CLAP: A web-server for automatic classification of proteins with special reference to multi-domain proteins

Background

The function of a protein can be deciphered with higher accuracy from its structure than from its amino acid sequence. Due to the huge gap in the available protein sequence and structural space, tools that can generate functionally homogeneous clusters using only the sequence information, hold great importance. For this, traditional alignment-based tools work well in most cases and clustering is performed on the basis of sequence similarity. But, in the case of multi-domain proteins, the alignment quality might be poor due to varied lengths of the proteins, domain shuffling or circular permutations. Multi-domain proteins are ubiquitous in nature, hence alignment-free tools, which overcome the shortcomings of alignment-based protein comparison methods, are required. Further, existing tools classify proteins using only domain-level information and hence miss out on the information encoded in the tethered regions or accessory domains. Our method, on the other hand, takes into account the full-length sequence of a protein, consolidating the complete sequence information to understand a given protein better.

Results

Our web-server, CLAP (Classification of Proteins), is one such alignment-free software for automatic classification of protein sequences. It utilizes a pattern-matching algorithm that assigns local matching scores (LMS) to residues that are a part of the matched patterns between two sequences being compared. CLAP works on full-length sequences and does not require prior domain definitions.Pilot studies undertaken previously on protein kinases and immunoglobulins have shown that CLAP yields clusters, which have high functional and domain architectural similarity. Moreover, parsing at a statistically determined cut-off resulted in clusters that corroborated with the sub-family level classification of that particular domain family.

Conclusions

CLAP is a useful protein-clustering tool, independent of domain assignment, domain order, sequence length and domain diversity. Our method can be used for any set of protein sequences, yielding functionally relevant clusters with high domain architectural homogeneity. The CLAP web server is freely available for academic use at http://nslab.mbu.iisc.ernet.in/clap/.     

Characterization of Nucleotide Misincorporation Patterns in the Iceman's Mitochondrial DNA

Background

The degradation of DNA represents one of the main issues in the genetic analysis of archeological specimens. In the recent years, a particular kind of post-mortem DNA modification giving rise to nucleotide misincorporation (“miscoding lesions”) has been the object of extensive investigations.

Methodology/Principal Findings

To improve our knowledge regarding the nature and incidence of ancient DNA nucleotide misincorporations, we have utilized 6,859 (629,975 bp) mitochondrial (mt) DNA sequences obtained from the 5,350–5,100-years-old, freeze-desiccated human mummy popularly known as the Tyrolean Iceman or Ötzi. To generate the sequences, we have applied a mixed PCR/pyrosequencing procedure allowing one to obtain a particularly high sequence coverage. As a control, we have produced further 8,982 (805,155 bp) mtDNA sequences from a contemporary specimen using the same system and starting from the same template copy number of the ancient sample. From the analysis of the nucleotide misincorporation rate in ancient, modern, and putative contaminant sequences, we observed that the rate of misincorporation is significantly lower in modern and putative contaminant sequence datasets than in ancient sequences. In contrast, type 2 transitions represent the vast majority (85%) of the observed nucleotide misincorporations in ancient sequences.

Conclusions/Significance

This study provides a further contribution to the knowledge of nucleotide misincorporation patterns in DNA sequences obtained from freeze-preserved archeological specimens. In the Iceman system, ancient sequences can be clearly distinguished from contaminants on the basis of nucleotide misincorporation rates. This observation confirms a previous identification of the ancient mummy sequences made on a purely phylogenetical basis. The present investigation provides further indication that the majority of ancient DNA damage is reflected by type 2 (cytosine→thymine/guanine→adenine) transitions and that type 1 transitions are essentially PCR artifacts.     

Identifying Cis-Regulatory Sequences by Word Profile Similarity

Background

Recognizing regulatory sequences in genomes is a continuing challenge, despite a wealth of available genomic data and a growing number of experimentally validated examples.

Methodology/Principal Findings

We discuss here a simple approach to search for regulatory sequences based on the compositional similarity of genomic regions and known cis-regulatory sequences. This method, which is not limited to searching for predefined motifs, recovers sequences known to be under similar regulatory control. The words shared by the recovered sequences often correspond to known binding sites. Furthermore, we show that although local word profile clustering is predictive for the regulatory sequences involved in blastoderm segmentation, local dissimilarity is a more universal feature of known regulatory sequences in Drosophila.

