TETRA: a web-service and a stand-alone program for the analysis and comparison of tetranucleotide usage patterns in DNA sequences

By H. Teeling, Jost Waldmann, T. Lombardot, Margarete Bauer, Frank Oliver Glöckner. BMC Bioinformatics, 2004

383 citations recorded by the source corpus.

AbstractBackgroundIn the emerging field of environmental genomics, direct cloning and sequencing of genomic fragments from complex microbial communities has proven to be a valuable source of new enzymes, expanding the knowledge of basic biological processes. The central problem of this so called metagenome-approach is that the cloned fragments often lack suitable phylogenetic marker genes, rendering the identification of clones that are likely to originate from the same genome difficult or impossible. In such cases, the analysis of intrinsic DNA-signatures like tetranucleotide frequencies can provide valuable hints on fragment affiliation. With this application in mind, the TETRA web-service and the TETRA stand-alone program have been developed, both of which automate the task of comparative tetranucleotide frequency analysis. Availability:http://www.megx.net/tetraResultsTETRA provides a statistical analysis of tetranucleotide usage patterns in genomic fragments, either via a web-service or a stand-alone program. With respect to discriminatory power, such an analysis outperforms the assignment of genomic fragments based on the (G+C)-content, which is a widely-used sequence-based measure for assessing fragment relatedness. While the web-service is restricted to the calculation of correlation coefficients between tetranucleotide usage patterns of submitted DNA sequences, the stand-alone program generates a much more detailed output, comprising all raw data and graphical plots. The stand-alone program is controlled via a graphical user interface and can batch-process a multitude of sequences. Furthermore, it comes with pre-computed tetranucleotide usage patterns for 166 prokaryote chromosomes, providing a useful reference dataset and source for data-mining.ConclusionsUp to now, the analysis of skewed oligonucleotide distributions within DNA sequences is not a commonly used tool within metagenomics. With the TETRA web-service and stand-alone program, the method is now accessible in an easy to use manner for a broad audience. This will hopefully facilitate the interrelation of genomic fragments from metagenome libraries, ultimately leading to new insights into the genetic potentials of yet uncultured microorganisms.

Subfields: Ecology, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/8f088a748456ba6bd5456d6f1f3bcb8770c37e15

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Citations in the corpus

MetaBAT, an efficient tool for accurately reconstructing single genomes from complex microbial communities (2015, methodology): “64 We use tetranucleotide frequency as sequence composition signatures as it has been 65 previously shown that different microbial genomes have distinct TNF biases (Mrazek 2009; 66 Pride et al. 2003; Saeed et al. 2012; Teeling et al. 2004a).”
A Primer on Metagenomics (2010, methodology): “For example, tetranucleotides are being used by the TETRA [83] program in the following fashion.”
Bioinformatics for Whole-Genome Shotgun Sequencing of Microbial Communities (2005, background): “There is a web server, Tetra, that computes tetranucleotide frequencies for metagenomics projects [39,40].”
Towards the human intestinal microbiota phylogenetic core. (2009, result): “Furthermore, tetranucleotide frequency count (Teeling et al., 2004) also showed the same trend and this work confirmed that this non-alignment-based method enabled a fast and accurate phylogenetic assignation.”
Computational meta'omics for microbial community studies (2013, methodology): “An even more reference-independent approach is possible by using only composition-based clustering (e.g., TETRA (Teeling et al , 2004)), which can then be paired with further downstream analysis.”
Machine learning for metagenomics: methods and tools (2015, methodology): “To the extent of our knowledge, the first application of k-mer distribution to the binning problem was proposed by Teeling in 2004 with a tool called Tetra (Teeling et al., 2004).”
The Road to Metagenomics: From Microbiology to DNA Sequencing Technologies and Bioinformatics (2015, methodology): “Examples of software that perform sequence classiﬁcation by composition are TETRA (Teeling et al., 2004), PhylophytiaS (McHardy et al., 2007), and MetaclusterTA (Wang et al., 2014) ( Table 2 ).”