Dataset Information

Towards realistic benchmarks for multiple alignments of non-coding sequences.

ABSTRACT:

Background

With the continued development of new computational tools for multiple sequence alignment, it is necessary today to develop benchmarks that aid the selection of the most effective tools. Simulation-based benchmarks have been proposed to meet this necessity, especially for non-coding sequences. However, it is not clear if such benchmarks truly represent real sequence data from any given group of species, in terms of the difficulty of alignment tasks.

Results

We find that the conventional simulation approach, which relies on empirically estimated values for various parameters such as substitution rate or insertion/deletion rates, is unable to generate synthetic sequences reflecting the broad genomic variation in conservation levels. We tackle this problem with a new method for simulating non-coding sequence evolution, by relying on genome-wide distributions of evolutionary parameters rather than their averages. We then generate synthetic data sets to mimic orthologous sequences from the Drosophila group of species, and show that these data sets truly represent the variability observed in genomic data in terms of the difficulty of the alignment task. This allows us to make significant progress towards estimating the alignment accuracy of current tools in an absolute sense, going beyond only a relative assessment of different tools. We evaluate six widely used multiple alignment tools in the context of Drosophila non-coding sequences, and find the accuracy to be significantly different from previously reported values. Interestingly, the performance of most tools degrades more rapidly when there are more insertions than deletions in the data set, suggesting an asymmetric handling of insertions and deletions, even though none of the evaluated tools explicitly distinguishes these two types of events. We also examine the accuracy of two existing tools for annotating insertions versus deletions, and find their performance to be close to optimal in Drosophila non-coding sequences if provided with the true alignments.

Conclusion

We have developed a method to generate benchmarks for multiple alignments of Drosophila non-coding sequences, and shown it to be more realistic than traditional benchmarks. Apart from helping to select the most effective tools, these benchmarks will help practitioners of comparative genomics deal with the effects of alignment errors, by providing accurate estimates of the extent of these errors.

SUBMITTER: Kim J

PROVIDER: S-EPMC2823711 | biostudies-literature | 2010 Jan

REPOSITORIES: biostudies-literature

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Publications

Towards realistic benchmarks for multiple alignments of non-coding sequences.

Kim Jaebum J Sinha Saurabh S

BMC bioinformatics 20100126

<h4>Background</h4>With the continued development of new computational tools for multiple sequence alignment, it is necessary today to develop benchmarks that aid the selection of the most effective tools. Simulation-based benchmarks have been proposed to meet this necessity, especially for non-coding sequences. However, it is not clear if such benchmarks truly represent real sequence data from any given group of species, in terms of the difficulty of alignment tasks.<h4>Results</h4>We find that ...[more]

PMID: 20102627

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Project description:BackgroundInteins are self-splicing protein elements. They are translated as inserts within host proteins that excise themselves and ligate the flanking portions of the host protein (exteins) with a peptide bond. They are encoded as in-frame insertions within the genes for the host proteins. Inteins are found in all three domains of life and in viruses, but have a very sporadic distribution. Only a small number of intein coding sequences have been identified in eukaryotic nuclear genes, and all of these are from ascomycete or basidiomycete fungi.ResultsWe identified seven intein coding sequences within nuclear genes coding for the second largest subunits of RNA polymerase. These sequences were found in diverse eukaryotes: one is in the second largest subunit of RNA polymerase I (RPA2) from the ascomycete fungus Phaeosphaeria nodorum, one is in the RNA polymerase III (RPC2) of the slime mould Dictyostelium discoideum and four intein coding sequences are in RNA polymerase II genes (RPB2), one each from the green alga Chlamydomonas reinhardtii, the zygomycete fungus Spiromyces aspiralis and the chytrid fungi Batrachochytrium dendrobatidis and Coelomomyces stegomyiae. The remaining intein coding sequence is in a viral relic embedded within the genome of the oomycete Phytophthora ramorum. The Chlamydomonas and Dictyostelium inteins are the first nuclear-encoded inteins found outside of the fungi. These new inteins represent a unique dataset: they are found in homologous proteins that form a paralogous group. Although these paralogues diverged early in eukaryotic evolution, their sequences can be aligned over most of their length. The inteins are inserted at multiple distinct sites, each of which corresponds to a highly conserved region of RNA polymerase. This dataset supports earlier work suggesting that inteins preferentially occur in highly conserved regions of their host proteins.ConclusionThe identification of these new inteins increases the known host range of intein sequences in eukaryotes, and provides fresh insights into their origins and evolution. We conclude that inteins are ancient eukaryote elements once found widely among microbial eukaryotes. They persist as rarities in the genomes of a sporadic array of microorganisms, occupying highly conserved sites in diverse proteins.

Project description:BackgroundProtein pairs that have the same secondary structure packing arrangement but have different topologies have attracted much attention in terms of both evolution and physical chemistry of protein structures. Further investigation of such protein relationships would give us a hint as to how proteins can change their fold in the course of evolution, as well as a insight into physico-chemical properties of secondary structure packing. For this purpose, highly accurate sequence order independent structure comparison methods are needed.ResultsWe have developed a novel protein structure alignment algorithm, MICAN (a structure alignment algorithm that can handle Multiple-chain complexes, Inverse direction of secondary structures, Cα only models, Alternative alignments, and Non-sequential alignments). The algorithm was designed so as to identify the best structural alignment between protein pairs by disregarding the connectivity between secondary structure elements (SSE). One of the key feature of the algorithm is utilizing the multiple vector representation for each SSE, which enables us to correctly treat bent or twisted nature of long SSE. We compared MICAN with other 9 publicly available structure alignment programs, using both reference-dependent and reference-independent evaluation methods on a variety of benchmark test sets which include both sequential and non-sequential alignments. We show that MICAN outperforms the other existing methods for reproducing reference alignments of non-sequential test sets. Further, although MICAN does not specialize in sequential structure alignment, it showed the top level performance on the sequential test sets. We also show that MICAN program is the fastest non-sequential structure alignment program among all the programs we examined here.ConclusionsMICAN is the fastest and the most accurate program among non-sequential alignment programs we examined here. These results suggest that MICAN is a highly effective tool for automatically detecting non-trivial structural relationships of proteins, such as circular permutations and segment-swapping, many of which have been identified manually by human experts so far. The source code of MICAN is freely download-able at http://www.tbp.cse.nagoya-u.ac.jp/MICAN.

Dataset Information

Towards realistic benchmarks for multiple alignments of non-coding sequences.

Background

Results

Conclusion

Publications

Towards realistic benchmarks for multiple alignments of non-coding sequences.

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