Conclusions/Significance

Our method leverages sequence motifs within a known regulatory sequence to identify co-regulated sequences without explicitly defining binding sites. We also show that regulatory sequences can be distinguished from surrounding sequences by local sequence dissimilarity, a novel feature in identifying regulatory sequences across a genome. Source code for WPH-finder is available for download at http://rana.lbl.gov/downloads/wph.tar.gz.     

The structure of selective dinucleotide interactions and periodicities in D melanogaster mtDNA

Background

We found a strong selective 3-sites periodicity of deviations from randomness of the dinucleotide (DN) distribution, where both bases of DN were separated by 1, 2, K sites in prokaryotes and mtDNA. Three main aspects are studied. I) the specific 3 K-sites periodic structure of the 16 DN. II) to discard the possibility that the periodicity was produced by the highly nonrandom interactive association of contiguous bases, by studying the interaction of non-contiguous bases, the first one chosen each I sites and the second chosen J sites downstream. III) the difference between this selective periodicity of association (distance to randomness) of the four bases with the described fixed periodicities of base sequences.

Results

I) The 16 pairs presented a consistent periodicity in the strength of association of both bases of the pairs; the most deviated pairs are those where G and C are involved and the least deviated ones are those where A and T are involved. II) we found significant non-random interactions when the first nucleotide is chosen every I sites and the second J sites downstream until I = J = 76. III) we showed conclusive differences between these internucleotide association periodicities and sequence periodicities.

Conclusions

This relational selective periodicity is different from sequence periodicities and indicates that any base strongly interacts with the bases of the residual genome; this interaction and periodicity is highly structured and systematic for every pair of bases. This interaction should be destroyed in few generations by recurrent mutation; it is only compatible with the Synthetic Theory of Evolution and agrees with the Wright’s adaptive landscape conception and evolution by shifting balanced adaptive peaks.

Electronic supplementary material

The online version of this article (doi:10.1186/0717-6287-47-18) contains supplementary material, which is available to authorized users.     

Clustering of protein families into functional subtypes using Relative Complexity Measure with reduced amino acid alphabets

Background  

Phylogenetic analysis can be used to divide a protein family into subfamilies in the absence of experimental information. Most phylogenetic analysis methods utilize multiple alignment of sequences and are based on an evolutionary model. However, multiple alignment is not an automated procedure and requires human intervention to maintain alignment integrity and to produce phylogenies consistent with the functional splits in underlying sequences. To address this problem, we propose to use the alignment-free Relative Complexity Measure (RCM) combined with reduced amino acid alphabets to cluster protein families into functional subtypes purely on sequence criteria. Comparison with an alignment-based approach was also carried out to test the quality of the clustering.     

A Scalable Method for Analysis and Display of DNA Sequences

Background

Comparative DNA sequence analysis provides insight into evolution and helps construct a natural classification reflecting the Tree of Life. The growing numbers of organisms represented in DNA databases challenge tree-building techniques and the vertical hierarchical classification may obscure relationships among some groups. Approaches that can incorporate sequence data from large numbers of taxa and enable visualization of affinities across groups are desirable.

Methodology/Principal Findings

Toward this end, we developed a procedure for extracting diagnostic patterns in the form of indicator vectors from DNA sequences of taxonomic groups. In the present instance the indicator vectors were derived from mitochondrial cytochrome c oxidase I (COI) sequences of those groups and further analyzed on this basis. In the first example, indicator vectors for birds, fish, and butterflies were constructed from a training set of COI sequences, then correlations with test sequences not used to construct the indicator vector were determined. In all cases, correlation with the indicator vector correctly assigned test sequences to their proper group. In the second example, this approach was explored at the species level within the bird grouping; this also gave correct assignment, suggesting the possibility of automated procedures for classification at various taxonomic levels. A false-color matrix of vector correlations displayed affinities among species consistent with higher-order taxonomy.

Conclusions/Significance

The indicator vectors preserved DNA character information and provided quantitative measures of correlations among taxonomic groups. This method is scalable to the largest datasets envisioned in this field, provides a visually-intuitive display that captures relational affinities derived from sequence data across a diversity of life forms, and is potentially a useful complement to current tree-building techniques for studying evolutionary processes based on DNA sequence data.     

