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AlignMiner: a Web-based tool for detection of divergent regions in multiple sequence alignments of conserved sequences.

Guerrero D, Bautista R, Villalobos DP, Cantón FR, Claros MG - Algorithms Mol Biol (2010)

Bottom Line: It accepts alignments (protein or nucleic acid) obtained using any of a variety of algorithms, which does not appear to have a significant impact on the final results.Users do not need to wait until execution is complete and can.even inspect their results on a different computer.In silico and experimental proof-of-concept cases have shown that AlignMiner can be successfully used to designing specific polymerase chain reaction primers as well as potential epitopes for antibodies.

View Article: PubMed Central - HTML - PubMed

Affiliation: Plataforma Andaluza de Bioinformática (Universidad de Málaga), Severo Ochoa, 34, 29590 Málaga, Spain. claros@uma.es.

ABSTRACT

Background: Multiple sequence alignments are used to study gene or protein function, phylogenetic relations, genome evolution hypotheses and even gene polymorphisms. Virtually without exception, all available tools focus on conserved segments or residues. Small divergent regions, however, are biologically important for specific quantitative polymerase chain reaction, genotyping, molecular markers and preparation of specific antibodies, and yet have received little attention. As a consequence, they must be selected empirically by the researcher. AlignMiner has been developed to fill this gap in bioinformatic analyses.

Results: AlignMiner is a Web-based application for detection of conserved and divergent regions in alignments of conserved sequences, focusing particularly on divergence. It accepts alignments (protein or nucleic acid) obtained using any of a variety of algorithms, which does not appear to have a significant impact on the final results. AlignMiner uses different scoring methods for assessing conserved/divergent regions, Entropy being the method that provides the highest number of regions with the greatest length, and Weighted being the most restrictive. Conserved/divergent regions can be generated either with respect to the consensus sequence or to one master sequence. The resulting data are presented in a graphical interface developed in AJAX, which provides remarkable user interaction capabilities. Users do not need to wait until execution is complete and can.even inspect their results on a different computer. Data can be downloaded onto a user disk, in standard formats. In silico and experimental proof-of-concept cases have shown that AlignMiner can be successfully used to designing specific polymerase chain reaction primers as well as potential epitopes for antibodies. Primer design is assisted by a module that deploys several oligonucleotide parameters for designing primers "on the fly".

Conclusions: AlignMiner can be used to reliably detect divergent regions via several scoring methods that provide different levels of selectivity. Its predictions have been verified by experimental means. Hence, it is expected that its usage will save researchers' time and ensure an objective selection of the best-possible divergent region when closely related sequences are analysed. AlignMiner is freely available at http://www.scbi.uma.es/alignminer.

No MeSH data available.


The AlignMiner algorithm. (A) Flow diagram of the main components of the algorithm, as explained in the text; the bold boxes are detalied in B. (B) The details of how a divergent region is obtained using a given scoring method. The "score calculation" renders a single numeric value for each MSA column. "FFT" is a fast Fourier transform for smoothing the curve of raw scores. The original (left branch) and Fourier-transformed (right branch) curves are trimmed with their respective "cutoffs" in order to obtain putative SNPs and conserved/divergent regions, respectively. The bold dashed boxes are detailed in C. (C) Details of the determination of the final cutoffs used for trimming scores and providing the validated conserved/divergent regions.
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Figure 1: The AlignMiner algorithm. (A) Flow diagram of the main components of the algorithm, as explained in the text; the bold boxes are detalied in B. (B) The details of how a divergent region is obtained using a given scoring method. The "score calculation" renders a single numeric value for each MSA column. "FFT" is a fast Fourier transform for smoothing the curve of raw scores. The original (left branch) and Fourier-transformed (right branch) curves are trimmed with their respective "cutoffs" in order to obtain putative SNPs and conserved/divergent regions, respectively. The bold dashed boxes are detailed in C. (C) Details of the determination of the final cutoffs used for trimming scores and providing the validated conserved/divergent regions.

Mentions: The AlignMiner algorithm is outlined in Figure 1A. It can be divided into the following main steps:


AlignMiner: a Web-based tool for detection of divergent regions in multiple sequence alignments of conserved sequences.

