Bacterial comparative genomics

A report on 'Genomes 2004: International Conference on the Analysis of Microbial and Other Genomes', Hinxton, UK, 14-17 April 2004.     

GECO--linear visualization for comparative genomics

In order to understand and interpret phylogenetic and functional relationships between multiple prokaryotic species, qualitative and quantitative data must be correlated and displayed. GECO allows linear visualization of multiple genomes using a client/server based approach by dynamically creating .png- or .pdf-formatted images. It is able to display ortholog relations calculated using BLASTCLUST by color coding ortholog representations. Irregularities on the genomic level can be identified by anomalous G/C composition. Thus, this software will enable researchers to detect horizontally transferred genes, pseudogenes and insertions/deletions in related microbial genomes. AVAILABILITY: http://bioinfo.mikrobio.med.uni-giessen.de/geco2/GecoMainServlet     

Datasets for evolutionary comparative genomics

Many decisions about genome sequencing projects are directed by perceived gaps in the tree of life, or towards model organisms. With the goal of a better understanding of biology through the lens of evolution, however, there are additional genomes that are worth sequencing. One such rationale for whole-genome sequencing is discussed here, along with other important strategies for understanding the phenotypic divergence of species.     

Datasets for evolutionary comparative genomics

Many decisions about genome sequencing projects are directed by perceived gaps in the tree of life, or towards model organisms. With the goal of a better understanding of biology through the lens of evolution, however, there are additional genomes that are worth sequencing. One such rationale for whole-genome sequencing is discussed here, along with other important strategies for understanding the phenotypic divergence of species.     

The Princeton Protein Orthology Database (P-POD): a comparative genomics analysis tool for biologists

Many biological databases that provide comparative genomics information and tools are now available on the internet. While certainly quite useful, to our knowledge none of the existing databases combine results from multiple comparative genomics methods with manually curated information from the literature. Here we describe the Princeton Protein Orthology Database (P-POD, http://ortholog.princeton.edu), a user-friendly database system that allows users to find and visualize the phylogenetic relationships among predicted orthologs (based on the OrthoMCL method) to a query gene from any of eight eukaryotic organisms, and to see the orthologs in a wider evolutionary context (based on the Jaccard clustering method). In addition to the phylogenetic information, the database contains experimental results manually collected from the literature that can be compared to the computational analyses, as well as links to relevant human disease and gene information via the OMIM, model organism, and sequence databases. Our aim is for the P-POD resource to be extremely useful to typical experimental biologists wanting to learn more about the evolutionary context of their favorite genes. P-POD is based on the commonly used Generic Model Organism Database (GMOD) schema and can be downloaded in its entirety for installation on one's own system. Thus, bioinformaticians and software developers may also find P-POD useful because they can use the P-POD database infrastructure when developing their own comparative genomics resources and database tools.     

Comprehensive splice-site analysis using comparative genomics

We have collected over half a million splice sites from five species-Homo sapiens, Mus musculus, Drosophila melanogaster, Caenorhabditis elegans and Arabidopsis thaliana-and classified them into four subtypes: U2-type GT-AG and GC-AG and U12-type GT-AG and AT-AC. We have also found new examples of rare splice-site categories, such as U12-type introns without canonical borders, and U2-dependent AT-AC introns. The splice-site sequences and several tools to explore them are available on a public website (SpliceRack). For the U12-type introns, we find several features conserved across species, as well as a clustering of these introns on genes. Using the information content of the splice-site motifs, and the phylogenetic distance between them, we identify: (i) a higher degree of conservation in the exonic portion of the U2-type splice sites in more complex organisms; (ii) conservation of exonic nucleotides for U12-type splice sites; (iii) divergent evolution of C.elegans 3' splice sites (3'ss) and (iv) distinct evolutionary histories of 5' and 3'ss. Our study proves that the identification of broad patterns in naturally-occurring splice sites, through the analysis of genomic datasets, provides mechanistic and evolutionary insights into pre-mRNA splicing.     

Ensembl 2002: accommodating comparative genomics

The Ensembl (http://www.ensembl.org/) database project provides a bioinformatics framework to organise biology around the sequences of large genomes. It is a comprehensive source of stable automatic annotation of human, mouse and other genome sequences, available as either an interactive web site or as flat files. Ensembl also integrates manually annotated gene structures from external sources where available. As well as being one of the leading sources of genome annotation, Ensembl is an open source software engineering project to develop a portable system able to handle very large genomes and associated requirements. These range from sequence analysis to data storage and visualisation and installations exist around the world in both companies and at academic sites. With both human and mouse genome sequences available and more vertebrate sequences to follow, many of the recent developments in Ensembl have focusing on developing automatic comparative genome analysis and visualisation.     

