Unexpressed Genes Research Articles

Application of community phylogenetic approaches to understand gene expression: differential exploration of venom gene space in predatory marine gastropods.

BackgroundPredatory marine gastropods of the genus Conus exhibit substantial variation in venom composition both within and among species. Apart from mechanisms associated with extensive turnover of gene families and rapid evolution of genes that encode venom components (‘conotoxins’), the evolution of distinct conotoxin expression patterns is an additional source of variation that may drive interspecific differences in the utilization of species’ ‘venom gene space’. To determine the evolution of expression patterns of venom genes of Conus species, we evaluated the expression of A-superfamily conotoxin genes of a set of closely related Conus species by comparing recovered transcripts of A-superfamily genes that were previously identified from the genomes of these species. We modified community phylogenetics approaches to incorporate phylogenetic history and disparity of genes and their expression profiles to determine patterns of venom gene space utilization.ResultsLess than half of the A-superfamily gene repertoire of these species is expressed, and only a few orthologous genes are coexpressed among species. Species exhibit substantially distinct expression strategies, with some expressing sets of closely related loci (‘under-dispersed’ expression of available genes) while others express sets of more disparate genes (‘over-dispersed’ expression). In addition, expressed genes show higher dN/dS values than either unexpressed or ancestral genes; this implies that expression exposes genes to selection and facilitates rapid evolution of these genes. Few recent lineage-specific gene duplicates are expressed simultaneously, suggesting that expression divergence among redundant gene copies may be established shortly after gene duplication.ConclusionsOur study demonstrates that venom gene space is explored differentially by Conus species, a process that effectively permits the independent and rapid evolution of venoms in these species.

The dynamics of sex ratio evolution Dynamics of global population parameters

Classical formalizations of the Fisherian theory of sex ratio evolution are based on the assumption that the number of grand offspring of a female serves as a measure of fitness. However, the classical population genetics approach also considers the contribution of male individuals to gene proliferation. The difference between the predictions of phenotypic and genetic models is that the phenotypic approach describes the primary sex ratio of 0.5 as the ESS value, while genetic models describe the stable state of a population by a combination of the stable states of the male and female subpopulations. In this paper, we formulate an alternative model of sex ratio evolution that is focused on the dynamics and quantitative properties of this process and that combine a rigorous genetic approach with a game theoretic strategic analysis. In the new model, females are the strategic agents and males are the passive carriers on unexpressed genes. Fitness functions in the new model are derived with respect to a “fitness exchange” effect, i.e. the contribution of male individuals to female fitness and vice versa. This new model shows that the dynamics of this system are complex and consist of two phases. The first, rapid, phase converges the system to a stable manifold (termed the male subpopulation equilibrium—MSE) where the male subpopulation state is in equilibrium, conditional on the current state of the female subpopulation. Double phase dynamics occur when the population state is not compatible with the current strategic composition of the population (determined by the value of the primary sex ratio) which can be caused by ecological factors. The trajectory of convergence to the MSE can be very complicated and may contain a dramatic change in the primary sex ratio. Thus, the primary sex ratio of 0.5 is unstable for perturbations of gene frequencies among male carriers. Therefore, the new model supports predictions of genetic models that the evolutionary stability of the sex ratio should be characterized by a combination of a stable value of the primary sex ratio and the male subpopulation equilibrium.

Abstract PR1: Integrating expression data improves mutational significance analysis of lung squamous carcinoma

