Multiple displacement amplification for complex mixtures of DNA fragments
1 Université Paris-Sud 11, CNRS UMR 8126 Interactions Moléculaires et Cancer, Institut de Cancérologie Gustave-Roussy, 94805 Villejuif Cedex, France
2 Institut Pasteur, URA 2171, Unité de Génétique des Génomes Bactériens, 75724 Paris Cedex 15, France
BMC Genomics 2008, 9:415 doi:10.1186/1471-2164-9-415Published: 15 September 2008
A fundamental requirement for genomic studies is the availability of genetic material of good quality and quantity. The desired quantity and quality are often hard to obtain when target DNA is composed of complex mixtures of relatively short DNA fragments. Here, we sought to develop a method to representatively amplify such complex mixtures by converting them to long linear and circular concatamers, from minute amounts of starting material, followed by phi29-based multiple displacement amplification.
We report here proportional amplification of DNA fragments that were first converted into concatamers starting from DNA amounts as low as 1 pg. Religations at low concentration (< 1 ng/μL) preferentially lead to fragment self-circularization, which are then amplified independently, and result in non-uniform amplification. To circumvent this problem, an additional (stuffer) DNA was added during religation (religation concentration > 10 ng/μL), which helped in the formation of long concatamers and hence resulted in uniform amplification. To confirm its usefulness in research, DP1 bound chromatin was isolated through ChIP and presence of DHFR promoter was detected using q-PCR and compared with an irrelevant GAPDH promoter. The results clearly indicated that when ChIP material was religated in presence of stuffer DNA (improved MDA), it allowed to recover the original pattern, while standard MDA and MDA without stuffer DNA failed to do so.
We believe that this method allows for generation of abundant amounts of good quality genetic material from a complex mixture of short DNA fragments, which can be further used in high throughput genetic analysis.