ARS | Publication request: AFLP ANALYSIS USING GENEMAPPER SOFTWARE AND AN EXCEL MACRO THAT ALIGNS AND CONVERTS OUTPUT TO BINARY

Submitted to: Biotechniques
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: April 29, 2004
Publication Date: September 10, 2004
Repository URL: http://www.ars.usda.gov/sp2UserFiles/Place/64040500/RinehartPDF/Rinehart372.pdf
Citation: Rinehart, T.A. 2004. Aflp analysis using genemapper software and an excel macro that aligns and converts output to binary. Biotechniques. vol.37(2)pp. 186-188

Interpretive Summary: GeneMapper is an expensive and powerful software package available from Applied Biosystems (ABI) to automate molecular marker analyses on their capillary array systems. Unfortunately, Amplified Fragment Length Polymorphism (AFLP) analysis is not supported. This paper describes how to adjust the settings in GeneMappe to analyze AFLP data and introduces an Excel macro to properly format the results. Currently, researchers must align and convert data by hand which is labor intensive and prone to error. The software tool is available free of charge and will increase efficiency by automating AFLP analysis.

Technical Abstract: The automated generation of amplified fragment length polymorphism (AFLP) markers using capillary array systems and fluorescently labeled primers is appealing to researchers with large numbers of samples. Of the commercially available equipment for automated fragment analysis, Applied Biosystems (Foster City, CA, USA) sells several of the most widely used capillary array systems. Unfortunately, GeneMapper, the latest fragment analysis software from Applied Biosystems, does not support AFLP analysis. This paper describes how to optimize GeneMapper parameters for automated AFLP fragment sizing and introduces a novel Excel macro that converts GeneMapper output into a binary alignment compatible with phylogenetic analysis software. A semi-automated approach to AFLP using GeneMapper enables researchers with Applied Biosystems instruments to produce quality data with a minimum of manual editing and formatting.