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PubMed2002

In Ssarch of new anti-bacterial target genes: a comparative/structural genomics approach.

We outline a joint academic/industrial (CNRS/AVENTIS) functional genomics project aiming at the discovery of new anti-bacterial gene targets. Starting from all publicly available bacterial genomes, a subset of the most evolutionary conserved protein-coding genes has been identified. We retained genes with clear homolog in E. coli and at least one gram-positive bacterium among B.subtilis, M. tuberculosis, L. lactis or S. pyogenes. This subset was further reduced to genes encoding non-membrane proteins of unknown or hypothetical functions. The 221 E. coli Open Reading Frames (ORFs) identified through this comprehensive bioinformatic analysis are now submitted to a systematic 3-D structure determination protocol including cloning, protein expression and purification, crystallisation and X-ray diffraction. Our strategy was designed to focus on promising wide-spectrum targets as well as original biochemical pathways. Bioinformatics is used throughout all phases of project, including the initial large-scale comparative genomics analyses, the purification/expression and crystallisation stages for the detection of helpful sequence-specific features (e.g. cofactor binding motifs, non-structured N- or C- term extremities, etc ), and finally for the interpretation of the structures in conjunction with multiple sequence alignments for the identification of key residues, interaction areas on molecular surfaces, and overall function predictions.

Anti-Infective Agents↗
PubMed2007

Paired-end genomic signature tags: a method for the functional analysis of genomes and epigenomes.

Because paired-end genomic signature tags are sequenced-based, they have the potential to become an alternate tool to tiled microarray hybridization as a method for genome-wide localization of transcription factors and other sequence-specific DNA binding proteins. As outlined here the method also can be used for global analysis of DNA methylation. One advantage of this approach is the ability to easily switch between different genome types without having to fabricate a new microarray for each and every DNA type. However, the method does have some disadvantages. Among the most rate-limiting steps of our PE-GST protocol are the need to concatemerize the diTAGs, size fractionate them and then clone them prior to sequencing. This is usually followed by additional steps to amplify and size select for long (> or = 500) concatemer inserts prior to sequencing. These time-consuming steps are important for standard DNA sequencing as they increase efficiency approximately 20-30-fold since each amplified concatemer can now provide information on multiple tags; the limitation on data acqui- sition is read length during sequencing. However, the development of new sequencing methods such as Life Sciences' 454 new nanotechnology-based sequencing instrument (41) could increase tag sequencing efficiency by several orders of magnitude (> or = 100,000 diTAG reads/run), which is sufficient to provide in-depth global analysis of all ChIP PE-GSTs in a single run. This is because the lengths of our paired-end diTAGs (approximately 60 bp) fall well within the region of high accuracy for read lengths on this instrument. In principle, sequence analysis of diTAGs could begin as soon as they are generated, thereby completely bypassing the need for the concatemerization, sizing, downstream cloning steps and sequencing template purification. In addition, our protocol places any one of several unique four-base long nucleotide sequences, such as GATC, between each and every diTAG pair, which could be used to help the instrument's software keep base register and also provide a well-located peak height indicator in the middle of every sequence run. This additional feature could permit multiplexing of the data by simultaneous sequencing of several pooled libraries if each used a different linker sequence during diTAG formation (Figure 4).

Base Sequence↗
PubMed1999

Assigning protein functions by comparative genome analysis: protein phylogenetic profiles.

Determining protein functions from genomic sequences is a central goal of bioinformatics. We present a method based on the assumption that proteins that function together in a pathway or structural complex are likely to evolve in a correlated fashion. During evolution, all such functionally linked proteins tend to be either preserved or eliminated in a new species. We describe this property of correlated evolution by characterizing each protein by its phylogenetic profile, a string that encodes the presence or absence of a protein in every known genome. We show that proteins having matching or similar profiles strongly tend to be functionally linked. This method of phylogenetic profiling allows us to predict the function of uncharacterized proteins.

Bacterial Proteins↗
PubMed2005

Genome-wide selection of unique and valid oligonucleotides.

Functional genomics methods are used to investigate the huge amount of information contained in genomes. Numerous experimental methods rely on the use of oligo- or polynucleotides. Nucleotide strand hybridization forms the underlying principle for these methods. For all these techniques, the probes should be unique for analyzed genes. In addition to being unique for the studied genes, the probes should fulfill a large number of criteria to be usable and valid. The criteria include for example, avoidance of self-annealing, suitable melting temperature and nucleotide composition. We developed a method for searching unique and valid oligonucleotides or probes for genes so that there is not even a similar (approximate) occurrence in any other location of the whole genome. By using probe size 25, we analyzed 17 complete genomes representing a wide range of both prokaryotic and eukaryotic organisms. More than 92% of all the genes in the investigated genomes contained valid oligonucleotides. Extensive statistical tests were performed to characterize the properties of unique and valid oligonucleotides. Unique and valid oligonucleotides were relatively evenly distributed in genes except for the beginning and end, which were somewhat overrepresented. The flanking regions in eukaryotes were clearly underrepresented among suitable oligonucleotides. In addition to distributions within genes, the effects on codon and amino acid usage were also studied.

Amino Acids↗
PubMed2005

A compendium of Caenorhabditis elegans regulatory transcription factors: a resource for mapping transcription regulatory networks.

BACKGROUND: Transcription regulatory networks are composed of interactions between transcription factors and their target genes. Whereas unicellular networks have been studied extensively, metazoan transcription regulatory networks remain largely unexplored. Caenorhabditis elegans provides a powerful model to study such metazoan networks because its genome is completely sequenced and many functional genomic tools are available. While C. elegans gene predictions have undergone continuous refinement, this is not true for the annotation of functional transcription factors. The comprehensive identification of transcription factors is essential for the systematic mapping of transcription regulatory networks because it enables the creation of physical transcription factor resources that can be used in assays to map interactions between transcription factors and their target genes. RESULTS: By computational searches and extensive manual curation, we have identified a compendium of 934 transcription factor genes (referred to as wTF2.0). We find that manual curation drastically reduces the number of both false positive and false negative transcription factor predictions. We discuss how transcription factor splice variants and dimer formation may affect the total number of functional transcription factors. In contrast to mouse transcription factor genes, we find that C. elegans transcription factor genes do not undergo significantly more splicing than other genes. This difference may contribute to differences in organism complexity. We identify candidate redundant worm transcription factor genes and orthologous worm and human transcription factor pairs. Finally, we discuss how wTF2.0 can be used together with physical transcription factor clone resources to facilitate the systematic mapping of C. elegans transcription regulatory networks. CONCLUSION: wTF2.0 provides a starting point to decipher the transcription regulatory networks that control metazoan development and function.

Animals↗
PubMed2006

[Nutrigenomics. Scientific basis, status and perspectives of application].

Nutrigenomics investigates the interaction between nutrition and the genome, thereby combining nutritional research with functional genomics. Its aims are (1) to correlate heterogeneous effects of nutrients with sequence variations in the genome and (2) to investigate the effects of nutrients and other food components on gene expression at a genome-wide scale (mRNA profiling), and on patterns of metabolite alterations in serum (metabolite profiling). The field will provide important information as to the biological effects of food components, and to the functional consequences of genetic variance. This information will improve the prevention of nutrition-related diseases, e. g. by establishing personalised nutritional recommendations.

Adult↗
PubMed2005

Genome-wide introgression lines and their use in genetic and molecular dissection of complex phenotypes in rice (Oryza sativa L.).

Tremendous efforts have been taken worldwide to develop genome-wide genetic stocks for rice functional genomic (FG) research since the rice genome was completely sequenced. To facilitate FG research of complex polygenic phenotypes in rice, we report the development of over 20,000 introgression lines (ILs) in three elite rice genetic backgrounds for a wide range of complex traits, including resistances/tolerances to many biotic and abiotic stresses, morpho-agronomic traits, physiological traits, etc., by selective introgression. ILs within each genetic background are phenotypically similar to their recurrent parent but each carries one or a few traits introgressed from a known donor. Together, these ILs contain a significant portion of loci affecting the selected complex phenotypes at which allelic diversity exists in the primary gene pool of rice. A forward genetics strategy was proposed and demonstrated with examples on how to use these ILs for large-scale FG research. Complementary to the genome-wide insertional mutants, these ILs opens a new way for highly efficient discovery, candidate gene identification and cloning of important QTLs for specific phenotypes based on convergent evidence from QTL position, expression profiling, functional and molecular diversity analyses of candidate genes, highlights the importance of genetic networks underlying complex phenotypes in rice that may ultimately lead to more complete understanding of the genetic and molecular bases of quantitative trait variation in rice.

Adaptation, Physiological↗
PubMed1999

Gene expression profiling, genetic networks, and cellular states: an integrating concept for tumorigenesis and drug discovery.

Genome-wide expression monitoring, a novel tool of functional genomics, is currently used mainly to identify groups of coregulated genes and to discover genes expressed differentially in distinct situations that could serve as drug targets. This descriptive approach. however, fails to extract "distributed" information embedded in the genomic regulatory network and manifested in distinct gene activation profiles. A model based on the formalism of boolean genetic networks in which cellular states are represented by attractors in a discrete dynamic system can serve as a conceptual framework for an integrative interpretation of gene expression profiles. Such a global (genome-wide) view of "gene function" in the regulation of the dynamic relationship between proliferation, differentiation, and apoptosis can provide new insights into cellular homeostasis and the origins of neoplasia. Implications for a rational approach to the identification of new drug targets for cancer treatment are discussed.

Biotechnology↗
PubMed2006

Genome increase as a clock for the origin and evolution of life.

BACKGROUND: The size of non-redundant functional genome can be an indicator of biological complexity of living organisms. Several positive feedback mechanisms including gene cooperation and duplication with subsequent specialization may result in the exponential growth of biological complexity in macro-evolution. RESULTS: I propose a hypothesis that biological complexity increased exponentially during evolution. Regression of the logarithm of functional non-redundant genome size versus time of origin in major groups of organisms showed a 7.8-fold increase per 1 billion years, and hence the increase of complexity can be viewed as a clock of macro-evolution. A strong version of the exponential hypothesis is that the rate of complexity increase in early (pre-prokaryotic) evolution of life was at most the same (or even slower) than observed in the evolution of prokaryotes and eukaryotes. CONCLUSION: The increase of functional non-redundant genome size in macro-evolution was consistent with the exponential hypothesis. If the strong exponential hypothesis is true, then the origin of life should be dated 10 billion years ago. Thus, the possibility of panspermia as a source of life on earth should be discussed on equal basis with alternative hypotheses of de-novo life origin. Panspermia may be proven if bacteria similar to terrestrial ones are found on other planets or satellites in the solar system. REVIEWERS: This article was reviewed by Eugene V. Koonin, Chris Adami and Arcady Mushegian.

Journal Article↗
PubMed2004

Analyzing protein function on a genomic scale: the importance of gold-standard positives and negatives for network prediction.

The concept of 'protein function' is rather 'fuzzy' because it is often based on whimsical terms or contradictory nomenclature. This currently presents a challenge for functional genomics because precise definitions are essential for most computational approaches. Addressing this challenge, the notion of networks between biological entities (including molecular and genetic interaction networks as well as transcriptional regulatory relationships) potentially provides a unifying language suitable for the systematic description of protein function. Predicting the edges in protein networks requires reference sets of examples with known outcome (that is, 'gold standards'). Such reference sets should ideally include positive examples - as is now widely appreciated - but also, equally importantly, negative ones. Moreover, it is necessary to consider the expected relative occurrence of positives and negatives because this affects the misclassification rates of experiments and computational predictions. For instance, a reason why genome-wide, experimental protein-protein interaction networks have high inaccuracies is that the prior probability of finding interactions (positives) rather than non-interacting protein pairs (negatives) in unbiased screens is very small. These problems can be addressed by constructing well-defined sets of non-interacting proteins from subcellular localization data, which allows computing the probability of interactions based on evidence from multiple datasets.

Algorithms↗
PubMed2004

Analysis of molecular aberrations in ovarian cancer allows novel target identification.

The completion of the Human Genome Project and recent advances in functional genomic, proteomic, and high-throughput screening methodologies have provided powerful tools for determining the mechanisms of human diseases, including complex polygenic diseases such as ovarian cancer. These developments may eventually lead to individualized molecular medicine, which is the treatment of patients based on the underlying genetic defects in their tumours and their own genetic makeup. A plethora of novel therapeutic agents that act on specific molecular targets defined by cancer genetics are under development. There is thus a great deal of interest in determining how specific genes and proteins function in cancers, in order to further the understanding of cancer initiation and progression; to aid in identifying biomarkers, therapeutic targets, and determinants of drug responsiveness; and to progress the development of novel antitumour agents.

Antineoplastic Agents↗
PubMed2005

A common sex-dependent mutation in a RET enhancer underlies Hirschsprung disease risk.

The identification of common variants that contribute to the genesis of human inherited disorders remains a significant challenge. Hirschsprung disease (HSCR) is a multifactorial, non-mendelian disorder in which rare high-penetrance coding sequence mutations in the receptor tyrosine kinase RET contribute to risk in combination with mutations at other genes. We have used family-based association studies to identify a disease interval, and integrated this with comparative and functional genomic analysis to prioritize conserved and functional elements within which mutations can be sought. We now show that a common non-coding RET variant within a conserved enhancer-like sequence in intron 1 is significantly associated with HSCR susceptibility and makes a 20-fold greater contribution to risk than rare alleles do. This mutation reduces in vitro enhancer activity markedly, has low penetrance, has different genetic effects in males and females, and explains several features of the complex inheritance pattern of HSCR. Thus, common low-penetrance variants, identified by association studies, can underlie both common and rare diseases.

Animals↗
PubMed2006

Systematic gene function prediction from gene expression data by using a fuzzy nearest-cluster method.

BACKGROUND: Quantitative simultaneous monitoring of the expression levels of thousands of genes under various experimental conditions is now possible using microarray experiments. However, there are still gaps toward whole-genome functional annotation of genes using the gene expression data. RESULTS: In this paper, we propose a novel technique called Fuzzy Nearest Clusters for genome-wide functional annotation of unclassified genes. The technique consists of two steps: an initial hierarchical clustering step to detect homogeneous co-expressed gene subgroups or clusters in each possibly heterogeneous functional class; followed by a classification step to predict the functional roles of the unclassified genes based on their corresponding similarities to the detected functional clusters. CONCLUSION: Our experimental results with yeast gene expression data showed that the proposed method can accurately predict the genes' functions, even those with multiple functional roles, and the prediction performance is most independent of the underlying heterogeneity of the complex functional classes, as compared to the other conventional gene function prediction approaches.

Algorithms↗
PubMed2002

Expression profile of the channel catfish spleen: analysis of genes involved in immune functions.

Both qualitative and quantitative patterns of tissue-specific gene expression can be determined using gene profiling. Expressed sequence tag (EST) analysis is an efficient approach not only for gene discovery and examining gene expression, but also for development of molecular resources useful for functional genomics. As part of an ongoing transcriptome analysis of channel catfish (Ictalurus punctatus), EST analysis was conducted for gene annotations and profiling using a complementary DNA library developed from messenger RNA of the spleen. A total of 1204 spleen cDNA clones were analyzed. Of the 1204 clones, 665 clones (55.2%) were identified as orthologs of known genes from other organisms by BLAST searches and 539 clones (44.8%) as unknown gene clones. In total 147 novel genes were identified, and annotations were made to 118 of them. In addition, 389 novel EST clusters were identified. Expression profile was analyzed in relation to metabolic functional groups. A total of 28 known genes were involved in immune functions, of which 10 were identified for the first time in channel catfish. Microsatellite-containing clones were also identified that may be potentially useful for genome mapping. This work contributed to the Catfish Gene Index, and toward a Unigene set useful for functional genomics research concerning spleen gene functions in relation to disease defenses.

Journal Article↗
PubMed2005

[Research strategies towards a holistic characterization of rheumatoid arthritis--a systems biology approach].

Genome-wide screening methods used in functional genomics (genome, transcriptome, proteome and metabolom analysis) have increasingly been conducted in integrative research platforms to enable a comprehensive holistic characterization of multifactorial polygenic diseases. First results of this research strategy demonstrate that extended data sets are compiled whose quality is ensured by the application of standard operating procedures (SOPs) and the integration of specific laboratory information management systems (LIMS). Experimental data derived from this technology and methodology platform are obtained by applying standardized sampling procedures followed by comprehensive experimental validation and bioinformatic comparisons with the world knowledge publicly available. This research strategy should finally lead to a holistic understanding of the pathogenesis presented in rheumatoid arthritis by identifying disease-associated regulatory networks (pathways) and assigning them to cell populations involved in the disease mechanisms. In addition, it has to be investigated to what extent genetic as well as epigenetic factors direct disease initiation and progression in potential conjunction with environmental impacts (infections, smoking, etc.).

Animals↗
PubMed2006

Non-target-site herbicide resistance: a family business.

We have witnessed a dramatic increase in the frequency and diversity of herbicide-resistant weed biotypes over the past two decades, which poses a threat to the sustainability of agriculture at both local and global levels. In addition, non-target-site mechanisms of herbicide resistance seem to be increasingly implicated. Non-target-site herbicide resistance normally involves the biochemical modification of the herbicide and/or the compartmentation of the herbicide (and its metabolites). In contrast to herbicide target site mutations, fewer non-target mechanisms have been elucidated at the molecular level because of the inherently complicated biochemical processes and the limited genomic information available for weedy species. To further understand the mechanisms of non-target-site resistance, we propose an integrated genomics approach to dissect systematically the functional genomics of four gene families in economically important weed species.

Genomics↗
PubMed1999

Plant genomics.

The rapidity with which genomic sequences of the model plant Arabidopsis thaliana and soon of rice are becoming available has strongly boosted plant molecular biology research. Here, two main genomic fields will be discussed: the progress in different structural genome projects, such as mapping, sequencing, genome organization and comparative genomics, and the so-called functional genomics approaches to analyze the genome using such molecular tools as transcript profiling, micro-arrays, and insertional mutagenesis. In addition a section on bioinformatics is included.

DNA, Plant↗
PubMed2002

Physical and functional interactions among basic chromosome organizational features govern early steps of meiotic chiasma formation.

Analysis of meiotic recombination by functional genomic approaches reveals prominent spatial and functional interactions among diverse organizational determinants. Recombination occurs between chromatin loop sequences; however, these sequences are spatially tethered to underlying chromosome axes via their recombinosomes. Meiotic chromosomal protein, Red1, localizes to chromosome axes; however, Red1 loading is modulated by R/G-bands isochores and thus by bulk chromatin state. Recombination is also modulated by isochore determinants: R-bands differentially favor double-strand break (DSB) formation but disfavor subsequent loading of meiotic RecA homolog, Dmc1. Red1 promotes DSB formation in both R- and G-bands and then promotes Dmc1 loading, specifically counteracting disfavoring R-band effects. These complexities are discussed in the context of chiasma formation as a series of coordinated local changes at the DNA and chromosome-axis levels.

Cell Cycle Proteins↗