共查询到20条相似文献，搜索用时 15 毫秒
1.
Background
Next-generation sequencing technologies are rapidly generating whole-genome datasets for an increasing number of organisms. However, phylogenetic reconstruction of genomic data remains difficult because de novo assembly for non-model genomes and multi-genome alignment are challenging.Results
To greatly simplify the analysis, we present an Assembly and Alignment-Free (AAF) method (https://sourceforge.net/projects/aaf-phylogeny) that constructs phylogenies directly from unassembled genome sequence data, bypassing both genome assembly and alignment. Using mathematical calculations, models of sequence evolution, and simulated sequencing of published genomes, we address both evolutionary and sampling issues caused by direct reconstruction, including homoplasy, sequencing errors, and incomplete sequencing coverage. From these results, we calculate the statistical properties of the pairwise distances between genomes, allowing us to optimize parameter selection and perform bootstrapping. As a test case with real data, we successfully reconstructed the phylogeny of 12 mammals using raw sequencing reads. We also applied AAF to 21 tropical tree genome datasets with low coverage to demonstrate its effectiveness on non-model organisms.Conclusion
Our AAF method opens up phylogenomics for species without an appropriate reference genome or high sequence coverage, and rapidly creates a phylogenetic framework for further analysis of genome structure and diversity among non-model organisms.Electronic supplementary material
The online version of this article (doi:10.1186/s12864-015-1647-5) contains supplementary material, which is available to authorized users. 相似文献2.
Jose Alfredo Samaniego Castruita Marie Lisandra Zepeda Mendoza Ross Barnett Nathan Wales M Thomas P. Gilbert 《BMC bioinformatics》2015,16(1)
Background
Cellular organelles with genomes of their own (e.g. plastids and mitochondria) can pass genetic sequences to other organellar genomes within the cell in many species across the eukaryote phylogeny. The extent of the occurrence of these organellar-derived inserted sequences (odins) is still unknown, but if not accounted for in genomic and phylogenetic studies, they can be a source of error. However, if correctly identified, these inserted sequences can be used for evolutionary and comparative genomic studies. Although such insertions can be detected using various laboratory and bioinformatic strategies, there is currently no straightforward way to apply them as a standard organellar genome assembly on next-generation sequencing data. Furthermore, most current methods for identification of such insertions are unsuitable for use on non-model organisms or ancient DNA datasets.Results
We present a bioinformatic method that uses phasing algorithms to reconstruct both source and inserted organelle sequences. The method was tested in different shotgun and organellar-enriched DNA high-throughput sequencing (HTS) datasets from ancient and modern samples. Specifically, we used datasets from lions (Panthera leo ssp. and Panthera leo leo) to characterize insertions from mitochondrial origin, and from common grapevine (Vitis vinifera) and bugle (Ajuga reptans) to characterize insertions derived from plastid genomes. Comparison of the results against other available organelle genome assembly methods demonstrated that our new method provides an improvement in the sequence assembly.Conclusion
Using datasets from a wide range of species and different levels of complexity we showed that our novel bioinformatic method based on phasing algorithms can be used to achieve the next two goals: i) reference-guided assembly of chloroplast/mitochondrial genomes from HTS data and ii) identification and simultaneous assembly of odins. This method represents the first application of haplotype phasing for automatic detection of odins and reference-based organellar genome assembly.Electronic supplementary material
The online version of this article (doi:10.1186/s12859-015-0682-1) contains supplementary material, which is available to authorized users. 相似文献3.
Background
Fuelled by the advent and subsequent development of next generation sequencing technologies, metagenomics became a powerful tool for the analysis of microbial communities both scientifically and diagnostically. The biggest challenge is the extraction of relevant information from the huge sequence datasets generated for metagenomics studies. Although a plethora of tools are available, data analysis is still a bottleneck.Results
To overcome the bottleneck of data analysis, we developed an automated computational workflow called RIEMS – Reliable Information Extraction from Metagenomic Sequence datasets. RIEMS assigns every individual read sequence within a dataset taxonomically by cascading different sequence analyses with decreasing stringency of the assignments using various software applications. After completion of the analyses, the results are summarised in a clearly structured result protocol organised taxonomically. The high accuracy and performance of RIEMS analyses were proven in comparison with other tools for metagenomics data analysis using simulated sequencing read datasets.Conclusions
RIEMS has the potential to fill the gap that still exists with regard to data analysis for metagenomics studies. The usefulness and power of RIEMS for the analysis of genuine sequencing datasets was demonstrated with an early version of RIEMS in 2011 when it was used to detect the orthobunyavirus sequences leading to the discovery of Schmallenberg virus.Electronic supplementary material
The online version of this article (doi:10.1186/s12859-015-0503-6) contains supplementary material, which is available to authorized users. 相似文献4.
