Literature DB >> 17696213

A study of comparability in amplified fragment length polymorphism profiling using a simple model system.

Lina Partis1, Malcolm Burns, Koichi Chiba, Philippe Corbisier, David Gancberg, Marcia J Holden, Jing Wang, Qing Yan Liu, Tomoya Okunishi, Inchul Yang, Maxim Vonsky, Kerry R Emslie.   

Abstract

A simple amplified fragment length polymorphism (AFLP) model, using the bacteriophage lambda genome, was developed to test the reproducibility of this technique in an international comparative study. Using either non-selective or selective primers, nine fragments or subsets of two or three fragments, respectively, were predicted using in silico software. Under optimized conditions, all predicted fragments were experimentally generated. The reproducibility of the AFLP model was tested by submitting both "unknown" DNA template that had been restricted and ligated with AFLP linkers (R/L mixture) and corresponding primer pairs to nine laboratories participating in the study. Participants completed the final PCR step and then used either slab gel electrophoresis or CE to detect the AFLP fragments. The predicted fragments were identified by the majority of participants with size estimates consistently up to 3 base pair (bp) larger for slab gel electrophoresis than for CE. Shadow fragments, 3 bp larger than the predicted fragments, were often observed by study participants and organizers. The nine AFLP fragments exhibited relative intensities ranging from less than 3% to 22% and, apart from the two weakest fragments, with a % CV of 16 to 25. Fragments containing the highest guanine-cytosine (GC) content of 50-56% showed the greatest stability in the AFLP profiles.

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Year:  2007        PMID: 17696213     DOI: 10.1002/elps.200700247

Source DB:  PubMed          Journal:  Electrophoresis        ISSN: 0173-0835            Impact factor:   3.535


  1 in total

1.  Amplified fragment length homoplasy: in silico analysis for model and non-model species.

Authors:  Margot Paris; Benjamin Bonnes; Gentile Francesco Ficetola; Bénédicte N Poncet; Laurence Després
Journal:  BMC Genomics       Date:  2010-05-07       Impact factor: 3.969

  1 in total

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