Molecular Taxonomy of Phytopathogenic Fungi: A Case Study in Peronospora

Background

Inappropriate taxon definitions may have severe consequences in many areas. For instance, biologically sensible species delimitation of plant pathogens is crucial for measures such as plant protection or biological control and for comparative studies involving model organisms. However, delimiting species is challenging in the case of organisms for which often only molecular data are available, such as prokaryotes, fungi, and many unicellular eukaryotes. Even in the case of organisms with well-established morphological characteristics, molecular taxonomy is often necessary to emend current taxonomic concepts and to analyze DNA sequences directly sampled from the environment. Typically, for this purpose clustering approaches to delineate molecular operational taxonomic units have been applied using arbitrary choices regarding the distance threshold values, and the clustering algorithms.

Methodology

Here, we report on a clustering optimization method to establish a molecular taxonomy of Peronospora based on ITS nrDNA sequences. Peronospora is the largest genus within the downy mildews, which are obligate parasites of higher plants, and includes various economically important pathogens. The method determines the distance function and clustering setting that result in an optimal agreement with selected reference data. Optimization was based on both taxonomy-based and host-based reference information, yielding the same outcome. Resampling and permutation methods indicate that the method is robust regarding taxon sampling and errors in the reference data. Tests with newly obtained ITS sequences demonstrate the use of the re-classified dataset in molecular identification of downy mildews.

Conclusions

A corrected taxonomy is provided for all Peronospora ITS sequences contained in public databases. Clustering optimization appears to be broadly applicable in automated, sequence-based taxonomy. The method connects traditional and modern taxonomic disciplines by specifically addressing the issue of how to optimally account for both traditional species concepts and genetic divergence.     

SUBTLEX-CH: Chinese Word and Character Frequencies Based on Film Subtitles

Background

Word frequency is the most important variable in language research. However, despite the growing interest in the Chinese language, there are only a few sources of word frequency measures available to researchers, and the quality is less than what researchers in other languages are used to.

Methodology

Following recent work by New, Brysbaert, and colleagues in English, French and Dutch, we assembled a database of word and character frequencies based on a corpus of film and television subtitles (46.8 million characters, 33.5 million words). In line with what has been found in the other languages, the new word and character frequencies explain significantly more of the variance in Chinese word naming and lexical decision performance than measures based on written texts.

Conclusions

Our results confirm that word frequencies based on subtitles are a good estimate of daily language exposure and capture much of the variance in word processing efficiency. In addition, our database is the first to include information about the contextual diversity of the words and to provide good frequency estimates for multi-character words and the different syntactic roles in which the words are used. The word frequencies are freely available for research purposes.     

Characterization of microRNAs identified in a table grapevine cultivar with validation of computationally predicted grapevine miRNAs by miR-RACE

Background

Alignment analysis of the Vv-miRNAs identified from various grapevine cultivars indicates that over 30% orthologous Vv-miRNAs exhibit a 1–3 nucleotide discrepancy only at their ends, suggesting that this sequence discrepancy is not a random event, but might mainly derive from divergence of cultivars. With advantages of miR-RACE technology in determining precise sequences of potential miRNAs from bioinformatics prediction, the precise sequences of vv-miRNAs predicted computationally can be verified with miR-RACE in a different grapevine cultivar. This presents itself as a new approach for large scale discovery of precise miRNAs in different grapevine varieties.

Methodology/Principal Findings

Among 88 unique sequences of Vv-miRNAs from bioinformatics prediction, 83 (96.3%) were successfully validated with MiR-RACE in grapevine cv. ‘Summer Black’. All the validated sequences were identical to their corresponding ones obtained from deep sequencing of the small RNA library of ‘Summer Black’. Quantitative RT-PCR analysis of the expressions levels of 10 Vv-miRNA/target gene pairs in grapevine tissues showed some negative correlation trends. Finally, comparison of Vv-miRNA sequences with their orthologs in Arabidopsis and study on the influence of divergent bases of the orthologous miRNAs on their targeting patterns in grapevine were also done.

Conclusion

The validation of precise sequences of potential Vv-miRNAs from computational prediction in a different grapevine cultivar can be a new way to identify the orthologous Vv-miRNAs. Nucleotide discrepancy of orthologous Vv-miRNAs from different grapevine cultivars normally does not change their target genes. However, sequence variations of some orthologous miRNAs in grapevine and Arabidopsis can change their targeting patterns. These precise Vv-miRNAs sequences validated in our study could benefit some further study on grapevine functional genomics.     

