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PubMed2006

Gene expression patterns in the developing murine placenta.

OBJECTIVE: Successful placental development is crucial for optimal growth, maturation, and survival of the embryo/fetus. To examine genetic aspects of placental development, we investigated gene expression patterns in the murine placenta at embryonic day 10.5 (E10.5), E12.5, E15.5, and E17.5. METHODS: By use of the Affymetrix MU74A array (Affymetrix, Santa Clara, CA), we measured expression levels for 12,473 probe sets. Using pairwise analysis we selected 622 probe sets, corresponding to 599 genes, that were up- or down-regulated by more than fourfold between time points E10.5 and E12.5, E12.5 and E15.5, E15.5 and E17.5. We analyzed and functionally annotated those genes regulated during development. RESULTS: In comparing E10.5 to E12.5 we found that angiogenesis and fatty acid metabolism and transport related genes were up-regulated at E10.5, while genes involved in hormonal control and ribosomal proteins were up-regulated at E12.5. When comparing E12.5 to E15.5 we noted that genes involved in the cell cycle and RNA metabolism were strongly up-regulated at E12.5, while genes involved in cellular transport were up-regulated at E15.5. Finally, when comparing E15.5 to E17.5, we found genes related to cell cycle control, genes expressed in the nucleus and involved in RNA metabolism were up-regulated at E17.5. CONCLUSION: Microarray analysis has allowed us to describe gene expression patterns and profiles in the developing mouse placenta. Further analysis has demonstrated that several functional classes are up- and down-regulated at specific time points in placental development. These changes may have significant implications for placental development in the human.

Animals↗

PubMed2005

Gene fusions and gene duplications: relevance to genomic annotation and functional analysis.

BACKGROUND: Escherichia coli a model organism provides information for annotation of other genomes. Our analysis of its genome has shown that proteins encoded by fused genes need special attention. Such composite (multimodular) proteins consist of two or more components (modules) encoding distinct functions. Multimodular proteins have been found to complicate both annotation and generation of sequence similar groups. Previous work overstated the number of multimodular proteins in E. coli. This work corrects the identification of modules by including sequence information from proteins in 50 sequenced microbial genomes. RESULTS: Multimodular E. coli K-12 proteins were identified from sequence similarities between their component modules and non-fused proteins in 50 genomes and from the literature. We found 109 multimodular proteins in E. coli containing either two or three modules. Most modules had standalone sequence relatives in other genomes. The separated modules together with all the single (un-fused) proteins constitute the sum of all unimodular proteins of E. coli. Pairwise sequence relationships among all E. coli unimodular proteins generated 490 sequence similar, paralogous groups. Groups ranged in size from 92 to 2 members and had varying degrees of relatedness among their members. Some E. coli enzyme groups were compared to homologs in other bacterial genomes. CONCLUSION: The deleterious effects of multimodular proteins on annotation and on the formation of groups of paralogs are emphasized. To improve annotation results, all multimodular proteins in an organism should be detected and when known each function should be connected with its location in the sequence of the protein. When transferring functions by sequence similarity, alignment locations must be noted, particularly when alignments cover only part of the sequences, in order to enable transfer of the correct function. Separating multimodular proteins into module units makes it possible to generate protein groups related by both sequence and function, avoiding mixing of unrelated sequences. Organisms differ in sizes of groups of sequence-related proteins. A sample comparison of orthologs to selected E. coli paralogous groups correlates with known physiological and taxonomic relationships between the organisms.

Computational Biology↗

PubMed2004

Automatic extraction of gene/protein biological functions from biomedical text.

