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Identification of miRNA-mRNA regulatory network for Human Atrial Aging [miRNA]

ABSTRACT: Identification of miRNA-mRNA regulatory network for Human Atrial Aging [miRNA]

PROVIDER: PRJNA564073 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR10072400.fastq.gz	Fastqsanger.gz
	SRR10072377.fastq.gz	Fastqsanger.gz
	SRR10072378.fastq.gz	Fastqsanger.gz
	SRR10072379.fastq.gz	Fastqsanger.gz
	SRR10072380.fastq.gz	Fastqsanger.gz

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Identification of miRNA-mRNA regulatory network for Human Atrial Aging

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Identification of miRNA-mRNA regulatory network for Human Atrial Aging [mRNA]

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Genome-Wide Profiling of miRNA-mRNA regulatory network in Skeletal Muscle with Aging [miRNA]

Project description:Skeletal muscle degenerates progressively, loses mass (sarcopenia) along in years, and leads to reduced physical ability, often causing secondary diseases such as diabetes and obesity. It is known that regulation of gene expression by microRNAs is a key event in muscle development and disease. To understand genome-wide changes in microRNAs and mRNAs during muscle aging, we sequenced microRNAs as well as mRNAs from mouse gastrocnemius muscles at two different ages (6 versus 24-month-old). Thirty-four microRNAs (15 up-regulated and 19 down-regulated) were differentially expressed with age among which were microRNAs such as miR-206 or -434 which were differentially expressed in aged muscle in previous studies. Interestingly, seven microRNAs in a microRNA cluster at imprinted Dlk1-Dio3 locus on chromosome 12 were coordinately down-regulated. In addition, sixteen novel microRNAs were identified. Integrative analysis of microRNA and mRNA expression revealed that microRNAs contribute to muscle aging possibly through the positive regulation of transcription, metabolic process, and kinase activity. Many of the age-related microRNAs were implicated in human muscular diseases. We suggest that genome-wide microRNA profiling helps to expand our knowledge of microRNA function in the muscle aging process. miRNA profiles of gastrocnemius muscle tissues (n=10) were generated by deep sequencing using Illumina Hiseq-2000

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