Jointly analyzing gene expression and copy number data in breast cancer using data reduction models

With the growing surge of biological measurements, the problem of integrating and analyzing different types of genomic measurements has become an immediate challenge for elucidating events at the molecular level. In order to address the problem of integrating different data types, we present a framework that locates variation patterns in two biological inputs based on the generalized singular value decomposition (GSVD). In this work, we jointly examine gene expression and copy number data and iteratively project the data on different decomposition directions defined by the projection angle /spl theta/ in the GSVD. With the proper choice of /spl theta/, we locate similar and dissimilar patterns of variation between both data types. We discuss the properties of our algorithm using simulated data and conduct a case study with biologically verified results. Ultimately, we demonstrate the efficacy of our method on two genome-wide breast cancer studies to identify genes with large variation in expression and copy number across numerous cell line and tumor samples. Our method identifies genes that are statistically significant in both input measurements. The proposed method is useful for a wide variety of joint copy number and expression-based studies. Supplementary information is available online, including software implementations and experimental data.     

DNA variation in the metallothionein genes in wild rice Oryza rufipogon: relationship between DNA sequence polymorphism, codon bias and gene expression

This study examines the relationship between DNA sequence variation and level of gene expression in four metallothionein genes from wild rice Oryza rufipogon. The nucleotide diversity was 0.0028 to 0.0117 over the entire coding and non-coding region, and it was negatively correlated with gene expression for three type 2 metallothionein genes. In contrast, codon bias and percent of preferred codons correlated positively with gene expression. These results indicate that the intensity of natural selection depends on the level of gene expression, which in turn shapes the level of nucleotide polymorphism. In addition, significant linkage disequilibria were frequent between the metallothionein genes, although significance was not confirmed after multiple test correction. This result suggests that metallothionein genes expressed at different levels are epistatic with respect to fitness, and that gene expression is an important factor determining level of DNA polymorphism.     

Optimizing heterologous expression in dictyostelium: importance of 5' codon adaptation

Expression of heterologous proteins in Dictyostelium discoideum presents unique research opportunities, such as the functional analysis of complex human glycoproteins after random mutagenesis. In one study, human chorionic gonadotropin (hCG) and human follicle stimulating hormone were expressed in Dictyostelium. During the course of these experiments, we also investigated the role of codon usage and of the DNA sequence upstream of the ATG start codon. The Dictyostelium genome has a higher AT content than the human, resulting in a different codon preference. The hCG-β gene contains three clusters with infrequently used codons that were changed to codons that are preferred by Dictyostelium. The results reported here show that optimizing the first 5–17 codons of the hCG gene contributes to 4- to 5-fold increased expression levels, but that further optimization has no significant effect. These observations suggest that optimal codon usage contributes to ribosome stabilization, but does not play an important role during the elongation phase of translation. Furthermore, adapting the 5′-sequence of the hCG gene to the Dictyostelium ‘Kozak’-like sequence increased expression levels ~1.5-fold. Thus, using both codon optimization and ‘Kozak’ adaptation, a 6- to 8-fold increase in expression levels could be obtained for hCG.     

CRCView: a web server for analyzing and visualizing microarray gene expression data using model-based clustering

CRCView is a user-friendly point-and-click web server for analyzing and visualizing microarray gene expression data using a Dirichlet process mixture model-based clustering algorithm. CRCView is designed to clustering genes based on their expression profiles. It allows flexible input data format, rich graphical illustration as well as integrated GO term based annotation/interpretation of clustering results. Availability: http://helab.bioinformatics.med.umich.edu/crcview/.     

Determining the relationship of gene expression and global mRNA stability in Drosophila melanogaster and Escherichia coli using linear models

There are several sequence-dependent factors regulating gene expression. Some of them have been extensively studied, among the most prominent are GC content and codon usage bias. Other factors hypothesized to have an impact on gene expression are gene length and the thermodynamic stability of mRNA secondary structure. In this work, we analyzed two different microarray datasets of Drosophila melanogaster gene expression and one dataset of Escherichia coli. To investigate the relationship between gene expression, codon usage bias and GC content of first, second and third codon position, gene length and mRNA stability we employed a multiple regression analysis using a comprehensive linear model. It is shown that codon usage bias and GC content of the first, second and third codon position show a significant influence on gene expression, whereas no significant effect of mRNA secondary structure stability is observed.     

Learning rule-based models of biological process from gene expression time profiles using gene ontology

MOTIVATION: Microarray technology enables large-scale inference of the participation of genes in biological process from similar expression profiles. Our aim is to induce classificatory models from expression data and biological knowledge that can automatically associate genes with novel hypotheses of biological process. RESULTS: We report a systematic supervised learning approach to predicting biological process from time series of gene expression data and biological knowledge. Biological knowledge is expressed using gene ontology and this knowledge is associated with discriminatory expression-based features to form minimal decision rules. The resulting rule model is first evaluated on genes coding for proteins with known biological process roles using cross validation. Then it is used to generate hypotheses for genes for which no knowledge of participation in biological process could be found. The theoretical foundation for the methodology based on rough sets is outlined in the paper, and its practical application demonstrated on a data set previously published by Cho et al. (Nat. Genet., 27, 48-54, 2001). AVAILABILITY: The Rosetta system is available at http://www.idi.ntnu.no/~aleks/rosetta. SUPPLEMENTARY INFORMATION: http://www.lcb.uu.se/~hvidsten/bioinf_cho/     

Revisiting the concept of lineage in prokaryotes: a phylogenetic perspective

Mutation and lateral transfer are two categories of processes generating genetic diversity in prokaryotic genomes. Their relative importance varies between lineages, yet both are complementary rather than independent, separable evolutionary forces. The replication process inevitably merges together their effects on the genome. We develop the concept of “open lineages” to characterize evolutionary lineages that over time accumulate more changes in their genomes by lateral transfer than by mutation. They contrast with “closed lineages,” in which most of the changes are caused by mutation. Open and closed lineages are interspersed along the branches of any tree of prokaryotes. This patchy distribution conflicts with the basic assumptions of traditional phylogenetic approaches. As a result, a tree representation including both open and closed lineages is a misrepresentation. The evolution of all prokaryotic lineages cannot be studied under a single model unless new phylogenetic approaches that are more pluralistic about lineage evolution are designed.     

Maize adaptation to temperate climate: relationship between population structure and polymorphism in the Dwarf8 gene

To investigate the genetic basis of maize adaptation to temperate climate, collections of 375 inbred lines and 275 landraces, representative of American and European diversity, were evaluated for flowering time under short- and long-day conditions. The inbred line collection was genotyped for 55 genomewide simple sequence repeat (SSR) markers. Comparison of inbred line population structure with that of landraces, as determined with 24 SSR loci, underlined strong effects of both historical and modern selection on population structure and a clear relationship with geographical origins. The late tropical groups and the early "Northern Flint" group from the northern United States and northern Europe exhibited different flowering times. Both collections were genotyped for a 6-bp insertion/deletion in the Dwarf8 (D8idp) gene, previously reported to be potentially involved in flowering time variation in a 102 American inbred panel. Among-group D8idp differentiation was much higher than that for any SSR marker, suggesting diversifying selection. Correcting for population structure, D8idp was associated with flowering time under long-day conditions, the deletion allele showing an average earlier flowering of 29 degree days for inbreds and 145 degree days for landraces. Additionally, the deletion allele occurred at a high frequency (>80%) in Northern Flint while being almost absent (<5%) in tropical materials. Altogether, these results indicate that Dwarf8 could be involved in maize climatic adaptation through diversifying selection for flowering time.     

The relationship among gene expression, folding free energy and codon usage bias in Escherichia coli

Taking advantage of microarray data in Escherichia coli genome, the relationship among mRNA expression levels, folding free energy and codon usage bias are investigated. Our results indicate that mRNA expression is correlated to the stability of mRNA secondary structure and the codon usage bias. The decrease of the stability of mRNA structure contributes to the increase of mRNA expression. There is a negative correlation between codon adaptation index (CAI) and mRNA expression in genes with less stable structure. The relationship between the stability of mRNA structure and mRNA half-life indicates the stability of mRNA structure is different from mRNA half-life.     