MOTIVATION: With the rapid advancement of biomedical science and the development of high-throughput analysis methods, the extraction of various types of information from biomedical text has become critical. Since automatic functional annotations of genes are quite useful for interpreting large amounts of high-throughput data efficiently, the demand for automatic extraction of information related to gene functions from text has been increasing. RESULTS: We have developed a method for automatically extracting the biological process functions of genes/protein/families based on Gene Ontology (GO) from text using a shallow parser and sentence structure analysis techniques. When the gene/protein/family names and their functions are described in ACTOR (doer of action) and OBJECT (receiver of action) relationships, the corresponding GO-IDs are assigned to the genes/proteins/families. The gene/protein/family names are recognized using the gene/protein/family name dictionaries developed by our group. To achieve wide recognition of the gene/protein/family functions, we semi-automatically gather functional terms based on GO using co-occurrence, collocation similarities and rule-based techniques. A preliminary experiment demonstrated that our method has an estimated recall of 54-64% with a precision of 91-94% for actually described functions in abstracts. When applied to the PUBMED, it extracted over 190 000 gene-GO relationships and 150 000 family-GO relationships for major eukaryotes.

Abstracting and Indexing↗

PubMed2006

Biclustering of gene expression data by Non-smooth Non-negative Matrix Factorization.

BACKGROUND: The extended use of microarray technologies has enabled the generation and accumulation of gene expression datasets that contain expression levels of thousands of genes across tens or hundreds of different experimental conditions. One of the major challenges in the analysis of such datasets is to discover local structures composed by sets of genes that show coherent expression patterns across subsets of experimental conditions. These patterns may provide clues about the main biological processes associated to different physiological states. RESULTS: In this work we present a methodology able to cluster genes and conditions highly related in sub-portions of the data. Our approach is based on a new data mining technique, Non-smooth Non-Negative Matrix Factorization (nsNMF), able to identify localized patterns in large datasets. We assessed the potential of this methodology analyzing several synthetic datasets as well as two large and heterogeneous sets of gene expression profiles. In all cases the method was able to identify localized features related to sets of genes that show consistent expression patterns across subsets of experimental conditions. The uncovered structures showed a clear biological meaning in terms of relationships among functional annotations of genes and the phenotypes or physiological states of the associated conditions. CONCLUSION: The proposed approach can be a useful tool to analyze large and heterogeneous gene expression datasets. The method is able to identify complex relationships among genes and conditions that are difficult to identify by standard clustering algorithms.

Algorithms↗

PubMed2005

A whole lotta jumpin' goin' on: new transposon tools for vertebrate functional genomics.

Genome sequences of vertebrate model organisms are becoming available, fuelling the next challenging phase of research: annotating all of the genes with functional information. The functional annotation of all of the approximately 35 000 genes in mammals will undoubtedly require complementing the technologies of forward and reverse genetics in mutagenesis screens. Two recent articles report on the construction of retrotransposable elements that efficiently 'jump' in mammalian cells. These new elements hold great promise as useful vectors for insertional mutagenesis screens in the mouse.

Animals↗

PubMed2004

Comparing functional annotation analyses with Catmap.

BACKGROUND: Ranked gene lists from microarray experiments are usually analysed by assigning significance to predefined gene categories, e.g., based on functional annotations. Tools performing such analyses are often restricted to a category score based on a cutoff in the ranked list and a significance calculation based on random gene permutations as null hypothesis. RESULTS: We analysed three publicly available data sets, in each of which samples were divided in two classes and genes ranked according to their correlation to class labels. We developed a program, Catmap (available for download at http://bioinfo.thep.lu.se/Catmap), to compare different scores and null hypotheses in gene category analysis, using Gene Ontology annotations for category definition. When a cutoff-based score was used, results depended strongly on the choice of cutoff, introducing an arbitrariness in the analysis. Comparing results using random gene permutations and random sample permutations, respectively, we found that the assigned significance of a category depended strongly on the choice of null hypothesis. Compared to sample label permutations, gene permutations gave much smaller p-values for large categories with many coexpressed genes. CONCLUSIONS: In gene category analyses of ranked gene lists, a cutoff independent score is preferable. The choice of null hypothesis is very important; random gene permutations does not work well as an approximation to sample label permutations.

