Conversion of cDNA differential display results (DDRT-PCR) into quantitative transcription profiles

• Main Authors: Koopmann Birger, Hettwer Ursula, Venkatesh Balakrishnan, Karlovsky Petr
• Format: Article
• Language: English
• Published: BMC 2005-04-01
• Series: BMC Genomics
• Online Access: http://www.biomedcentral.com/1471-2164/6/51

<p>Abstract</p> <p>Background</p> <p>Gene expression studies on non-model organisms require open-end strategies for transcription profiling. Gel-based analysis of cDNA fragments allows to detect alterations in gene expression for genes which have neither been sequenced yet nor are available in cDNA libraries. Commonly used protocols for gel-based transcript profiling are cDNA differential display (DDRT-PCR) and cDNA-AFLP. Both methods have been used merely as qualitative gene discovery tools so far.</p> <p>Results</p> <p>We developed procedures for the conversion of cDNA Differential Display data into quantitative transcription profiles. Amplified cDNA fragments are separated on a DNA sequencer and detector signals are converted into virtual gel images suitable for semi-automatic analysis. Data processing consists of four steps: (i) cDNA bands in lanes corresponding to samples treated with the same primer combination are matched in order to identify fragments originating from the same transcript, (ii) intensity of bands is determined by densitometry, (iii) densitometric values are normalized, and (iv) intensity ratio is calculated for each pair of corresponding bands. Transcription profiles are represented by sets of intensity ratios (control vs. treatment) for cDNA fragments defined by primer combination and DNA mobility. We demonstrated the procedure by analyzing DDRT-PCR data on the effect of secondary metabolites of oilseed rape <it>Brassica napus </it>on the transcriptome of the pathogenic fungus <it>Leptosphaeria maculans</it>.</p> <p>Conclusion</p> <p>We developed a data processing procedure for the quantitative analysis of amplified cDNA fragments separated by electrophoresis. The system utilizes common software and provides an open-end alternative to DNA microarray analysis of the transcriptome. It is expected to work equally well with DDRT-PCR and cDNA-AFLP data and be useful particularly in reseach on organisms for which microarray analysis is not available or economical.</p>