RisaAligner software for aligning fluorescence data between Agilent 2100 Bioanalyzer chips: Application to soil microbial community analysis

Ribosomal Intergenic Spacer Analysis (RISA) is a high-resolution and highly reproducible fingerprinting technique for discriminating between microbial communities. The community profiles can be visualized using the Agilent 2100 Bioanalyzer. Comparison between fingerprints relies upon precise estimat...

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Published inBioTechniques Vol. 59; no. 6; pp. 347 - 358
Main Authors Navarro, Elisabeth, Fabrègue, Olivier, Scorretti, Riccardo, Reboulet, Jérémy, Simonet, Pascal, Dawson, Lorna, Demanèche, Sandrine
Format Journal Article
LanguageEnglish
Published England Future Science Ltd 01.12.2015
Eaton Publishing
Taylor & Francis Group
Subjects
Algorithms
alignment tool
DNA Fingerprinting - methods
DNA, Intergenic - chemistry
Electric power
Engineering Sciences
microbial ecology
Nonlinear Dynamics
Principal Component Analysis
RISA comparison
Software
Soil Microbiology
microbial ecology
RISA comparison
alignment tool
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Summary:Ribosomal Intergenic Spacer Analysis (RISA) is a high-resolution and highly reproducible fingerprinting technique for discriminating between microbial communities. The community profiles can be visualized using the Agilent 2100 Bioanalyzer. Comparison between fingerprints relies upon precise estimation of all amplified DNA fragment lengths; however, size standard computation can vary between gel runs. For complex samples such as soil microbial communities, discrimination by fragment size is not always sufficient. In such cases, the comparison of whole fluorescence data as a function of time (electrophoregrams) is more appropriate. When electrophoregrams [fluorescence = f (time)] are used, and more than one chip is involved, electrophoregram comparisons are challenging due to experimental variations between chips and the lack of correction by the Agilent software in such situations. Here we present RisaAligner software for analyzing and comparing electrophoregrams from Agilent chips using a nonlinear ladder-alignment algorithm. We demonstrate the robustness and substantial improvement of data analysis by analyzing soil microbial profiles obtained with Agilent DNA 1000 and High Sensitivity chips.
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ISSN:0736-6205
1940-9818
1940-9818
DOI:10.2144/000114363