Digital analysis of cDNA abundance; expression profiling by means of restriction fragment fingerprinting

Abstract

Background: Gene expression profiling among different tissues is of paramount interest in various areas of biomedical research. We have developed a novel method (DADA, Digital Analysis of cDNA Abundance), that calculates the relative abundance of genes in cDNA libraries.

Results: DADA is based upon multiple restriction fragment length analysis of pools of clones from cDNA libraries and the identification of gene-specific restriction fingerprints in the resulting complex fragment mixtures. A specific cDNA cloning vector had to be constructed that governed missing or incomplete cDNA inserts which would generate misleading fingerprints in standard cloning vectors. Double stranded cDNA was synthesized using an anchored oligo dT primer, uni-directionally inserted into the DADA vector and cDNA libraries were constructed in E. coli. The cDNA fingerprints were generated in a PCR-free procedure that allows for parallel plasmid preparation, labeling, restriction digest and fragment separation of pools of 96 colonies each. This multiplexing significantly enhanced the throughput in comparison to sequence-based methods (e.g. EST approach). The data of the fragment mixtures were integrated into a relational database system and queried with fingerprints experimentally produced by analyzing single colonies. Due to limited predictability of the position of DNA fragments on the polyacrylamid gels of a given size, fingerprints derived solely from cDNA sequences were not accurate enough to be used for the analysis. We applied DADA to the analysis of gene expression profiles in a model for impaired wound healing (treatment of mice with dexamethasone).

Conclusions: The method proved to be capable of identifying pharmacologically relevant target genes that had not been identified by other standard methods routinely used to find differentially expressed genes. Due to the above mentioned limited predictability of the fingerprints, the method was yet tested only with a limited number of experimentally determined fingerprints and was able to detect differences in gene expression of transcripts representing 0.05% of the total mRNA population (e.g. medium abundant gene transcripts).

Figure 1

Experimental flow. The procedure can be performed with either a single colony from a cDNA library at a time (single clone analysis, SCA) or several colonies in parallel (96 in mixed analysis, MA). After splitting up the plasmid preparation into 6 aliquots, two at a time are labeled at a Bgl I site with one of the fluorescent dyes FAM (blue), JOE (green), or NED (yellow) – step 1. Subsequently, the 6 fractions are digested individually employing 6 different restriction enzymes recognizing sites of 4 base pairs – step 2. 3 digests are mixed together and resolved on a gel in the presence of an internal size marker labelled with the dye ROX (red) – step 3. For the digital analysis, the existence of patterns derived from a SCA is probed in the MA. In the example given, the fingerprint is identified in lanes 1,3, and 6, thus 3 out of the 6 time 96 colonies analyzed contained the cDNA of the specific gene.

Figure 2

Close up of the one strand labelling procedure. Only those Bgl I sites that incidentally contain CCT in the arbitrary 5 N stretch inside GCC-NNNNN-GGC ligate to the fluorescently labelled oligo. Moreover, due to the in general non-palindrome nature of the 5 N stretch, only the side of the construct is labelled that contains the cDNA.

Figure 3

DADA vector. Panel A depicts the situation for conventional fragment length analysis in a standard vector. It can yield either the desired cDNA fragments or any number of wrong fragments stemming from the vector that cannot be distinguished. In Panel B the situation in the DADA vector is shown. The insertion of an approx. 1 kb long vector segment, containing none of the 4 bp cutter sites that are used for the analysis, pushes all of the undesired fragments out of the detection window. Additionally only the cDNA from the 3' end towards the gene is marked with fluorescent dye to avoid signals from vector on the 3' side. Gene variants (e.g. splice variants) can only be discriminated if the variation is located within the most 3' 900 bps of the cDNA sequence.

Figure 4

Visualizing the digital counting of patterns (and thus genes) in cDNA libraries. After a pattern for a given gene is determined (eg. via SCA, described in the method section), every lane from the mixed analysis to be examined receives a count that contains all 3 fragments of a fingerprint at the same time (actually all 6 from 2 lanes of the 2 corresponding gels). The width of the search windows indicate that the search algorithm tolerates small deviations in fragment lengths. Due to the higher variations in the analysis of long fragments, the width of the search window is adjusted accordingly.