Evidence for symmetric chromosomal inversions around the replication origin in bacteria.

BackgroundWhole-genome comparisons can provide great insight into many aspects of biology. Until recently, however, comparisons were mainly possible only between distantly related species. Complete genome sequences are now becoming available from multiple sets of closely related strains or species.ResultsBy comparing the recently completed genome sequences of Vibrio cholerae, Streptococcus pneumoniae and Mycobacterium tuberculosis to those of closely related species - Escherichia coli, Streptococcus pyogenes and Mycobacterium leprae, respectively - we have identified an unusual and previously unobserved feature of bacterial genome structure. Scatterplots of the conserved sequences (both DNA and protein) between each pair of species produce a distinct X-shaped pattern, which we call an X-alignment. The key feature of these alignments is that they have symmetry around the replication origin and terminus; that is, the distance of a particular conserved feature (DNA or protein) from the replication origin (or terminus) is conserved between closely related pairs of species. Statistically significant X-alignments are also found within some genomes, indicating that there is symmetry about the replication origin for paralogous features as well.ConclusionsThe most likely mechanism of generation of X-alignments involves large chromosomal inversions that reverse the genomic sequence symmetrically around the origin of replication. The finding of these X-alignments between many pairs of species suggests that chromosomal inversions around the origin are a common feature of bacterial genome evolution

Re-Assembly of the Genome of Francisella tularensis Subsp. holarctica OSU18

Francisella tularensis is a highly infectious human intracellular pathogen that is the causative agent of tularemia. It occurs in several major subtypes, including the live vaccine strain holarctica (type B). F. tularensis is classified as category A biodefense agent in part because a relatively small number of organisms can cause severe illness. Three complete genomes of subspecies holarctica have been sequenced and deposited in public archives, of which OSU18 was the first and the only strain for which a scientific publication has appeared [1]. We re-assembled the OSU18 strain using both de novo and comparative assembly techniques, and found that the published sequence has two large inversion mis-assemblies. We generated a corrected assembly of the entire genome along with detailed information on the placement of individual reads within the assembly. This assembly will provide a more accurate basis for future comparative studies of this pathogen

Search extension transforms Wiki into a relational system: A case for flavonoid metabolite database

<p>Abstract</p> <p>Background</p> <p>In computer science, database systems are based on the relational model founded by Edgar Codd in 1970. On the other hand, in the area of biology the word 'database' often refers to loosely formatted, very large text files. Although such bio-databases may describe conflicts or ambiguities (e.g. a protein pair do and do not interact, or unknown parameters) in a positive sense, the flexibility of the data format sacrifices a systematic query mechanism equivalent to the widely used SQL.</p> <p>Results</p> <p>To overcome this disadvantage, we propose embeddable string-search commands on a Wiki-based system and designed a half-formatted database. As proof of principle, a database of flavonoid with 6902 molecular structures from over 1687 plant species was implemented on MediaWiki, the background system of Wikipedia. Registered users can describe any information in an arbitrary format. Structured part is subject to text-string searches to realize relational operations. The system was written in PHP language as the extension of MediaWiki. All modifications are open-source and publicly available.</p> <p>Conclusion</p> <p>This scheme benefits from both the free-formatted Wiki style and the concise and structured relational-database style. MediaWiki supports multi-user environments for document management, and the cost for database maintenance is alleviated.</p

Improving Phrap-Based Assembly of the Rat Using “Reliable” Overlaps

The assembly methods used for whole-genome shotgun (WGS) data have a major impact on the quality of resulting draft genomes. We present a novel algorithm to generate a set of “reliable” overlaps based on identifying repeat k-mers. To demonstrate the benefits of using reliable overlaps, we have created a version of the Phrap assembly program that uses only overlaps from a specific list. We call this version PhrapUMD. Integrating PhrapUMD and our “reliable-overlap” algorithm with the Baylor College of Medicine assembler, Atlas, we assemble the BACs from the Rattus norvegicus genome project. Starting with the same data as the Nov. 2002 Atlas assembly, we compare our results and the Atlas assembly to the 4.3 Mb of rat sequence in the 21 BACs that have been finished. Our version of the draft assembly of the 21 BACs increases the coverage of finished sequence from 93.4% to 96.3%, while simultaneously reducing the base error rate from 4.5 to 1.1 errors per 10,000 bases. There are a number of ways of assessing the relative merits of assemblies when the finished sequence is available. If one views the overall quality of an assembly as proportional to the inverse of the product of the error rate and sequence missed, then the assembly presented here is seven times better. The UMD Overlapper with options for reliable overlaps is available from the authors at http://www.genome.umd.edu. We also provide the changes to the Phrap source code enabling it to use only the reliable overlaps

