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

Abstract

BackgroundGene 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.ResultsWe 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 Brassica napus on the transcriptome of the pathogenic fungus Leptosphaeria maculans.ConclusionWe 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.

cDNA-AFLP analysis of gene expression changes in apple trees induced by phytoplasma infection during compatible interaction

“…To date, a number of methods have been successfully developed to identify differential gene expression in various biological systems (Frolov et al 2003;Venkatesh et al 2005), however the cDNA-AFLP analysis is a comprehensive transcript profiling methodology (Donson et al 2002) for genome-wide expression analysis that does not require any prior knowledge of gene sequences. This technique allows detecting rarely expressed genes and distinguishing between homologous genes (Reijans et al 2003).…”

Arbitrary Multi-gene Reference for Normalization of Real-Time PCR Gene Expression Data

“…Results from DDRT-PCR, which uses arbitrary primers, also demonstrate a low level of differentially displayed bands (Liang and Pardee 1992). Quantification of DDRT-PCR data has shown that the percentage of fungal genes showing three-to ninefold increased expression after phytoalexin treatment is only 0.03% and that approximately the same percentage of genes show decreased expression (Venkatesh et al 2005). Results were obtained in an A. thaliana DDRT-PCR study examining circadian patterns of gene expression, which found that only 0.017% of the Fig.…”

GOGOT: a method for the identification of differentially expressed fragments from cDNA-AFLP data

“…Although we here calculated the normalization factor N using the average peak height of the selected TDFs (GOGOTnormH) to compare the effect of different sets of TDFs, there are many other possible approaches for calculating the normalization factor N such as the median, the trimmed mean [29], Tukey's one-step biweight method [30], and so on. Further improvement in the choice of those methods as well as the selection of valid TDFs remains to be studied.…”

“…There are a number of methods for analyzing 1-D electrophoretic data produced by various experimental technologies [19,21-29]. Compared to them, GOGOT can be positioned a method specialized for cDNA-AFLP data analysis.…”