Patrick Kück Sandra A Meid Christian Gro? Johann W W?gele Bernhard Misof 《BMC bioinformatics》2014,15(1)
Background
Masking of multiple sequence alignment blocks has become a powerful method to enhance the tree-likeness of the underlying data. However, existing masking approaches are insensitive to heterogeneous sequence divergence which can mislead tree reconstructions. We present AliGROOVE, a new method based on a sliding window and a Monte Carlo resampling approach, that visualizes heterogeneous sequence divergence or alignment ambiguity related to single taxa or subsets of taxa within a multiple sequence alignment and tags suspicious branches on a given tree.Results
We used simulated multiple sequence alignments to show that the extent of alignment ambiguity in pairwise sequence comparison is correlated with the frequency of misplaced taxa in tree reconstructions. The approach implemented in AliGROOVE allows to detect nodes within a tree that are supported despite the absence of phylogenetic signal in the underlying multiple sequence alignment. We show that AliGROOVE equally well detects heterogeneous sequence divergence in a case study based on an empirical data set of mitochondrial DNA sequences of chelicerates.Conclusions
The AliGROOVE approach has the potential to identify single taxa or subsets of taxa which show predominantly randomized sequence similarity in comparison with other taxa in a multiple sequence alignment. It further allows to evaluate the reliability of node support in a novel way.Electronic supplementary material
The online version of this article (doi:10.1186/1471-2105-15-294) contains supplementary material, which is available to authorized users. 相似文献5.
Background
With the number of available genome sequences increasing rapidly, the magnitude of sequence data required for multiple-genome analyses is a challenging problem. When large-scale rearrangements break the collinearity of gene orders among genomes, genome comparison algorithms must first identify sets of short well-conserved sequences present in each genome, termed anchors. Previously, anchor identification among multiple genomes has been achieved using pairwise alignment tools like BLASTZ through progressive alignment tools like TBA, but the computational requirements for sequence comparisons of multiple genomes quickly becomes a limiting factor as the number and scale of genomes grows.Methodology/Principal Findings
Our algorithm, named Murasaki, makes it possible to identify anchors within multiple large sequences on the scale of several hundred megabases in few minutes using a single CPU. Two advanced features of Murasaki are (1) adaptive hash function generation, which enables efficient use of arbitrary mismatch patterns (spaced seeds) and therefore the comparison of multiple mammalian genomes in a practical amount of computation time, and (2) parallelizable execution that decreases the required wall-clock and CPU times. Murasaki can perform a sensitive anchoring of eight mammalian genomes (human, chimp, rhesus, orangutan, mouse, rat, dog, and cow) in 21 hours CPU time (42 minutes wall time). This is the first single-pass in-core anchoring of multiple mammalian genomes. We evaluated Murasaki by comparing it with the genome alignment programs BLASTZ and TBA. We show that Murasaki can anchor multiple genomes in near linear time, compared to the quadratic time requirements of BLASTZ and TBA, while improving overall accuracy.Conclusions/Significance
Murasaki provides an open source platform to take advantage of long patterns, cluster computing, and novel hash algorithms to produce accurate anchors across multiple genomes with computational efficiency significantly greater than existing methods. Murasaki is available under GPL at http://murasaki.sourceforge.net. 相似文献6.
