Searching across hundreds of databases

Our searching services are busy right now. Your search will reload in five seconds.

X
Forgot Password

If you have forgotten your password you can enter your email here and get a temporary password sent to your email.

X
Forgot Password

If you have forgotten your password you can enter your email here and get a temporary password sent to your email.

This service exclusively searches for literature that cites resources. Please be aware that the total number of searchable documents is limited to those containing RRIDs and does not include all open-access literature.

Search

Type in a keyword to search

On page 1 showing 1 ~ 7 papers out of 7 papers

The Roles of Four Novel P450 Genes in Pesticides Resistance in Apis cerana cerana Fabricius: Expression Levels and Detoxification Efficiency.

  • Weixing Zhang‎ et al.
  • Frontiers in genetics‎
  • 2019‎

Cytochrome P450 monooxygenases (P450s) are widely distributed multifunctional enzymes that play crucial roles in insecticide detoxification or activation. In this study, to ascertain the molecular mechanisms of P450s in the detoxification of Chinese honeybees, Apis cerana cerana Fabricius (A. c. cerana), we isolated and characterized four new P450 genes (Acc301A1, Acc303A1, Acc306A1, and Acc315A1). The open reading frames of the four genes are 1263 to 1608 bp in length and encode four predicted polypeptides of 499 to 517 amino acids in length. Real-time quantitative PCR (RT-qPCR) results showed that expression of all four genes was observed in all developmental stages. In addition, Western blot assays further indicated the RT-qPCR results that showed that the four genes were induced by pesticide (thiamethoxam, deltamethrin, dichlorovos, and paraquat) treatments. Furthermore, we also used double-stranded RNA-mediated RNA interference to investigate the functions of Acc301A1, Acc303A1,and Acc306A1 in the antioxidant defense of honeybees. RNA interference targeting Acc301A1, Acc303A1, and Acc306A1 significantly increased the mortality rate of A. c. cerana upon pesticide treatment. These results provide important evidence about the role of the four P450 genes involved in detoxification.


Bioinformatics Analysis Identified miR-584-5p and Key miRNA-mRNA Networks Involved in the Osteogenic Differentiation of Human Periodontal Ligament Stem Cells.

  • Chengze Wang‎ et al.
  • Frontiers in genetics‎
  • 2021‎

Human periodontal ligament cells (PDLCs) play an important role in periodontal tissue stabilization and function. In the process of osteogenic differentiation of PDLSCs, the regulation of molecular signal pathways are complicated. In this study, the sequencing results of three datasets on GEO were used to comprehensively analyze the miRNA-mRNA network during the osteogenic differentiation of PDLSCs. Using the GSE99958 and GSE159507, a total of 114 common differentially expressed genes (DEGs) were identified, including 62 up-regulated genes and 52 down-regulated genes. GO enrichment analysis was performed. The up-regulated 10 hub genes and down-regulated 10 hub genes were screened out by protein-protein interaction network (PPI) analysis and STRING in Cytoscape. Similarly, differentially expressed miRNAs (DEMs) were selected by limma package from GSE159508. Then, using the miRwalk website, we further selected 11 miRNAs from 16 DEMs that may have a negative regulatory relationship with hub genes. In vitro RT-PCR verification revealed that nine DEMs and 18 hub genes showed the same trend as the RNA-seq results during the osteogenic differentiation of PDLSCs. Finally, using miR-584-5p inhibitor and mimics, it was found that miR-584-5p negatively regulates the osteogenic differentiation of PDLSCs in vitro. In summary, the present results found several potential osteogenic-related genes and identified candidate miRNA-mRNA networks for the further study of osteogenic differentiation of PDLSCs.


Systematic Analysis of Competing Endogenous RNA Networks in Diffuse Large B-Cell Lymphoma and Hodgkin's Lymphoma.

