Background Insertion Sequence (IS) elements are mobile genetic elements widely distributed among bacteria. Their activities cause mutations, promoting genetic diversity and sometimes adaptation. Previous studies have examined their copy number and distribution in Escherichia coli K-12 and natural isolates. Here, we map most of the IS elements in E. coli B and compare their locations with the published genomes of K-12 and O157:H7. Results The genomic locations of IS elements reveal numerous differences between B, K-12, and O157:H7. IS elements occur in hok-sok loci (homologous to plasmid stabilization systems) in both B and K-12, whereas these same loci lack IS elements in O157:H7. IS elements in B and K-12 are often found in locations corresponding to O157:H7-specific sequences, which suggests IS involvement in chromosomal rearrangements including the incorporation of foreign DNA. Some sequences specific to B are identified, as reported previously for O157:H7. The extent of nucleotide sequence divergence between B and K-12 is <2% for most sequences adjacent to IS elements. By contrast, B and K-12 share only a few IS locations besides those in hok-sok loci. Several phenotypic features of B are explained by IS elements, including differential porin expression from K-12. Conclusions These data reveal a high level of IS activity since E. coli B, K-12, and O157:H7 diverged from a common ancestor, including IS association with deletions and incorporation of horizontally acquired genes as well as transpositions. These findings indicate the important role of IS elements in genome plasticity and divergence.

Background Gene expression profiling among different tissues is of paramount interest in various areas of biomedical research. We have developed a novel method (DADA, Digital Analysis of cDNA Abundance), that calculates the relative abundance of genes in cDNA libraries. Results DADA is based upon multiple restriction fragment length analysis of pools of clones from cDNA libraries and the identification of gene-specific restriction fingerprints in the resulting complex fragment mixtures. A specific cDNA cloning vector had to be constructed that governed missing or incomplete cDNA inserts which would generate misleading fingerprints in standard cloning vectors. Double stranded cDNA was synthesized using an anchored oligo dT primer, uni-directionally inserted into the DADA vector and cDNA libraries were constructed in E. coli. The cDNA fingerprints were generated in a PCR-free procedure that allows for parallel plasmid preparation, labeling, restriction digest and fragment separation of pools of 96 colonies each. This multiplexing significantly enhanced the throughput in comparison to sequence-based methods (e.g. EST approach). The data of the fragment mixtures were integrated into a relational database system and queried with fingerprints experimentally produced by analyzing single colonies. Due to limited predictability of the position of DNA fragments on the polyacrylamid gels of a given size, fingerprints derived solely from cDNA sequences were not accurate enough to be used for the analysis. We applied DADA to the analysis of gene expression profiles in a model for impaired wound healing (treatment of mice with dexamethasone). Conclusions The method proved to be capable of identifying pharmacologically relevant target genes that had not been identified by other standard methods routinely used to find differentially expressed genes. Due to the above mentioned limited predictability of the fingerprints, the method was yet tested only with a limited number of experimentally determined fingerprints and was able to detect differences in gene expression of transcripts representing 0.05% of the total mRNA population (e.g. medium abundant gene transcripts).

Background The availability of complete genome sequences enables all the members of a gene family to be identified without limitations imposed by temporal, spatial or quantitative aspects of mRNA expression. Using the nearly completed human genome sequence, we combined in silico and experimental approaches to define the complete human nuclear receptor (NR) set. This information was used to carry out a comparative genomic study of the NR superfamily. Results Our analysis of the human genome identified two novel NR sequences. Both these contained stop codons within the coding regions, indicating that both are pseudogenes. One (HNF4 γ-related) contained no introns and expressed no detectable mRNA, whereas the other (FXR-related) produced mRNA at relatively high levels in testis. If translated, the latter is predicted to encode a short, non-functional protein. Our analysis indicates that there are fewer than 50 functional human NRs, dramatically fewer than in Caenorhabditis elegans and about twice as many as in Drosophila. Using the complete human NR set we made comparisons with the NR sets of C. elegans and Drosophila. Searches for the >200 NRs unique to C. elegans revealed no human homologs. The comparative analysis also revealed a Drosophila member of NR subfamily NR3, confirming an ancient metazoan origin for this subfamily. Conclusions This work provides the basis for new insights into the evolution and functional relationships of NR superfamily members.