Whole genome capture of vector-borne pathogens from mixed DNA samples: a case study of Borrelia burgdorferi

Background

Rapid and accurate retrieval of whole genome sequences of human pathogens from disease vectors or animal reservoirs will enable fine-resolution studies of pathogen epidemiological and evolutionary dynamics. However, next generation sequencing technologies have not yet been fully harnessed for the study of vector-borne and zoonotic pathogens, due to the difficulty of obtaining high-quality pathogen sequence data directly from field specimens with a high ratio of host to pathogen DNA.

Results

We addressed this challenge by using custom probes for multiplexed hybrid capture to enrich for and sequence 30 Borrelia burgdorferi genomes from field samples of its arthropod vector. Hybrid capture enabled sequencing of nearly the complete genome (~99.5 %) of the Borrelia burgdorferi pathogen with 132-fold coverage, and identification of up to 12,291 single nucleotide polymorphisms per genome.

Conclusions

The proprosed culture-independent method enables efficient whole genome capture and sequencing of pathogens directly from arthropod vectors, thus making population genomic study of vector-borne and zoonotic infectious diseases economically feasible and scalable. Furthermore, given the similarities of invertebrate field specimens to other mixed DNA templates characterized by a high ratio of host to pathogen DNA, we discuss the potential applicabilty of hybrid capture for genomic study across diverse study systems.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1634-x) contains supplementary material, which is available to authorized users.     

Next Generation Sequencing-Based Analysis of Repetitive DNA in the Model Dioceous Plant Silene latifolia

Background

Silene latifolia is a dioceous plant with well distinguished X and Y chromosomes that is used as a model to study sex determination and sex chromosome evolution in plants. However, efficient utilization of this species has been hampered by the lack of large-scale sequencing resources and detailed analysis of its genome composition, especially with respect to repetitive DNA, which makes up the majority of the genome.

Methodology/Principal Findings

We performed low-pass 454 sequencing followed by similarity-based clustering of 454 reads in order to identify and characterize sequences of all major groups of S. latifolia repeats. Illumina sequencing data from male and female genomes were also generated and employed to quantify the genomic proportions of individual repeat families. The majority of identified repeats belonged to LTR-retrotransposons, constituting about 50% of genomic DNA, with Ty3/gypsy elements being more frequent than Ty1/copia. While there were differences between the male and female genome in the abundance of several repeat families, their overall repeat composition was highly similar. Specific localization patterns on sex chromosomes were found for several satellite repeats using in situ hybridization with probes based on k-mer frequency analysis of Illumina sequencing data.

Conclusions/Significance

This study provides comprehensive information about the sequence composition and abundance of repeats representing over 60% of the S. latifolia genome. The results revealed generally low divergence in repeat composition between the sex chromosomes, which is consistent with their relatively recent origin. In addition, the study generated various data resources that are available for future exploration of the S. latifolia genome.     

Defining reference sequences for Nocardia species by similarity and clustering analyses of 16S rRNA gene sequence data

Background

The intra- and inter-species genetic diversity of bacteria and the absence of ‘reference’, or the most representative, sequences of individual species present a significant challenge for sequence-based identification. The aims of this study were to determine the utility, and compare the performance of several clustering and classification algorithms to identify the species of 364 sequences of 16S rRNA gene with a defined species in GenBank, and 110 sequences of 16S rRNA gene with no defined species, all within the genus Nocardia.

Methods

A total of 364 16S rRNA gene sequences of Nocardia species were studied. In addition, 110 16S rRNA gene sequences assigned only to the Nocardia genus level at the time of submission to GenBank were used for machine learning classification experiments. Different clustering algorithms were compared with a novel algorithm or the linear mapping (LM) of the distance matrix. Principal Components Analysis was used for the dimensionality reduction and visualization.

Results

The LM algorithm achieved the highest performance and classified the set of 364 16S rRNA sequences into 80 clusters, the majority of which (83.52%) corresponded with the original species. The most representative 16S rRNA sequences for individual Nocardia species have been identified as ‘centroids’ in respective clusters from which the distances to all other sequences were minimized; 110 16S rRNA gene sequences with identifications recorded only at the genus level were classified using machine learning methods. Simple kNN machine learning demonstrated the highest performance and classified Nocardia species sequences with an accuracy of 92.7% and a mean frequency of 0.578.