Guerrero D, Bautista R, Villalobos DP, Cantón FR, Claros MG - Algorithms Mol Biol (2010)

The AlignMiner algorithm. (A) Flow diagram of the main components of the algorithm, as explained in the text; the bold boxes are detalied in B. (B) The details of how a divergent region is obtained using a given scoring method. The "score calculation" renders a single numeric value for each MSA column. "FFT" is a fast Fourier transform for smoothing the curve of raw scores. The original (left branch) and Fourier-transformed (right branch) curves are trimmed with their respective "cutoffs" in order to obtain putative SNPs and conserved/divergent regions, respectively. The bold dashed boxes are detailed in C. (C) Details of the determination of the final cutoffs used for trimming scores and providing the validated conserved/divergent regions.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2902484&req=5

Figure 1: The AlignMiner algorithm. (A) Flow diagram of the main components of the algorithm, as explained in the text; the bold boxes are detalied in B. (B) The details of how a divergent region is obtained using a given scoring method. The "score calculation" renders a single numeric value for each MSA column. "FFT" is a fast Fourier transform for smoothing the curve of raw scores. The original (left branch) and Fourier-transformed (right branch) curves are trimmed with their respective "cutoffs" in order to obtain putative SNPs and conserved/divergent regions, respectively. The bold dashed boxes are detailed in C. (C) Details of the determination of the final cutoffs used for trimming scores and providing the validated conserved/divergent regions.
Mentions: The AlignMiner algorithm is outlined in Figure 1A. It can be divided into the following main steps:

Bottom Line: It accepts alignments (protein or nucleic acid) obtained using any of a variety of algorithms, which does not appear to have a significant impact on the final results.Users do not need to wait until execution is complete and can.even inspect their results on a different computer.In silico and experimental proof-of-concept cases have shown that AlignMiner can be successfully used to designing specific polymerase chain reaction primers as well as potential epitopes for antibodies.

View Article: PubMed Central - HTML - PubMed

Affiliation: Plataforma Andaluza de Bioinformática (Universidad de Málaga), Severo Ochoa, 34, 29590 Málaga, Spain. claros@uma.es.

ABSTRACT

Background: Multiple sequence alignments are used to study gene or protein function, phylogenetic relations, genome evolution hypotheses and even gene polymorphisms. Virtually without exception, all available tools focus on conserved segments or residues. Small divergent regions, however, are biologically important for specific quantitative polymerase chain reaction, genotyping, molecular markers and preparation of specific antibodies, and yet have received little attention. As a consequence, they must be selected empirically by the researcher. AlignMiner has been developed to fill this gap in bioinformatic analyses.

Results: AlignMiner is a Web-based application for detection of conserved and divergent regions in alignments of conserved sequences, focusing particularly on divergence. It accepts alignments (protein or nucleic acid) obtained using any of a variety of algorithms, which does not appear to have a significant impact on the final results. AlignMiner uses different scoring methods for assessing conserved/divergent regions, Entropy being the method that provides the highest number of regions with the greatest length, and Weighted being the most restrictive. Conserved/divergent regions can be generated either with respect to the consensus sequence or to one master sequence. The resulting data are presented in a graphical interface developed in AJAX, which provides remarkable user interaction capabilities. Users do not need to wait until execution is complete and can.even inspect their results on a different computer. Data can be downloaded onto a user disk, in standard formats. In silico and experimental proof-of-concept cases have shown that AlignMiner can be successfully used to designing specific polymerase chain reaction primers as well as potential epitopes for antibodies. Primer design is assisted by a module that deploys several oligonucleotide parameters for designing primers "on the fly".

Conclusions: AlignMiner can be used to reliably detect divergent regions via several scoring methods that provide different levels of selectivity. Its predictions have been verified by experimental means. Hence, it is expected that its usage will save researchers' time and ensure an objective selection of the best-possible divergent region when closely related sequences are analysed. AlignMiner is freely available at http://www.scbi.uma.es/alignminer.

No MeSH data available.