Background
Comparing and aligning genomes is a key step in analyzing closely related genomes. Despite the development of many genome aligners in the last 15 years, the problem is not yet fully resolved, even when aligning closely related bacterial genomes of the same species. In addition, no procedures are available to assess the quality of genome alignments or to compare genome aligners.Results
We designed an original method for pairwise genome alignment, named YOC, which employs a highly sensitive similarity detection method together with a recent collinear chaining strategy that allows overlaps. YOC improves the reliability of collinear genome alignments, while preserving or even improving sensitivity. We also propose an original qualitative evaluation criterion for measuring the relevance of genome alignments. We used this criterion to compare and benchmark YOC with five recent genome aligners on large bacterial genome datasets, and showed it is suitable for identifying the specificities and the potential flaws of their underlying strategies.Conclusions
The YOC prototype is available at https://github.com/ruricaru/YOC. It has several advantages over existing genome aligners: (1) it is based on a simplified two phase alignment strategy, (2) it is easy to parameterize, (3) it produces reliable genome alignments, which are easier to analyze and to use.Electronic supplementary material
The online version of this article (doi:10.1186/s12859-015-0530-3) contains supplementary material, which is available to authorized users. 相似文献7.
Background
Rigorous study of mitochondrial functions and cell biology in the budding yeast, Saccharomyces cerevisiae has advanced our understanding of mitochondrial genetics. This yeast is now a powerful model for population genetics, owing to large genetic diversity and highly structured populations among wild isolates. Comparative mitochondrial genomic analyses between yeast species have revealed broad evolutionary changes in genome organization and architecture. A fine-scale view of recent evolutionary changes within S. cerevisiae has not been possible due to low numbers of complete mitochondrial sequences.Results
To address challenges of sequencing AT-rich and repetitive mitochondrial DNAs (mtDNAs), we sequenced two divergent S. cerevisiae mtDNAs using a single-molecule sequencing platform (PacBio RS). Using de novo assemblies, we generated highly accurate complete mtDNA sequences. These mtDNA sequences were compared with 98 additional mtDNA sequences gathered from various published collections. Phylogenies based on mitochondrial coding sequences and intron profiles revealed that intraspecific diversity in mitochondrial genomes generally recapitulated the population structure of nuclear genomes. Analysis of intergenic sequence indicated a recent expansion of mobile elements in certain populations. Additionally, our analyses revealed that certain populations lacked introns previously believed conserved throughout the species, as well as the presence of introns never before reported in S. cerevisiae.Conclusions
Our results revealed that the extensive variation in S. cerevisiae mtDNAs is often population specific, thus offering a window into the recent evolutionary processes shaping these genomes. In addition, we offer an effective strategy for sequencing these challenging AT-rich mitochondrial genomes for small scale projects.Electronic supplementary material
The online version of this article (doi:10.1186/s12864-015-1664-4) contains supplementary material, which is available to authorized users. 相似文献8.
9.
Background
The increasing abundance of neuromorphological data provides both the opportunity and the challenge to compare massive numbers of neurons from a wide diversity of sources efficiently and effectively. We implemented a modified global alignment algorithm representing axonal and dendritic bifurcations as strings of characters. Sequence alignment quantifies neuronal similarity by identifying branch-level correspondences between trees.Results
The space generated from pairwise similarities is capable of classifying neuronal arbor types as well as, or better than, traditional topological metrics. Unsupervised cluster analysis produces groups that significantly correspond with known cell classes for axons, dendrites, and pyramidal apical dendrites. Furthermore, the distinguishing consensus topology generated by multiple sequence alignment of a group of neurons reveals their shared branching blueprint. Interestingly, the axons of dendritic-targeting interneurons in the rodent cortex associates with pyramidal axons but apart from the (more topologically symmetric) axons of perisomatic-targeting interneurons.Conclusions
Global pairwise and multiple sequence alignment of neurite topologies enables detailed comparison of neurites and identification of conserved topological features in alignment-defined clusters. The methods presented also provide a framework for incorporation of additional branch-level morphological features. Moreover, comparison of multiple alignment with motif analysis shows that the two techniques provide complementary information respectively revealing global and local features.Electronic supplementary material
The online version of this article (doi:10.1186/s12859-015-0605-1) contains supplementary material, which is available to authorized users. 相似文献10.
11.
