Ensembl 2007

Genome Expression Pathway Analysis Tool--analysis and visualization of microarray gene expression data under genomic, proteomic and metabolic context

Background

Regulation of gene expression is relevant to many areas of biology and medicine, in the study of treatments, diseases, and developmental stages. Microarrays can be used to measure the expression level of thousands of mRNAs at the same time, allowing insight into or comparison of different cellular conditions. The data derived out of microarray experiments is highly dimensional and often noisy, and interpretation of the results can get intricate. Although programs for the statistical analysis of microarray data exist, most of them lack an integration of analysis results and biological interpretation.

Results

We have developed GEPAT, Genome Expression Pathway Analysis Tool, offering an analysis of gene expression data under genomic, proteomic and metabolic context. We provide an integration of statistical methods for data import and data analysis together with a biological interpretation for subsets of probes or single probes on the chip. GEPAT imports various types of oligonucleotide and cDNA array data formats. Different normalization methods can be applied to the data, afterwards data annotation is performed. After import, GEPAT offers various statistical data analysis methods, as hierarchical, k-means and PCA clustering, a linear model based t-test or chromosomal profile comparison. The results of the analysis can be interpreted by enrichment of biological terms, pathway analysis or interaction networks. Different biological databases are included, to give various information for each probe on the chip. GEPAT offers no linear work flow, but allows the usage of any subset of probes and samples as a start for a new data analysis. GEPAT relies on established data analysis packages, offers a modular approach for an easy extension, and can be run on a computer grid to allow a large number of users. It is freely available under the LGPL open source license for academic and commercial users at .

Conclusion

GEPAT is a modular, scalable and professional-grade software integrating analysis and interpretation of microarray gene expression data. An installation available for academic users can be found at .

MyHits: improvements to an interactive resource for analyzing protein sequences

The MyHits web site (http://myhits.isb-sib.ch) is an integrated service dedicated to the analysis of protein sequences. Since its first description in 2004, both the user interface and the back end of the server were improved. A number of tools (e.g. MAFFT, Jacop, Dotlet, Jalview, ESTScan) were added or updated to improve the usability of the service. The MySQL schema and its associated API were revamped and the database engine (HitKeeper) was separated from the web interface. This paper summarizes the current status of the server, with an emphasis on the new services.

A revised nomenclature for the human and rodent alpha-tubulin gene family

An essential component of microtubules, alpha-tubulin is also a multigene family in many species. An orthology-based nomenclature for this gene family has previously been difficult to assign due to incomplete genome builds and the high degree of sequence similarity between members of this family. Using the current genome builds, sequence analysis of human, mouse, and rat alpha-tubulin genes has enabled an updated nomenclature to be generated. This revised nomenclature provides a unified language for the discussion of these genes in mammalian species; it has been approved by the gene nomenclature committees of the three species and is supported by researchers in the field.

CARGO: a web portal to integrate customized biological information

There is a huge quantity of information generated in Life Sciences, and it is dispersed in many databases and repositories. Despite the broad availability of the information, there is a great demand for methods that are able to look for, gather and display distributed data in a standardized and friendly way. CARGO (Cancer And Related Genes Online) is a configurable biological web portal designed as a tool to facilitate, integrate and visualize results from Internet resources, independently of their native format or access method. Through the use of small agents, called widgets, supported by a Rich Internet Application (RIA) paradigm based on AJAX, CARGO provides pieces of minimal, relevant and descriptive biological information. The tool is designed to be used by experimental biologists with no training in bioinformatics. In the current state, the system presents a list of human cancer genes. Available at http://cargo.bioinfo.cnio.es.

Evolutionary and biomedical insights from the rhesus macaque genome

The rhesus macaque (Macaca mulatta) is an abundant primate species that diverged from the ancestors of Homo sapiens about 25 million years ago. Because they are genetically and physiologically similar to humans, rhesus monkeys are the most widely used nonhuman primate in basic and applied biomedical research. We determined the genome sequence of an Indian-origin Macaca mulatta female and compared the data with chimpanzees and humans to reveal the structure of ancestral primate genomes and to identify evidence for positive selection and lineage-specific expansions and contractions of gene families. A comparison of sequences from individual animals was used to investigate their underlying genetic diversity. The complete description of the macaque genome blueprint enhances the utility of this animal model for biomedical research and improves our understanding of the basic biology of the species.

Comparative genomics and experimental promoter analysis reveal functional liver-specific elements in mammalian hepatic lipase genes

BACKGROUND

Mammalian hepatic lipase (HL) genes are transcribed almost exclusively in hepatocytes. The basis for this liver-restricted expression is not completely understood. We hypothesized that the responsible cis-acting elements are conserved among mammalian HL genes. To identify these elements, we made a genomic comparison of 30 kb of 5'-flanking region of the rat, mouse, rhesus monkey, and human HL genes. The in silico data were verified by promoter-reporter assays in transfected hepatoma HepG2 and non-hepatoma HeLa cells using serial 5'-deletions of the rat HL (-2287/+9) and human HL (-685/+13) promoter region.