Abstract In contrast to lung adenocarcinoma in which a driving and potentially targetable genetic aberration can be identified in excess of 50% of tumors, only 10% can be found in squamous cell lung cancer, the second most common type of lung cancer, none of which are druggable by an approved targeted therapy. Our limited knowledge regarding targetable genetic alterations in squamous cell lung cancer is the result of a lack of detailed genomic study of this disease and the lack of experimental validation of identified putative therapeutic targets. We have analyzed exome sequencing data to identify novel driving mutations in 184 lung squamous cell carcinomas using previously successful methods (Integrated genomic analyses of ovarian carcinoma, Nature 2011), but these analyses are confounded by an unusually high mutation rate, 8-9/Mb on average, some reaching as many as 80/Mb. Many of the most significantly mutated genes in the analysis are unlikely related to the pathogenesis of the disease based on a lack of expression in lung and known role in cancer, suggesting that genes which are not expressed (or minimally expressed) escape negative selection and result in a higher mutation density as compared with expressed genes. Here, we present a method integrating expression and mutation data in order to more accurately determine the significance of a mutated gene based on the expression subclass in which it falls and the frequency at which it's mutated relative to our expectation; unexpressed genes are likely much more tolerant of mutations and should therefore have a higher expected background mutation rate. Analyses of this kind have removed many of the genes putatively irrelevant in this cancer type and have identified many biologically plausible novel genes that to date are unlinked with lung squamous cell carcinoma. We believe this method refines an already powerful analysis for identifying significantly mutated genes in cancer with a particularly high potential for separating signal and noise in the most highly mutated cancer types. This abstract is also presented as Poster A17.

Involvement of Elongation Factor-1α in Cytokinesis without Actomyosin Contractile Ring in the Primitive Red Alga <i>Cyanidioschyzon merolae</i>

Cytokinesis is a pivotal event in cell division in all living organisms. In mammals, cytokinesis progresses via constriction of the contractile ring, a bundle of actin filaments and myosin that is located on the equatorial plane. The eukaryotic elongation factor 1α (eEF-1α) is associated with the contractile ring in sea urchin eggs. Although eEF-1α is a ubiquitous protein translation factor and is highly conserved in eukaryotes, archaea, and prokaryotes, the archaebacterial EF-1α and the prokaryotic EF-1α ortholog EF-Tu do not function in cytokinesis, suggesting that the association between the contractile ring and EF-1α appeared at about the same time as the establishment of eukaryotic cells. However, the role of EF-1α in cytokinesis in primitive cells is unclear. In this study, we show that the primitive alga Cyanidioschyzon merolae elongation factor-lα (CmEF-1α) is localized in the contractile division plane, but not in the actomyosin contractile ring. The genome of C. merolae contains 2 unexpressed actin genes and lacks a myosin gene. Immunoblotting analyses revealed that the protein level of CmEF-1α remained constant during the G1 to M phase, and then peaked during cytokinesis. Immunofluorescent microscopy revealed 2 patterns of localization of CmEF-1α during the cell cycle: it was dispersed throughout the cytoplasm from G1 to early M phase, and then localized to the contractile region during cytokinesis. From the results of current study on cytokinesis in the primitive red algae C. merolae, our findings led us to hypothesize that when first established in the lower eukaryotes, cytokinesis fundamentally relied on eEF-1α, and the actomyosin system was acquired later during evolution.

Epigenetic Control of Inducible Gene Expression in the Immune System

It has been well documented that active genes, and their promoters and enhancers have a different chromatin or epigenomic environment compared with unexpressed genes. In addition, the epigenome may influence not only which genes are expressed, but also which genes can be induced in response to activation or differentiation signals. Immune cells respond to activation signals by rapidly inducing the expression of specific gene sets, and therefore this is a good system in which to examine the role of the epigenome in gene activation and cell differentiation. Several studies have now found that many immediate-early inducible genes exist in a similar epigenomic environment to active genes even in the unstimulated state. Some studies suggest that subsets of these genes may even have RNA polymerase II at their promoters and induction may be controlled downstream of its recruitment. Other inducible genes, however, undergo changes to histone modifications, levels or variant composition upon activation. In this article, we discuss how the epigenome of immune cells regulates inducible gene expression and discuss the differences between the immediate responses to activation signals and the longer term changes observed during differentiation.