Classification↗

PubMed2026

Pinpointing genomic regions conferring herbicide tolerance in cassava via genome-wide association mapping.

Cassava (Manihot esculenta Crantz) is a tropical crop of major socioeconomic importance, whose productivity can be limited by sensitivity to herbicides used for weed management. This study aimed to perform a genome-wide association study (GWAS) in 194 cassava genotypes to identify genomic regions associated with tolerance to the herbicides mesotrione, S-metolachlor, and chloransulam-methyl. The evaluations performed at 3, 6, 9, 15, and 30 days after application (DAA) were used to characterize the temporal progression of phytotoxicity. Based on this analysis, the phenotype obtained at 9 days after application (PhytoX9DAA) was selected for genome-wide association analyses because it represented the period of greatest symptom expression and the highest discrimination among genotypes. GWAS analyses were performed using de-regressed BLUPs and the MLM, MLMM, and BLINK models, incorporating kinship (K) and population structure (Q) matrices. Significant markers were detected across multiple chromosomes, and the corresponding genomic windows contained candidate genes with functional annotations related to herbicide response. The predominant functional categories included membrane transport, channel activity, signal peptide processing, protein phosphorylation, cellular signaling, and metabolic regulation. Key candidate genes included Manes.02G151900 and Manes.02G152700 (chromosome 2), associated with transmembrane transport and signal peptide processing; Manes.09G060900 (chromosome 9), associated with protein kinase activity, ATP binding, and protein phosphorylation; and Manes.15G083800 and Manes.15G084000 (chromosome 15), associated with S-adenosylmethionine-dependent methyltransferase activity, membrane-related functions, and protein phosphorylation. These genes participate in biochemical pathways involved in cellular signaling, membrane transport, and metabolic regulation that may contribute to herbicide tolerance. Overall, the results demonstrate that herbicide tolerance in cassava is a quantitative and polygenic trait governed by numerous small-effect loci. The integration of cellular signaling, metabolic regulation, and membrane transport supports the physiological resilience of the species under chemical exposure, providing valuable insights for breeding strategies and marker-assisted selection.

Genome-Wide Association Study↗

PubMed2006

Aetiology-specific patterns in end-stage heart failure patients identified by functional annotation and classification of microarray data.

BACKGROUND: The objective of the present study was to use gene expression profiling, functional annotations and classification to identify aetiology-specific biological processes and potential molecular markers for different aetiologies of end-stage heart failure. METHODS AND RESULTS: Individual left ventricular myocardial samples from eleven coronary artery disease and nine dilated cardiomyopathy transplant patients were co-hybridized with pooled RNA from four non-failing hearts on custom-made arrays of 7000 human genes. Significance analysis identified differential expression of 153 and 147 genes, respectively, in coronary artery disease or dilated cardiomyopathy versus non-failing hearts. Analysis of Gene Ontology biological process annotations indicated aetiology-specific patterns, primarily related to genes involved in catabolism and in regulation of protein kinase activity. Gene expression classifiers were obtained and used for class prediction of random samples of coronary artery diseased and dilated cardiomyopathic hearts. Best classifiers frequently included matrix metalloproteinase 3, fibulin 1, ATP-binding cassette, sub-family B member 1 and iroquois homeobox protein 5. CONCLUSION: Combining functional annotation from microarray data and classification analysis constitutes a potent strategy to identify disease-specific biological processes and gene expression markers in e.g. end-stage coronary artery disease and dilated cardiomyopathy.

Adult↗

PubMed2026

Genomes of the ex-type strains of Elsinoë mangiferae and E. perseae, the causal agents of scab on mango and avocado.

Elsinoë species are slow-growing, hemibiotrophic to necrotrophic fungi that cause scab diseases on economically important fruit crops. Genome resources for many host-specific species remain limited. We report high-quality draft genome assemblies for the ex-type strains of Elsinoë mangiferae (CBS 226.50) and E. perseae (CBS 406.34), causal agents of mango and avocado scab, respectively. Among 5 approaches tested, a Nanopore-only NextDenovo assembly produced the most contiguous genomes, yielding 24.5 Mb (E. mangiferae) and 25.1 Mb (E. perseae) assemblies with 13 and 18 contigs, respectively, BUSCO completeness scores of ∼94%, and multiple putative telomere-to-telomere chromosomes. Gene prediction identified 9,134 and 9,243 genes, respectively. Functional annotation revealed enrichment of metabolic and regulatory pathways, including those involved in posttranslational modification, protein transport, and secondary metabolism. Carbohydrate-active enzyme repertoires were small but conserved, consistent with stealth pathogenicity strategies and low plant cell wall degradation. Both genomes encoded large secretomes (>850 proteins), diverse protease repertoires (>300 proteins), Ecp2-like effector proteins, and multiple biosynthetic gene clusters, including clusters with similarity to those associated with elsinochrome and ACT-toxin II biosynthesis, some of which may contribute to host-pathogen interactions and disease development. A large fraction of genes lacked functional characterization, suggesting incomplete databases and/or the presence of lineage-specific genes potentially involved in virulence or host adaptation. These genome resources fill critical gaps for underrepresented Elsinoë species and provide taxonomically anchored references essential for diagnostics, comparative genomics, and research into the molecular basis of host specificity and pathogenicity in scab-causing fungi.

Persea↗

PubMed2005

Protein encoding genes in an ancient plant: analysis of codon usage, retained genes and splice sites in a moss, Physcomitrella patens.

BACKGROUND: The moss Physcomitrella patens is an emerging plant model system due to its high rate of homologous recombination, haploidy, simple body plan, physiological properties as well as phylogenetic position. Available EST data was clustered and assembled, and provided the basis for a genome-wide analysis of protein encoding genes. RESULTS: We have clustered and assembled Physcomitrella patens EST and CDS data in order to represent the transcriptome of this non-seed plant. Clustering of the publicly available data and subsequent prediction resulted in a total of 19,081 non-redundant ORF. Of these putative transcripts, approximately 30% have a homolog in both rice and Arabidopsis transcriptome. More than 130 transcripts are not present in seed plants but can be found in other kingdoms. These potential "retained genes" might have been lost during seed plant evolution. Functional annotation of these genes reveals unequal distribution among taxonomic groups and intriguing putative functions such as cytotoxicity and nucleic acid repair. Whereas introns in the moss are larger on average than in the seed plant Arabidopsis thaliana, position and amount of introns are approximately the same. Contrary to Arabidopsis, where CDS contain on average 44% G/C, in Physcomitrella the average G/C content is 50%. Interestingly, moss orthologs of Arabidopsis genes show a significant drift of codon fraction usage, towards the seed plant. While averaged codon bias is the same in Physcomitrella and Arabidopsis, the distribution pattern is different, with 15% of moss genes being unbiased. Species-specific, sensitive and selective splice site prediction for Physcomitrella has been developed using a dataset of 368 donor and acceptor sites, utilizing a support vector machine. The prediction accuracy is better than those achieved with tools trained on Arabidopsis data. CONCLUSION: Analysis of the moss transcriptome displays differences in gene structure, codon and splice site usage in comparison with the seed plant Arabidopsis. Putative retained genes exhibit possible functions that might explain the peculiar physiological properties of mosses. Both the transcriptome representation (including a BLAST and retrieval service) and splice site prediction have been made available on http://www.cosmoss.org, setting the basis for assembly and annotation of the Physcomitrella genome, of which draft shotgun sequences will become available in 2005.

Alternative Splicing↗

PubMed2023

Discussion on the mechanism of Lingguizhugan Decoction in treating hypertension based on network pharmacology and molecular simulation technology.

To explore the mechanism of Lingguizhugan Decoction in treating hypertension based on network pharmacology and molecular simulation. The active ingredients and potential targets were screened by the Systematic Pharmacological Analysis Platform of Traditional Chinese Medicine (TCMSP). Hypertension-related targets were obtained from OMIM and GeneCards databases. Common targets between drug and hypertension were screened in the Venny platform. A protein-protein interaction (PPI) network was constructed in the STRING database using intersection targets. Key targets in PPI network were analyzed by Cytoscape. R language program was used for Gene Ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Finally, the binding abilities of the main active ingredients to critical targets were verified by molecular simulation. Naringenin, quercetin, kaempferol, and β-sitosterol in Lingguizhugan Decoction, and potential targets such as STAT3, AKT1, TNF, IL6, JUN, PTGS2, MMP9, CASP3, TP53, and MAPK3, were screened out. KEGG Enrichment analysis revealed that the common targets of Lingguizhugan Decoction and hypertension are mainly involved in the lipid and atherosclerosis signaling pathway, AGE-RAGE signaling pathway in diabetic complications, fluid shear stress and atherosclerosis, and IL17 signaling pathway. The molecular simulation results showed that naringenin-MAPK3, quercetin-MMP9, quercetin-PTGS2, and quercetin-TP53 were the top four in the docking scores. Naringenin-MAPK3 and quercetin-MMP9 were stable, with binding free energies of -27.97 ± 1.41 kcal/mol and -21.15 ± 3.17 kcal/mol, respectively. The possible mechanism of Lingguizhugan Decoction in treating hypertension is characterized of multi-component, multi-target, and multi-pathway.Communicated by Ramaswamy H. Sarma.

Network Pharmacology↗

PubMed2026

[Effects and mechanisms of ethanol extract of Salvia miltiorrhiza on liver fibrosis in mice].

To identify clinically advantageous TCMs for anti-hepatic fibrosis and to elucidate the effects and molecular mechanisms of Salvia miltiorrhiza ethanol extract in the intervention of liver fibrosis, this study screened high-frequency anti-hepatic fibrosis TCMs through a review of clinical literature. The S. miltiorrhiza active components, potential targets, and liver fibrosis-related disease targets were obtained using the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP), the GeneCards database, and other databases. Gene Ontology(GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analyses were performed on the shared targets between drugs and diseases. Molecular docking was conducted to evaluate the binding affinities between key components and core targets. In animal experiments, male Kunming mice were used to establish a liver fibrosis model induced by carbon tetrachloride(CCl_4). The mice were administered low, medium, and high doses of S. miltiorrhiza ethanol extract by gavage. The liver index, as well as serum aspartate aminotransferase(AST) and alanine aminotransferase(ALT) levels, were measured. Histopathological changes in liver tissue were observed using hematoxylin-eosin(HE) staining and Masson's trichrome staining. Western blot analysis was used to detect the protein expression levels of α-smooth muscle actin(α-SMA), Collagen Ⅰ, and heat shock protein 90 alpha family class A member 1(HSP90AA1) in liver tissue. The results showed that S. miltiorrhiza was the most frequently used TCM in clinical anti-hepatic fibrosis. A total of 65 active components and 135 potential targets were identified, and 109 common targets were obtained by intersecting these with liver fibrosis-related targets. The core targets included tumor protein p53(TP53), serine/threonine protein kinase AKT1(AKT1), Jun proto-oncogene(JUN), signal transducer and activator of transcription 3(STAT3), and HSP90AA1, which were mainly enriched in pathways related to cancer, hepatitis B, and the PI3K-AKT signaling pathway. Molecular docking indicated that the main active components of S. miltiorrhiza bound stably to the core targets, with the strongest binding affinity observed for HSP90AA1. Animal experiments demonstrated that the liver index, serum ALT and AST levels, and the expression of α-SMA, Collagen Ⅰ, and HSP90AA1 in liver tissue were significantly increased in the model group, accompanied by obvious pathological manifestations of fibrosis. Compared with the model group, different dose groups of S. miltiorrhiza ethanol extract reduced the liver index and serum ALT and AST levels to varying degrees, alleviated pathological damage and collagen deposition in liver tissue, and downregulated the protein expression of α-SMA, Collagen Ⅰ, and HSP90AA1. In conclusion, S. miltiorrhiza ethanol extract exerts a significant protective effect on CCl_4-induced liver fibrosis in mice, and its mechanisms may be related to the inhibition of HSP90AA1 expression and the regulation of liver fibrosis-related signaling pathways.