RESULTS

Highly conserved elements were present at the proximal promoter region, and at 14 and 22 kb upstream of the transcriptional start site. Both of these upstream elements increased transcriptional activity of the human HL (-685/+13) promoter region 2-3 fold. Within the proximal HL promoter region, conserved clusters of transcription factor binding sites (TFBS) were identified at -240/-200 (module A), -80/-40 (module B), and -25/+5 (module C) by the rVista software. In HepG2 cells, modules B and C, but not module A, were important for basal transcription. Module B contains putative binding sites for hepatocyte nuclear factors HNF1alpha. In the presence of module B, transcription from the minimal HL promoter was increased 1.5-2 fold in HepG2 cells, but inhibited 2-4 fold in HeLa cells.

CONCLUSION

Our data demonstrate that searching for conserved non-coding sequences by comparative genomics is a valuable tool in identifying candidate enhancer elements. With this approach, we found two putative enhancer elements in the far upstream region of the HL gene. In addition, we obtained evidence that the -80/-40 region of the HL gene is responsible for enhanced HL promoter activity in hepatoma cells, and for silencing HL promoter activity in non-liver cells.

IDR knowledge base for primary immunodeficiencies

Background

The ImmunoDeficiency Resource (IDR) is a knowledge base for the integration of the clinical, biochemical, genetic, genomic, proteomic, structural, and computational data of primary immunodeficiencies. The need for the IDR arises from the lack of structured and systematic information about primary immunodeficiencies on the Internet, and from the lack of a common platform which enables doctors, researchers, students, nurses and patients to find out validated information about these diseases.

Description

The IDR knowledge base, first released in 1999, has grown substantially. It contains information for 158 diseases, both from a clinical as well as molecular point of view. The database and the user interface have been reformatted. This new IDR release has a richer and more complete breadth, depth and scope. The service provides the most complete and up-to-date dataset. The IDR has been integrated with several internal and external databases and services. The contents of the IDR are validated and selected for different types of users (doctors, nurses, researchers and students, as well as patients and their families). The search engine has been improved and allows either a detailed or a broad search from a simple user interface.

Conclusion

The IDR is the first knowledge base specifically designed to capture in a systematic and validated way both clinical and molecular information for primary immunodeficiencies. The service is freely available at http://bioinf.uta.fi/idr and is regularly updated. The IDR facilitates primary immunodeficiencies informatics and helps to parameterise in silico modelling of these diseases. The IDR is useful also as an advanced education tool for medical students, and physicians.

A new look towards BAC-based array CGH through a comprehensive comparison with oligo-based array CGH

BACKGROUND

Currently, two main technologies are used for screening of DNA copy number; the BAC (Bacterial Artificial Chromosome) and the recently developed oligonucleotide-based CGH (Chromosomal Comparative Genomic Hybridization) arrays which are capable of detecting small genomic regions with amplification or deletion. The correlation as well as the discriminative power of these platforms has never been compared statistically on a significant set of human patient samples.

RESULTS

In this paper, we present an exhaustive comparison between the two CGH platforms, undertaken at two independent sites using the same batch of DNA from 19 advanced prostate cancers. The comparison was performed directly on the raw data and a significant correlation was found between the two platforms. The correlation was greatly improved when the data were averaged over large chromosomic regions using a segmentation algorithm. In addition, this analysis has enabled the development of a statistical model to discriminate BAC outliers that might indicate microevents. These microevents were validated by the oligo platform results.

CONCLUSION

This article presents a genome-wide statistical validation of the oligo array platform on a large set of patient samples and demonstrates statistically its superiority over the BAC platform for the Identification of chromosomic events. Taking advantage of a large set of human samples treated by the two technologies, a statistical model has been developed to show that the BAC platform could also detect microevents.

UniRef: comprehensive and non-redundant UniProt reference clusters

MOTIVATION

Redundant protein sequences in biological databases hinder sequence similarity searches and make interpretation of search results difficult. Clustering of protein sequence space based on sequence similarity helps organize all sequences into manageable datasets and reduces sampling bias and overrepresentation of sequences.