A robust method for estimating gene expression states using Affymetrix microarray probe level data

BackgroundMicroarray technology is a high-throughput method for measuring the expression levels of thousand of genes simultaneously. The observed intensities combine a non-specific binding, which is a major disadvantage with microarray data. The Affymetrix GeneChip assigned a mismatch (MM) probe with the intention of measuring non-specific binding, but various opinions exist regarding usefulness of MM measures. It should be noted that not all observed intensities are associated with expressed genes and many of those are associated with unexpressed genes, of which measured values express mere noise due to non-specific binding, cross-hybridization, or stray signals. The implicit assumption that all genes are expressed leads to poor performance of microarray data analyses. We assume two functional states of a gene - expressed or unexpressed - and propose a robust method to estimate gene expression states using an order relationship between PM and MM measures.ResultsAn indicator 'probability of a gene being expressed' was obtained using the number of probe pairs within a probe set where the PM measure exceeds the MM measure. We examined the validity of the proposed indicator using Human Genome U95 data sets provided by Affymetrix. The usefulness of 'probability of a gene being expressed' is illustrated through an exploration of candidate genes involved in neuroblastoma prognosis. We identified the candidate genes for which expression states differed (un-expressed or expressed) when compared between two outcomes. The validity of this result was subsequently confirmed by quantitative RT-PCR.ConclusionThe proposed qualitative evaluation, 'probability of a gene being expressed', is a useful indicator for improving microarray data analysis. It is useful to reduce the number of false discoveries. Expression states - expressed or unexpressed - correspond to the most fundamental gene function 'On' and 'Off', which can lead to biologically meaningful results.

Evaluation of cDNA Microarray Data by Multiple Clones Mapping to the Same Transcript

Although novel technologies are rapidly emerging, the cDNA microarray data accumulated is still and will be an important source for bioinformatics and biological studies. Thus, the reliability and applicability of the cDNA microarray data warrants further evaluation. In cDNA microarrays, multiple clones are measured for a transcript, which can be exploited to evaluate the consistency of microarray data. We show that even for pairs of RCs, the average Pearson correlation coefficient of their measurements is not high. However, this low consistency could largely be explained by random noise signals for a fraction of unexpressed genes and/or low signal-to-noise ratios for low abundance transcripts. Encouragingly, a large fraction of inconsistent data will be filtered out in the procedure of selecting differentially expressed genes (DEGs). Therefore, although cDNA microarray data are of low consistency, applications based on DEGs selections could still reach correct biological results, especially at the functional modules level.

Complex developmental patterns of histone modifications associated with the human β-globin switch in primary cells

The regulation of the beta-globin switch remains undetermined, and understanding this mechanism has important benefits for clinical and basic science. Histone modifications regulate gene expression and this study determines the presence of three important histone modifications across the beta-globin locus in erythroblasts with different beta-like globin-expression profiles. Understanding the chromatin associated with weak gamma gene expression in bone marrow cells is an important objective, with the goal of ultimately inducing postnatal expression of weak gamma-globin to cure beta-hemoglobinopathies. These studies use uncultured primary fetal and bone marrow erythroblasts and human embryonic stem cell-derived primitive-like erythroblasts. Chromatin immunoprecipitation with antibodies against modified histones reveals DNA associated with such histones. Precipitated DNA is quantitated by real-time polymerase chain reaction for 40 sites across the locus. Distribution of histone modifications differs at each developmental stage. The most highly expressed genes at each stage are embedded within large domains of modifications associated with expression (acetylated histone H3 [H3ac] and dimethyl lysine 4 of histone H3 [H3K4me2]). Moderately expressed genes have H3ac and H3K4me2 in the immediate area around the gene. Dimethyl lysine 9 of histone H3 (H3K9me2), a mark associated with gene suppression, is present at the epsilon and gamma genes in bone marrow cells, suggesting active suppression of these genes. This study reveals complex patterns of histone modifications associated with highly expressed, moderately expressed, and unexpressed genes. Activation of gamma postnatally will likely require extensive modification of the histones in a large domain around the gamma genes.

Steady-state and dynamic flux balance analysis of ethanol production by Saccharomyces cerevisiae

Steady-state and dynamic flux balance analysis (DFBA) was used to investigate the effects of metabolic model complexity and parameters on ethanol production predictions for wild-type and engineered Saccharomyces cerevisiae. Three metabolic network models ranging from a single compartment representation of metabolism to a genome-scale reconstruction with seven compartments and detailed charge balancing were studied. Steady-state analysis showed that the models generated similar wild-type predictions for the biomass and ethanol yields, but for ten engineered strains the seven compartment model produced smaller ethanol yield enhancements. Simplification of the seven compartment model to two intracellular compartments produced increased ethanol yields, suggesting that reaction localisation had an impact on mutant phenotype predictions. Further analysis with the seven compartment model demonstrated that steady-state predictions can be sensitive to intracellular model parameters, with the biomass yield exhibiting high sensitivity to ATP utilisation parameters and the biomass composition. The incorporation of gene expression data through the zeroing of metabolic reactions associated with unexpressed genes was shown to produce negligible changes in steady-state predictions when the oxygen uptake rate was suitably constrained. Dynamic extensions of the single and seven compartment models were developed through the addition of glucose and oxygen uptake expressions and transient extracellular balances. While the dynamic models produced similar predictions of the optimal batch ethanol productivity for the wild type, the single compartment model produced significantly different predictions for four implementable gene insertions. A combined deletion/overexpression/insertion mutant with improved ethanol productivity capabilities was computationally identified by dynamically screening multiple combinations of the ten metabolic engineering strategies. The authors concluded that extensive compartmentalisation and detailed charge balancing can be important for reliably screening metabolic engineering strategies that rely on modification of the global redox balance and that DFBA offers the potential to identify novel mutants for enhanced metabolite production in batch and fed-batch cultures.

Molecular Characterization of Two Silenced y‐type Genes for Glu‐B1 in Triticum aestivum ssp. yunnanese and ssp. tibetanum

The high molecular weight glutenin subunits (HMW-GSs) are a major class of common wheat storage proteins. The bread-making quality of common wheat flour is influenced by the composition of HMW-GSs. In the present study, two unexpressed 1By genes from Triticum aesitvum L.ssp.yunnanese AS332 and T. aesitvum ssp.tibetanum AS908 were respectively cloned and characterized. The results indicated that both of the silenced 1By genes in AS332 and AS908 were 1By9. In contrast to previously reported mechanisms for silenced genes 1Ax and 1Ay, which was due to the insertion of transposon elements or the presence of premature stop codon via base substitution of C-->T transition in trinucleotides CAA or CAG, the silence of 1By9 genes was caused by premature stop codons via the deletion of base A in trinucleotide CAA, which lead to frameshift mutation and indirectly produced several premature stop codons (TAG) downstream of the coding sequence.

A high prevalence of antimicrobial resistantEscherichia coliisolated from pigs and a low prevalence of antimicrobial resistantE. colifrom cattle and sheep in Great Britain at slaughter

The incidence of antimicrobial resistance and expressed and unexpressed resistance genes among commensal Escherichia coli isolated from healthy farm animals at slaughter in Great Britain was investigated. The prevalence of antimicrobial resistance among the isolates varied according to the animal species; of 836 isolates from cattle tested only 5.7% were resistant to one or more antimicrobials, while only 3.0% of 836 isolates from sheep were resistant to one or more agents. However, 92.1% of 2480 isolates from pigs were resistant to at least one antimicrobial. Among isolates from pigs, resistance to some antimicrobials such as tetracycline (78.7%), sulphonamide (66.9%) and streptomycin (37.5%) was found to be common, but relatively rare to other agents such as amikacin (0.1%), ceftazidime (0.1%) and coamoxiclav (0.2%). The isolates had a diverse range of resistance gene profiles, with tet(B), sul2 and strAB identified most frequently. Seven out of 615 isolates investigated carried unexpressed resistance genes. One trimethoprim-susceptible isolate carried a complete dfrA17 gene but lacked a promoter for it. However, in the remaining six streptomycin-susceptible isolates, one of which carried strAB while the others carried aadA, no mutations or deletions in gene or promoter sequences were identified to account for susceptibility. The data indicate that antimicrobial resistance in E. coli of animal origin is due to a broad range of acquired genes.

