Software

FragIdent – Automatic identification and characterisation of cDNA-fragments

Dominik Seelow^1,2 , Heike Goehler^3,4 and Katrin Hoffmann^1,5

¹  Institut für Medizinische Genetik, Charité – Universitätsmedizin Berlin, Augustenburger Platz, 13353 Berlin, Germany

²  Department of Neuropaediatrics, Charité – Universitätsmedizin Berlin, Augustenburger Platz, 13353 Berlin, Germany

³  Max Delbrück Center für Molekulare Medizin, 13125 Berlin, Germany

⁴  Ruhr-Universität Bochum, Medizinisches Proteom-Center, 44801 Bochum, Germany

⁵  Max-Planck-Institut für Molekulare Genetik, Ihnestr. 73, 14169 Berlin, Germany

author email corresponding author email

BMC Genomics 2009, 10:95doi:10.1186/1471-2164-10-95

Published:	2 March 2009

Abstract

Background

Many genetic studies and functional assays are based on cDNA fragments. After the generation of cDNA fragments from an mRNA sample, their content is at first unknown and must be assigned by sequencing reactions or hybridisation experiments.

Even in characterised libraries, a considerable number of clones are wrongly annotated. Furthermore, mix-ups can happen in the laboratory. It is therefore essential to the relevance of experimental results to confirm or determine the identity of the employed cDNA fragments. However, the manual approach for the characterisation of these fragments using BLAST web interfaces is not suited for larger number of sequences and so far, no user-friendly software is publicly available.

Results

Here we present the development of FragIdent, an application for the automatic identification of open reading frames (ORFs) within cDNA-fragments. The software performs BLAST analyses to identify the genes represented by the sequences and suggests primers to complete the sequencing of the whole insert. Gene-specific information as well as the protein domains encoded by the cDNA fragment are retrieved from Internet-based databases and included in the output. The application features an intuitive graphical interface and is designed for researchers without any bioinformatics skills. It is suited for projects comprising up to several hundred different clones.

Conclusion

We used FragIdent to identify 84 cDNA clones from a yeast two-hybrid experiment. Furthermore, we identified 131 protein domains within our analysed clones. The source code is freely available from our homepage at http://compbio.charite.de/genetik/FragIdent/ webcite.