Physical mapping in large genomes: accelerating anchoring of BAC contigs to genetic maps through in silico analysis
2008
Paux, Etienne | Legeai, Fabrice, F. | Guilhot, Nicolas, N. | Adam-Blondon, Anne-Francoise, A.F. | Alaux, Michael, M. | Salse, Jerome, J. | Sourdille, Pierre | Leroy, Philippe | Feuillet, Catherine, C. | Génétique Diversité et Ecophysiologie des Céréales (GDEC) ; Institut National de la Recherche Agronomique (INRA)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP) | Unité de Recherche Génomique Info (URGI) ; Institut National de la Recherche Agronomique (INRA) | Unité de recherche en génomique végétale (URGV) ; Institut National de la Recherche Agronomique (INRA)-Université d'Évry-Val-d'Essonne (UEVE)-Centre National de la Recherche Scientifique (CNRS)
Anchored physical maps represent essential frameworks for map-based cloning, comparative genomics studies, and genome sequencing projects. High throughput anchoring can be achieved by polymerase chain reaction (PCR) screening of bacterial artificial chromosome (BAC) library pools with molecular markers. However, for large genomes such as wheat, the development of high dimension pools and the number of reactions that need to be performed can be extremely large making the screening laborious and costly. To improve the cost efficiency of anchoring in such large genomes, we have developed a new software named Elephant (electronic physical map anchoring tool) that combines BAC contig information generated by FingerPrinted Contig with results of BAC library pools screening to identify BAC addresses with a minimal amount of PCR reactions. Elephant was evaluated during the construction of a physical map of chromosome 3B of hexaploid wheat. Results show that a one dimensional pool screening can be sufficient to anchor a BAC contig while reducing the number of PCR by 384-fold thereby demonstrating that Elephant is an efficient and cost-effective toot to support physical mapping in large genomes.
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