Hadamard matrix methods in identifying differentially expressed genes from microarray experiments

Identifying differentially expressed genes is a basic objective in microarray experiments. Many statistical methods for detecting differentially expressed genes in multiple-slide experiments have been proposed. However, sometimes with limited experimental resources, only a single cDNA array or two Oligonuleotide arrays could be made or only insufficient replicated arrays could be conducted. Many current statistical models cannot be used because of the non-availability of replicated data. Simply using fold changes is also unreliable and inefficient [Chen et al. 1997. Ratio-based decisions and the quantitative analysis of cDNA microarray images. J. Biomed. Optics 2, 364–374; Newton et al. 2001. On differential variability of expression ratios: improving statistical inference about gene expression changes from microarray data. J. Comput. Biol. 8, 37–52; Pan et al. 2002. How many replicates of arrays are required to detect gene expression changes in microarray experiments? a mixture model approach. Genome Biol. 3, research0022.1-0022.10]. We propose a new method. If the log-transformed ratios for the expressed genes as well as unexpressed genes have equal variance, we use a Hadamard matrix to construct a t-test from a single array data. Basically, we test whether each doubtful gene has significantly differential expression compared to the unexpressed genes. We form some new random variables corresponding to the rows of a Hadamard matrix using the algebraic sum of gene expressions. A one-sample t-test is constructed and the p-value is calculated for each doubtful gene based on these random variables. By using any method for multiple testing, adjusted p-values could be obtained from original p-values and significance of doubtful genes can be determined. When the variance of expressed genes differs from the variance of unexpressed genes, we construct a z-statistic based on the result from application of Hadamard matrix and find the confidence interval to retain the null hypothesis. Using the interval, we determine differentially expressed genes. This method is also useful for multiple microarrays, especially when sufficient replicated data are not available for a traditional t-test. We apply our methodology to ApoAI data. The results appear to be promising. They not only confirm the early known differentially expressed genes, but also indicate more genes to be differentially expressed.

High-throughput mapping of the chromatin structure of human promoters

Our understanding of how chromatin structure influences cellular processes such as transcription and replication has been limited by a lack of nucleosome-positioning data in human cells. We describe a high-resolution microarray approach combined with an analysis algorithm to examine nucleosome positioning in 3,692 promoters within seven human cell lines. Unlike unexpressed genes without transcription-preinitiation complexes at their promoters, expressed genes or genes containing preinitiation complexes exhibit characteristic nucleosome-free regions at their transcription start sites. The combination of these nucleosome data with chromatin immunoprecipitation-chip analyses reveals that the melanocyte master regulator microphthalmia-associated transcription factor (MITF) predominantly binds nucleosome-free regions, supporting the model that nucleosomes limit sequence accessibility. This study presents a global view of human nucleosome positioning and provides a high-throughput tool for analyzing chromatin structure in development and disease.

Distinct DNase I hypersensitive sites are absent from promoters of transcriptionally incompetent genes in Arabidopsis

Specifically accessible chromatin sites, detected as DNase I hypersensitive sites (DNase I HSs), have been found at promoters of most genes in yeast, human as well as in Arabidopsis chromatin. The DNase I HSs are constitutively present at promoters of most genes both at inactive and activated states. On the other hand, appearance and disappearance of DNase I HSs have been observed at several developmentally regulated genes in different tissues of animals. Patterns of appearance and disappearance of DNase I HSs were correlated with transcriptional competency (potential of expression) of the associated genes, suggesting that DNase I HSs are absent from the promoters of transcriptionally incompetent (unexpressed nor inducible) genes. To test this hypothesis in plants, we analyzed DNase I hypersensitivity of several well- characterized genes showing distinct patterns of tissue-specific expression in Arabidopsis leaves, roots and suspension cells. Distinct DNase I HSs were present at transcriptionally competent gene promoters, but absent from incompetent gene promoters. The absence of DNase I HS suggests that nucleosomes are randomly positioned on incompetent promoters, and may contribute to the transcriptional incompetency by blocking the binding of activators in tissues where expression of these genes is unnecessary.