  • Juanjuan Kang‎ et al.
  • Frontiers in genetics‎
  • 2020‎

Lymphoma is a systemic malignancy, originating from the lymphatic system, which accounts for 3 to 4% of all tumors. There are two major subtypes of lymphoma, namely, diffuse large B-cell lymphoma (DLBCL) and Hodgkin's lymphoma (HL). Elucidation of the pathogenesis of these two lymphoma types is crucial for the identification of potential therapeutic targets. Compared with the corresponding knowledge of other diseases, the understanding of the regulatory networks involved in DLBCL and HL is relatively deficient. To address this, we comprehensively analyzed the mRNAs, lncRNAs, and miRNAs that were differentially expressed between normal and tumor samples of DLBCL and HL. In addition, functional enrichment analysis of the differentially expressed mRNAs was performed. We constructed two specific ceRNA networks of DLBCL and HL. The pathways enriched by dysregulated mRNAs in DLBCL and HL were mainly involved in immune responses, transcription process, and metabolism process. The ceRNA network analysis revealed that 45 ceRNAs were shared between the two ceRNA networks, including five pivotal lncRNAs (MALAT1, CTBP1-AS, THUMPD3-AS, PSMA3-AS1, and NUTM2A-AS1). In addition, we proposed a DLBCL survival risk model based on a DLBCL-specific network constructed by Lasso regression analysis. The model, which is based on eight mRNAs, exhibited excellent performance in regard to predicting outcomes in DLBCL patients, with a p value of 0.0017 and AUC of 0.9783. In summary, although the molecular mechanisms underlying tumorigenesis in DLBCL and HL were quite different, the same pivotal lncRNAs acted as key regulators. Our findings identify novel potential prognostic and therapeutic targets for DLBCL and HL.


Transcriptomic Analysis of circRNAs and mRNAs Reveals a Complex Regulatory Network That Participate in Follicular Development in Chickens.

  • Manman Shen‎ et al.
  • Frontiers in genetics‎
  • 2020‎

Follicular development plays a key role in poultry reproduction, affecting clutch traits and thus egg production. Follicular growth is determined by granulosa cells (GCs), theca cells (TCs), and oocyte at the transcription, translation, and secretion levels. With the development of bioinformatic and experimental techniques, non-coding RNAs have been shown to participate in many life events. In this study, we investigated the transcriptomes of GCs and TCs in three different physiological stages: small yellow follicle (SYF), smallest hierarchical follicle (F6), and largest hierarchical follicle (F1) stages. A differential expression (DE) analysis, weighted gene co-expression network analysis (WGCNA), and bioinformatic analyses were performed. A total of 18,016 novel circular RNAs (circRNAs) were detected in GCs and TCs, 8127 of which were abundantly expressed in both cell types. and more circRNAs were differentially expressed between GCs and TCs than mRNAs. Enrichment analysis showed that the DE transcripts were mainly involved in cell growth, proliferation, differentiation, and apoptosis. In the WGCNA analysis, we identified six specific modules that were related to the different cell types in different stages of development. A series of central hub genes, including MAPK1, CITED4, SOD2, STC1, MOS, GDF9, MDH1, CAPN2, and novel_circ0004730, were incorporated into a Cytoscape network. Notably, using both DE analysis and WGCNA, ESR1 was identified as a key gene during follicular development. Our results provide valuable information on the circRNAs involved in follicle development and identify potential genes for further research to determine their roles in the regulation of different biological processes during follicle growth.


Integrated Transcriptome and Histone Modification Analysis Reveals NDV Infection Under Heat Stress Affects Bursa Development and Proliferation in Susceptible Chicken Line.

  • Ganrea Chanthavixay‎ et al.
  • Frontiers in genetics‎
  • 2020‎

Two environmental factors, Newcastle disease and heat stress, are concurrently negatively impacting poultry worldwide and warrant greater attention into developing genetic resistance within chickens. Using two genetically distinct and highly inbred layer lines, Fayoumi and Leghorn, we explored how different genetic backgrounds affect the bursal response to a treatment of simultaneous Newcastle disease virus (NDV) infection at 6 days postinfection (dpi) while under chronic heat stress. The bursa is a primary lymphoid organ within birds and is crucial for the development of B cells. We performed RNA-seq and ChIP-seq targeting histone modifications on bursa tissue. Differential gene expression revealed that Leghorn, compared to Fayoumi, had significant down-regulation in genes involved in cell proliferation, cell cycle, and cell division. Interestingly, we also found greater differences in histone modification levels in response to treatment in Leghorns than Fayoumis, and biological processes enriched in associated target genes of H3K27ac and H3K4me1 were similarly associated with cell cycle and receptor signaling of lymphocytes. Lastly, we found candidate variants between the two genetic lines within exons of differentially expressed genes and regulatory elements with differential histone modification enrichment between the lines, which provides a strong foundation for understanding the effects of genetic variation on NDV resistance under heat stress. This study provides further understanding of the cellular mechanisms affected by NDV infection under heat stress in chicken bursa and identified potential genes and regulatory regions that may be targets for developing genetic resistance within chickens.