Accelerating comparative genomics using parallel computing

In the past decade there has been an increase in the number of completely sequenced genomes due to the race of multibillion-dollar genome-sequencing projects. The enormous biological sequence data thus flooding into the sequence databases necessitates the development of efficient tools for comparative genome sequence analysis. The information deduced by such analysis has various applications viz. structural and functional annotation of novel genes and proteins, finding gene order in the genome, gene fusion studies, constructing metabolic pathways etc. Such study also proves invaluable for pharmaceutical industries, such as in silico drug target identification and new drug discovery. There are various sequence analysis tools available for mining such useful information of which FASTA and Smith-Waterman algorithms are widely used. However, analyzing large datasets of genome sequences using the above codes seems to be impractical on uniprocessor machines. Hence there is a need for improving the performance of the above popular sequence analysis tools on parallel cluster computers. Performance of the Smith-Waterman (SSEARCH) and FASTA programs were studied on PARAM 10000, a parallel cluster of workstations designed and developed in-house. FASTA and SSEARCH programs, which are available from the University of Virginia, were ported on PARAM and were optimized. In this era of high performance computing, where the paradigm is shifting from conventional supercomputers to the cost-effective general-purpose cluster of workstations and PCs, this study finds extreme relevance. Good performance of sequence analysis tools on a cluster of workstations was demonstrated, which is important for accelerating identification of novel genes and drug targets by screening large databases.     

Computational tools for Brassica-Arabidopsis comparative genomics

Recent advances, such as the availability of extensive genome survey sequence (GSS) data and draft physical maps, are radically transforming the means by which we can dissect Brassica genome structure and systematically relate it to the Arabidopsis model. Hitherto, our view of the co-linearities between these closely related genomes had been largely inferred from comparative RFLP data, necessitating substantial interpolation and expert interpretation. Sequencing of the Brassica rapa genome by the Multinational Brassica Genome Project will, however, enable an entirely computational approach to this problem. Meanwhile we have been developing databases and bioinformatics tools to support our work in Brassica comparative genomics, including a recently completed draft physical map of B. rapa integrated with anchor probes derived from the Arabidopsis genome sequence. We are also exploring new ways to display the emerging Brassica-Arabidopsis sequence homology data. We have mapped all publicly available Brassica sequences in silico to the Arabidopsis TIGR v5 genome sequence and published this in the ATIDB database that uses Generic Genome Browser (GBrowse). This in silico approach potentially identifies all paralogous sequences and so we colour-code the significance of the mappings and offer an integrated, real-time multiple alignment tool to partition them into paralogous groups. The MySQL database driving GBrowse can also be directly interrogated, using the powerful API offered by the Perl BioColon, two colonsDBColon, two colonsGFF methods, facilitating a wide range of data-mining possibilities.     

灵长类比较基因组学的研究进展

随着人类和黑猩猩全基因组测序工作宣布完成,以及其他灵长类基因组测序工作的逐步开展,目前已经积累了大量的灵长类基因组数据,一个崭新的研究领域——灵长类比较基因组学应运而生。该文主要通过对人类和其他非人灵长类系统关系和基因组结构的比较,从系统进化、基因组结构和基因表达调控等方面评述该领域的研究进展,阐述人类、黑猩猩与其他非人灵长类之间的主要生物学差异,揭示人类进化的生物学机制。     

Low-pass sequencing for microbial comparative genomics

Background  

We studied four extremely halophilic archaea by low-pass shotgun sequencing: (1) the metabolically versatile Haloarcula marismortui; (2) the non-pigmented Natrialba asiatica; (3) the psychrophile Halorubrum lacusprofundi and (4) the Dead Sea isolate Halobaculum gomorrense. Approximately one thousand single pass genomic sequences per genome were obtained. The data were analyzed by comparative genomic analyses using the completed Halobacterium sp. NRC-1 genome as a reference. Low-pass shotgun sequencing is a simple, inexpensive, and rapid approach that can readily be performed on any cultured microbe.     

The latest buzz in comparative genomics

A second species of fruit fly has just been added to the growing list of organisms with complete and annotated genome sequences. The publication of the Drosophila pseudoobscura sequence provides a snapshot of how genomes have changed over tens of millions of years and sets the stage for the analysis of more fly genomes.     

Gramene,a tool for grass genomics

Gramene (http://www.gramene.org) is a comparative genome mapping database for grasses and a community resource for rice (Oryza sativa). It combines a semi-automatically generated database of cereal genomic and expressed sequence tag sequences, genetic maps, map relations, and publications, with a curated database of rice mutants (genes and alleles), molecular markers, and proteins. Gramene curators read and extract detailed information from published sources, summarize that information in a structured format, and establish links to related objects both inside and outside the database, providing seamless connections between independent sources of information. Genetic, physical, and sequence-based maps of rice serve as the fundamental organizing units and provide a common denominator for moving across species and genera within the grass family. Comparative maps of rice, maize (Zea mays), sorghum (Sorghum bicolor), barley (Hordeum vulgare), wheat (Triticum aestivum), and oat (Avena sativa) are anchored by a set of curated correspondences. In addition to sequence-based mappings found in comparative maps and rice genome displays, Gramene makes extensive use of controlled vocabularies to describe specific biological attributes in ways that permit users to query those domains and make comparisons across taxonomic groups. Proteins are annotated for functional significance using gene ontology terms that have been adopted by numerous model species databases. Genetic variants including phenotypes are annotated using plant ontology terms common to all plants and trait ontology terms that are specific to rice. In this paper, we present a brief overview of the search tools available to the plant research community in Gramene.