Kristoffer Sahlin Francesco Vezzi Bj?rn Nystedt Joakim Lundeberg Lars Arvestad 《BMC bioinformatics》2014,15(1)
Background
The use of short reads from High Throughput Sequencing (HTS) techniques is now commonplace in de novo assembly. Yet, obtaining contiguous assemblies from short reads is challenging, thus making scaffolding an important step in the assembly pipeline. Different algorithms have been proposed but many of them use the number of read pairs supporting a linking of two contigs as an indicator of reliability. This reasoning is intuitive, but fails to account for variation in link count due to contig features.We have also noted that published scaffolders are only evaluated on small datasets using output from only one assembler. Two issues arise from this. Firstly, some of the available tools are not well suited for complex genomes. Secondly, these evaluations provide little support for inferring a software’s general performance.Results
We propose a new algorithm, implemented in a tool called BESST, which can scaffold genomes of all sizes and complexities and was used to scaffold the genome of P. abies (20 Gbp). We performed a comprehensive comparison of BESST against the most popular stand-alone scaffolders on a large variety of datasets. Our results confirm that some of the popular scaffolders are not practical to run on complex datasets. Furthermore, no single stand-alone scaffolder outperforms the others on all datasets. However, BESST fares favorably to the other tested scaffolders on GAGE datasets and, moreover, outperforms the other methods when library insert size distribution is wide.Conclusion
We conclude from our results that information sources other than the quantity of links, as is commonly used, can provide useful information about genome structure when scaffolding.Electronic supplementary material
The online version of this article (doi:10.1186/1471-2105-15-281) contains supplementary material, which is available to authorized users. 相似文献12.
Background
Cytoplasmic male sterility (CMS) is an inability to produce functional pollen that is caused by mutation of the mitochondrial genome. Comparative analyses of mitochondrial genomes of lines with and without CMS in several species have revealed structural differences between genomes, including extensive rearrangements caused by recombination. However, the mitochondrial genome structure and the DNA rearrangements that may be related to CMS have not been characterized in Capsicum spp.Results
We obtained the complete mitochondrial genome sequences of the pepper CMS line FS4401 (507,452 bp) and the fertile line Jeju (511,530 bp). Comparative analysis between mitochondrial genomes of peppers and tobacco that are included in Solanaceae revealed extensive DNA rearrangements and poor conservation in non-coding DNA. In comparison between pepper lines, FS4401 and Jeju mitochondrial DNAs contained the same complement of protein coding genes except for one additional copy of an atp6 gene (ψatp6-2) in FS4401. In terms of genome structure, we found eighteen syntenic blocks in the two mitochondrial genomes, which have been rearranged in each genome. By contrast, sequences between syntenic blocks, which were specific to each line, accounted for 30,380 and 17,847 bp in FS4401 and Jeju, respectively. The previously-reported CMS candidate genes, orf507 and ψatp6-2, were located on the edges of the largest sequence segments that were specific to FS4401. In this region, large number of small sequence segments which were absent or found on different locations in Jeju mitochondrial genome were combined together. The incorporation of repeats and overlapping of connected sequence segments by a few nucleotides implied that extensive rearrangements by homologous recombination might be involved in evolution of this region. Further analysis using mtDNA pairs from other plant species revealed common features of DNA regions around CMS-associated genes.Conclusions
Although large portion of sequence context was shared by mitochondrial genomes of CMS and male-fertile pepper lines, extensive genome rearrangements were detected. CMS candidate genes located on the edges of highly-rearranged CMS-specific DNA regions and near to repeat sequences. These characteristics were detected among CMS-associated genes in other species, implying a common mechanism might be involved in the evolution of CMS-associated genes.Electronic supplementary material
The online version of this article (doi:10.1186/1471-2164-15-561) contains supplementary material, which is available to authorized users. 相似文献13.
Background
Metagenomics is a powerful methodology to study microbial communities, but it is highly dependent on nucleotide sequence similarity searching against sequence databases. Metagenomic analyses with next-generation sequencing technologies produce enormous numbers of reads from microbial communities, and many reads are derived from microbes whose genomes have not yet been sequenced, limiting the usefulness of existing sequence similarity search tools. Therefore, there is a clear need for a sequence similarity search tool that can rapidly detect weak similarity in large datasets.Results
We developed a tool, which we named CLAST (CUDA implemented large-scale alignment search tool), that enables analyses of millions of reads and thousands of reference genome sequences, and runs on NVIDIA Fermi architecture graphics processing units. CLAST has four main advantages over existing alignment tools. First, CLAST was capable of identifying sequence similarities ~80.8 times faster than BLAST and 9.6 times faster than BLAT. Second, CLAST executes global alignment as the default (local alignment is also an option), enabling CLAST to assign reads to taxonomic and functional groups based on evolutionarily distant nucleotide sequences with high accuracy. Third, CLAST does not need a preprocessed sequence database like Burrows–Wheeler Transform-based tools, and this enables CLAST to incorporate large, frequently updated sequence databases. Fourth, CLAST requires <2 GB of main memory, making it possible to run CLAST on a standard desktop computer or server node.Conclusions
CLAST achieved very high speed (similar to the Burrows–Wheeler Transform-based Bowtie 2 for long reads) and sensitivity (equal to BLAST, BLAT, and FR-HIT) without the need for extensive database preprocessing or a specialized computing platform. Our results demonstrate that CLAST has the potential to be one of the most powerful and realistic approaches to analyze the massive amount of sequence data from next-generation sequencing technologies.Electronic supplementary material
The online version of this article (doi:10.1186/s12859-014-0406-y) contains supplementary material, which is available to authorized users. 相似文献14.