Animals↗

PubMed2006

Using local gene expression similarities to discover regulatory binding site modules.

BACKGROUND: We present an approach designed to identify gene regulation patterns using sequence and expression data collected for Saccharomyces cerevisae. Our main goal is to relate the combinations of transcription factor binding sites (also referred to as binding site modules) identified in gene promoters to the expression of these genes. The novel aspects include local expression similarity clustering and an exact IF-THEN rule inference algorithm. We also provide a method of rule generalization to include genes with unknown expression profiles. RESULTS: We have implemented the proposed framework and tested it on publicly available datasets from yeast S. cerevisae. The testing procedure consists of thorough statistical analyses of the groups of genes matching the rules we infer from expression data against known sets of co-regulated genes. For this purpose we have used published ChIP-Chip data and Gene Ontology annotations. In order to make these tests more objective we compare our results with recently published similar studies. CONCLUSION: Results we obtain show that local expression similarity clustering greatly enhances overall quality of the derived rules, both in terms of enrichment of Gene Ontology functional annotation and coherence with ChIP-Chip binding data. Our approach thus provides reliable hypotheses on co-regulation that can be experimentally verified. An important feature of the method is its reliance only on widely accessible sequence and expression data. The same procedure can be easily applied to other microbial organisms.

Binding Sites↗

PubMed2005

CLIP: a method for identifying protein-RNA interaction sites in living cells.

Nucleic-acid binding proteins constitute nearly one-fourth of all functionally annotated human genes. Genome-wide analysis of protein-nucleic acid contacts has not yet been performed for most of these proteins, restricting attempts to establish a comprehensive understanding of protein function. UV cross-linking is a method typically used to determine the position of direct interactions between proteins and nucleic acids. We have developed the cross-linking and immunoprecipitation assay, which exploits the covalent protein-nucleic acid cross-linking to stringently purify a specific protein-RNA complex using immunoprecipitation followed by SDS-PAGE separation. In this way, the vast majority of non-specific contaminating RNA, which can bind to co-immunoprecipitated proteins or beads, can be removed. Here, we present an improved protocol that performs RNA linker ligation before the SDS-PAGE step, and describe its application to the specific purification and amplification of RNA ligands of Nova in neurons.

Animals↗

PubMed2000

KEGG: kyoto encyclopedia of genes and genomes.

KEGG (Kyoto Encyclopedia of Genes and Genomes) is a knowledge base for systematic analysis of gene functions, linking genomic information with higher order functional information. The genomic information is stored in the GENES database, which is a collection of gene catalogs for all the completely sequenced genomes and some partial genomes with up-to-date annotation of gene functions. The higher order functional information is stored in the PATHWAY database, which contains graphical representations of cellular processes, such as metabolism, membrane transport, signal transduction and cell cycle. The PATHWAY database is supplemented by a set of ortholog group tables for the information about conserved subpathways (pathway motifs), which are often encoded by positionally coupled genes on the chromosome and which are especially useful in predicting gene functions. A third database in KEGG is LIGAND for the information about chemical compounds, enzyme molecules and enzymatic reactions. KEGG provides Java graphics tools for browsing genome maps, comparing two genome maps and manipulating expression maps, as well as computational tools for sequence comparison, graph comparison and path computation. The KEGG databases are daily updated and made freely available (http://www. genome.ad.jp/kegg/).

