF content, eight pigs from the same breed and management were selected and divided into two groups: a high IMF (>12%, H) and low IMF group (<5%, L). Whole-transcriptome sequencing was performed to explore the differentially expressed (DE) genes between these two groups. Results: The IMF content varied greatly among Laiwu pig individuals (2.17% to 13.93%). Seventeen DE lncRNAs (11 upregulated and 6 downregulated) and 180 mRNAs (112 upregulated and 68 downregulated) were found. Gene Ontology analysis indicated that the following biological processes played an important role in IMF deposition: fatty acid and lipid biosynthetic processes; the extracellular signal-regulated kinase cascade; and white fat cell differentiation. In addition, the peroxisome proliferator-activated receptor, phosphatidylinositol-3-kinase-protein kinase B, and mammalian target of rapamycin pathways were enriched in the pathway analysis. Intersection analysis of the target genes of DE lncRNAs and mRNAs revealed seven candidate genes associated with IMF accumulation. Five DE lncRNAs and 20 DE mRNAs based on the pig quantitative trait locus database were identified and shown to be related to fat deposition. The expression of five DE lncRNAs and mRNAs was verified by quantitative real time polymerase chain reaction (qRT-PCR). The results of qRT-PCR and RNA-sequencing were consistent. Conclusion: These results demonstrated that the different IMF contents among pig individuals may be due to the DE lncRNAs and mRNAs associated with lipid droplets and fat deposition.

Draft Genome Assembly and Annotation for Cutaneotrichosporon dermatis NICC30027, an Oleaginous Yeast Capable of Simultaneous Glucose and Xylose Assimilation

  • Wang, Laiyou;Guo, Shuxian;Zeng, Bo;Wang, Shanshan;Chen, Yan;Cheng, Shuang;Liu, Bingbing;Wang, Chunyan;Wang, Yu;Meng, Qingshan
    • Mycobiology
    • /
    • v.50 no.1
    • /
    • pp.66-78
    • /
    • 2022
  • The identification of oleaginous yeast species capable of simultaneously utilizing xylose and glucose as substrates to generate value-added biological products is an area of key economic interest. We have previously demonstrated that the Cutaneotrichosporon dermatis NICC30027 yeast strain is capable of simultaneously assimilating both xylose and glucose, resulting in considerable lipid accumulation. However, as no high-quality genome sequencing data or associated annotations for this strain are available at present, it remains challenging to study the metabolic mechanisms underlying this phenotype. Herein, we report a 39,305,439 bp draft genome assembly for C. dermatis NICC30027 comprised of 37 scaffolds, with 60.15% GC content. Within this genome, we identified 524 tRNAs, 142 sRNAs, 53 miRNAs, 28 snRNAs, and eight rRNA clusters. Moreover, repeat sequences totaling 1,032,129 bp in length were identified (2.63% of the genome), as were 14,238 unigenes that were 1,789.35 bp in length on average (64.82% of the genome). The NCBI non-redundant protein sequences (NR) database was employed to successfully annotate 11,795 of these unigenes, while 3,621 and 11,902 were annotated with the Swiss-Prot and TrEMBL databases, respectively. Unigenes were additionally subjected to pathway enrichment analyses using the Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Cluster of Orthologous Groups of proteins (COG), Clusters of orthologous groups for eukaryotic complete genomes (KOG), and Non-supervised Orthologous Groups (eggNOG) databases. Together, these results provide a foundation for future studies aimed at clarifying the mechanistic basis for the ability of C. dermatis NICC30027 to simultaneously utilize glucose and xylose to synthesize lipids.

Analysis of Global Gene Expression Profile of Human Adipose Tissue Derived Mesenchymal Stem Cell Cultured with Cancer Cells (암세포주와 공동 배양된 인간 지방 조직 유래 중간엽 줄기 세포의 유전자 발현 분석)

  • Kim, Jong-Myung;Yu, Ji-Min;Bae, Yong-Chan;Jung, Jin-Sup
    • Journal of Life Science
    • /
    • v.21 no.5
    • /
    • pp.631-646
    • /
    • 2011
  • Mesenchymal stem cells (MSC) are multipotent and can be isolated from diverse human tissues including bone marrow, fat, placenta, dental pulp, synovium, tonsil, and the thymus. They function as regulators of tissue homeostasis. Because of their various advantages such as plasticity, easy isolation and manipulation, chemotaxis to cancer, and immune regulatory function, MSCs have been considered to be a potent cell source for regenerative medicine, cancer treatment and other cell based therapy such as GVHD. However, relating to its supportive feature for surrounding cell and tissue, it has been frequently reported that MSCs accelerate tumor growth by modulating cancer microenvironment through promoting angiogenesis, secreting growth factors, and suppressing anti-tumorigenic immune reaction. Thus, clinical application of MSCs has been limited. To understand the underlying mechanism which modulates MSCs to function as tumor supportive cells, we co-cultured human adipose tissue derived mesenchymal stem cells (ASC) with cancer cell lines H460 and U87MG. Then, expression data of ASCs co-cultured with cancer cells and cultured alone were obtained via microarray. Comparative expression analysis was carried out using DAVID (Database for Annotation, Visualization and Integrated Discovery) and PANTHER (Protein ANalysis THrough Evolutionary Relationships) in divers aspects including biological process, molecular function, cellular component, protein class, disease, tissue expression, and signal pathway. We found that cancer cells alter the expression profile of MSCs to cancer associated fibroblast like cells by modulating its energy metabolism, stemness, cell structure components, and paracrine effect in a variety of levels. These findings will improve the clinical efficacy and safety of MSCs based cell therapy.

The Classification System and Information Service for Establishing a National Collaborative R&D Strategy in Infectious Diseases: Focusing on the Classification Model for Overseas Coronavirus R&D Projects (국가 감염병 공동R&D전략 수립을 위한 분류체계 및 정보서비스에 대한 연구: 해외 코로나바이러스 R&D과제의 분류모델을 중심으로)

  • Lee, Doyeon;Lee, Jae-Seong;Jun, Seung-pyo;Kim, Keun-Hwan
    • Journal of Intelligence and Information Systems
    • /
    • v.26 no.3
    • /
    • pp.127-147
    • /
    • 2020
  • The world is suffering from numerous human and economic losses due to the novel coronavirus infection (COVID-19). The Korean government established a strategy to overcome the national infectious disease crisis through research and development. It is difficult to find distinctive features and changes in a specific R&D field when using the existing technical classification or science and technology standard classification. Recently, a few studies have been conducted to establish a classification system to provide information about the investment research areas of infectious diseases in Korea through a comparative analysis of Korea government-funded research projects. However, these studies did not provide the necessary information for establishing cooperative research strategies among countries in the infectious diseases, which is required as an execution plan to achieve the goals of national health security and fostering new growth industries. Therefore, it is inevitable to study information services based on the classification system and classification model for establishing a national collaborative R&D strategy. Seven classification - Diagnosis_biomarker, Drug_discovery, Epidemiology, Evaluation_validation, Mechanism_signaling pathway, Prediction, and Vaccine_therapeutic antibody - systems were derived through reviewing infectious diseases-related national-funded research projects of South Korea. A classification system model was trained by combining Scopus data with a bidirectional RNN model. The classification performance of the final model secured robustness with an accuracy of over 90%. In order to conduct the empirical study, an infectious disease classification system was applied to the coronavirus-related research and development projects of major countries such as the STAR Metrics (National Institutes of Health) and NSF (National Science Foundation) of the United States(US), the CORDIS (Community Research & Development Information Service)of the European Union(EU), and the KAKEN (Database of Grants-in-Aid for Scientific Research) of Japan. It can be seen that the research and development trends of infectious diseases (coronavirus) in major countries are mostly concentrated in the prediction that deals with predicting success for clinical trials at the new drug development stage or predicting toxicity that causes side effects. The intriguing result is that for all of these nations, the portion of national investment in the vaccine_therapeutic antibody, which is recognized as an area of research and development aimed at the development of vaccines and treatments, was also very small (5.1%). It indirectly explained the reason of the poor development of vaccines and treatments. Based on the result of examining the investment status of coronavirus-related research projects through comparative analysis by country, it was found that the US and Japan are relatively evenly investing in all infectious diseases-related research areas, while Europe has relatively large investments in specific research areas such as diagnosis_biomarker. Moreover, the information on major coronavirus-related research organizations in major countries was provided by the classification system, thereby allowing establishing an international collaborative R&D projects.