Conclusion

The identification of centroids of 16S rRNA gene sequence clusters using novel distance matrix clustering enables the identification of the most representative sequences for each individual species of Nocardia and allows the quantitation of inter- and intra-species variability.     

A 28,000 years old Cro-Magnon mtDNA sequence differs from all potentially contaminating modern sequences

Background

DNA sequences from ancient speciments may in fact result from undetected contamination of the ancient specimens by modern DNA, and the problem is particularly challenging in studies of human fossils. Doubts on the authenticity of the available sequences have so far hampered genetic comparisons between anatomically archaic (Neandertal) and early modern (Cro-Magnoid) Europeans.

Methodology/Principal Findings

We typed the mitochondrial DNA (mtDNA) hypervariable region I in a 28,000 years old Cro-Magnoid individual from the Paglicci cave, in Italy (Paglicci 23) and in all the people who had contact with the sample since its discovery in 2003. The Paglicci 23 sequence, determined through the analysis of 152 clones, is the Cambridge reference sequence, and cannot possibly reflect contamination because it differs from all potentially contaminating modern sequences.

Conclusions/Significance:

The Paglicci 23 individual carried a mtDNA sequence that is still common in Europe, and which radically differs from those of the almost contemporary Neandertals, demonstrating a genealogical continuity across 28,000 years, from Cro-Magnoid to modern Europeans. Because all potential sources of modern DNA contamination are known, the Paglicci 23 sample will offer a unique opportunity to get insight for the first time into the nuclear genes of early modern Europeans.     

PCR Primers for Metazoan Nuclear 18S and 28S Ribosomal DNA Sequences

Background

Metagenetic analyses, which amplify and sequence target marker DNA regions from environmental samples, are increasingly employed to assess the biodiversity of communities of small organisms. Using this approach, our understanding of microbial diversity has expanded greatly. In contrast, only a few studies using this approach to characterize metazoan diversity have been reported, despite the fact that many metazoan species are small and difficult to identify or are undescribed. One of the reasons for this discrepancy is the availability of universal primers for the target taxa. In microbial studies, analysis of the 16S ribosomal DNA is standard. In contrast, the best gene for metazoan metagenetics is less clear. In the present study, we have designed primers that amplify the nuclear 18S and 28S ribosomal DNA sequences of most metazoan species with the goal of providing effective approaches for metagenetic analyses of metazoan diversity in environmental samples, with a particular emphasis on marine biodiversity.

Methodology/Principal Findings

Conserved regions suitable for designing PCR primers were identified using 14,503 and 1,072 metazoan sequences of the nuclear 18S and 28S rDNA regions, respectively. The sequence similarity of both these newly designed and the previously reported primers to the target regions of these primers were compared for each phylum to determine the expected amplification efficacy. The nucleotide diversity of the flanking regions of the primers was also estimated for genera or higher taxonomic groups of 11 phyla to determine the variable regions within the genes.

Conclusions/Significance

The identified nuclear ribosomal DNA primers (five primer pairs for 18S and eleven for 28S) and the results of the nucleotide diversity analyses provide options for primer combinations for metazoan metagenetic analyses. Additionally, advantages and disadvantages of not only the 18S and 28S ribosomal DNA, but also other marker regions as targets for metazoan metagenetic analyses, are discussed.     

CLUSS: Clustering of protein sequences based on a new similarity measure

Background  

The rapid burgeoning of available protein data makes the use of clustering within families of proteins increasingly important. The challenge is to identify subfamilies of evolutionarily related sequences. This identification reveals phylogenetic relationships, which provide prior knowledge to help researchers understand biological phenomena. A good evolutionary model is essential to achieve a clustering that reflects the biological reality, and an accurate estimate of protein sequence similarity is crucial to the building of such a model. Most existing algorithms estimate this similarity using techniques that are not necessarily biologically plausible, especially for hard-to-align sequences such as proteins with different domain structures, which cause many difficulties for the alignment-dependent algorithms. In this paper, we propose a novel similarity measure based on matching amino acid subsequences. This measure, named SMS for Substitution Matching Similarity, is especially designed for application to non-aligned protein sequences. It allows us to develop a new alignment-free algorithm, named CLUSS, for clustering protein families. To the best of our knowledge, this is the first alignment-free algorithm for clustering protein sequences. Unlike other clustering algorithms, CLUSS is effective on both alignable and non-alignable protein families. In the rest of the paper, we use the term "phylogenetic" in the sense of "relatedness of biological functions".