Background Any DNA sequence is a result of compromise between the selection and mutation pressures exerted on it during evolution. It is difficult to estimate the relative influence of each of these pressures on the rate of accumulation of substitutions. However, it is important to discriminate between the effect of mutations, and the effect of selection, when studying the phylogenic relations between taxa. Results We have tested in computer simulations, and analytically, the available substitution matrices for many genomes, and we have found that DNA strands in equilibrium under mutational pressure have unique feature: the fraction of each type of nucleotide is linearly dependent on the time needed for substitution of half of nucleotides of a given type, with a correlation coefficient close to 1. Substitution matrices found for sequences under selection pressure do not have this property. A substitution matrix for the leading strand of the Borrelia burgdorferi genome, having reached equilibrium in computer simulation, gives a DNA sequence with nucleotide composition and asymmetry corresponding precisely to the third positions in codons of protein coding genes located on the leading strand. Conclusions Parameters of mutational pressure allow us to count DNA composition in equilibrium with this mutational pressure. Comparing any real DNA sequence with the sequence in equilibrium it is possible to estimate the distance between these sequences, which could be used as a measure of the selection pressure. Furthermore, the parameters of the mutational pressure enable direct estimation of the relative mutation rates in any DNA sequence in the studied genome.

Background A computational system for analysis of the repetitive structure of genomic sequences is described. The method uses suffix trees to organize and search the input sequences; this data structure has been used previously for efficient computation of exact and degenerate repeats. Results The resulting software tool collects all repeat classes and outputs summary statistics as well as a file containing multiple sequences (multi fasta), that can be used as the target of searches. Its use is demonstrated here on several complete microbial genomes, the entire Arabidopsis thaliana genome, and a large collection of rice bacterial artificial chromosome end sequences. Conclusions We propose a new clustering method for analysis of the repeat data captured in suffix trees. This method has been incorporated into a system that can find repeats in individual genome sequences or sets of sequences, and that can organize those repeats into classes. It quickly and accurately creates repeat databases from small and large genomes. The associated software (RepeatFinder), should prove helpful in the analysis of repeat structure for both complete and partial genome sequences.

Background Alternative DNA conformations are of particular interest as potential signals to mark important sites on the genome. The structural variability of CA microsatellites is particularly pronounced; these are repetitive poly(CA) · poly(TG) DNA sequences spread in all eukaryotic genomes as tracts of up to 60 base pairs long. Many in vitro studies have shown that the structure of poly(CA) · poly(TG) can vary markedly from the classical right handed DNA double helix and adopt diverse alternative conformations. Here we have studied the mechanism of formation and the structure of an alternative DNA structure, named Form X, which was observed previously by polyacrylamide gel electrophoresis of DNA fragments containing a tract of the CA microsatellite poly(CA) · poly(TG) but had not yet been characterized. Results Formation of Form X was found to occur upon reassociation of the strands of a DNA fragment containing a tract of poly(CA) · poly(TG), in a process strongly stimulated by the nuclear proteins HMG1 and HMG2. By inserting Form X into DNA minicircles, we show that the DNA strands do not run fully side by side but instead form a DNA knot. When present in a closed DNA molecule, Form X becomes resistant to heating to 100°C and to alkaline pH. Conclusions Our data strongly support a model of Form X consisting in a DNA loop at the base of which the two DNA duplexes cross, with one of the strands of one duplex passing between the strands of the other duplex, and reciprocally, to form a semicatenated DNA junction also called a DNA hemicatenane.

