bluuebunny/crossref_metadata_2025 huggingface dataset:
Unraveling condition specific gene transcriptional regulatory networks in Saccharomyces cerevisiae
Authors: Kim Hyunsoo , Hu William , Kluger Yuval
Published: April 2006

Background

Gene expression and transcription factor (TF) binding data have been used to reveal gene transcriptional regulatory networks. Existing knowledge of gene regulation can be presented using gene connectivity networks. However, these composite connectivity networks do not specify the range of biological conditions of the activity of each link in the network.

Results

We present a novel method that utilizes the expression and binding patterns of the neighboring nodes of each link in existing experimentally-based, literature-derived gene transcriptional regulatory networks and extend them in silico using TF-gene binding motifs and a compendium of large expression data from Saccharomyces cerevisiae. Using this method, we predict several hundreds of new transcriptional regulatory TF-gene links, along with experimental conditions in which known and predicted links become active. This approach unravels new links in the yeast gene transcriptional regulatory network by utilizing the known transcriptional regulatory interactions, and is particularly useful for breaking down the composite transcriptional regulatory network to condition specific networks.

Conclusion

Our methods can facilitate future binding experiments, as they can considerably help focus on the TFs that must be surveyed to understand gene regulation.

(Supplemental material and the latest version of the MATLAB implementation of the United Signature Algorithm is available online at [1] or [see Additional files 1, 2, 3, 4, 5, 6, 7, 8, 9, 10])
SNPs3D: Candidate gene and SNP selection for association studies
Authors: Yue Peng , Melamud Eugene , Moult John
Published: April 2006

Background

The relationship between disease susceptibility and genetic variation is complex, and many different types of data are relevant. We describe a web resource and database that provides and integrates as much information as possible on disease/gene relationships at the molecular level.

Description

The resource http://www.SNPs3D.org has three primary modules. One module identifies which genes are candidates for involvement in a specified disease. A second module provides information about the relationships between sets of candidate genes. The third module analyzes the likely impact of non-synonymous SNPs on protein function. Disease/candidate gene relationships and gene-gene relationships are derived from the literature using simple but effective text profiling. SNP/protein function relationships are derived by two methods, one using principles of protein structure and stability, the other based on sequence conservation. Entries for each gene include a number of links to other data, such as expression profiles, pathway context, mouse knockout information and papers. Gene-gene interactions are presented in an interactive graphical interface, providing rapid access to the underlying information, as well as convenient navigation through the network. Use of the resource is illustrated with aspects of the inflammatory response and hypertension.

Conclusion

The combination of SNP impact analysis, a knowledge based network of gene relationships and candidate genes, and access to a wide range of data and literature allow a user to quickly assimilate available information, and so develop models of gene-pathway-disease interaction.
Prediction of indirect interactions in proteins
Authors: Prusis Peteris , Uhlén Staffan , Petrovska Ramona , Lapinsh Maris , Wikberg Jarl ES
Published: April 2006

Background

Both direct and indirect interactions determine molecular recognition of ligands by proteins. Indirect interactions can be defined as effects on recognition controlled from distant sites in the proteins, e.g. by changes in protein conformation and mobility, whereas direct interactions occur in close proximity of the protein's amino acids and the ligand. Molecular recognition is traditionally studied using three-dimensional methods, but with such techniques it is difficult to predict the effects caused by mutational changes of amino acids located far away from the ligand-binding site. We recently developed an approach, proteochemometrics, to the study of molecular recognition that models the chemical effects involved in the recognition of ligands by proteins using statistical sampling and mathematical modelling.

Results

A proteochemometric model was built, based on a statistically designed protein library's (melanocortin receptors') interaction with three peptides and used to predict which amino acids and sequence fragments that are involved in direct and indirect ligand interactions. The model predictions were confirmed by directed mutagenesis. The predicted presumed direct interactions were in good agreement with previous three-dimensional studies of ligand recognition. However, in addition the model could also correctly predict the location of indirect effects on ligand recognition arising from distant sites in the receptors, something that three-dimensional modelling could not afford.

Conclusion

We demonstrate experimentally that proteochemometric modelling can be used with high accuracy to predict the site of origin of direct and indirect effects on ligand recognitions by proteins.
GEM System: automatic prototyping of cell-wide metabolic pathway models from genomes
Authors: Arakawa Kazuharu , Yamada Yohei , Shinoda Kosaku , Nakayama Yoichi , Tomita Masaru
Published: April 2006

Background

Successful realization of a "systems biology" approach to analyzing cells is a grand challenge for our understanding of life. However, current modeling approaches to cell simulation are labor-intensive, manual affairs, and therefore constitute a major bottleneck in the evolution of computational cell biology.

Results

We developed the Genome-based Modeling (GEM) System for the purpose of automatically prototyping simulation models of cell-wide metabolic pathways from genome sequences and other public biological information. Models generated by the GEM System include an entire Escherichia coli metabolism model comprising 968 reactions of 1195 metabolites, achieving 100% coverage when compared with the KEGG database, 92.38% with the EcoCyc database, and 95.06% with iJR904 genome-scale model.

Conclusion

The GEM System prototypes qualitative models to reduce the labor-intensive tasks required for systems biology research. Models of over 90 bacterial genomes are available at our web site.
BioWarehouse: a bioinformatics database warehouse toolkit
Authors: Lee Thomas J , Pouliot Yannick , Wagner Valerie , Gupta Priyanka , Stringer-Calvert David WJ , Tenenbaum Jessica D , Karp Peter D
Published: April 2006

Background

This article addresses the problem of interoperation of heterogeneous bioinformatics databases.

Results

We introduce BioWarehouse, an open source toolkit for constructing bioinformatics database warehouses using the MySQL and Oracle relational database managers. BioWarehouse integrates its component databases into a common representational framework within a single database management system, thus enabling multi-database queries using the Structured Query Language (SQL) but also facilitating a variety of database integration tasks such as comparative analysis and data mining. BioWarehouse currently supports the integration of a pathway-centric set of databases including ENZYME, KEGG, and BioCyc, and in addition the UniProt, GenBank, NCBI Taxonomy, and CMR databases, and the Gene Ontology. Loader tools, written in the C and JAVA languages, parse and load these databases into a relational database schema. The loaders also apply a degree of semantic normalization to their respective source data, decreasing semantic heterogeneity. The schema supports the following bioinformatics datatypes: chemical compounds, biochemical reactions, metabolic pathways, proteins, genes, nucleic acid sequences, features on protein and nucleic-acid sequences, organisms, organism taxonomies, and controlled vocabularies. As an application example, we applied BioWarehouse to determine the fraction of biochemically characterized enzyme activities for which no sequences exist in the public sequence databases. The answer is that no sequence exists for 36% of enzyme activities for which EC numbers have been assigned. These gaps in sequence data significantly limit the accuracy of genome annotation and metabolic pathway prediction, and are a barrier for metabolic engineering. Complex queries of this type provide examples of the value of the data warehousing approach to bioinformatics research.

Conclusion

BioWarehouse embodies significant progress on the database integration problem for bioinformatics.
GENOMEMASKER package for designing unique genomic PCR primers
Authors: Andreson Reidar , Reppo Eric , Kaplinski Lauris , Remm Maido
Published: April 2006

Background

The design of oligonucleotides and PCR primers for studying large genomes is complicated by the redundancy of sequences. The eukaryotic genomes are particularly difficult to study due to abundant repeats. The speed of most existing primer evaluation programs is not sufficient for large-scale experiments.

Results

In order to improve the efficiency and success rate of automatic primer/oligo design, we created a novel method which allows rapid masking of repeats in large sequence files, for example in eukaryotic genomes. It also allows the detection of all alternative binding sites of PCR primers and the prediction of PCR products. The new method was implemented in a collection of efficient programs, the GENOMEMASKER package. The performance of the programs was compared to other similar programs. We also modified the PRIMER3 program, to be able to design primers from lowercase-masked sequences.

Conclusion

The GENOMEMASKER package is able to mask the entire human genome for non-unique primers within 6 hours and find locations of all binding sites for 10 000 designed primer pairs within 10 minutes. Additionally, it predicts all alternative PCR products from large genomes for given primer pairs.
Detection of non-coding RNAs on the basis of predicted secondary structure formation free energy change
Authors: Uzilov Andrew V , Keegan Joshua M , Mathews David H
Published: April 2006

Background

Non-coding RNAs (ncRNAs) have a multitude of roles in the cell, many of which remain to be discovered. However, it is difficult to detect novel ncRNAs in biochemical screens. To advance biological knowledge, computational methods that can accurately detect ncRNAs in sequenced genomes are therefore desirable. The increasing number of genomic sequences provides a rich dataset for computational comparative sequence analysis and detection of novel ncRNAs.

Results

Here, Dynalign, a program for predicting secondary structures common to two RNA sequences on the basis of minimizing folding free energy change, is utilized as a computational ncRNA detection tool. The Dynalign-computed optimal total free energy change, which scores the structural alignment and the free energy change of folding into a common structure for two RNA sequences, is shown to be an effective measure for distinguishing ncRNA from randomized sequences. To make the classification as a ncRNA, the total free energy change of an input sequence pair can either be compared with the total free energy changes of a set of control sequence pairs, or be used in combination with sequence length and nucleotide frequencies as input to a classification support vector machine. The latter method is much faster, but slightly less sensitive at a given specificity. Additionally, the classification support vector machine method is shown to be sensitive and specific on genomic ncRNA screens of two different Escherichia coli and Salmonella typhi genome alignments, in which many ncRNAs are known. The Dynalign computational experiments are also compared with two other ncRNA detection programs, RNAz and QRNA.

Conclusion

The Dynalign-based support vector machine method is more sensitive for known ncRNAs in the test genomic screens than RNAz and QRNA. Additionally, both Dynalign-based methods are more sensitive than RNAz and QRNA at low sequence pair identities. Dynalign can be used as a comparable or more accurate tool than RNAz or QRNA in genomic screens, especially for low-identity regions. Dynalign provides a method for discovering ncRNAs in sequenced genomes that other methods may not identify. Significant improvements in Dynalign runtime have also been achieved.
UVPAR: fast detection of functional shifts in duplicate genes
Authors: Arnau Vicente , Gallach Miguel , Lucas J Ignasi , Marín Ignacio
Published: April 2006

Background

The imprint of natural selection on gene sequences is often difficult to detect. A plethora of methods have been devised to detect genetic changes due to selective processes. However, many of those methods depend heavily on underlying assumptions regarding the mode of change of DNA sequences and often require sophisticated mathematical treatments that made them computationally slow. The development of fast and effective methods to detect modifications in the selective constraints of genes is therefore of great interest.

Results

We describe UVPAR, a program designed to quickly test for changes in the functional constraints of duplicate genes. Starting with alignments of the proteins encoded by couples of duplicate genes in two different species, UVPAR detects the regions in which modifications of the functional constraints in the paralogs occurred since both species diverged. Sequences can be analyzed with UVPAR in just a few minutes on a standard PC computer. To demonstrate the power of the program, we first show how the results obtained with UVPAR compare to those based on other approaches, using data for vertebrate Hox genes. We then describe a comprehensive study of the RBR family of ubiquitin ligases in which we have performed 529 analyses involving 14 duplicate genes in seven model species. A significant increase in the number of functional shifts was observed for the species Danio rerio and for the gene Ariadne-2.

Conclusion

These results show that UVPAR can be used to generate sensitive analyses to detect changes in the selection constraints acting on paralogs. The high speed of the program allows its application to genome-scale analyses.
LS-NMF: A modified non-negative matrix factorization algorithm utilizing uncertainty estimates
Authors: Wang Guoli , Kossenkov Andrew V , Ochs Michael F
Published: April 2006

Background

Non-negative matrix factorisation (NMF), a machine learning algorithm, has been applied to the analysis of microarray data. A key feature of NMF is the ability to identify patterns that together explain the data as a linear combination of expression signatures. Microarray data generally includes individual estimates of uncertainty for each gene in each condition, however NMF does not exploit this information. Previous work has shown that such uncertainties can be extremely valuable for pattern recognition.

Results

We have created a new algorithm, least squares non-negative matrix factorization, LS-NMF, which integrates uncertainty measurements of gene expression data into NMF updating rules. While the LS-NMF algorithm maintains the advantages of original NMF algorithm, such as easy implementation and a guaranteed locally optimal solution, the performance in terms of linking functionally related genes has been improved. LS-NMF exceeds NMF significantly in terms of identifying functionally related genes as determined from annotations in the MIPS database.

Conclusion

Uncertainty measurements on gene expression data provide valuable information for data analysis, and use of this information in the LS-NMF algorithm significantly improves the power of the NMF technique.
Identifying metabolic enzymes with multiple types of association evidence
Authors: Kharchenko Peter , Chen Lifeng , Freund Yoav , Vitkup Dennis , Church George M
Published: April 2006

Background

Existing large-scale metabolic models of sequenced organisms commonly include enzymatic functions which can not be attributed to any gene in that organism. Existing computational strategies for identifying such missing genes rely primarily on sequence homology to known enzyme-encoding genes.

Results

We present a novel method for identifying genes encoding for a specific metabolic function based on a local structure of metabolic network and multiple types of functional association evidence, including clustering of genes on the chromosome, similarity of phylogenetic profiles, gene expression, protein fusion events and others. Using E. coli and S. cerevisiae metabolic networks, we illustrate predictive ability of each individual type of association evidence and show that significantly better predictions can be obtained based on the combination of all data. In this way our method is able to predict 60% of enzyme-encoding genes of E. coli metabolism within the top 10 (out of 3551) candidates for their enzymatic function, and as a top candidate within 43% of the cases.

Conclusion

We illustrate that a combination of genome context and other functional association evidence is effective in predicting genes encoding metabolic enzymes. Our approach does not rely on direct sequence homology to known enzyme-encoding genes, and can be used in conjunction with traditional homology-based metabolic reconstruction methods. The method can also be used to target orphan metabolic activities.
Protein secondary structure prediction for a single-sequence using hidden semi-Markov models
Authors: Aydin Zafer , Altunbasak Yucel , Borodovsky Mark
Published: April 2006

Background

The accuracy of protein secondary structure prediction has been improving steadily towards the 88% estimated theoretical limit. There are two types of prediction algorithms: Single-sequence prediction algorithms imply that information about other (homologous) proteins is not available, while algorithms of the second type imply that information about homologous proteins is available, and use it intensively. The single-sequence algorithms could make an important contribution to studies of proteins with no detected homologs, however the accuracy of protein secondary structure prediction from a single-sequence is not as high as when the additional evolutionary information is present.

Results

In this paper, we further refine and extend the hidden semi-Markov model (HSMM) initially considered in the BSPSS algorithm. We introduce an improved residue dependency model by considering the patterns of statistically significant amino acid correlation at structural segment borders. We also derive models that specialize on different sections of the dependency structure and incorporate them into HSMM. In addition, we implement an iterative training method to refine estimates of HSMM parameters. The three-state-per-residue accuracy and other accuracy measures of the new method, IPSSP, are shown to be comparable or better than ones for BSPSS as well as for PSIPRED, tested under the single-sequence condition.

Conclusions

We have shown that new dependency models and training methods bring further improvements to single-sequence protein secondary structure prediction. The results are obtained under cross-validation conditions using a dataset with no pair of sequences having significant sequence similarity. As new sequences are added to the database it is possible to augment the dependency structure and obtain even higher accuracy. Current and future advances should contribute to the improvement of function prediction for orphan proteins inscrutable to current similarity search methods.
AtRTPrimer: database for Arabidopsis genome-wide homogeneous and specific RT-PCR primer-pairs
Authors: Han Sangjo , Kim Dongsup
Published: April 2006

Background

Primer design is a critical step in all types of RT-PCR methods to ensure specificity and efficiency of a target amplicon. However, most traditional primer design programs suggest primers on a single template of limited genetic complexity. To provide researchers with a sufficient number of pre-designed specific RT-PCR primer pairs for whole genes in Arabidopsis, we aimed to construct a genome-wide primer-pair database.

Description

We considered the homogeneous physical and chemical properties of each primer (homogeneity) of a gene, non-specific binding against all other known genes (specificity), and other possible amplicons from its corresponding genomic DNA or similar cDNAs (additional information). Then, we evaluated the reliability of our database with selected primer pairs from 15 genes using conventional and real time RT-PCR.

Conclusion

Approximately 97% of 28,952 genes investigated were finally registered in AtRTPrimer. Unlike other freely available primer databases for Arabidopsis thaliana, AtRTPrimer provides a large number of reliable primer pairs for each gene so that researchers can perform various types of RT-PCR experiments for their specific needs. Furthermore, by experimentally evaluating our database, we made sure that our database provides good starting primer pairs for Arabidopsis researchers to perform various types of RT-PCR experiments.
A two-stage approach for improved prediction of residue contact maps
Authors: Vullo Alessandro , Walsh Ian , Pollastri Gianluca
Published: April 2006

Background

Protein topology representations such as residue contact maps are an important intermediate step towards ab initio prediction of protein structure. Although improvements have occurred over the last years, the problem of accurately predicting residue contact maps from primary sequences is still largely unsolved. Among the reasons for this are the unbalanced nature of the problem (with far fewer examples of contacts than non-contacts), the formidable challenge of capturing long-range interactions in the maps, the intrinsic difficulty of mapping one-dimensional input sequences into two-dimensional output maps.

In order to alleviate these problems and achieve improved contact map predictions, in this paper we split the task into two stages: the prediction of a map's principal eigenvector (PE) from the primary sequence; the reconstruction of the contact map from the PE and primary sequence. Predicting the PE from the primary sequence consists in mapping a vector into a vector. This task is less complex than mapping vectors directly into two-dimensional matrices since the size of the problem is drastically reduced and so is the scale length of interactions that need to be learned.

Results

We develop architectures composed of ensembles of two-layered bidirectional recurrent neural networks to classify the components of the PE in 2, 3 and 4 classes from protein primary sequence, predicted secondary structure, and hydrophobicity interaction scales. Our predictor, tested on a non redundant set of 2171 proteins, achieves classification performances of up to 72.6%, 16% above a base-line statistical predictor.

We design a system for the prediction of contact maps from the predicted PE. Our results show that predicting maps through the PE yields sizeable gains especially for long-range contacts which are particularly critical for accurate protein 3D reconstruction. The final predictor's accuracy on a non-redundant set of 327 targets is 35.4% and 19.8% for minimum contact separations of 12 and 24, respectively, when the top length/5 contacts are selected. On the 11 CASP6 Novel Fold targets we achieve similar accuracies (36.5% and 19.7%). This favourably compares with the best automated predictors at CASP6.

Conclusion

Our final system for contact map prediction achieves state-of-the-art performances, and may provide valuable constraints for improved ab initio prediction of protein structures. A suite of predictors of structural features, including the PE, and PE-based contact maps, is available at http://distill.ucd.ie.
Cloning and characterization of mr-s, a novel SAM domain protein, predominantly expressed in retinal photoreceptor cells
Authors: Inoue Tatsuya , Terada Koji , Furukawa Akiko , Koike Chieko , Tamaki Yasuhiro , Araie Makoto , Furukawa Takahisa
Published: April 2006

Background

Sterile alpha motif (SAM) domains are ~70 residues long and have been reported as common protein-protein interaction modules. This domain is found in a large number of proteins, including Polycomb group (PcG) proteins and ETS family transcription factors. In this work, we report the cloning and functional characterization of a novel SAM domain-containing protein, which is predominantly expressed in retinal photoreceptors and the pineal gland and is designated mouse mr-s (major retinal SAM domain protein).

