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What Is The Role Of ERNA And Exrna In Pathogenic Mechanisms?

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Recently, extracellular vesicles (EVs) including encapsulated exRNA, have emerged as important mediators of intercellular cell communication for regulating a diverse range of biological processes. EV and exRNA carry information that not only identifies themselves but also are capable of altering functions of the targeted cells. The significance of this intercellular communication process has been recognized in diseases such as cancer, neurodegenerative disorders, and infectious diseases [52-58]. Previous studies have shown that pathogenic fungi including Cn and Ca produce EVs [59]. However, until now, EV and exRNA technology has not been used to investigate intracellular trafficking or pathogenesis in these fungi.

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exRNA was submitted to the Beijing Genome Institute (BGI, Shenzhen, China) for cDNA synthesis and RNA-Seq. Approximately 100 ng cDNA from each strain was each subject to illumina deep sequencing using BGISEQ-500 technology. A total of 27,084,174 clean sRNA reads was obtained from the cin1 mutant and 27,402,307 clean reads were obtained from WT (Table 1). The length of sRNA is between 18 nt and 30 nt. The initial sRNA annotation provided by BGI suggested that approximately 96% sRNA sequences were mapped to the available sRNA database including miRBase and Rfam. Further annotation, prediction, expression, screening of differentially expressed sRNA, and miRNA target prediction will be performed under the direction of Dr. Taylor. Using this methodology, we will determine the role of Cin1 in secretion and uptake of sRNA.

3b. mRNA and lncRNA analysis In addition to sRNAs, mRNAs and lncRNAs (> 200 nt) were also analyzed by RNA-Seq. In comparison to mRNA that conveys genetic codes from DNA to protein, lncRNA is a non-protein coding RNA that may be significant in transcriptional regulation of gene expression. For example, several lncRNAs have been described as either oncogenes or tumor suppressors (reviewed by [60, 61]). Three prediction programs, including CPC, txCdsPredict, and CNC, as well as the pfam data base, were used to separate mRNA from lncRNA in our RNA-Seq study. A significant number of

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