Background In microarray data analysis, the comparison of gene-expression profiles with respect to different conditions and the selection of biologically interesting genes are crucial tasks. Multivariate statistical methods have been applied to analyze these large datasets. Less work has been published concerning the assessment of the reliability of gene-selection procedures. Here we describe a method to assess reliability in multivariate microarray data analysis using permutation-validated principal components analysis (PCA). The approach is designed for microarray data with a group structure. Results We used PCA to detect the major sources of variance underlying the hybridization conditions followed by gene selection based on PCA-derived and permutation-based test statistics. We validated our method by applying it to well characterized yeast cell-cycle data and to two datasets from our laboratory. We could describe the major sources of variance, select informative genes and visualize the relationship of genes and arrays. We observed differences in the level of the explained variance and the interpretability of the selected genes. Conclusions Combining data visualization and permutation-based gene selection, permutation-validated PCA enables one to illustrate gene-expression variance between several conditions and to select genes by taking into account the relationship of between-group to within-group variance of genes. The method can be used to extract the leading sources of variance from microarray data, to visualize relationships between genes and hybridizations and to select informative genes in a statistically reliable manner. This selection accounts for the level of reproducibility of replicates or group structure as well as gene-specific scatter. Visualization of the data can support a straightforward biological interpretation.

Background Microarray experiments offer a potent solution to the problem of making and comparing large numbers of gene expression measurements either in different cell types or in the same cell type under different conditions. Inferences about the biological relevance of observed changes in expression depend on the statistical significance of the changes. In lieu of many replicates with which to determine accurate intensity means and variances, reliable estimates of statistical significance remain problematic. Without such estimates, overly conservative choices for significance must be enforced. Results A simple statistical method for estimating variances from microarray control data which does not require multiple replicates is presented. Comparison of datasets from two commercial entities using this difference-averaging method demonstrates that the standard deviation of the signal scales at a level intermediate between the signal intensity and its square root. Application of the method to a dataset related to the β-catenin pathway yields a larger number of biologically reasonable genes whose expression is altered than the ratio method. Conclusions The difference-averaging method enables determination of variances as a function of signal intensities by averaging over the entire dataset. The method also provides a platform-independent view of important statistical properties of microarray data.

Background The power of DNA microarrays derives from their ability to monitor the expression levels of many genes in parallel. One of the limitations of such powerful analytical tools is the inability to detect certain transcripts in the target sample because of artifacts caused by background noise or poor hybridization kinetics. The use of base-modified analogs of nucleoside triphosphates has been shown to increase complementary duplex stability in other applications, and here we attempted to enhance microarray hybridization signal across a wide range of sequences and expression levels by incorporating these nucleotides into labeled cRNA targets. Results RNA samples containing 2-aminoadenosine showed increases in signal intensity for a majority of the sequences. These results were similar, and additive, to those seen with an increase in the hybridization time. In contrast, 5-methyluridine and 5-methylcytidine decreased signal intensities. Hybridization specificity, as assessed by mismatch controls, was dependent on both target sequence and extent of substitution with the modified nucleotide. Concurrent incorporation of modified and unmodified ATP in a 1:1 ratio resulted in significantly greater numbers of above-threshold ratio calls across tissues, while preserving ratio integrity and reproducibility. Conclusions Incorporation of 2-aminoadenosine triphosphate into cRNA targets is a promising method for increasing signal detection in microarrays. Furthermore, this approach can be optimized to minimize impact on yield of amplified material and to increase the number of expression changes that can be detected.

Background Transcriptional regulation in eukaryotes generally operates at the level of individual genes. Regulation of sets of adjacent genes by mechanisms operating at the level of chromosomal domains has been demonstrated in a number of cases, but the fraction of genes in the genome subject to regulation at this level is unknown. Results Drosophila gene-expression profiles that were determined from over 80 experimental conditions using high-density oligonucleotide microarrays were searched for groups of adjacent genes that show similar expression profiles. We found about 200 groups of adjacent and similarly expressed genes, each having between 10 and 30 members; together these groups account for over 20% of assayed genes. Each group covers between 20 and 200 kilobase pairs of genomic sequence, with a mean group size of about 100 kilobase pairs. Groups do not appear to show any correlation with polytene banding patterns or other known chromosomal structures, nor were genes within groups functionally related to one another. Conclusions Groups of adjacent and co-regulated genes that are not otherwise functionally related in any obvious way can be identified by expression profiling in Drosophila. The mechanism underlying this phenomenon is not yet known.