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Hepatic transcription response to high‐fat treatment in mice: Microarray comparison of individual vs. pooled RNA samples
Author(s) -
Do GyeongMin,
Kwon EunYoung,
Kim Eunjung,
Kim HyengSoo,
Choi MyungSook
Publication year - 2010
Publication title -
biotechnology journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.144
H-Index - 84
eISSN - 1860-7314
pISSN - 1860-6768
DOI - 10.1002/biot.201000046
Subject(s) - rna , microarray , biology , microarray analysis techniques , pooling , gene , gene expression , gene expression profiling , messenger rna , microbiology and biotechnology , computational biology , genetics , computer science , artificial intelligence
Microarray analysis is an important tool in studying gene expression profiles in genomic research. Despite many concerns raised, mRNA samples are often pooled in microarray experiments to reduce the cost and complexity of analysis of transcript profiling. This study reports the results of microarray experiments designed to compare effects of pooling RNA samples and its impact on identifying profiles of mRNA transcripts and differentially expressed genes (DEGs) in the liver of C57BL/6J mice fed normal and high‐fat diet. Pearson's correlation coefficient of transcripts between pooled and non‐pooled RNA samples was 0.98 to 1.0. The impact of pooled vs. non‐pooled RNA samples was also compared by number of transcripts or DEGs. Agreement of significant genes between pooled and non‐pooled sets was fairly desirable based on t ‐test <0.05 and/or signal intensity ≥2‐fold. Biological process profile and the correlation coefficiency of fold change in the hepatic gene transcripts between pooled and non‐pooled samples were also higher than 0.97. This suggests that pooling hepatic RNA samples can reflect the expression pattern of individual samples, and that properly constructed pools can provide nearly identical measures of transcription response to individual RNA sample.