Background
The correct taxonomic assignment of bacterial genomes is a primary and challenging task. With the availability of whole genome sequences, the gene content based approaches appear promising in inferring the bacterial taxonomy. The complete genome sequencing of a bacterial genome often reveals a substantial number of unique genes present only in that genome which can be used for its taxonomic classification.Results
In this study, we have proposed a comprehensive method which uses the taxon-specific genes for the correct taxonomic assignment of existing and new bacterial genomes. The taxon-specific genes identified at each taxonomic rank have been successfully used for the taxonomic classification of 2,342 genomes present in the NCBI genomes, 36 newly sequenced genomes, and 17 genomes for which the complete taxonomy is not yet known. This approach has been implemented for the development of a tool ‘Microtaxi’ which can be used for the taxonomic assignment of complete bacterial genomes.Conclusion
The taxon-specific gene based approach provides an alternate valuable methodology to carry out the taxonomic classification of newly sequenced or existing bacterial genomes.Electronic supplementary material
The online version of this article (doi:10.1186/s12864-015-1542-0) contains supplementary material, which is available to authorized users. 相似文献15.
Background
Discovering causal genetic variants from large genetic association studies poses many difficult challenges. Assessing which genetic markers are involved in determining trait status is a computationally demanding task, especially in the presence of gene-gene interactions.Results
A non-parametric Bayesian approach in the form of a Bayesian neural network is proposed for use in analyzing genetic association studies. Demonstrations on synthetic and real data reveal they are able to efficiently and accurately determine which variants are involved in determining case-control status. By using graphics processing units (GPUs) the time needed to build these models is decreased by several orders of magnitude. In comparison with commonly used approaches for detecting interactions, Bayesian neural networks perform very well across a broad spectrum of possible genetic relationships.Conclusions
The proposed framework is shown to be a powerful method for detecting causal SNPs while being computationally efficient enough to handle large datasets.Electronic supplementary material
The online version of this article (doi:10.1186/s12859-014-0368-0) contains supplementary material, which is available to authorized users. 相似文献16.
Background
Guide-trees are used as part of an essential heuristic to enable the calculation of multiple sequence alignments. They have been the focus of much method development but there has been little effort at determining systematically, which guide-trees, if any, give the best alignments. Some guide-tree construction schemes are based on pair-wise distances amongst unaligned sequences. Others try to emulate an underlying evolutionary tree and involve various iteration methods.Results
We explore all possible guide-trees for a set of protein alignments of up to eight sequences. We find that pairwise distance based default guide-trees sometimes outperform evolutionary guide-trees, as measured by structure derived reference alignments. However, default guide-trees fall way short of the optimum attainable scores. On average chained guide-trees perform better than balanced ones but are not better than default guide-trees for small alignments.Conclusions
Alignment methods that use Consistency or hidden Markov models to make alignments are less susceptible to sub-optimal guide-trees than simpler methods, that basically use conventional sequence alignment between profiles. The latter appear to be affected positively by evolutionary based guide-trees for difficult alignments and negatively for easy alignments. One phylogeny aware alignment program can strongly discriminate between good and bad guide-trees. The results for randomly chained guide-trees improve with the number of sequences.Electronic supplementary material
The online version of this article (doi:10.1186/1471-2105-15-338) contains supplementary material, which is available to authorized users. 相似文献17.
