CiteULike: hpaces's bioinformatics

MEGAN analysis of metagenomic data.

DH Huson — 2008-02-14T19:21:34-00:00

Genome Res, Vol. 17, No. 3. (March 2007), pp. 377-386.

Metagenomics is the study of the genomic content of a sample of organisms obtained from a common habitat using targeted or random sequencing. Goals include understanding the extent and role of microbial diversity. The taxonomical content of such a sample is usually estimated by comparison against sequence databases of known sequences. Most published studies use the analysis of paired-end reads, complete sequences of environmental fosmid and BAC clones, or environmental assemblies. Emerging sequencing-by-synthesis technologies with very high throughput are paving the way to low-cost random "shotgun" approaches. This paper introduces MEGAN, a new computer program that allows laptop analysis of large metagenomic data sets. In a preprocessing step, the set of DNA sequences is compared against databases of known sequences using BLAST or another comparison tool. MEGAN is then used to compute and explore the taxonomical content of the data set, employing the NCBI taxonomy to summarize and order the results. A simple lowest common ancestor algorithm assigns reads to taxa such that the taxonomical level of the assigned taxon reflects the level of conservation of the sequence. The software allows large data sets to be dissected without the need for assembly or the targeting of specific phylogenetic markers. It provides graphical and statistical output for comparing different data sets. The approach is applied to several data sets, including the Sargasso Sea data set, a recently published metagenomic data set sampled from a mammoth bone, and several complete microbial genomes. Also, simulations that evaluate the performance of the approach for different read lengths are presented.

Understanding the recent evolution of the human genome: insights from human-chimpanzee genome comparisons

Hildegard Kehrer-Sawatzki — 2007-01-16T17:58:20-00:00

Human Mutation, Vol. 28, No. 2. (2007), pp. 99-130.

The sequencing of the chimpanzee genome and the comparison with its human counterpart have begun to reveal the spectrum of genetic changes that has accompanied human evolution. In addition to gross karyotypic rearrangements such as the fusion that formed human chromosome 2 and the human-specific pericentric inversions of chromosomes 1 and 18, there is considerable submicroscopic structural variation involving deletions, duplications, and inversions. Lineage-specific segmental duplications, detected by array comparative genomic hybridization and direct sequence comparison, have made a very significant contribution to this structural divergence, which is at least three-fold greater than that due to nucleotide substitutions. Since structural genomic changes may have given rise to irreversible functional differences between the diverging species, their detailed analysis could help to identify the biological processes that have accompanied speciation. To this end, interspecies comparisons have revealed numerous human-specific gains and losses of genes as well as changes in gene expression. The very considerable structural diversity (polymorphism) evident within both lineages has, however, hampered the analysis of the structural divergence between the human and chimpanzee genomes. The concomitant evaluation of genetic divergence and diversity at the nucleotide level has nevertheless served to identify many genes that have evolved under positive selection and may thus have been involved in the development of human lineage-specific traits. Genes that display signs of weak negative selection have also been identified and could represent candidate loci for complex genomic disorders. Here, we review recent progress in comparing the human and chimpanzee genomes and discuss how the differences detected have improved our understanding of the evolution of the human genome. Hum Mutat 28(2), 99-130, 2007. © 2006 Wiley-Liss, Inc.

KEGG for linking genomes to life and the environment

Minoru Kanehisa — 2007-12-13T06:01:37-00:00

Nucl. Acids Res. (12 December 2007), gkm882.

KEGG (http://www.genome.jp/kegg/) is a database of biological systems that integrates genomic, chemical and systemic functional information. KEGG provides a reference knowledge base for linking genomes to life through the process of PATHWAY mapping, which is to map, for example, a genomic or transcriptomic content of genes to KEGG reference pathways to infer systemic behaviors of the cell or the organism. In addition, KEGG provides a reference knowledge base for linking genomes to the environment, such as for the analysis of drug-target relationships, through the process of BRITE mapping. KEGG BRITE is an ontology database representing functional hierarchies of various biological objects, including molecules, cells, organisms, diseases and drugs, as well as relationships among them. KEGG PATHWAY is now supplemented with a new global map of metabolic pathways, which is essentially a combined map of about 120 existing pathway maps. In addition, smaller pathway modules are defined and stored in KEGG MODULE that also contains other functional units and complexes. The KEGG resource is being expanded to suit the needs for practical applications. KEGG DRUG contains all approved drugs in the US and Japan, and KEGG DISEASE is a new database linking disease genes, pathways, drugs and diagnostic markers. 10.1093/nar/gkm882

Vir-Mir db: prediction of viral microRNA candidate hairpins.

