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TRiFLe, a program for in silico terminal restriction fragment length polymorphism analysis with user-defined sequence sets.

ABSTRACT: We describe TRiFLe, a freely accessible computer program that generates theoretical terminal restriction fragments (T-RFs) from any user-supplied sequence set tailored to a particular group of organisms, sequences from clone libraries, or sequences from specific genes. The program allows a rapid identification of the most polymorphic enzymes, creates a collection of T-RFs for the data set, and can potentially identify specific T-RFs in T-RF length polymorphism (T-RFLP) patterns by comparing theoretical and experimental results. TRiFLE was used for analyzing T-RFLP data generated for the amoA and pmoA genes. The peaks identified in the T-RFLP patterns show an overlap of ammonia- and methane-oxidizing bacteria in the metalimnion of a subtropical lake.

SUBMITTER: Junier P

PROVIDER: S-EPMC2570284 | biostudies-literature | 2008 Oct

REPOSITORIES: biostudies-literature

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TRiFLe, a program for in silico terminal restriction fragment length polymorphism analysis with user-defined sequence sets.

Junier Pilar P Junier Thomas T Witzel Karl-Paul KP

Applied and environmental microbiology 20080829 20

We describe TRiFLe, a freely accessible computer program that generates theoretical terminal restriction fragments (T-RFs) from any user-supplied sequence set tailored to a particular group of organisms, sequences from clone libraries, or sequences from specific genes. The program allows a rapid identification of the most polymorphic enzymes, creates a collection of T-RFs for the data set, and can potentially identify specific T-RFs in T-RF length polymorphism (T-RFLP) patterns by comparing theo ...[more]

PMID: 18757578

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Project description:Terminal restriction fragment length polymorphism (T-RFLP) analysis of PCR-amplified genes is a widely used fingerprinting technique in molecular microbial ecology. In this study, we show that besides expected terminal restriction fragments (T-RFs), additional secondary T-RFs occur in T-RFLP analysis of amplicons from cloned 16S rRNA genes at high frequency. A total of 50% of 109 bacterial and 78% of 68 archaeal clones from the guts of cetoniid beetle larvae, using MspI and AluI as restriction enzymes, respectively, were affected by the presence of these additional T-RFs. These peaks were called "pseudo-T-RFs" since they can be detected as terminal fluorescently labeled fragments in T-RFLP analysis but do not represent the primary terminal restriction site as indicated by sequence data analysis. Pseudo-T-RFs were also identified in T-RFLP profiles of pure culture and environmental DNA extracts. Digestion of amplicons with the single-strand-specific mung bean nuclease prior to T-RFLP analysis completely eliminated pseudo-T-RFs. This clearly indicates that single-stranded amplicons are the reason for the formation of pseudo-T-RFs, most probably because single-stranded restriction sites cannot be cleaved by restriction enzymes. The strong dependence of pseudo-T-RF formation on the number of cycles used in PCR indicates that (partly) single-stranded amplicons can be formed during amplification of 16S rRNA genes. In a model, we explain how transiently formed secondary structures of single-stranded amplicons may render single-stranded amplicons accessible to restriction enzymes. The occurrence of pseudo-T-RFs has consequences for the interpretation of T-RFLP profiles from environmental samples, since pseudo-T-RFs may lead to an overestimation of microbial diversity. Therefore, it is advisable to establish 16S rRNA gene sequence clone libraries in parallel with T-RFLP analysis from the same sample and to check clones for their in vitro digestion T-RF pattern to facilitate the detection of pseudo-T-RFs.

Dataset Information

TRiFLe, a program for in silico terminal restriction fragment length polymorphism analysis with user-defined sequence sets.

Publications

TRiFLe, a program for in silico terminal restriction fragment length polymorphism analysis with user-defined sequence sets.

Similar Datasets

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