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 ~ 3 papers out of 3 papers

Identification of Ramie Genes in Response to Pratylenchus coffeae Infection Challenge by Digital Gene Expression Analysis.

  • Yongting Yu‎ et al.
  • International journal of molecular sciences‎
  • 2015‎

Root lesion disease, caused by Pratylenchus coffeae, seriously impairs the growth and yield of ramie, an important natural fiber crop. The ramie defense mechanism against P. coffeae infection is poorly understood, which hinders efforts to improve resistance via breeding programs. In this study, the transcriptome of the resistant ramie cultivar Qingdaye was characterized using Illumina sequence technology. About 46.3 million clean pair end (PE) reads were generated and assembled into 40,826 unigenes with a mean length of 830 bp. Digital gene expression (DGE) analysis was performed on both the control roots (CK) and P. coffeae-challenged roots (CH), and the differentially expressed genes (DEGs) were identified. Approximately 10.16 and 8.07 million cDNA reads in the CK and CH cDNA libraries were sequenced, respectively. A total of 137 genes exhibited different transcript abundances between the two libraries. Among them, the expressions of 117 and 20 DEGs were up- and down-regulated in P. coffeae-challenged ramie, respectively. The expression patterns of 15 candidate genes determined by qRT-PCR confirmed the results of DGE analysis. Time-course expression profiles of eight defense-related genes in susceptible and resistant ramie cultivars were different after P. coffeae inoculation. The differential expression of protease inhibitors, pathogenesis-related proteins (PRs), and transcription factors in resistant and susceptible ramie during P. coffeae infection indicated that cystatin likely plays an important role in nematode resistance.


Genome-Wide Comprehensive Analysis of the GASA Gene Family in Populus.

  • Shuo Han‎ et al.
  • International journal of molecular sciences‎
  • 2021‎

Gibberellic acid-stimulated Arabidopsis (GASA) proteins, as cysteine-rich peptides (CRPs), play roles in development and reproduction and biotic and abiotic stresses. Although the GASA gene family has been identified in plants, the knowledge about GASAs in Populus euphratica, the woody model plant for studying abiotic stress, remains limited. Here, we referenced the well-sequenced Populus trichocarpa genome, and identified the GASAs in the whole genome of P. euphratica and P. trichocarpa. 21 candidate genes in P. trichocarpa and 19 candidate genes in P. euphratica were identified and categorized into three subfamilies by phylogenetic analysis. Most GASAs with signal peptides were located extracellularly. The GASA genes in Populus have experienced multiple gene duplication events, especially in the subfamily A. The evolution of the subfamily A, with the largest number of members, can be attributed to whole-genome duplication (WGD) and tandem duplication (TD). Collinearity analysis showed that WGD genes played a leading role in the evolution of GASA genes subfamily B. The expression patterns of P. trichocarpa and P. euphratica were investigated using the PlantGenIE database and the real-time quantitative PCR (qRT-PCR), respectively. GASA genes in P. trichocarpa and P. euphratica were mainly expressed in young tissues and organs, and almost rarely expressed in mature leaves. GASA genes in P. euphratica leaves were also widely involved in hormone responses and drought stress responses. GUS activity assay showed that PeuGASA15 was widely present in various organs of the plant, especially in vascular bundles, and was induced by auxin and inhibited by mannitol dramatically. In summary, this present study provides a theoretical foundation for further research on the function of GASA genes in P. euphratica.


High-Fat Diets with Differential Fatty Acids Induce Obesity and Perturb Gut Microbiota in Honey Bee.

  • Xiaofei Wang‎ et al.
  • International journal of molecular sciences‎
  • 2021‎

HFD (high-fat diet) induces obesity and metabolic disorders, which is associated with the alteration in gut microbiota profiles. However, the underlying molecular mechanisms of the processes are poorly understood. In this study, we used the simple model organism honey bee to explore how different amounts and types of dietary fats affect the host metabolism and the gut microbiota. Excess dietary fat, especially palm oil, elicited higher weight gain, lower survival rates, hyperglycemic, and fat accumulation in honey bees. However, microbiota-free honey bees reared on high-fat diets did not significantly change their phenotypes. Different fatty acid compositions in palm and soybean oil altered the lipid profiles of the honey bee body. Remarkably, dietary fats regulated lipid metabolism and immune-related gene expression at the transcriptional level. Gene set enrichment analysis showed that biological processes, including transcription factors, insulin secretion, and Toll and Imd signaling pathways, were significantly different in the gut of bees on different dietary fats. Moreover, a high-fat diet increased the relative abundance of Gilliamella, while the level of Bartonella was significantly decreased in palm oil groups. This study establishes a novel honey bee model of studying the crosstalk between dietary fat, gut microbiota, and host metabolism.


  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: