MISHIMA - a new method for high speed multiple alignment of nucleotide sequences of bacterial genome scale data

Background  

Large nucleotide sequence datasets are becoming increasingly common objects of comparison. Complete bacterial genomes are reported almost everyday. This creates challenges for developing new multiple sequence alignment methods. Conventional multiple alignment methods are based on pairwise alignment and/or progressive alignment techniques. These approaches have performance problems when the number of sequences is large and when dealing with genome scale sequences.     

Estimating recombination rates from population-genetic data

Obtaining an accurate measure of how recombination rates vary across the genome has implications for understanding the molecular basis of recombination, its evolutionary significance and the distribution of linkage disequilibrium in natural populations. Although measuring the recombination rate is experimentally challenging, good estimates can be obtained by applying population-genetic methods to DNA sequences taken from natural populations. Statistical methods are now providing insights into the nature and scale of variation in the recombination rate, particularly in humans. Such knowledge will become increasingly important owing to the growing use of population-genetic methods in biomedical research.     

Assignment of protein function in the postgenomic era

Genome sequencing projects have provided researchers with an unprecedented boon of molecular information that promises to revolutionize our understanding of life and lead to new treatments of its disorders. However, genome sequences alone offer only limited insights into the biochemical pathways that determine cell and tissue function. These complex metabolic and signaling networks are largely mediated by proteins. The vast number of uncharacterized proteins found in prokaryotic and eukaryotic systems suggests that our knowledge of cellular biochemistry is far from complete. Here, we highlight a new breed of 'postgenomic' methods that aim to assign functions to proteins through the integrated application of chemical and biological techniques.     

Estimation of protein coding density in a corpus of DNA sequence data.

A number of experimental methods have been reported for estimating the number of genes in a genome, or the closely related coding density of a genome, defined as the fraction of base pairs in codons. Recently, DNA sequence data representative of the genome as a whole have become available for several organisms, making the problem of estimating coding density amenable to sequence analytic methods. Estimates of coding density for a single genome vary widely, so that methods with characterized error bounds have become increasingly desirable. We present a method to estimate the protein coding density in a corpus of DNA sequence data, in which a 'coding statistic' is calculated for a large number of windows of the sequence under study, and the distribution of the statistic is decomposed into two normal distributions, assumed to be the distributions of the coding statistic in the coding and noncoding fractions of the sequence windows. The accuracy of the method is evaluated using known data and application is made to the yeast chromosome III sequence and to C. elegans cosmid sequences. It can also be applied to fragmentary data, for example a collection of short sequences determined in the course of STS mapping.     

Apollo: a sequence annotation editor

The well-established inaccuracy of purely computational methods for annotating genome sequences necessitates an interactive tool to allow biological experts to refine these approximations by viewing and independently evaluating the data supporting each annotation. Apollo was developed to meet this need, enabling curators to inspect genome annotations closely and edit them. FlyBase biologists successfully used Apollo to annotate the Drosophila melanogaster genome and it is increasingly being used as a starting point for the development of customized annotation editing tools for other genome projects.     

Considering transposable element diversification in de novo annotation approaches

Transposable elements (TEs) are mobile, repetitive DNA sequences that are almost ubiquitous in prokaryotic and eukaryotic genomes. They have a large impact on genome structure, function and evolution. With the recent development of high-throughput sequencing methods, many genome sequences have become available, making possible comparative studies of TE dynamics at an unprecedented scale. Several methods have been proposed for the de novo identification of TEs in sequenced genomes. Most begin with the detection of genomic repeats, but the subsequent steps for defining TE families differ. High-quality TE annotations are available for the Drosophila melanogaster and Arabidopsis thaliana genome sequences, providing a solid basis for the benchmarking of such methods. We compared the performance of specific algorithms for the clustering of interspersed repeats and found that only a particular combination of algorithms detected TE families with good recovery of the reference sequences. We then applied a new procedure for reconciling the different clustering results and classifying TE sequences. The whole approach was implemented in a pipeline using the REPET package. Finally, we show that our combined approach highlights the dynamics of well defined TE families by making it possible to identify structural variations among their copies. This approach makes it possible to annotate TE families and to study their diversification in a single analysis, improving our understanding of TE dynamics at the whole-genome scale and for diverse species.     

Paleogenomics in vertebrates, or the recovery of lost genomes from the mist of time

Knowledge of the structure of ancestral genomes provides the basis of a new framework to better represent and interpret results from genomic and evolutionary studies. Because these ancestors lived tens of hundreds of million years ago, this knowledge will inevitably take the form of abstract representations, reconstructed on the basis both of experimental evidence collected on extant genomes and of our understanding of evolutionary processes. This is the field of Paleogenomics, a young discipline that is providing an increasingly precise picture of our ancestral vertebrate genomes based on cytogenetic data, genome sequences and new algorithmic developments. Many recent studies have focused on the ancestral placental mammal and teleost fish genomes, although the outlines of even more distant pre-vertebrate ancestors are being reported.     

Gene's Functional Arrangement as a Measure of thePhylogenetic Relationships of Microorganisms

With the development of genome sequencing more whole genomes of microorganisms were completed, many methods wereintroduced to reconstruct the phylogenetic tree of those microorganismswith the information extracted from the whole genomes through variousways of transforming or mapping the whole genome sequences into otherforms which can describe the evolutionary distance in a new way. We thinkit might be possible that there exists information buried in the wholegenome transferred along lineage, which remains stable and is moreessential than sequence conservation of individual genes or the arrangementof some genes of a selected set. We need to find one measurement that caninvolve as many phylogenetic features as possible that are beyond thegenome sequence itself. We converted each genome sequence of themicroorganisms into another linear sequence to represent the functionalstructure of the sequence, and we used a new information function tocalculate the discrepancy of sequences and to get one distance matrix of thegenomes, and built one phylogenetic tree with a neighbor joining method.The resulting tree shows that the major lineages are consistent with theresult based on their 16srRNA sequences. Our method discovered onephylogenetic feature derived from the genome sequences and the encodedgenes that can rebuild the phylogenetic tree correctly. The mapping of onegenome sequence to its new form representing the relative positions of thefunctional genes provides a new way to measure the phylogeneticrelationships, and with the more specific classification of gene functions theresult could be more sensitive.     

Information overload: assigning genetic functionality in the age of genomics and large-scale screening

As more and more genome sequences are completed, it is becoming increasingly evident that our understanding of the function of most bacterial gene products is lacking. This is frustrating, particularly in the study of pathogens, where an understanding of the role of individual gene products would probably facilitate the development of novel antimicrobials and vaccines. Recently, we devised a technique known as virulence-attenuated pool (VAP) screening to help assign genetic functionality to gene products that the pathogen Vibrio cholerae requires for colonization. This screen and potential new applications of the VAP technique are discussed here.     

Inference of functional properties from large-scale analysis of enzyme superfamilies

As increasingly large amounts of data from genome and other sequencing projects become available, new approaches are needed to determine the functions of the proteins these genes encode. We show how large-scale computational analysis can help to address this challenge by linking functional information to sequence and structural similarities using protein similarity networks. Network analyses using three functionally diverse enzyme superfamilies illustrate the use of these approaches for facile updating and comparison of available structures for a large superfamily, for creation of functional hypotheses for metagenomic sequences, and to summarize the limits of our functional knowledge about even well studied superfamilies.     

Genomic Treasure Troves: Complete Genome Sequencing of Herbarium and Insect Museum Specimens

Unlocking the vast genomic diversity stored in natural history collections would create unprecedented opportunities for genome-scale evolutionary, phylogenetic, domestication and population genomic studies. Many researchers have been discouraged from using historical specimens in molecular studies because of both generally limited success of DNA extraction and the challenges associated with PCR-amplifying highly degraded DNA. In today''s next-generation sequencing (NGS) world, opportunities and prospects for historical DNA have changed dramatically, as most NGS methods are actually designed for taking short fragmented DNA molecules as templates. Here we show that using a standard multiplex and paired-end Illumina sequencing approach, genome-scale sequence data can be generated reliably from dry-preserved plant, fungal and insect specimens collected up to 115 years ago, and with minimal destructive sampling. Using a reference-based assembly approach, we were able to produce the entire nuclear genome of a 43-year-old Arabidopsis thaliana (Brassicaceae) herbarium specimen with high and uniform sequence coverage. Nuclear genome sequences of three fungal specimens of 22–82 years of age (Agaricus bisporus, Laccaria bicolor, Pleurotus ostreatus) were generated with 81.4–97.9% exome coverage. Complete organellar genome sequences were assembled for all specimens. Using de novo assembly we retrieved between 16.2–71.0% of coding sequence regions, and hence remain somewhat cautious about prospects for de novo genome assembly from historical specimens. Non-target sequence contaminations were observed in 2 of our insect museum specimens. We anticipate that future museum genomics projects will perhaps not generate entire genome sequences in all cases (our specimens contained relatively small and low-complexity genomes), but at least generating vital comparative genomic data for testing (phylo)genetic, demographic and genetic hypotheses, that become increasingly more horizontal. Furthermore, NGS of historical DNA enables recovering crucial genetic information from old type specimens that to date have remained mostly unutilized and, thus, opens up a new frontier for taxonomic research as well.     

Sequence organization of the mitochondrial genome of yeast--a review

We have compiled the available primary structural data for the mitochondrial genome of Saccharomyces cerevisiae and have estimated the size of the remaining gaps, which represent 12-13% of the genome. The lengths of sequenced regions and of gaps lead to a new assessment of genome sizes; these range (in round figures) from 85 000 bp for the long genomes, to 78 000 bp for the short genomes, to 74 000 bp for the supershort genome of Saccharomyces carlsbergensis. These values are 8-11% higher than those previously estimated from restriction fragments. Interstrain differences concern not only facultative intervening sequences (introns) and mini-inserts, but also insertions/deletions in intergenic sequences. The primary structure appears to be extremely conserved in genes and ori sequences, and highly conserved in intergenic sequences. Since coding sequences represent at most 33-35% of the genome, at least two thirds of the genome are formed by noncoding and yet highly conserved sequences. The G + C level of genes or exon is 25%, and that of intronic open reading frames (ORFs) 22%; increasingly lower values are shown by intronic closed reading frames (CRFs), 20%, ori sequences, 19%, intergenic ORFs, 17.5% and intergenic sequences, 15%.     

PhyloPro: a web-based tool for the generation and visualization of phylogenetic profiles across Eukarya

SUMMARY: With increasing numbers of eukaryotic genome sequences, phylogenetic profiles of eukaryotic genes are becoming increasingly informative. Here, we introduce a new web-tool Phylopro (http://compsysbio.org/phylopro/), which uses the 120 available eukaryotic genome sequences to visualize the evolutionary trajectories of user-defined subsets of model organism genes. Applied to pathways or complexes, PhyloPro allows the user to rapidly identify core conserved elements of biological processes together with those that may represent lineage-specific innovations. PhyloPro thus provides a valuable resource for the evolutionary and comparative studies of biological systems.     

Glocal alignment: finding rearrangements during alignment

MOTIVATION: To compare entire genomes from different species, biologists increasingly need alignment methods that are efficient enough to handle long sequences, and accurate enough to correctly align the conserved biological features between distant species. The two main classes of pairwise alignments are global alignment, where one string is transformed into the other, and local alignment, where all locations of similarity between the two strings are returned. Global alignments are less prone to demonstrating false homology as each letter of one sequence is constrained to being aligned to only one letter of the other. Local alignments, on the other hand, can cope with rearrangements between non-syntenic, orthologous sequences by identifying similar regions in sequences; this, however, comes at the expense of a higher false positive rate due to the inability of local aligners to take into account overall conservation maps. RESULTS: In this paper we introduce the notion of glocal alignment, a combination of global and local methods, where one creates a map that transforms one sequence into the other while allowing for rearrangement events. We present Shuffle-LAGAN, a glocal alignment algorithm that is based on the CHAOS local alignment algorithm and the LAGAN global aligner, and is able to align long genomic sequences. To test Shuffle-LAGAN we split the mouse genome into BAC-sized pieces, and aligned these pieces to the human genome. We demonstrate that Shuffle-LAGAN compares favorably in terms of sensitivity and specificity with standard local and global aligners. From the alignments we conclude that about 9% of human/mouse homology may be attributed to small rearrangements, 63% of which are duplications.     

Genomic strategies to identify mammalian regulatory sequences

With the continuing accomplishments of the human genome project, high-throughput strategies to identify DNA sequences that are important in mammalian gene regulation are becoming increasingly feasible. In contrast to the historic, labour-intensive, wet-laboratory methods for identifying regulatory sequences, many modern approaches are heavily focused on the computational analysis of large genomic data sets. Data from inter-species genomic sequence comparisons and genome-wide expression profiling, integrated with various computational tools, are poised to contribute to the decoding of genomic sequence and to the identification of those sequences that orchestrate gene regulation. In this review, we highlight several genomic approaches that are being used to identify regulatory sequences in mammalian genomes.     

Inferring horizontal transfers in the presence of rearrangements by the minimum evolution criterion

MOTIVATION: The evolution of viruses is very rapid and in addition to local point mutations (insertion, deletion, substitution) it also includes frequent recombinations, genome rearrangements and horizontal transfer of genetic materials (HGTS). Evolutionary analysis of viral sequences is therefore a complicated matter for two main reasons: First, due to HGTs and recombinations, the right model of evolution is a network and not a tree. Second, due to genome rearrangements, an alignment of the input sequences is not guaranteed. These facts encourage developing methods for inferring phylogenetic networks that do not require aligned sequences as input. RESULTS: In this work, we present the first computational approach which deals with both genome rearrangements and horizontal gene transfers and does not require a multiple alignment as input. We formalize a new set of computational problems which involve analyzing such complex models of evolution. We investigate their computational complexity, and devise algorithms for solving them. Moreover, we demonstrate the viability of our methods on several synthetic datasets as well as four biological datasets. AVAILABILITY: The code is available from the authors upon request.     

An integrated computational pipeline and database to support whole-genome sequence annotation

We describe here our experience in annotating the Drosophila melanogaster genome sequence, in the course of which we developed several new open-source software tools and a database schema to support large-scale genome annotation. We have developed these into an integrated and reusable software system for whole-genome annotation. The key contributions to overall annotation quality are the marshalling of high-quality sequences for alignments and the design of a system with an adaptable and expandable flexible architecture.