SC Li — 2008-05-11T15:08:43-00:00

Nucleic acids research, Vol. 36, No. Database issue. (January 2008)

MicroRNAs have been found in various organisms and play essential roles in gene expression regulation of many critical cellular processes. Large-scale computational prediction of miRNAs has been conducted for many organisms using known genomic sequences; however, there has been no such effort for the thousands of known viral genomes. Some viruses utilize existing host cellular pathways for their own benefit. Furthermore, viruses are capable of encoding miRNAs and using them to repress host genes. Thus, identifying potential miRNAs in all viral genomes would be valuable to virologists who study virus-host interactions. Based on our previously reported hairpin secondary structure and feature selection filters, we have examined the 2266 available viral genome sequences for putative miRNA hairpins and identified 33 691 hairpin candidates in 1491 genomes. Evaluation of the system performance indicated that our discovery pipeline exhibited 84.4% sensitivity. We established an interface for users to query the predicted viral miRNA hairpins based on taxonomic classification, and a host target gene prediction service based on the RNAhybrid program and the 3'-UTR gene sequences of human, mouse, rat, zebrafish, rice and Arabidopsis. The viral miRNA prediction database (Vir-Mir) can be accessed via http://alk.ibms.sinica.edu.tw.

Mapping and sequencing of structural variation from eight human genomes

Jeffrey Kidd — 2008-04-30T19:31:59-00:00

Nature, Vol. 453, No. 7191., pp. 56-64.

Poor prognosis in carcinoma is associated with a gene expression signature of aberrant PTEN tumor suppressor pathway activity.

LH Saal — 2007-11-20T16:05:43-00:00

Proc Natl Acad Sci U S A, Vol. 104, No. 18. (1 May 2007), pp. 7564-7569.

Pathway-specific therapy is the future of cancer management. The oncogenic phosphatidylinositol 3-kinase (PI3K) pathway is frequently activated in solid tumors; however, currently, no reliable test for PI3K pathway activation exists for human tumors. Taking advantage of the observation that loss of PTEN, the negative regulator of PI3K, results in robust activation of this pathway, we developed and validated a microarray gene expression signature for immunohistochemistry (IHC)-detectable PTEN loss in breast cancer (BC). The most significant signature gene was PTEN itself, indicating that PTEN mRNA levels are the primary determinant of PTEN protein levels in BC. Some PTEN IHC-positive BCs exhibited the signature of PTEN loss, which was associated to moderately reduced PTEN mRNA levels cooperating with specific types of PIK3CA mutations and/or amplification of HER2. This demonstrates that the signature is more sensitive than PTEN IHC for identifying tumors with pathway activation. In independent data sets of breast, prostate, and bladder carcinoma, prediction of pathway activity by the signature correlated significantly to poor patient outcome. Stathmin, encoded by the signature gene STMN1, was an accurate IHC marker of the signature and had prognostic significance in BC. Stathmin was also pathway-pharmacodynamic in vitro and in vivo. Thus, the signature or its components such as stathmin may be clinically useful tests for stratification of patients for anti-PI3K pathway therapy and monitoring therapeutic efficacy. This study indicates that aberrant PI3K pathway signaling is strongly associated with metastasis and poor survival across carcinoma types, highlighting the enormous potential impact on patient survival that pathway inhibition could achieve.

What is principal component analysis?

Markus Ringnér — 2008-03-09T04:13:08-00:00

Nature Biotechnology, Vol. 26, No. 3., pp. 303-304.

Ringo - an R/Bioconductor package for analyzing ChIP-chip readouts

Joern Toedling — 2007-06-27T13:35:34-00:00

BMC Bioinformatics, Vol. 8 (26 June 2007), 221.

Automated generation of heuristics for biological sequence comparison

Guy Slater — 2007-05-29T13:09:02-00:00

BMC Bioinformatics, Vol. 6, No. 1. (2005)

BACKGROUND:Exhaustive methods of sequence alignment are accurate but slow, whereas heuristic approaches run quickly, but their complexity makes them more difficult to implement. We introduce bounded sparse dynamic programming (BSDP) to allow rapid approximation to exhaustive alignment. This is used within a framework whereby the alignment algorithms are described in terms of their underlying model, to allow automated development of efficient heuristic implementations which may be applied to a general set of sequence comparison problems.RESULTS:The speed and accuracy of this approach compares favourably with existing methods. Examples of its use in the context of genome annotation are given.CONCLUSIONS:This system allows rapid implementation of heuristics approximating to many complex alignment models, and has been incorporated into the freely available sequence alignment program, exonerate.

Chaos game representation for comparison of whole genomes

Jijoy Joseph — 2007-12-22T18:31:31-00:00

BMC Bioinformatics, Vol. 7, No. 1. (2006)

BACKGROUND:Chaos game representation of genome sequences has been used for visual representation of genome sequence patterns as well as alignment-free comparisons of sequences based on oligonucleotide frequencies. However the potential of this representation for making alignment-based comparisons of whole genome sequences has not been exploited.RESULTS:We present here a fast algorithm for identifying all local alignments between two long DNA sequences using the sequence information contained in CGR points. The local alignments can be depicted graphically in a dot-matrix plot or in text form, and the significant similarities and differences between the two sequences can be identified. We demonstrate the method through comparison of whole genomes of several microbial species. Given two closely related genomes we generate information on mismatches, insertions, deletions and shuffles that differentiate the two genomes.CONCLUSION:Addition of the possibility of large scale sequence alignment to the repertoire of alignment-free sequence analysis applications of chaos game representation, positions CGR as a powerful sequence analysis tool.

The ENCODE (ENCyclopedia Of DNA Elements) Project.

E Encode — 2005-04-04T06:53:10-00:00

Science, Vol. 306, No. 5696. (22 October 2004), pp. 636-640.

The ENCyclopedia Of DNA Elements (ENCODE) Project aims to identify all functional elements in the human genome sequence. The pilot phase of the Project is focused on a specified 30 megabases (approximately 1%) of the human genome sequence and is organized as an international consortium of computational and laboratory-based scientists working to develop and apply high-throughput approaches for detecting all sequence elements that confer biological function. The results of this pilot phase will guide future efforts to analyze the entire human genome.

Identification of disulfide reductases in Campylobacterales: a bioinformatics investigation.

NO Kaakoush — 2007-12-11T09:02:25-00:00

Antonie Van Leeuwenhoek, Vol. 92, No. 4. (November 2007), pp. 429-441.

Disulfide reductases of host-colonising bacteria are involved in the expression of virulence factors, resistance to drugs, and elimination of toxic compounds. Large-scale genome analyses of 281 prokaryotes identified CXXC and CXXC-derived motifs in each microorganism. The total number of these motifs showed correlations with genome size and oxygen tolerance of the prokaryotes. Specific bioinformatic analyses served to identify putative disulfide reductases in the Campylobacterales Campylobacter jejuni, Helicobacter pylori, Wolinella succinogenes and Arcobacter butzleri which colonise the gastrointestinal tract of higher animals. Three filters applied to the genomes of these species yielded 35, 25, 28 and 34 genes, respectively, encoding proteins with the characteristics of disulfide reductases. Ten proteins were common to the four species, including four belonging to the thioredoxin system. The presence of thioredoxin reductase activities was detected in the four bacterial species by observing dithiobis-2-nitrobenzoic acid reduction with beta-nicotinamide adenine dinucleotide phosphate as cofactor. Phylogenetic analyses of the thioredoxin reductases TrxB(1) and TrxB(2) of the four Campylobacterales were performed. Their TrxB(1) proteins were more closely related to those of Firmicutes than to the corresponding proteins of other Proteobacteria. The Campylobacterales TrxB(2) proteins were closer to glutathione reductases of other organisms than to their respective TrxB(1) proteins. The phylogenetic features of the Campylobacterales thioredoxin reductases suggested a special role for these enzymes in the physiology of these bacteria.

Recent Evolutions of Multiple Sequence Alignment Algorithms

Cédric Notredame — 2007-08-31T12:29:48-00:00

PLoS Computational Biology, Vol. 3, No. 8. (1 August 2007), e123.

Using Likelihood-Free Inference to Compare Evolutionary Dynamics of the Protein Networks of H. pylori and P. falciparum

Oliver Ratmann — 2007-12-01T08:59:40-00:00

PLoS Computational Biology, Vol. 3, No. 11. (1 November 2007), e230.

