Identification and prevention of a GC content bias in SAGE libraries
Author(s) -
Elliott H. Margulies,
Sharon L. R. Kardia,
Jeffrey W. Innis
Publication year - 2001
Publication title -
nucleic acids research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 9.008
H-Index - 537
eISSN - 1362-4954
pISSN - 0305-1048
DOI - 10.1093/nar/29.12.e60
Subject(s) - sage , serial analysis of gene expression , biology , computational biology , identification (biology) , genetics , gene expression profiling , gene , gene expression , physics , nuclear physics , botany
Serial Analysis of Gene Expression (SAGE) is becoming a widely used gene expression profiling method for the study of development, cancer and other human diseases. Investigators using SAGE rely heavily on the quantitative aspect of this method for cataloging gene expression and comparing multiple SAGE libraries. We have developed additional computational and statistical tools to assess the quality and reproducibility of a SAGE library. Using these methods, a critical variable in the SAGE protocol was identified that has the potential to bias the Tag distribution relative to the GC content of the 10 bp SAGE Tag DNA sequence. We also detected this bias in a number of publicly available SAGE libraries. It is important to note that the GC content bias went undetected by quality control procedures in the current SAGE protocol and was only identified with the use of these statistical analyses on as few as 750 SAGE Tags. In addition to keeping any solution of free DiTags on ice, an analysis of the GC content should be performed before sequencing large numbers of SAGE Tags to be confident that SAGE libraries are free from experimental bias.
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