Results

mr-s is evolutionarily conserved from zebrafish through human, organisms through which the mechanism of photoreceptor development is also highly conserved. Phylogenetic analysis suggests that the SAM domain of mr-s is most closely related to a mouse polyhomeotic (ph) ortholog, Mph1/Rae28, which is known as an epigenetic molecule involved in chromatin modifications. These findings provide the possibility that mr-s may play a critical role by regulating gene expression in photoreceptor development. mr-s is preferentially expressed in the photoreceptors at postnatal day 3–6 (P3-6), when photoreceptors undergo terminal differentiation, and in the adult pineal gland. Transcription of mr-s is directly regulated by the cone-rod homeodomain protein Crx. Immunoprecipitation assay showed that the mr-s protein self-associates mainly through the SAM domain-containing region as well as ph. The mr-s protein localizes mainly in the nucleus, when mr-s is overexpressed in HEK293T cells. Moreover, in the luciferase assays, we found that mr-s protein fused to GAL4 DNA-binding domain functions as a transcriptional repressor. We revealed that the repression activity of mr-s is not due to a homophilic interaction through its SAM domain but to the C-terminal region.

Conclusion

We identified a novel gene, mr-s, which is predominantly expressed in retinal photoreceptors and pineal gland. Based on its expression pattern and biochemical analysis, we predict that mr-s may function as a transcriptional repressor in photoreceptor cells and in pinealocytes of the pineal gland.
Multi-character perspectives on the evolution of intraspecific differentiation in a neotropical hylid frog
Authors: Lougheed Stephen C , Austin James D , Bogart James P , Boag Peter T , Chek Andrew A
Published: April 2006

Background

Multi-character empirical studies are important contributions to our understanding of the process of speciation. The relatively conserved morphology of, and importance of the mate recognition system in anurans, combined with phylogenetic tools, provide an opportunity to address predictions about the relative role of each in the process of speciation. We examine the relationship among patterns of variation in morphology, call characters, and 16S gene sequences across seven populations of a neotropical hylid frog, Hyla leucophyllata, to infer their relative importance in predicting the early stages of population differentiation.

Results

Multivariate analyses demonstrate that both morphological and call characteristics were significantly variable among populations, characterized by significantly lower intra-population dispersion in call space than morphological space, and significantly greater among-population variation in call structure. We found lack of concordance between a 16S DNA phylogeny of Hyla leucophyllata and the significant population-level differentiation evident in both external morphology and male advertisement call. Comparisons of the reconstructed gene trees to simulated lineages support the notion that variation in call cannot be simply explained by population history.

Conclusion

Discordance among traits may reflect sampling biases (e.g. single genetic marker effects), or imply a decoupling of evolution of different suites of characters. Diagnostic differences among populations in call structure possibly reflect local selection pressures presented by different heterospecific calling assemblages and may serve as a precursor of species-wide differentiation. Differentiation among populations in morphology may be due to ecophenotypic variation or to diversifying selection on body size directly, or on frequency attributes of calls (mediated by female choice) that show a strong relationship to body size.
Fast "coalescent" simulation
Authors: Marjoram Paul , Wall Jeff D
Published: April 2006

Background

The amount of genome-wide molecular data is increasing rapidly, as is interest in developing methods appropriate for such data. There is a consequent increasing need for methods that are able to efficiently simulate such data. In this paper we implement the sequentially Markovian coalescent algorithm described by McVean and Cardin and present a further modification to that algorithm which slightly improves the closeness of the approximation to the full coalescent model. The algorithm ignores a class of recombination events known to affect the behavior of the genealogy of the sample, but which do not appear to affect the behavior of generated samples to any substantial degree.

Results

We show that our software is able to simulate large chromosomal regions, such as those appropriate in a consideration of genome-wide data, in a way that is several orders of magnitude faster than existing coalescent algorithms.

Conclusion

This algorithm provides a useful resource for those needing to simulate large quantities of data for chromosomal-length regions using an approach that is much more efficient than traditional coalescent models.
Comparative salivary gland transcriptomics of sandfly vectors of visceral leishmaniasis
Authors: Anderson Jennifer M , Oliveira Fabiano , Kamhawi Shaden , Mans Ben J , Reynoso David , Seitz Amy E , Lawyer Phillip , Garfield Mark , Pham MyVan , Valenzuela Jesus G
Published: April 2006

Background

Immune responses to sandfly saliva have been shown to protect animals againstLeishmaniainfection. Yet very little is known about the molecular characteristics of salivary proteins from different sandflies, particularly from vectors transmitting visceral leishmaniasis, the fatal form of the disease. Further knowledge of the repertoire of these salivary proteins will give us insights into the molecular evolution of these proteins and will help us select relevant antigens for the development of a vector based anti-Leishmaniavaccine.

Results

Two salivary gland cDNA libraries from female sandfliesPhlebotomus argentipesandP. perniciosuswere constructed, sequenced and proteomic analysis of the salivary proteins was performed. The majority of the sequenced transcripts from the two cDNA libraries coded for secreted proteins. In this analysis we identified transcripts coding for protein families not previously described in sandflies. A comparative sandfly salivary transcriptome analysis was performed by using these two cDNA libraries and two other sandfly salivary gland cDNA libraries fromP. ariasiandLutzomyia longipalpis, also vectors of visceral leishmaniasis. Full-length secreted proteins from each sandfly library were compared using a stand-alone version of BLAST, creating formatted protein databases of each sandfly library. Related groups of proteins from each sandfly species were combined into defined families of proteins. With this comparison, we identified families of salivary proteins common among all of the sandflies studied, proteins to be genus specific and proteins that appear to be species specific. The common proteins included apyrase, yellow-related protein, antigen-5, PpSP15 and PpSP32-related protein, a 33-kDa protein, D7-related protein, a 39- and a 16.1- kDa protein and an endonuclease-like protein. Some of these families contained multiple members, including PPSP15-like, yellow proteins and D7-related proteins suggesting gene expansion in these proteins.

Conclusion

This comprehensive analysis allows us the identification of genus- specific proteins, species-specific proteins and, more importantly, proteins common among these different sandflies. These results give us insights into the repertoire of salivary proteins that are potential candidates for a vector-based vaccine.
A gene-based high-resolution comparative radiation hybrid map as a framework for genome sequence assembly of a bovine chromosome 6 region associated with QTL for growth, body composition, and milk performance traits
Authors: Weikard Rosemarie , Goldammer Tom , Laurent Pascal , Womack James E , Kuehn Christa
Published: April 2006

Background

A number of different quantitative trait loci (QTL) for various phenotypic traits, including milk production, functional, and conformation traits in dairy cattle as well as growth and body composition traits in meat cattle, have been mapped consistently in the middle region of bovine chromosome 6 (BTA6). Dense genetic and physical maps and, ultimately, a fully annotated genome sequence as well as their mutual connections are required to efficiently identify genes and gene variants responsible for genetic variation of phenotypic traits. A comprehensive high-resolution gene-rich map linking densely spaced bovine markers and genes to the annotated human genome sequence is required as a framework to facilitate this approach for the region on BTA6 carrying the QTL.

Results

Therefore, we constructed a high-resolution radiation hybrid (RH) map for the QTL containing chromosomal region of BTA6. This new RH map with a total of 234 loci including 115 genes and ESTs displays a substantial increase in loci density compared to existing physical BTA6 maps. Screening the available bovine genome sequence resources, a total of 73 loci could be assigned to sequence contigs, which were already identified as specific for BTA6. For 43 loci, corresponding sequence contigs, which were not yet placed on the bovine genome assembly, were identified. In addition, the improved potential of this high-resolution RH map for BTA6 with respect to comparative mapping was demonstrated. Mapping a large number of genes on BTA6 and cross-referencing them with map locations in corresponding syntenic multi-species chromosome segments (human, mouse, rat, dog, chicken) achieved a refined accurate alignment of conserved segments and evolutionary breakpoints across the species included.

Conclusion

The gene-anchored high-resolution RH map (1 locus/300 kb) for the targeted region of BTA6 presented here will provide a valuable platform to guide high-quality assembling and annotation of the currently existing bovine genome sequence draft to establish the final architecture of BTA6. Hence, a sequence-based map will provide a key resource to facilitate prospective continued efforts for the selection and validation of relevant positional and functional candidates underlying QTL for milk production and growth-related traits mapped on BTA6 and on similar chromosomal regions from evolutionary closely related species like sheep and goat. Furthermore, the high-resolution sequence-referenced BTA6 map will enable precise identification of multi-species conserved chromosome segments and evolutionary breakpoints in mammalian phylogenetic studies.
A multispecies comparison of the metazoan 3'-processing downstream elements and the CstF-64 RNA recognition motif
Authors: Salisbury Jesse , Hutchison Keith W , Graber Joel H
Published: April 2006

Background

The Cleavage Stimulation Factor (CstF) is a required protein complex for eukaryotic mRNA 3'-processing. CstF interacts with 3'-processing downstream elements (DSEs) through its 64-kDa subunit, CstF-64; however, the exact nature of this interaction has remained unclear. We used EST-to-genome alignments to identify and extract large sets of putative 3'-processing sites for mRNA from ten metazoan species, including Homo sapiens, Canis familiaris, Rattus norvegicus, Mus musculus, Gallus gallus, Danio rerio, Takifugu rubripes, Drosophila melanogaster, Anopheles gambiae, and Caenorhabditis elegans. In order to further delineate the details of the mRNA-protein interaction, we obtained and multiply aligned CstF-64 protein sequences from the same species.

Results

We characterized the sequence content and specific positioning of putative DSEs across the range of organisms studied. Our analysis characterized the downstream element (DSE) as two distinct parts – a proximal UG-rich element and a distal U-rich element. We find that while the U-rich element is largely conserved in all of the organisms studied, the UG-rich element is not. Multiple alignment of the CstF-64 RNA recognition motif revealed that, while it is highly conserved throughout metazoans, we can identify amino acid changes that correlate with observed variation in the sequence content and positioning of the DSEs.

Conclusion

Our analysis confirms the early reports of separate U- and UG-rich DSEs. The correlated variations in protein sequence and mRNA binding sequences provide novel insights into the interactions between the precursor mRNA and the 3'-processing machinery.
Using pyrosequencing to shed light on deep mine microbial ecology
Authors: Edwards Robert A , Rodriguez-Brito Beltran , Wegley Linda , Haynes Matthew , Breitbart Mya , Peterson Dean M , Saar Martin O , Alexander Scott , Alexander E Calvin , Rohwer Forest
Published: April 2006

Background

Contrasting biological, chemical and hydrogeological analyses highlights the fundamental processes that shape different environments. Generating and interpreting the biological sequence data was a costly and time-consuming process in defining an environment. Here we have used pyrosequencing, a rapid and relatively inexpensive sequencing technology, to generate environmental genome sequences from two sites in the Soudan Mine, Minnesota, USA. These sites were adjacent to each other, but differed significantly in chemistry and hydrogeology.

Results

Comparisons of the microbes and the subsystems identified in the two samples highlighted important differences in metabolic potential in each environment. The microbes were performing distinct biochemistry on the available substrates, and subsystems such as carbon utilization, iron acquisition mechanisms, nitrogen assimilation, and respiratory pathways separated the two communities. Although the correlation between much of the microbial metabolism occurring and the geochemical conditions from which the samples were isolated could be explained, the reason for the presence of many pathways in these environments remains to be determined. Despite being physically close, these two communities were markedly different from each other. In addition, the communities were also completely different from other microbial communities sequenced to date.

Conclusion

We anticipate that pyrosequencing will be widely used to sequence environmental samples because of the speed, cost, and technical advantages. Furthermore, subsystem comparisons rapidly identify the important metabolisms employed by the microbes in different environments.
Comparison of gene coverage of mouse oligonucleotide microarray platforms
Authors: Verdugo Ricardo A , Medrano Juan F
Published: April 2006

Background

The increasing use of DNA microarrays for genetical genomics studies generates a need for platforms with complete coverage of the genome. We have compared the effective gene coverage in the mouse genome of different commercial and noncommercial oligonucleotide microarray platforms by performing an in-house gene annotation of probes. We only used information about probes that is available from vendors and followed a process that any researcher may take to find the gene targeted by a given probe. In order to make consistent comparisons between platforms, probes in each microarray were annotated with an Entrez Gene id and the chromosomal position for each gene was obtained from the UCSC Genome Browser Database. Gene coverage was estimated as the percentage of Entrez Genes with a unique position in the UCSC Genome database that is tested by a given microarray platform.

Results

A MySQL relational database was created to store the mapping information for 25,416 mouse genes and for the probes in five microarray platforms (gene coverage level in parenthesis): Affymetrix430 2.0 (75.6%), ABI Genome Survey (81.24%), Agilent (79.33%), Codelink (78.09%), Sentrix (90.47%); and four array-ready oligosets: Sigma (47.95%), Operon v.3 (69.89%), Operon v.4 (84.03%), and MEEBO (84.03%). The differences in coverage between platforms were highly conserved across chromosomes. Differences in the number of redundant and unspecific probes were also found among arrays. The database can be queried to compare specific genomic regions using a web interface. The software used to create, update and query the database is freely available as a toolbox named ArrayGene.

Conclusion

The software developed here allows researchers to create updated custom databases by using public or proprietary information on genes for any organisms. ArrayGene allows easy comparisons of gene coverage between microarray platforms for any region of the genome. The comparison presented here reveals that the commercial microarray Sentrix, which is based on the MEEBO public oligoset, showed the best mouse genome coverage currently available. We also suggest the creation of guidelines to standardize the minimum set of information that vendors should provide to allow researchers to accurately evaluate the advantages and disadvantages of using a given platform.
Large scale real-time PCR validation on gene expression measurements from two commercial long-oligonucleotide microarrays
Authors: Wang Yulei , Barbacioru Catalin , Hyland Fiona , Xiao Wenming , Hunkapiller Kathryn L , Blake Julie , Chan Frances , Gonzalez Carolyn , Zhang Lu , Samaha Raymond R
Published: April 2006

Background

DNA microarrays are rapidly becoming a fundamental tool in discovery-based genomic and biomedical research. However, the reliability of the microarray results is being challenged due to the existence of different technologies and non-standard methods of data analysis and interpretation. In the absence of a "gold standard"/"reference method" for the gene expression measurements, studies evaluating and comparing the performance of various microarray platforms have often yielded subjective and conflicting conclusions. To address this issue we have conducted a large scale TaqMan® Gene Expression Assay based real-time PCR experiment and used this data set as the reference to evaluate the performance of two representative commercial microarray platforms.

Results

In this study, we analyzed the gene expression profiles of three human tissues: brain, lung, liver and one universal human reference sample (UHR) using two representative commercial long-oligonucleotide microarray platforms: (1) Applied Biosystems Human Genome Survey Microarrays (based on single-color detection); (2) Agilent Whole Human Genome Oligo Microarrays (based on two-color detection). 1,375 genes represented by both microarray platforms and spanning a wide dynamic range in gene expression levels, were selected for TaqMan® Gene Expression Assay based real-time PCR validation. For each platform, four technical replicates were performed on the same total RNA samples according to each manufacturer's standard protocols. For Agilent arrays, comparative hybridization was performed using incorporation of Cy5 for brain/lung/liver RNA and Cy3 for UHR RNA (common reference). Using the TaqMan® Gene Expression Assay based real-time PCR data set as the reference set, the performance of the two microarray platforms was evaluated focusing on the following criteria: (1) Sensitivity and accuracy in detection of expression; (2) Fold change correlation with real-time PCR data in pair-wise tissues as well as in gene expression profiles determined across all tissues; (3) Sensitivity and accuracy in detection of differential expression.

Conclusion

Our study provides one of the largest "reference" data set of gene expression measurements using TaqMan® Gene Expression Assay based real-time PCR technology. This data set allowed us to use an alternative gene expression technology to evaluate the performance of different microarray platforms. We conclude that microarrays are indeed invaluable discovery tools with acceptable reliability for genome-wide gene expression screening, though validation of putative changes in gene expression remains advisable. Our study also characterizes the limitations of microarrays; understanding these limitations will enable researchers to more effectively evaluate microarray results in a more cautious and appropriate manner.
The complete chloroplast genome sequence of Gossypium hirsutum: organization and phylogenetic relationships to other angiosperms
Authors: Lee Seung-Bum , Kaittanis Charalambos , Jansen Robert K , Hostetler Jessica B , Tallon Luke J , Town Christopher D , Daniell Henry
Published: April 2006

Background

Cotton (Gossypium hirsutum) is the most important fiber crop grown in 90 countries. In 2004–2005, US farmers planted 79% of the 5.7-million hectares of nuclear transgenic cotton. Unfortunately, genetically modified cotton has the potential to hybridize with other cultivated and wild relatives, resulting in geographical restrictions to cultivation. However, chloroplast genetic engineering offers the possibility of containment because of maternal inheritance of transgenes. The complete chloroplast genome of cotton provides essential information required for genetic engineering. In addition, the sequence data were used to assess phylogenetic relationships among the major clades of rosids using cotton and 25 other completely sequenced angiosperm chloroplast genomes.

Results

The complete cotton chloroplast genome is 160,301 bp in length, with 112 unique genes and 19 duplicated genes within the IR, containing a total of 131 genes. There are four ribosomal RNAs, 30 distinct tRNA genes and 17 intron-containing genes. The gene order in cotton is identical to that of tobacco but lacksrpl22andinfA. There are 30 direct and 24 inverted repeats 30 bp or longer with a sequence identity ≥ 90%. Most of the direct repeats are within intergenic spacer regions, introns and a 72 bp-long direct repeat is within thepsaAandpsaBgenes. Comparison of protein coding sequences with expressed sequence tags (ESTs) revealed nucleotide substitutions resulting in amino acid changes inndhC, rpl23, rpl20, rps3andclpP. Phylogenetic analysis of a data set including 61 protein-coding genes using both maximum likelihood and maximum parsimony were performed for 28 taxa, including cotton and five other angiosperm chloroplast genomes that were not included in any previous phylogenies.

Conclusion

Cotton chloroplast genome lacksrpl22andinfAand contains a number of dispersed direct and inverted repeats. RNA editing resulted in amino acid changes with significant impact on their hydropathy. Phylogenetic analysis provides strong support for the position of cotton in the Malvales in the eurosids II clade sister toArabidopsisin the Brassicales. Furthermore, there is strong support for the placement of the Myrtales sister to the eurosid I clade, although expanded taxon sampling is needed to further test this relationship.
Exploring the reasons for the large density of triplex-forming oligonucleotide target sequences in the human regulatory regions
Authors: Goñi Josep Ramon , Vaquerizas Juan Manuel , Dopazo Joaquin , Orozco Modesto
Published: April 2006

Background

DNA duplex sequences that can be targets for triplex formation are highly over-represented in the human genome, especially in regulatory regions.

Results

Here we studied using bioinformatics tools several properties of triplex target sequences in an attempt to determine those that make these sequences so special in the genome.

Conclusion

Our results strongly suggest that the unique physical properties of these sequences make them particularly suitable as "separators" between protein-recognition sites in the promoter region.