Transcriptome Analysis of Long Noncoding RNAs and mRNAs in Granulosa Cells of Jinghai Yellow Chickens Illuminated With Red Light.

  • Ying Wang‎ et al.
  • Frontiers in genetics‎
  • 2021‎

Jinghai Yellow chickens are a new indigenous breed with a dual purpose in China, but their egg laying performance is limited. Compared with white light (WL), exposure to red light (RL) can improve the egg laying performance of hens. Herein, to elucidate the molecular mechanism by which RL affects the egg laying performance, RNA sequencing was used to analyze long noncoding RNAs (lncRNAs) and mRNAs from granulosa cells of small yellow follicles from Jinghai Yellow chickens in RL and WL groups. A total of 12,466 lncRNAs were identified among the assembled transcripts, of which 168 lncRNAs were significantly different between the RL and WL groups (101 downregulated and 67 upregulated). Additionally, 1182 differentially expressed mRNAs were identified (958 downregulated and 224 upregulated). Integrated network analysis demonstrated that numerous differential mRNAs were involved in follicular development through steroid hormone synthesis, oocyte meiosis, and the PI3K-Akt signaling pathway. The impact of lncRNAs on cis and trans target mRNAs indicates that some lncRNAs play important roles in follicular development of small yellow follicles. The results provide a starting point for studies aimed at understanding the molecular mechanisms by which monochromatic light affects follicular development and egg production in hens.


Insights Into Walnut Lipid Metabolism From Metabolome and Transcriptome Analysis.

  • Suxian Yan‎ et al.
  • Frontiers in genetics‎
  • 2021‎

Walnut oil is an excellent source of essential fatty acids. Systematic evaluation of walnut lipids has significance for the development of the nutritional and functional value of walnut. Ultra-performance liquid chromatography/Orbitrap high-resolution mass spectrometry (UHPLC-Orbitrap HRMS) was used to characterize the lipids of walnut. A total of 525 lipids were detected and triacylglycerols (TG) (18:2/18:2/18:3) and diacylglycerols (DG) (18:2/18:2) were the main glycerolipids present. Essential fatty acids, such as linoleic acid and linolenic acid, were the main DG and TG fatty acid chains. Many types of phospholipids were observed with phosphatidic acid being present in the highest concentration (5.58%). Using a combination of metabolome and transcriptome analysis, the present study mapped the main lipid metabolism pathway in walnut. These results may provide a theoretical basis for further study and specific gene targets to enable the development of walnut with increased oil content and modified fatty acid composition.


  1. SciCrunch.org Resources

    Welcome to the FDI Lab - SciCrunch.org Resources search. From here you can search through a compilation of resources used by FDI Lab - SciCrunch.org and see how data is organized within our community.

  2. Navigation

    You are currently on the Community Resources tab looking through categories and sources that FDI Lab - SciCrunch.org has compiled. You can navigate through those categories from here or change to a different tab to execute your search through. Each tab gives a different perspective on data.

  3. Logging in and Registering

    If you have an account on FDI Lab - SciCrunch.org then you can log in from here to get additional features in FDI Lab - SciCrunch.org such as Collections, Saved Searches, and managing Resources.

  4. Searching

    Here is the search term that is being executed, you can type in anything you want to search for. Some tips to help searching:

    1. Use quotes around phrases you want to match exactly
    2. You can manually AND and OR terms to change how we search between words
    3. You can add "-" to terms to make sure no results return with that term in them (ex. Cerebellum -CA1)
    4. You can add "+" to terms to require they be in the data
    5. Using autocomplete specifies which branch of our semantics you with to search and can help refine your search
  5. Save Your Search

    You can save any searches you perform for quick access to later from here.

  6. Query Expansion

    We recognized your search term and included synonyms and inferred terms along side your term to help get the data you are looking for.

  7. Collections

    If you are logged into FDI Lab - SciCrunch.org you can add data records to your collections to create custom spreadsheets across multiple sources of data.

  8. Facets

    Here are the facets that you can filter your papers by.

  9. Options

    From here we'll present any options for the literature, such as exporting your current results.

  10. Further Questions

    If you have any further questions please check out our FAQs Page to ask questions and see our tutorials. Click this button to view this tutorial again.

Publications Per Year

X

Year:

Count: