Adaptive quality-based clustering of gene expression profiles

MOTIVATION: Microarray experiments generate a considerable amount of data, which analyzed properly help us gain a huge amount of biologically relevant information about the global cellular behaviour. Clustering (grouping genes with similar expression profiles) is one of the first steps in data analysis of high-throughput expression measurements. A number of clustering algorithms have proved useful to make sense of such data. These classical algorithms, though useful, suffer from several drawbacks (e.g. they require the predefinition of arbitrary parameters like the number of clusters; they force every gene into a cluster despite a low correlation with other cluster members). In the following we describe a novel adaptive quality-based clustering algorithm that tackles some of these drawbacks. RESULTS: We propose a heuristic iterative two-step algorithm: First, we find in the high-dimensional representation of the data a sphere where the "density" of expression profiles is locally maximal (based on a preliminary estimate of the radius of the cluster-quality-based approach). In a second step, we derive an optimal radius of the cluster (adaptive approach) so that only the significantly coexpressed genes are included in the cluster. This estimation is achieved by fitting a model to the data using an EM-algorithm. By inferring the radius from the data itself, the biologist is freed from finding an optimal value for this radius by trial-and-error. The computational complexity of this method is approximately linear in the number of gene expression profiles in the data set. Finally, our method is successfully validated using existing data sets. AVAILABILITY: http://www.esat.kuleuven.ac.be/~thijs/Work/Clustering.html     

Evolutionary significance of gene expression divergence

Recent large-scale studies of evolutionary changes in gene expression among mammalian species have led to the proposal that gene expression divergence may be neutral with respect to organismic fitness. Here, we employ a comparative analysis of mammalian gene sequence divergence and gene expression divergence to test the hypothesis that the evolution of gene expression is predominantly neutral. Two models of neutral gene expression evolution are considered: 1-purely neutral evolution (i.e., no selective constraint) of gene expression levels and patterns and 2-neutral evolution accompanied by selective constraint. With respect to purely neutral evolution, levels of change in gene expression between human-mouse orthologs are correlated with levels of gene sequence divergence that are determined largely by purifying selection. In contrast, evolutionary changes of tissue-specific gene expression profiles do not show such a correlation with sequence divergence. However, divergence of both gene expression levels and profiles are significantly lower for orthologous human-mouse gene pairs than for pairs of randomly chosen human and mouse genes. These data clearly point to the action of selective constraint on gene expression divergence and are inconsistent with the purely neutral model; however, there is likely to be a neutral component in evolution of gene expression, particularly, in tissues where the expression of a given gene is low and functionally irrelevant. The model of neutral evolution with selective constraint predicts a regular, clock-like accumulation of gene expression divergence. However, relative rate tests of the divergence among human-mouse-rat orthologous gene sets reveal clock-like evolution for gene sequence divergence, and to a lesser extent for gene expression level divergence, but not for the divergence of tissue-specific gene expression profiles. Taken together, these results indicate that gene expression divergence is subject to the effects of purifying selective constraint and suggest that it might also be substantially influenced by positive Darwinian selection.     

Analysis of dysregulation of immune system in pancreatic cancer based on gene expression profile

The aim of this study was to explore the dysregulated expression of the immune system in pancreatic cancer and clarify the pathogenesis of pancreatic cancer. The Dataset GSE15471 was downloaded from GEO database, Student’s t test was used to screen differentially expressed genes (DEGs) between the pancreatic cancer group and the normal control group. Kyoto Encyclopedia of Genes and Genomes (KEGG) provides functional annotation was employed to explore the significant DEGs involved in biological functions. We got 988 significantly DEGs, including 832 up-regulated genes and 156 down-regulated genes. The ratio of up-regulated genes and down-regulated genes was 5.3. Total 13 biological pathways which were significant enriched with DEGs by KEGG pathway enrichment analysis. Finally, we constructed a overall network of the immune system in pancreatic cancer with these biological pathways information. Our study reveals that dysregulated pathways in pancreatic cancer associated with the immune system. Besides, we also identify some important molecular biomarkers of the pancreatic cancer, including CXCR4 and CD4. Dysfunctional pathways and important molecular biomarkers of pancreatic cancer will provide useful information for potential treatment of pancreatic cancer.     