Animals↗

PubMed2006

Regulation of gene expression in RAW 264.7 macrophage cell line by interferon-gamma.

Macrophages play an important role in immune responses and in inflammatory disease states such as atherosclerosis. Interferon-gamma (IFN-gamma) is a major cytokine involved in the activation of macrophages. To elucidate the primary response of various genes and biological pathways regulated by IFN-gamma in macrophage, we analyzed the gene expression profile in RAW 264.7 macrophage cells treated with IFN-gamma for 4h. Microarray analysis revealed that about 400 genes were differentially expressed, of which about 250 genes were up-regulated and 150 were down-regulated. Functional organization of the transcriptome revealed that induced genes are involved in antimicrobial and antiviral responses, antigen presentation, chemokine and cytokine signaling, and inhibition of cell growth. We also found that expression of genes involved in cell-cycle control, DNA repair, and lipid metabolism was suppressed by IFN-gamma. We also identified induction of multiple transcription factors by IFN-gamma in RAW 264.7 cells. Functional annotation of genes regulated by IFN-gamma in RAW 264.7 cells may provide novel insights into the role of macrophages in immunity and in inflammatory disease.

Animals↗

PubMed2006

Differential evolutionary conservation of motif modes in the yeast protein interaction network.

BACKGROUND: The importance of a network motif (a recurring interconnected pattern of special topology which is over-represented in a biological network) lies in its position in the hierarchy between the protein molecule and the module in a protein-protein interaction network. Until now, however, the methods available have greatly restricted the scope of research. While they have focused on the analysis in the resolution of a motif topology, they have not been able to distinguish particular motifs of the same topology in a protein-protein interaction network. RESULTS: We have been able to assign the molecular function annotations of Gene Ontology to each protein in the protein-protein interactions of Saccharomyces cerevisiae. For various motif topologies, we have developed an algorithm, enabling us to unveil one million "motif modes", each of which features a unique topological combination of molecular functions. To our surprise, the conservation ratio, i.e., the extent of the evolutionary constraints upon the motif modes of the same motif topology, varies significantly, clearly indicative of distinct differences in the evolutionary constraints upon motifs of the same motif topology. Equally important, for all motif modes, we have found a power-law distribution of the motif counts on each motif mode. We postulate that motif modes may very well represent the evolutionary-conserved topological units of a protein interaction network. CONCLUSION: For the first time, the motifs of a protein interaction network have been investigated beyond the scope of motif topology. The motif modes determined in this study have not only enabled us to differentiate among different evolutionary constraints on motifs of the same topology but have also opened up new avenues through which protein interaction networks can be analyzed.

Algorithms↗

PubMed1997

Sequencing and functional annotation of the Bacillus subtilis genes in the 200 kb rrnB-dnaB region.

The 200 kb region of the Bacillus subtilis chromosome spanning from 255 to 275 degrees on the genetic map was sequenced. The strategy applied, based on use of yeast artificial chromosomes and multiplex Long Accurate PCR, proved to be very efficient for sequencing a large bacterial chromosome area. A total of 193 genes of this part of the chromosome was classified by level of knowledge and biological category of their functions. Five levels of gene function understanding are defined. These are: (i) experimental evidence is available of gene product or biological function; (ii) strong homology exists for the putative gene product with proteins from other organisms; (iii) some indication of the function can be derived from homologies with known proteins; (iv) the gene product can be clustered with hypothetical proteins; (v) no indication on the gene function exists. The percentage of detected genes in each category was: 20, 28, 20, 15 and 17, respectively. In the sequenced region, a high percentage of genes are implicated in transport and metabolic linking of glycolysis and the citric acid cycle. A functional connection of several genes from this region and the genes close to 140 degrees in the chromosome was also observed.

Bacillus subtilis↗