Gene duplication with subsequent interaction divergence is one of the primary driving forces in the evolution of genetic systems. Yet little is known about the precise mechanisms and the role of duplication divergence in the evolution of protein networks from the prokaryote and eukaryote domains. We developed a novel, model-based approach for Bayesian inference on biological network data that centres on approximate Bayesian computation, or likelihood-free inference. Instead of computing the intractable likelihood of the protein network topology, our method summarizes key features of the network and, based on these, uses a MCMC algorithm to approximate the posterior distribution of the model parameters. This allowed us to reliably fit a flexible mixture model that captures hallmarks of evolution by gene duplication and subfunctionalization to protein interaction network data of Helicobacter pylori and Plasmodium falciparum. The 80% credible intervals for the duplication–divergence component are [0.64, 0.98] for H. pylori and [0.87, 0.99] for P. falciparum. The remaining parameter estimates are not inconsistent with sequence data. An extensive sensitivity analysis showed that incompleteness of PIN data does not largely affect the analysis of models of protein network evolution, and that the degree sequence alone barely captures the evolutionary footprints of protein networks relative to other statistics. Our likelihood-free inference approach enables a fully Bayesian analysis of a complex and highly stochastic system that is otherwise intractable at present. Modelling the evolutionary history of PIN data, it transpires that only the simultaneous analysis of several global aspects of protein networks enables credible and consistent inference to be made from available datasets. Our results indicate that gene duplication has played a larger part in the network evolution of the eukaryote than in the prokaryote, and suggests that single gene duplications with immediate divergence alone may explain more than 60% of biological network data in both domains.

MORPH: Probabilistic Alignment Combined with Hidden Markov Models of cis-Regulatory Modules

Saurabh Sinha — 2007-11-10T02:00:31-00:00

PLoS Computational Biology, Vol. 3, No. 11. (1 November 2007), e216.

The discovery and analysis of cis-regulatory modules (CRMs) in metazoan genomes is crucial for understanding the transcriptional control of development and many other biological processes. Cross-species sequence comparison holds much promise for improving computational prediction of CRMs, for elucidating their binding site composition, and for understanding how they evolve. Current methods for analyzing orthologous CRMs from multiple species rely upon sequence alignments produced by off-the-shelf alignment algorithms, which do not exploit the presence of binding sites in the sequences. We present here a unified probabilistic framework, called MORPH, that integrates the alignment task with binding site predictions, allowing more robust CRM analysis in two species. The framework sums over all possible alignments of two sequences, thus accounting for alignment ambiguities in a natural way. We perform extensive tests on orthologous CRMs from two moderately diverged species Drosophila melanogaster and D. mojavensis, to demonstrate the advantages of the new approach. We show that it can overcome certain computational artifacts of traditional alignment tools and provide a different, likely more accurate, picture of cis-regulatory evolution than that obtained from existing methods. The burgeoning field of cis-regulatory evolution, which is amply supported by the availability of many related genomes, is currently thwarted by the lack of accurate alignments of regulatory regions. Our work will fill in this void and enable more reliable analysis of CRM evolution.

Detecting Coevolution in and among Protein Domains

Chen-Hsiang Yeang — 2007-11-15T12:49:13-00:00

PLoS Computational Biology, Vol. 3, No. 11. (1 November 2007), e211.

Correlated changes of nucleic or amino acids have provided strong information about the structures and interactions of molecules. Despite the rich literature in coevolutionary sequence analysis, previous methods often have to trade off between generality, simplicity, phylogenetic information, and specific knowledge about interactions. Furthermore, despite the evidence of coevolution in selected protein families, a comprehensive screening of coevolution among all protein domains is still lacking. We propose an augmented continuous-time Markov process model for sequence coevolution. The model can handle different types of interactions, incorporate phylogenetic information and sequence substitution, has only one extra free parameter, and requires no knowledge about interaction rules. We employ this model to large-scale screenings on the entire protein domain database (Pfam). Strikingly, with 0.1 trillion tests executed, the majority of the inferred coevolving protein domains are functionally related, and the coevolving amino acid residues are spatially coupled. Moreover, many of the coevolving positions are located at functionally important sites of proteins/protein complexes, such as the subunit linkers of superoxide dismutase, the tRNA binding sites of ribosomes, the DNA binding region of RNA polymerase, and the active and ligand binding sites of various enzymes. The results suggest sequence coevolution manifests structural and functional constraints of proteins. The intricate relations between sequence coevolution and various selective constraints are worth pursuing at a deeper level.

A forest-based approach to identifying gene and gene gene interactions

Xiang Chen — 2007-11-29T08:30:32-00:00

Proceedings of the National Academy of Sciences (28 November 2007), 0709868104.

Multiple genes, gene-by-gene interactions, and gene-by-environment interactions are believed to underlie most complex diseases. However, such interactions are difficult to identify. Although there have been recent successes in identifying genetic variants for complex diseases, it still remains difficult to identify genegene and geneenvironment interactions. To overcome this difficulty, we propose a forest-based approach and a concept of variable importance. The proposed approach is demonstrated by simulation study for its validity and illustrated by a real data analysis for its use. Analyses of both real data and simulated data based on published genetic models show the effectiveness of our approach. For example, our analysis of a published data set on age-related macular degeneration (AMD) not only confirmed a known genetic variant (P value = 2E-6) for AMD, but also revealed an unreported haplotype surrounding single-nucleotide polymorphism (SNP) rs10272438 on chromosome 7 that was significantly associated with AMD (P value = 0.0024). These significance levels are obtained after the consideration for a large number of SNPs. Thus, the importance of this work is twofold: it proposes a powerful and flexible method to identify high-risk haplotypes and their interactions and reveals a potentially protective variant for AMD. 10.1073/pnas.0709868104

Predicting protein function from sequence and structure

David Lee — 2007-11-26T13:23:50-00:00

Nat Rev Mol Cell Biol, Vol. 8, No. 12. (December 2007), pp. 995-1005.

Interactive Tree Of Life (iTOL): an online tool for phylogenetic tree display and annotation

Letunic — 2006-12-25T11:16:04-00:00

Bioinformatics, Vol. 23, No. 1. (1 January 2007), pp. 127-128.

EVOLUTION: Passages Found Through Labyrinth of Bacterial Evolution

Elizabeth Pennisi — 2007-12-09T08:01:03-00:00

Science, Vol. 301, No. 5634. (8 August 2003), pp. 745a-746.

10.1126/science.301.5634.745a

An efficient algorithm for large-scale detection of protein families.

AJ Enright — 2005-04-13T16:58:22-00:00

Nucleic Acids Res, Vol. 30, No. 7. (1 April 2002), pp. 1575-1584.

Detection of protein families in large databases is one of the principal research objectives in structural and functional genomics. Protein family classification can significantly contribute to the delineation of functional diversity of homologous proteins, the prediction of function based on domain architecture or the presence of sequence motifs as well as comparative genomics, providing valuable evolutionary insights. We present a novel approach called TRIBE-MCL for rapid and accurate clustering of protein sequences into families. The method relies on the Markov cluster (MCL) algorithm for the assignment of proteins into families based on precomputed sequence similarity information. This novel approach does not suffer from the problems that normally hinder other protein sequence clustering algorithms, such as the presence of multi-domain proteins, promiscuous domains and fragmented proteins. The method has been rigorously tested and validated on a number of very large databases, including SwissProt, InterPro, SCOP and the draft human genome. Our results indicate that the method is ideally suited to the rapid and accurate detection of protein families on a large scale. The method has been used to detect and categorise protein families within the draft human genome and the resulting families have been used to annotate a large proportion of human proteins.

Discovery of functional elements in 12 Drosophila genomes using evolutionary signatures

Alexander Stark — 2007-11-07T18:45:14-00:00

Nature, Vol. 450, No. 7167., pp. 219-232.

Quantification of ortholog losses in insects and vertebrates.

Stefan Wyder — 2007-11-16T21:23:46-00:00

Genome Biology, Vol. 8 (16 November 2007), R242.

WAViS server for handling, visualization and presentation of multiple alignments of nucleotide or amino acids sequences.

R Zika — 2007-11-13T16:08:25-00:00

Nucleic Acids Res, Vol. 32, No. Web Server issue. (1 July 2004)

Web Alignment Visualization Server contains a set of web-tools designed for quick generation of publication-quality color figures of multiple alignments of nucleotide or amino acids sequences. It can be used for identification of conserved regions and gaps within many sequences using only common web browsers. The server is accessible at http://wavis.img.cas.cz.

Representing GC variation along eukaryotic chromosomes

Jan Paces — 2007-11-13T16:06:08-00:00

Gene, Vol. 333 (26 May 2004), pp. 135-141.

Genome sequencing now permits direct visual representation, at any scale, of GC heterogeneity along the chromosomes of several higher eukaryotes. Plots can be easily obtained from the chromosomal sequences, yet sequence releases of mammalian or plant chromosomes still tend to use small scales or window sizes that obscure important large-scale compositional features. To faithfully reveal, at one glance, the compositional variation at a given scale, we have devised a simple scheme that combines line plots with color-coded shading of the regions underneath the plots. The scheme can be applied to different eukaryotic genomes to facilitate their comparison, as illustrated here for a sample of chromosomes chosen from seven selected species. As a complement to a previously published compact view of isochores in the human genome sequence [FEBS Lett. 511 (2002a) 165], we include here an analogous map for the recently sequenced mouse genome, and discuss the contribution of repetitive DNA to the GC variation along the plots. Supplementary information, including a database of color-coded GC profiles for all recently sequenced eukaryotes and the program draw_chromosomes_gc.pl used to obtain them, are available at http://genomat.img.cas.cz.

The Bioperl Toolkit: Perl Modules for the Life Sciences

Jason Stajich — 2005-11-30T16:53:45-00:00

Genome Res., Vol. 12, No. 10. (1 October 2002), pp. 1611-1618.

The Bioperl project is an international open-source collaboration of biologists, bioinformaticians, and computer scientists that has evolved over the past 7 yr into the most comprehensive library of Perl modules available for managing and manipulating life-science information. Bioperl provides an easy-to-use, stable, and consistent programming interface for bioinformatics application programmers. The Bioperl modules have been successfully and repeatedly used to reduce otherwise complex tasks to only a few lines of code. The Bioperl object model has been proven to be flexible enough to support enterprise-level applications such as EnsEMBL, while maintaining an easy learning curve for novice Perl programmers. Bioperl is capable of executing analyses and processing results from programs such as BLAST, ClustalW, or the EMBOSS suite. Interoperation with modules written in Python and Java is supported through the evolving BioCORBA bridge. Bioperl provides access to data stores such as GenBank and SwissProt via a flexible series of sequence input/output modules, and to the emerging common sequence data storage format of the Open Bioinformatics Database Access project. This study describes the overall architecture of the toolkit, the problem domains that it addresses, and gives specific examples of how the toolkit can be used to solve common life-sciences problems. We conclude with a discussion of how the open-source nature of the project has contributed to the development effort.[Supplemental material is available online at www.genome.org. Bioperl is available as open-source software free of charge and is licensed under the Perl Artistic License (http://www.perl.com/pub/a/language/misc/Artistic.html). It is available for download at http://www.bioperl.org. Support inquiries should be addressed to bioperl-l@bioperl.org.]

Inferring genome-scale rearrangement phylogeny and ancestral gene order: A Drosophila case study

Arjun Bhutkar — 2007-11-09T08:38:41-00:00

Genome Biology, Vol. 8 (08 November 2007), R236.

The Global Landscape of Sequence Diversity

Jose Peregrin-Alvarez — 2007-11-09T08:38:41-00:00

Genome Biology, Vol. 8 (08 November 2007), R238.

Executable cell biology

Jasmin Fisher — 2007-11-08T17:06:30-00:00

Nat Biotech, Vol. 25, No. 11. (November 2007), pp. 1239-1249.

Organization and Evolution of Primate Centromeric DNA from Whole-Genome Shotgun Sequence Data

Can Alkan — 2007-11-02T08:08:29-00:00

PLoS Computational Biology, Vol. 3, No. 9. (1 September 2007), e181.

The major DNA constituent of primate centromeres is alpha satellite DNA. As much as 2%–5% of sequence generated as part of primate genome sequencing projects consists of this material, which is fragmented or not assembled as part of published genome sequences due to its highly repetitive nature. Here, we develop computational methods to rapidly recover and categorize alpha-satellite sequences from previously uncharacterized whole-genome shotgun sequence data. We present an algorithm to computationally predict potential higher-order array structure based on paired-end sequence data and then experimentally validate its organization and distribution by experimental analyses. Using whole-genome shotgun data from the human, chimpanzee, and macaque genomes, we examine the phylogenetic relationship of these sequences and provide further support for a model for their evolution and mutation over the last 25 million years. Our results confirm fundamental differences in the dispersal and evolution of centromeric satellites in the Old World monkey and ape lineages of evolution.

A Computational Approach to the Functional Screening of Genomes

Davide Chiarugi — 2007-10-30T10:02:12-00:00

PLoS Computational Biology, Vol. 3, No. 9. (1 September 2007), e174.

Comparative genomics usually involves managing the functional aspects of genomes, by simply comparing gene-by-gene functions. Following this approach, Mushegian and Koonin proposed a hypothetical minimal genome, Minimal Gene Set (MGS), aiming for a possible oldest ancestor genome. They obtained MGS by comparing the genomes of two simple bacteria and eliminating duplicated or functionally identical genes. The authors raised the fundamental question of whether a hypothetical organism possessing MGS is able to live or not. We attacked this viability problem specifying in silico the metabolic pathways of the MGS-based prokaryote. We then performed a dynamic simulation of cellular metabolic activities in order to check whether the MGS-prokaryote reaches some equilibrium state and produces the necessary biomass. We assumed these two conditions to be necessary for a living organism. Our simulations clearly show that the MGS does not express an organism that is able to live. We then iteratively proceeded with functional replacements in order to obtain a genome composition that gives rise to equilibrium. We ruled out 76 of the original 254 genes in the MGS, because they resulted in duplication from a functional point of view. We also added seven genes not present in the MGS. These genes encode for enzymes involved in critical nodes of the metabolic network. These modifications led to a genome composed of 187 elements expressing a virtually living organism, Virtual Cell (ViCe), that exhibits homeostatic capabilities and produces biomass. Moreover, the steady-state distribution of the concentrations of virtual metabolites that resulted was similar to that experimentally measured in bacteria. We conclude then that ViCe is able to “live in silico.”

Structural motifs of biomolecules

Jayanth Banavar — 2007-10-31T16:36:26-00:00

Proceedings of the National Academy of Sciences, Vol. 104, No. 44. (30 October 2007), pp. 17283-17286.

Biomolecular structures are assemblies of emergent anisotropic building modules such as uniaxial helices or biaxial strands. We provide an approach to understanding a marginally compact phase of matter that is occupied by proteins and DNA. This phase, which is in some respects analogous to the liquid crystal phase for chain molecules, stabilizes a range of shapes that can be obtained by sequence-independent interactions occurring intra- and intermolecularly between polymeric molecules. We present a singularity-free self-interaction for a tube in the continuum limit and show that this results in the tube being positioned in the marginally compact phase. Our work provides a unified framework for understanding the building blocks of biomolecules. 10.1073/pnas.0704594104

Mapping sequences by parts

Gilles Didier — 2007-09-20T18:31:54-00:00

Algorithms for Molecular Biology, Vol. 2 (19 September 2007), 11.

Bayesian methods in bioinformatics and computational systems biology.

Darren J Wilkinson — 2007-04-14T19:31:41-00:00

Brief Bioinform (12 April 2007)

Bayesian methods are valuable, inter alia, whenever there is a need to extract information from data that are uncertain or subject to any kind of error or noise (including measurement error and experimental error, as well as noise or random variation intrinsic to the process of interest). Bayesian methods offer a number of advantages over more conventional statistical techniques that make them particularly appropriate for complex data. It is therefore no surprise that Bayesian methods are becoming more widely used in the fields of genetics, genomics, bioinformatics and computational systems biology, where making sense of complex noisy data is the norm. This review provides an introduction to the growing literature in this area, with particular emphasis on recent developments in Bayesian bioinformatics relevant to computational systems biology.

A reality check for alignments and trees

William Martin — 2007-10-31T08:49:19-00:00

Trends in Genetics, Vol. 23, No. 10. (October 2007), pp. 478-480.

Making multiple sequence alignments is one of the more commonplace procedures in modern biology. Multiple alignments are typically generated by feeding sequences into the alignment program from the N-terminus to the C-terminus. Recent results show that if the same sequences are processed from the C- to the N-terminus, a different alignment is often obtained. Because phylogenetic trees are built from alignments, the resulting trees can also differ. The new findings highlight sequence alignment as a crucial step in molecular evolutionary studies and provide straightforward measures to assess alignment reliability.

The entire organization of transcription units on the Bacillus subtilis genome

Hirokazu Kobayashi — 2007-06-29T10:54:07-00:00

BMC Genomics, Vol. 8 (28 June 2007), 197.

Changes in alternative splicing of human and mouse genes are accompanied by faster evolution of constitutive exons.

BP Cusack — 2005-12-12T12:40:54-00:00

Mol Biol Evol, Vol. 22, No. 11. (November 2005), pp. 2198-2208.

Alternative splicing is known to be an important source of protein sequence variation, but its evolutionary impact has not been explored in detail. Studying alternative splicing requires extensive sampling of the transcriptome, but new data sets based on expressed sequence tags aligned to chromosomes make it possible to study alternative splicing on a genome-wide scale. Although genes showing alternative splicing by exon skipping are conserved as compared to the genome as a whole, we find that genes where structural differences between human and mouse result in genome-specific alternatively spliced exons in one species show almost 60% greater nonsynonymous divergence in constitutive exons than genes where exon skipping is conserved. This effect is also seen for genes showing species-specific patterns of alternative splicing where gene structure is conserved. Our observations are not attributable to an inherent difference in rate of evolution between these two sets of proteins or to differences with respect to predictors of evolutionary rate such as expression level, tissue specificity, or genetic redundancy. Where genome-specific alternatively spliced exons are seen in mammals, the vast majority of skipped exons appear to be recent additions to gene structures. Furthermore, among genes with genome-specific alternatively spliced exons, the degree of nonsynonymous divergence in constitutive sequence is a function of the frequency of incorporation of these alternative exons into transcripts. These results suggest that alterations in alternative splicing pattern can have knock-on effects in terms of accelerated sequence evolution in constant regions of the protein.

Simplified ontologies allowing comparison of developmental mammalian gene expression

Adele Kruger — 2007-10-26T18:59:06-00:00

Genome Biology, Vol. 8 (25 October 2007), R229.

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

Tomas Bonet — 2007-10-31T06:52:47-00:00

Genome Biology, Vol. 8, No. 10. (2007)

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.CONCLUSIONS: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.

Evaluation of clustering algorithms for protein-protein interaction networks

Sylvain Brohee — 2006-11-06T23:08:06-00:00

BMC Bioinformatics, Vol. 7 (06 November 2006), 488.

Detection of DNA copy number alterations in cancer by array comparative genomic hybridization.

E Michels — 2007-09-19T03:02:46-00:00

Genet Med, Vol. 9, No. 9. (September 2007), pp. 574-584.

Over the past few years, various reliable platforms for high-resolution detection of DNA copy number changes have become widely available. Together with optimized protocols for labeling and hybridization and algorithms for data analysis and representation, this has lead to a rapid increase in the application of this technology in the study of copy number variation in the human genome in normal cells and copy number imbalances in genetic diseases, including cancer. In this review, we briefly discuss specific technical issues relevant for array comparative genomic hybridization analysis in cancer tissues. We specifically focus on recent successes of array comparative genomic hybridization technology in the progress of our understanding of oncogenesis in a variety of cancer types. A third section highlights the potential of sensitive genome-wide detection of patterns of DNA imbalances or molecular portraits for class discovery and therapeutic stratification.

Superparamagnetic Clustering of Data

Marcelo Blatt — 2007-10-30T12:10:46-00:00

Physical Review Letters, Vol. 76, No. 18. (29 April 1996), 3251.

We present a new approach for clustering; based on the physical properties of an inhomogeneous ferromagnetic model. We do not assume any structure of the underlying distribution of the data. A Potts spin is assigned to each data point and short range interactions between neighboring points are introduced. Spin-spin correlations; measured (by Monte Carlo procedure) in a superparamagnetic regime in which aligned domains appear; serve to partition the data points into clusters. Our method outperforms other algorithms for toy problems as well as for real data.

Having a BLAST with bioinformatics (and avoiding BLASTphemy).

A Pertsemlidis — 2005-01-25T14:28:27-00:00

Genome Biol, Vol. 2, No. 10. (2001)

Searching for similarities between biological sequences is the principal means by which bioinformatics contributes to our understanding of biology. Of the various informatics tools developed to accomplish this task, the most widely used is BLAST, the basic local alignment search tool. This article discusses the principles, workings, applications and potential pitfalls of BLAST, focusing on the implementation developed at the National Center for Biotechnology Information.