Ori-Finder: A web-based system for finding oriCs in unannotated bacterial genomes

<p>Abstract</p> <p>Background</p> <p>Chromosomal replication is the central event in the bacterial cell cycle. Identification of replication origins (<it>oriC</it>s) is necessary for almost all newly sequenced bacterial genomes. Given the increasing pace of genome sequencing, the current available software for predicting <it>oriC</it>s, however, still leaves much to be desired. Therefore, the increasing availability of genome sequences calls for improved software to identify <it>oriC</it>s in newly sequenced and unannotated bacterial genomes.</p> <p>Results</p> <p>We have developed Ori-Finder, an online system for finding <it>oriC</it>s in bacterial genomes based on an integrated method comprising the analysis of base composition asymmetry using the <it>Z</it>-curve method, distribution of DnaA boxes, and the occurrence of genes frequently close to <it>oriC</it>s. The program can also deal with unannotated genome sequences by integrating the gene-finding program ZCURVE 1.02. Output of the predicted results is exported to an HTML report, which offers convenient views on the results in both graphical and tabular formats.</p> <p>Conclusion</p> <p>A web-based system to predict replication origins of bacterial genomes has been presented here. Based on this system, <it>oriC </it>regions have been predicted for the bacterial genomes available in GenBank currently. It is hoped that Ori-Finder will become a useful tool for the identification and analysis of <it>oriC</it>s in both bacterial and archaeal genomes.</p

Safe and complete contig assembly via omnitigs

Contig assembly is the first stage that most assemblers solve when reconstructing a genome from a set of reads. Its output consists of contigs -- a set of strings that are promised to appear in any genome that could have generated the reads. From the introduction of contigs 20 years ago, assemblers have tried to obtain longer and longer contigs, but the following question was never solved: given a genome graph $G$ (e.g. a de Bruijn, or a string graph), what are all the strings that can be safely reported from $G$ as contigs? In this paper we finally answer this question, and also give a polynomial time algorithm to find them. Our experiments show that these strings, which we call omnitigs, are 66% to 82% longer on average than the popular unitigs, and 29% of dbSNP locations have more neighbors in omnitigs than in unitigs.Comment: Full version of the paper in the proceedings of RECOMB 201

Genome Assembly Has a Major Impact on Gene Content: A Comparison of Annotation in Two Bos Taurus Assemblies

Gene and SNP annotation are among the first and most important steps in analyzing a genome. As the number of sequenced genomes continues to grow, a key question is: how does the quality of the assembled sequence affect the annotations? We compared the gene and SNP annotations for two different Bos taurus genome assemblies built from the same data but with significant improvements in the later assembly. The same annotation software was used for annotating both sequences. While some annotation differences are expected even between high-quality assemblies such as these, we found that a staggering 40% of the genes (>9,500) varied significantly between assemblies, due in part to the availability of new gene evidence but primarily to genome mis-assembly events and local sequence variations. For instance, although the later assembly is generally superior, 660 protein coding genes in the earlier assembly are entirely missing from the later genome's annotation, and approximately 3,600 (15%) of the genes have complex structural differences between the two assemblies. In addition, 12–20% of the predicted proteins in both assemblies have relatively large sequence differences when compared to their RefSeq models, and 6–15% of bovine dbSNP records are unrecoverable in the two assemblies. Our findings highlight the consequences of genome assembly quality on gene and SNP annotation and argue for continued improvements in any draft genome sequence. We also found that tracking a gene between different assemblies of the same genome is surprisingly difficult, due to the numerous changes, both small and large, that occur in some genes. As a side benefit, our analyses helped us identify many specific loci for improvement in the Bos taurus genome assembly

Authorship Analysis Approaches

This chapter presents an overview of authorship analysis from multiple standpoints. It includes historical perspective, description of stylometric features, and authorship analysis techniques and their limitations