Background
Homoeologous sequences pose a particular challenge if bacterial artificial chromosome (BAC) contigs shall be established for specific regions of an allopolyploid genome. Single nucleotide polymorphisms (SNPs) differentiating between homoeologous genomes (intergenomic SNPs) may represent a suitable screening tool for such purposes, since they do not only identify homoeologous sequences but also differentiate between them.Results
Sequence alignments between Brassica rapa (AA) and Brassica oleracea (CC) sequences mapping to corresponding regions on chromosomes A1 and C1, respectively were used to identify single nucleotide polymorphisms between the A and C genomes. A large fraction of these polymorphisms was also present in Brassica napus (AACC), an allopolyploid species that originated from hybridisation of A and C genome species. Intergenomic SNPs mapping throughout homoeologous chromosome segments spanning approximately one Mbp each were included in Illumina’s GoldenGate® Genotyping Assay and used to screen multidimensional pools of a Brassica napus bacterial artificial chromosome library with tenfold genome coverage. Based on the results of 50 SNP assays, a BAC contig for the Brassica napus A subgenome was established that spanned the entire region of interest. The C subgenome region was represented in three BAC contigs.Conclusions
This proof-of-concept study shows that sequence resources of diploid progenitor genomes can be used to deduce intergenomic SNPs suitable for multiplex polymerase chain reaction (PCR)-based screening of multidimensional BAC pools of a polyploid organism. Owing to their high abundance and ease of identification, intergenomic SNPs represent a versatile tool to establish BAC contigs for homoeologous regions of a polyploid genome.Electronic supplementary material
The online version of this article (doi:10.1186/1471-2164-15-560) contains supplementary material, which is available to authorized users. 相似文献18.
Florian Plaza Onate Jean-Michel Batto Catherine Juste Jehane Fadlallah Cyrielle Fougeroux Doriane Gouas Nicolas Pons Sean Kennedy Florence Levenez Joel Dore S Dusko Ehrlich Guy Gorochov Martin Larsen 《BMC genomics》2015,16(1)
Background
The biological and clinical consequences of the tight interactions between host and microbiota are rapidly being unraveled by next generation sequencing technologies and sophisticated bioinformatics, also referred to as microbiota metagenomics. The recent success of metagenomics has created a demand to rapidly apply the technology to large case–control cohort studies and to studies of microbiota from various habitats, including habitats relatively poor in microbes. It is therefore of foremost importance to enable a robust and rapid quality assessment of metagenomic data from samples that challenge present technological limits (sample numbers and size). Here we demonstrate that the distribution of overlapping k-mers of metagenome sequence data predicts sequence quality as defined by gene distribution and efficiency of sequence mapping to a reference gene catalogue.Results
We used serial dilutions of gut microbiota metagenomic datasets to generate well-defined high to low quality metagenomes. We also analyzed a collection of 52 microbiota-derived metagenomes. We demonstrate that k-mer distributions of metagenomic sequence data identify sequence contaminations, such as sequences derived from “empty” ligation products. Of note, k-mer distributions were also able to predict the frequency of sequences mapping to a reference gene catalogue not only for the well-defined serial dilution datasets, but also for 52 human gut microbiota derived metagenomic datasets.Conclusions
We propose that k-mer analysis of raw metagenome sequence reads should be implemented as a first quality assessment prior to more extensive bioinformatics analysis, such as sequence filtering and gene mapping. With the rising demand for metagenomic analysis of microbiota it is crucial to provide tools for rapid and efficient decision making. This will eventually lead to a faster turn-around time, improved analytical quality including sample quality metrics and a significant cost reduction. Finally, improved quality assessment will have a major impact on the robustness of biological and clinical conclusions drawn from metagenomic studies.Electronic supplementary material
The online version of this article (doi:10.1186/s12864-015-1406-7) contains supplementary material, which is available to authorized users. 相似文献19.
Dario Copetti Jianwei Zhang Moaine El Baidouri Dongying Gao Jun Wang Elena Barghini Rosa M. Cossu Angelina Angelova Carlos E. Maldonado L. Stefan Roffler Hajime Ohyanagi Thomas Wicker Chuanzhu Fan Andrea Zuccolo Mingsheng Chen Antonio Costa de Oliveira Bin Han Robert Henry Yue-ie Hsing Nori Kurata Wen Wang Scott A. Jackson Olivier Panaud Rod A. Wing 《BMC genomics》2015,16(1)