Evidence of Antibiotic Resistance Gene Silencing in Escherichia coli

The possibility that unexpressed antibiotic resistance genes are carried by bacterial genomes is seldom investigated. Potential silencing of the resistance genes bla(OXA-2), aadA1, sul1, and tetA carried on the plasmid pVE46 in a recent porcine isolate of Escherichia coli was investigated following oral inoculation of the strain into organic piglets. A small proportion of isolates recovered from feces did not express one or more resistance genes, despite retaining the pVE46 plasmid. Different combinations of unexpressed resistance genes were observed, and 12 representative isolates were selected for further study. Surprisingly, in most cases the resistance genes and their promoters, although not expressed, were intact, with fully wild-type sequences. Apart from four isolates exhibiting intermediate-level tetracycline resistance, no mRNA for the unexpressed genes was detected. Silencing of resistance genes was reversible at low frequencies between 10(-6) and 10(-10). Introduction of the plasmid from silenced isolates to another strain restored expression, indicating that gene silencing was a property of the host chromosome rather than the plasmid itself. When the same recent porcine E. coli strain carrying the unrelated plasmid RP1 was inoculated into piglets, three isolates (of 9,492) that no longer expressed RP1-encoded resistance genes were recovered. As with pVE46, in most cases the coding sequences and promoter regions of these genes were found to be intact, but they were not transcribed. Such gene silencing indicates a previously unrecognized form of transcriptional control that overrides standard expression signals to shut down gene expression. These findings suggest that unexpressed resistance genes may occur in the wild and hence may have clinical implications.

Crew pairing optimization by a genetic algorithm with unexpressed genes

We propose a genetic algorithm to solve the pairing optimization problem for subway crew scheduling. Our genetic algorithm employs new crossover and mutation operators specially designed to work with the chromosomes of set-oriented representation. To enhance the efficiency of the search with the newly designed genetic operators, we let a chromosome consist of an expressed part and an unexpressed part. While the genes in both parts evolve, only the genes in the expressed part are used when an individual is evaluated. The purpose of the unexpressed part is to preserve information susceptible to be lost by the application of genetic operators, and thus to maintain the diversity of the search. Experiments with real-world data have shown that our genetic algorithm outperforms other local search methods such as simulated annealing and tabu search.

Integrated analysis of transcriptomic and proteomic data of Desulfovibrio vulgaris: zero-inflated Poisson regression models to predict abundance of undetected proteins

Integrated analysis of global scale transcriptomic and proteomic data can provide important insights into the metabolic mechanisms underlying complex biological systems. However, because the relationship between protein abundance and mRNA expression level is complicated by many cellular and physical processes, sophisticated statistical models need to be developed to capture their relationship. In this study, we describe a novel data-driven statistical model to integrate whole-genome microarray and proteomic data collected from Desulfovibrio vulgaris grown under three different conditions. Based on the Poisson distribution pattern of proteomic data and the fact that a large number of proteins were undetected (excess zeros), zero-inflated Poisson (ZIP)-based models were proposed to define the correlation pattern between mRNA and protein abundance. In addition, by assuming that there is a probability mass at zero representing unexpressed genes and expressed proteins that were undetected owing to technical limitations, a Potential ZIP model was established. Two significant improvements introduced by this approach are (1) the predicted protein abundance level values for experimentally detected proteins are corrected by considering their mRNA levels and (2) protein abundance values can be predicted for undetected proteins (in the case of this study, approximately 83% of the proteins in the D.vulgaris genome) for better biological interpretation. We demonstrated the use of these statistical models by comparatively analyzing proteomic and microarray results from D.vulgaris grown on lactate-based versus formate-based media. These models correctly predicted increased expression of Ech hydrogenase and decreased expression of Coo hydrogenase for D.vulgaris grown on formate.

