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Streptococcus pneumoniae is an opportunistic human pathogen that typically colonizes the nasopharyngeal passage and causes lethal disease in other host niches such as the lung or the meninges. How pneumococcal genes are expressed and regulated at the different stages of its life cycle, as commensal or as pathogen, has not been entirely described. To chart the transcriptional responses of S. pneumoniae, we quantified the transcriptome under 22 different infection-relevant conditions. The transcriptomic compendium exposed a high level of dynamic expression and, strikingly, all annotated pneumococcal genomic features were expressed in at least one of the studied conditions. By computing the correlation of gene expression of every two genes across all studied conditions, we created a co-expression matrix that provides valuable information on both operon structure and regulatory processes. The co-expression data is highly consistent with well-characterized operons and regulons, such as the PyrR, ComE and ComX regulons, and has allowed us to identify a new member of the competence regulon. Finally, we created an interactive data center named PneumoExpress (www.veeninglab.com/pneumoexpress) that enables users to access the expression data as well as the co-expression matrix in an intuitive and efficient manner, providing a valuable resource to the pneumococcal research community.

DNA Differences The extent to which genetic variation affects an individual's phenotype has been difficult to predict because the majority of variation lies outside the coding regions of genes. Now, three studies examine the extent to which genetic variation affects the chromatin of individuals with diverse ancestry and genetic variation (see the Perspective by Furey and Sethupathy ). Kasowski et al. (p. 750 , published online 17 October) examined how genetic variation affects differences in chromatin states and their correlation to histone modifications, as well as more general DNA binding factors. Kilpinen et al. (p. 744 , published online 17 October) document how genetic variation is linked to allelic specificity in transcription factor binding, histone modifications, and transcription. McVicker et al. (p. 747 , published online 17 October) identified how quantitative trait loci affect histone modifications in Yoruban individuals and established which specific transcription factors affect such modifications.

Mammalian genomes contain highly conserved sequences that are not functionally transcribed. These sequences are single copy and comprise approximately 1-2% of the human genome. Evolutionary analysis strongly supports their functional conservation, although their potentially diverse, functional attributes remain unknown. It is likely that genomic variation in conserved non-genic sequences is associated with phenotypic variability and human disorders. So how might their function and contribution to human disorders be examined?

Two loci for nonsyndromic recessive deafness located on chromosome 21q22.3 have previously been reported, DFNB8 and DFNB10. Recently a gene which encodes a transmembrane serine protease, TMPRSS3 or ECHOS1, was found to be responsible for both the DFNB8 and DFNB10 phenotypes. To determine the contribution of TMPRSS3 mutations in the general congenital/childhood nonsyndromic deaf population we performed mutation analysis of the TMPRSS3 gene in 448 unrelated deaf patients from Spain, Italy, Greece, and Australia who did not have the common 35delG GJB2 mutation. From the 896 chromosomes studied we identified two novel pathogenic mutations accounting for four mutant alleles and at least 16 nonpathogenic sequence variants. The pathogenic mutations were a 1-bp deletion resulting in a frameshift and an amino acid substitution in the LDLRA domain of TMPRSS3. From this and another study we estimate the frequency of TMPRSS3 mutations in our sample as 0.45%, and approximately 0.38% in the general Caucasian childhood deaf population. However, TMPRSS3 is still an important contributor to genetic deafness in populations with large consanguineous families.

From the cDNAs of two defective RNAs naturally exhibiting a large difference in replication efficiency, a series of Sendai virus RNA chimeras were constructed by reciprocal exchanges of their 3′ end primary sequences. Using a reverse genetics system, the ability of these RNAs to replicate when expressed from cDNAs in the context of the viral proteins N, P, and L, also expressed from plasmids, was analyzed. First the extent of potential RNA 3′/5′ end complementarity was tested by disrupting and restoring the terminal 110-nucleotide complementarity of a copy-back RNA. Alternatively, this base pairing potential was gradually increased from 12 to 57 or to 98 nucleotides by continuous substitutions. In all cases, the restoration or the creation of more extended base pairing potential had no effect on RNA replication. Reciprocal exchanges were then made in order to identifycis-acting sequences that could induce high replication efficiency. It was found that nucleotides 1–31 of the antigenome 3′ end were sufficient to confer a high replication property (more than a 10-fold increase), regardless of the sequence adjacent to these terminal nucleotides. It is concluded that one of the most important features that modulate replication efficiency is contained in the promoter end primary sequence and that this feature is likely to operate independently of the ability to form a potential terminal base pairing.

Background PCR has the potential to detect and precisely quantify specific DNA sequences, but it is not yet often used as a fully quantitative method. A number of data collection and processing strategies have been described for the implementation of quantitative PCR. However, they can be experimentally cumbersome, their relative performances have not been evaluated systematically, and they often remain poorly validated statistically and/or experimentally. In this study, we evaluated the performance of known methods, and compared them with newly developed data processing strategies in terms of resolution, precision and robustness. Results Our results indicate that simple methods that do not rely on the estimation of the efficiency of the PCR amplification may provide reproducible and sensitive data, but that they do not quantify DNA with precision. Other evaluated methods based on sigmoidal or exponential curve fitting were generally of both poor resolution and precision. A statistical analysis of the parameters that influence efficiency indicated that it depends mostly on the selected amplicon and to a lesser extent on the particular biological sample analyzed. Thus, we devised various strategies based on individual or averaged efficiency values, which were used to assess the regulated expression of several genes in response to a growth factor. Conclusion Overall, qPCR data analysis methods differ significantly in their performance, and this analysis identifies methods that provide DNA quantification estimates of high precision, robustness and reliability. These methods allow reliable estimations of relative expression ratio of two-fold or higher, and our analysis provides an estimation of the number of biological samples that have to be analyzed to achieve a given precision.

Background Solexa/Illumina short-read ultra-high throughput DNA sequencing technology produces millions of short tags (up to 36 bases) by parallel sequencing-by-synthesis of DNA colonies. The processing and statistical analysis of such high-throughput data poses new challenges; currently a fair proportion of the tags are routinely discarded due to an inability to match them to a reference sequence, thereby reducing the effective throughput of the technology. Results We propose a novel base calling algorithm using model-based clustering and probability theory to identify ambiguous bases and code them with IUPAC symbols. We also select optimal sub-tags using a score based on information content to remove uncertain bases towards the ends of the reads. Conclusion We show that the method improves genome coverage and number of usable tags as compared with Solexa's data processing pipeline by an average of 15%. An R package is provided which allows fast and accurate base calling of Solexa's fluorescence intensity files and the production of informative diagnostic plots.