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[Identification of differentially expressed genes in myocardium of patients with heart failure by human whole genomic oligonucleotide microarray-assisted pathways analysis].

Xiaoxia Wu, Tao Wan, Hongjin Wu, Guang Zhi, Cangsong Xiao, Chang‐Qing Gao, Jiajin Wu

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Abstract

OBJECTIVE: To identify the differentially expressed gene profiles in myocardium of patients with heart failure using human whole genomic oligonucleotide microarray-assisted pathway analysis. METHODS: Phalanx whole genomic oligonucleotide microarrays were used to detect the gene expression profiles of myocardium in four patients died of heart failure and 4 brain died patients without heart diseases. The microarray findings were confirmed by real-time quantitative reverse transcriptase-polymerase chain reaction. The genes with a threshold of 1.2 times fold-change were selected and BioCarta Pathway and KEGG (Kyoto Encyclopaedia of Genes and Genomes) pathway databases were used to identify functionally related gene pathways. RESULTS: A total of 2806 genes with differentially expression were detected between the failing and non-failing heart samples, expression changes of 399 genes were more than 2-folds. Eleven pathways were identified by BioCarta pathway database and sixteen pathways were identified by KEGG PATHWAY Database. CONCLUSION: Genomic microarray-assisted pathway analysis could help to identify gene expression profiles in failing heart.

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What this paper is about

OBJECTIVE: To identify the differentially expressed gene profiles in myocardium of patients with heart failure using human whole genomic oligonucleotide microarray-assisted pathway analysis. METHODS: Phalanx whole genomic oligonucleotide microarrays were used to detect the gene expression profiles of myocardium in four patients died of heart failure and 4 brain died patients without heart diseases. The microarray findings were confirmed by real-time quantitative reverse transcriptase-polymerase chain reaction. The genes with a threshold of 1.2 times fold-change were selected and BioCarta Pathway and KEGG (Kyoto Encyclopaedia of Genes and Genomes) pathway databases were used to identify functionally related gene pathways. RESULTS: A total of 2806 genes with differentially expression were detected between the failing and non-failing heart samples, expression changes of 399 genes were more than 2-folds. Eleven pathways were identified by BioCarta pathway database and sixteen pathways were identified by KEGG PATHWAY Database. CONCLUSION: Genomic microarray-assisted pathway analysis could help to identify gene expression profiles in failing heart.

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Available abstract

OBJECTIVE: To identify the differentially expressed gene profiles in myocardium of patients with heart failure using human whole genomic oligonucleotide microarray-assisted pathway analysis. METHODS: Phalanx whole genomic oligonucleotide microarrays were used to detect the gene expression profiles of myocardium in four patients died of heart failure and 4 brain died patients without heart diseases. The microarray findings were confirmed by real-time quantitative reverse transcriptase-polymerase chain reaction. The genes with a threshold of 1.2 times fold-change were selected and BioCarta Pathway and KEGG (Kyoto Encyclopaedia of Genes and Genomes) pathway databases were used to identify functionally related gene pathways. RESULTS: A total of 2806 genes with differentially expression were detected between the failing and non-failing heart samples, expression changes of 399 genes were more than 2-folds. Eleven pathways were identified by BioCarta pathway database and sixteen pathways were identified by KEGG PATHWAY Database. CONCLUSION: Genomic microarray-assisted pathway analysis could help to identify gene expression profiles in failing heart.

Key concepts: KEGG, Microarray, Gene, DNA microarray, Microarray analysis techniques, Biological pathway, Gene expression, Microarray databases

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[Identification of differentially expressed genes in myocardium of patients with heart failure by human whole genomic oligonucleotide microarray-assisted pathways analysis]. — Research Paper | ScholarLens