Analysis of tag-position bias in MPSS technology

BackgroundMassively Parallel Signature Sequencing (MPSS) technology was recently developed as a high-throughput technology for measuring the concentration of mRNA transcripts in a sample. It has previously been observed that the position of the signature tag in a transcript (distance from 3' end) can affect the measurement, but this effect has not been studied in detail.ResultsWe quantify the effect of tag-position bias in Classic and Signature MPSS technology using published data from Arabidopsis, rice and human. We investigate the relationship between measured concentration and tag-position using nonlinear regression methods. The observed relationship is shown to be broadly consistent across different data sets. We find that there exist different and significant biases in both Classic and Signature MPSS data. For Classic MPSS data, genes with tag-position in the middle-range have highest measured abundance on average while genes with tag-position in the high-range, far from the 3' end, show a significant decrease. For Signature MPSS data, high-range tag-position genes tend to have a flatter relationship between tag-position and measured abundance. Thus, our results confirm that the Signature MPSS method fixes a substantial problem with the Classic MPSS method. For both Classic and Signature MPSS data there is a positive correlation between measured abundance and tag-position for low-range tag-position genes. Compared with the effects of mRNA length and number of exons, tag-position bias seems to be more significant in Arabadopsis. The tag-position bias is reflected both in the measured abundance of genes with a significant tag count and in the proportion of unexpressed genes identified.ConclusionTag-position bias should be taken into consideration when measuring mRNA transcript abundance using MPSS technology, both in Classic and Signature MPSS methods.

Changes in gene expression in response to mechanical strain in human scleral fibroblasts

Scleral fibroblasts are involved in scleral remodeling during axial elongation in myopia. Mechanical load is a potent stimulator of gene expression. This study seeks to identify changes in gene expression of scleral fibroblasts in response to mechanical load and speculate on possible mechanisms of scleral remodeling in the development of myopia. Human scleral fibroblasts (HSFs) were mechanically stretched for 30 min and 24 hr. A gene microarray analysis was used to measure changes in gene expression. A total of 237 genes revealed differential and significant changes in expression ( P<0·01) after 30 min of stretching. Of these, 28 unexpressed genes began to be expressed (turned on), while 31 expressed genes were no longer expressed (turned off). After 24 hr, 308 genes showed reproducible changes in expression ( P<0·01), while 29 genes were turned on and 17 genes were turned off. After 30 min, 25 genes showed at least a threefold change in expression. These included genes for cell receptors, protein kinases, cell growth/differentiation factors, extracellular matrix (ECM) proteins, lipid metabolism, protein metabolism, transcription factors, binding proteins and water channels. After 24 hr, 21 genes showed at least a threefold change in expression. These included genes for cell receptors, protein kinases, cell growth/differentiation factors, lipid metabolism, ECM proteins, transcription factors, and carbohydrate metabolism. RT-PCR and Southern blotting confirmed the changes in expression of selected genes. In this study we identified a large number of early and late mechanical response genes in HSFs. These changes in gene expression will provide potential candidate genes that might be involved in scleral remodeling during axial elongation in myopia.

The African trypanosome genome

The haploid nuclear genome of the African trypanosome, Trypanosoma brucei, is about 35 Mb and varies in size among different trypanosome isolates by as much as 25%. The nuclear DNA of this diploid organism is distributed among three size classes of chromosomes: the megabase chromosomes of which there are at least 11 pairs ranging from 1 Mb to more than 6 Mb (numbered I–XI from smallest to largest); several intermediate chromosomes of 200–900 kb and uncertain ploidy; and about 100 linear minichromosomes of 50–150 kb. Size differences of as much as four-fold can occur, both between the two homologues of a megabase chromosome pair in a specific trypanosome isolate and among chromosome pairs in different isolates. The genomic DNA sequences determined to date indicated that about 50% of the genome is coding sequence. The chromosomal telomeres possess TTAGGG repeats and many, if not all, of the telomeres of the megabase and intermediate chromosomes are linked to expression sites for genes encoding variant surface glycoproteins (VSGs). The minichromosomes serve as repositories for VSG genes since some but not all of their telomeres are linked to unexpressed VSG genes. A gene discovery program, based on sequencing the ends of cloned genomic DNA fragments, has generated more than 20 Mb of discontinuous single-pass genomic sequence data during the past year, and the complete sequences of chromosomes I and II (about 1 Mb each) in T. brucei GUTat 10.1 are currently being determined. It is anticipated that the entire genomic sequence of this organism will be known in a few years. Analysis of a test microarray of 400 cDNAs and small random genomic DNA fragments probed with RNAs from two developmental stages of T. brucei demonstrates that the microarray technology can be used to identify batteries of genes differentially expressed during the various life cycle stages of this parasite.