Nonspecific stimulation of the maternal immune system. II. Effects on gene expression in the fetus

BACKGROUND: Maternal immune stimulation reduces malformations caused by chemical teratogens. Mechanisms for this effect are not known. Altered expression of regulatory molecules (e.g., transforming growth factor [TGF-beta], tumor necrosis factor-alpha [TNF-alpha]) has been reported in fetuses from immunostimulated mice, which may affect gene expression. Expression of selected genes that function to control proliferation, differentiation, or apoptosis was evaluated in chemical-exposed fetuses, with or without maternal immunostimulation. METHODS: Ethyl carbamate (urethane) was given to pregnant ICR mice on day 10 of gestation to induce cleft palate. Before teratogen administration, the immune system of the female mice was stimulated by footpad injection with Freund's complete adjuvant (FCA) or by intraperitoneal injection with interferon-gamma (IFN-gamma). RESULTS: Maternal immunostimulation with interferon-gamma (IFN-gamma) decreased severity of the cleft palate lesion caused by urethane, while FCA decreased both incidence and severity of cleft palate. Gestation day 14 fetuses from urethane-exposed mothers displayed decreased expression of cell cycle/apoptotic genes bcl2alpha, bcl2beta, pkCalpha, and p53 in fetal heads. Immune stimulation with IFN-gamma-normalized expression of bcl2alpha, bcl2beta, and pkCalpha to control levels. Urethane also decreased the ratio of expression of bclalpha/p53, bclbeta/p53, and pkCalpha/p53, while maternal injection with IFN-gamma restored these expression ratios to control levels. Maternal immunization with FCA also significantly increased bcl2alpha/p53, bcl2beta/p53, and pkCalpha/p53 gene expression ratios. CONCLUSIONS: These results suggest that (1) the maternal immune system may possess heretofore unrecognized regulatory activity in fetal development, and (2) protection against urethane-induced cleft palate may be mediated through maternal immune regulation of fetal gene expression.     

Epigenetics: monoallelic expression in the immune system

Epigenetic modifications to DNA and chromatin programme important genome functions including gene expression, chromosomal architecture and stability, and the maintenance of developmental states. Recent findings further implicate epigenetic modifications in the control of allelic choice in the immune system.     

Nutritional stress affects the tsetse fly's immune gene expression

Tsetse-transmitted trypanosomiasis poses a serious threat to human and animal health in sub-Saharan Africa. The majority of tsetse flies ( Glossina spp.) in a natural population will not develop a mature infection of either Trypanosoma congolense or Trypanosoma brucei sp. because of refractoriness, a phenomenon that is affected by different factors, including the tsetse fly's immune defence. Starvation of tsetse flies significantly increases their susceptibility to the establishment of a trypanosome infection. This paper reports the effects of nutritional stress (starvation) on (a) uninduced baseline levels of gene expression of the antimicrobial peptides attacin, defensin and cecropin in the tsetse fly, and (b) levels of expression induced in response to bacterial ( Escherichia coli ) or trypanosomal challenge. In newly emerged, unfed tsetse flies, starvation significantly lowers baseline levels of antimicrobial peptide gene expression, especially for attacin and cecropin. In response to trypanosome challenge, only non-starved older flies showed a significant increase in antimicrobial peptide gene expression within 5 days of ingestion of a trypanosome-containing bloodmeal, especially with T. brucei bloodstream forms. These data suggest that a decreased expression of immune genes in newly hatched flies or a lack of immune responsiveness to trypanosomes in older flies, both occurring as a result of fly starvation, may be among the factors contributing to the increased susceptibility of nutritionally stressed tsetse flies to trypanosome infection.     

Adaptive immune responses are linked to the mating system of arvicoline rodents

ABSTRACT Males generally exhibit reduced immune responses and greater susceptibility to disease than females. The suppressive effect of testosterone on immune function is hypothesized to be one reason why males have lower immune responses than females. Presumably, this effect of testosterone should be more pronounced among polygynous than monogamous species because circulating testosterone is higher among polygynous than monogamous males. The present study examined the extent to which sex differences in specific humoral immunity are related to the endocrine status and mating system of two arvicoline rodents. Humoral immunity was evaluated among polygynous meadow voles (Microtus pennsylvanicus) and monogamous prairie voles (Microtus ochrogaster) by challenging them with the novel antigen keyhole limpet hemocyanin (KLH) and assessing specific immune responses 5, 10, and 15 d following immunization. Overall, meadow voles mounted higher anti-KLH IgM and IgG responses than prairie voles did. Sex differences were also apparent for anti-KLH IgM responses; male meadow voles mounted higher antibody responses than conspecific females, whereas female prairie voles mounted greater responses to KLH than did conspecific males. Male meadow voles had significantly higher testosterone concentrations and reproductive organ mass than male prairie voles did but had elevated immune responses, suggesting that testosterone may not be the primary factor involved in the observed sex and species differences in immune responses. Species and sex differences in corticosterone concentrations were also evident and may contribute to the observed differences in immune function. The influence of extrinsic factors on immune function is also discussed. Taken together, these data provide evidence that the mating system may influence endocrine-immune interactions.     

