Transcript-level annotation of Affymetrix probesets improves the interpretation of gene expression data

被引:35
|
作者
Yu, Hui [1 ]
Wang, Feng
Tu, Kang
Xie, Lu
Li, Yuan-Yuan
Li, Yi-Xue
Agrawal, Sunil
机构
[1] Shanghai Ctr Bioinformat Technol, Shanghai 200235, Peoples R China
[2] Shanghai Jiao Tong Univ, Sch Life Sci & Technol, Shanghai 200240, Peoples R China
[3] Chinese Acad Sci, Shanghai Inst Biol Sci, Key Lab Syst Biol, Shanghai 200031, Peoples R China
[4] Chinese Acad Sci, Shanghai Inst Biol Sci, Bioinformat Ctr, Shanghai 200031, Peoples R China
关键词
D O I
10.1186/1471-2105-8-194
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Background: The wide use of Affymetrix microarray in broadened fields of biological research has made the probeset annotation an important issue. Standard Affymetrix probeset annotation is at gene level, i.e. a probeset is precisely linked to a gene, and probeset intensity is interpreted as gene expression. The increased knowledge that one gene may have multiple transcript variants clearly brings up the necessity of updating this gene-level annotation to a refined transcript-level. Results: Through performing rigorous alignments of the Affymetrix probe sequences against a comprehensive pool of currently available transcript sequences, and further linking the probesets to the International Protein Index, we generated transcript-level or protein-level annotation tables for two popular Affymetrix expression arrays, Mouse Genome 430A 2.0 Array and Human Genome U133A Array. Application of our new annotations in re-examining existing expression data sets shows increased expression consistency among synonymous probesets and strengthened expression correlation between interacting proteins. Conclusion: By refining the standard Affymetrix annotation of microarray probesets from the gene level to the transcript level and protein level, one can achieve a more reliable interpretation of their experimental data, which may lead to discovery of more profound regulatory mechanism.
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页数:15
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