RESULTS

The UniRef (UniProt Reference Clusters) provide clustered sets of sequences from the UniProt Knowledgebase (UniProtKB) and selected UniProt Archive records to obtain complete coverage of sequence space at several resolutions while hiding redundant sequences. Currently covering >4 million source sequences, the UniRef100 database combines identical sequences and subfragments from any source organism into a single UniRef entry. UniRef90 and UniRef50 are built by clustering UniRef100 sequences at the 90 or 50% sequence identity levels. UniRef100, UniRef90 and UniRef50 yield a database size reduction of approximately 10, 40 and 70%, respectively, from the source sequence set. The reduced redundancy increases the speed of similarity searches and improves detection of distant relationships. UniRef entries contain summary cluster and membership information, including the sequence of a representative protein, member count and common taxonomy of the cluster, the accession numbers of all the merged entries and links to rich functional annotation in UniProtKB to facilitate biological discovery. UniRef has already been applied to broad research areas ranging from genome annotation to proteomics data analysis.

AVAILABILITY

UniRef is updated biweekly and is available for online search and retrieval at http://www.uniprot.org, as well as for download at ftp://ftp.uniprot.org/pub/databases/uniprot/uniref.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Non-coding sequence retrieval system for comparative genomic analysis of gene regulatory elements

Background

Completion of the human genome sequence along with other species allows for greater understanding of the biochemical mechanisms and processes that govern healthy as well as diseased states. The large size of the genome sequences has made them difficult to study using traditional methods. There are many studies focusing on the protein coding sequences, however, not much is known about the function of non-coding regions of the genome. It has been demonstrated that parts of the non-coding region play a critical role as gene regulatory elements. Enhancers that regulate transcription processes have been found in intergenic regions. Furthermore, it is observed that regulatory elements found in non-coding regions are highly conserved across different species. However, the analysis of these regulatory elements is not as straightforward as it may first seem. The development of a centralized resource that allows for the quick and easy retrieval of non-coding sequences from multiple species and is capable of handing multi-gene queries is critical for the analysis of non-coding sequences. Here we describe the development of a web-based non-coding sequence retrieval system.

Results

This paper presents a Non-Coding Sequences Retrieval System (NCSRS). The NCSRS is a web-based bioinformatics tool that performs fast and convenient retrieval of non-coding and coding sequences from multiple species related to a specific gene or set of genes. This tool has compiled resources from multiple sources into one easy to use and convenient web based interface. With no software installation necessary, the user needs only internet access to use this tool.

Conclusion

The unique features of this tool will be very helpful for those studying gene regulatory elements that exist in non-coding regions. The web based application can be accessed on the internet at: .

Quantification of ortholog losses in insects and vertebrates

BACKGROUND

The increasing number of sequenced insect and vertebrate genomes of variable divergence enables refined comparative analyses to quantify the major modes of animal genome evolution and allows tracing of gene genealogy (orthology) and pinpointing of gene extinctions (losses), which can reveal lineage-specific traits.

RESULTS

To consistently quantify losses of orthologous groups of genes, we compared the gene repertoires of five vertebrates and five insects, including honeybee and Tribolium beetle, that represent insect orders outside the previously sequenced Diptera. We found hundreds of lost Urbilateria genes in each of the lineages and assessed their phylogenetic origin. The rate of losses correlates well with the species' rates of molecular evolution and radiation times, without distinction between insects and vertebrates, indicating their stochastic nature. Remarkably, this extends to the universal single-copy orthologs, losses of dozens of which have been tolerated in each species. Nevertheless, the propensity for loss differs substantially among genes, where roughly 20% of the orthologs have an 8-fold higher chance of becoming extinct. Extrapolation of our data also suggests that the Urbilateria genome contained more than 7,000 genes.

CONCLUSION

Our results indicate that the seemingly higher number of observed gene losses in insects can be explained by their two- to three-fold higher evolutionary rate. Despite the profound effect of many losses on cellular machinery, overall, they seem to be guided by neutral evolution.

On the association between chromosomal rearrangements and genic evolution in humans and chimpanzees

BACKGROUND

The role that chromosomal rearrangements might have played in the speciation processes that have separated the lineages of humans and chimpanzees has recently come into the spotlight. To date, however, results are contradictory. Here we revisit this issue by making use of the available human and chimpanzee genome sequence to study the relationship between chromosomal rearrangements and rates of DNA sequence evolution.

RESULTS

Contrary to previous findings for this pair of species, we show that genes located in the rearranged chromosomes that differentiate the genomes of humans and chimpanzees, especially genes within rearrangements themselves, present lower divergence than genes elsewhere in the genome. Still, there are considerable differences between individual chromosomes. Chromosome 4, in particular, presents higher divergence in genes located within its rearrangement.

CONCLUSION

A first conclusion of our analysis is that divergence is lower for genes located in rearranged chromosomes than for those in colinear chromosomes. We also report that non-coding regions within rearranged regions tend to have lower divergence than non-coding regions outside them. These results suggest an association between chromosomal rearrangements and lower non-coding divergence that has not been reported before, even if some chromosomes do not follow this trend and could be potentially associated with a speciation episode. In summary, without excluding it, our results suggest that chromosomal speciation has not been common along the human and chimpanzee lineage.