Adaptive gene expression divergence inferred from population genomics

Detailed studies of individual genes have shown that gene expression divergence often results from adaptive evolution of regulatory sequence. Genome-wide analyses, however, have yet to unite patterns of gene expression with polymorphism and divergence to infer population genetic mechanisms underlying expression evolution. Here, we combined genomic expression data—analyzed in a phylogenetic context—with whole genome light-shotgun sequence data from six Drosophila simulans lines and reference sequences from D. melanogaster and D. yakuba. These data allowed us to use molecular population genetics to test for neutral versus adaptive gene expression divergence on a genomic scale. We identified recent and recurrent adaptive evolution along the D. simulans lineage by contrasting sequence polymorphism within D. simulans to divergence from D. melanogaster and D. yakuba. Genes that evolved higher levels of expression in D. simulans have experienced adaptive evolution of the associated 3′ flanking and amino acid sequence. Concomitantly, these genes are also decelerating in their rates of protein evolution, which is in agreement with the finding that highly expressed genes evolve slowly. Interestingly, adaptive evolution in 5′ cis-regulatory regions did not correspond strongly with expression evolution. Our results provide a genomic view of the intimate link between selection acting on a phenotype and associated genic evolution.     

Statistical significance analysis of longitudinal gene expression data

MOTIVATION: Time-course microarray experiments are designed to study biological processes in a temporal fashion. Longitudinal gene expression data arise when biological samples taken from the same subject at different time points are used to measure the gene expression levels. It has been observed that the gene expression patterns of samples of a given tumor measured at different time points are likely to be much more similar to each other than are the expression patterns of tumor samples of the same type taken from different subjects. In statistics, this phenomenon is called the within-subject correlation of repeated measurements on the same subject, and the resulting data are called longitudinal data. It is well known in other applications that valid statistical analyses have to appropriately take account of the possible within-subject correlation in longitudinal data. RESULTS: We apply estimating equation techniques to construct a robust statistic, which is a variant of the robust Wald statistic and accounts for the potential within-subject correlation of longitudinal gene expression data, to detect genes with temporal changes in expression. We associate significance levels to the proposed statistic by either incorporating the idea of the significance analysis of microarrays method or using the mixture model method to identify significant genes. The utility of the statistic is demonstrated by applying it to an important study of osteoblast lineage-specific differentiation. Using simulated data, we also show pitfalls in drawing statistical inference when the within-subject correlation in longitudinal gene expression data is ignored.     

Interacting gene clusters and the evolution of the vertebrate immune system

Unraveling the "code" of genome structure is an important goal of genomics research. Colocalization of genes in eukaryotic genomes may facilitate preservation of favorable allele combinations between epistasic loci or coregulation of functionally related genes. However, the presence of interacting gene clusters in the human genome has remained unclear. We systematically searched the human genome for evidence of closely linked genes whose protein products interact. We find 83 pairs of interacting genes that are located within 1 Mbp in the human genome or 37 if we exclude hub proteins. This number of interacting gene clusters is significantly more than expected by chance and is not the result of tandem duplications. Furthermore, we find that these clusters are significantly more conserved across vertebrate (but not chordate) genomes than other pairs of genes located within 1 Mbp in the human genome. In many cases, the genes are both present but not clustered in older vertebrate lineages. These results suggest gene cluster creation along the human lineage. These clusters are not enriched for housekeeping genes, but we find a significant contribution from genes involved in "response to stimulus." Many of these genes are involved in the immune response, including, but not limited to, known clusters such as the major histocompatibility complex. That these clusters were formed contemporaneously with the origin of adaptive immunity within the vertebrate lineage suggests that novel evolutionary and regulatory constraints were associated with the operation of the immune system.