A relationship between gene expression and protein interactions on the proteome scale: analysis of the bacteriophage T7 and the yeast Saccharomyces cerevisiae

The relationship between the similarity of expression patterns for a pair of genes and interaction of the proteins they encode is demonstrated both for the simple genome of the bacteriophage T7 and the considerably more complex genome of the yeast Saccharomyces cerevisiae. Statistical analysis of large-scale gene expression and protein interaction data shows that protein pairs encoded by co-expressed genes interact with each other more frequently than with random proteins. Furthermore, the mean similarity of expression profiles is significantly higher for respective interacting protein pairs than for random ones. Such coupled analysis of gene expression and protein interaction data may allow evaluation of the results of large-scale gene expression and protein interaction screens as demonstrated for several publicly available datasets. The role of this link between expression and interaction in the evolution from monomeric to oligomeric protein structures is also discussed.     

Revisiting the relationship between wages and sleep duration: The role of insomnia

This paper uses the 2005 and 2010 Canadian General Social Surveys (Time Use) to investigate the effect of wages on the sleep duration of individuals in the labour force. The endogeneity of wages is taken into account with an instrumental variables approach; we find that the wage rate affects sleeping time in general, corroborating Biddle and Hamermesh’s (1990) main conclusion. A ten percent increase in the wage rate leads to an 11–12 min decrease in sleep per week. But this number masks several effects. The responsiveness of sleep time to wage rate changes depends upon the sex of the individual, whether or not sleep problems are present and general economic conditions. By far the largest adjustment is found for insomniacs in 2010, a year of general economic downturn in Canada. We also investigate the non-randomness of insomnia in the population by using a Heckman procedure, and find that the sleep time of female non-insomniacs is even more responsive to wage rate changes once account is taken of this selection bias, but otherwise selection was not a problem in our samples.     

Natural selection on gene order in the genome reorganization process after whole-genome duplication of yeast

A genome must locate its coding genes on the chromosomes in a meaningful manner with the help of natural selection, but the mechanism of gene order evolution is poorly understood. To explore the role of selection in shaping the current order of coding genes and their cis-regulatory elements, a comparative genomic approach was applied to the baker's yeast Saccharomyces cerevisiae and its close relatives. S. cerevisiae have experienced a whole-genome duplication followed by an extensive reorganization process of gene order, during which a number of new adjacent gene pairs appeared. We found that the proportion of new adjacent gene pairs in divergent orientation is significantly reduced, suggesting that such new divergent gene pairs may be disfavored most likely because their coregulation may be deleterious. It is also found that such new divergent gene pairs have particularly long intergenic regions. These observations suggest that selection specifically worked against deletions in intergenic regions of new divergent gene pairs, perhaps because they should be physically kept away so that they are not coregulated. It is indicated that gene regulation would be one of the major factors to determine the order of coding genes.     

Prediction of gene expression under drought stress in spring wheat using codon usage pattern

Spring wheat (Triticum aestivum) is a staple food providing sources of essential proteins for human. In fact, gene expressions of wheat play an important role in growth and productivity that are affected by drought stress. The objective of this work focused on analysis gene feature on spring wheat represented by nucleotide and gene expressions under drought stress. It was found that the higher codon adaptation index was in both wheat root and L-galactono-1, 4-lactone dehydrogenase. It was also found that guanine and cytosine content were high (55.56%) in wheat root. Whereas, guanine and cytosine content were low (41.28%) in L-galactono-1, 4-lactone dehydrogenase. Moreover, the higher relative synonymous codon usage value was observed in codon CAA (1.20), GAA (1.33), GAT (1.00), and ATG (1.00) in wheat root and thus about 62.95% of the total variation in relative synonymous codon was explained by principal component analysis. Additionally, high averages frequency number of codon were (above 15.76) in Met, Lys, Ala, Gly, Phe, Asp, Glu, His, and Tyr; whereas, low averages were in remaining amino acids and majority (90%) of modified relative codon bias values was between 0.40 and 0.90. Shortly, calculations and analysis of codon usage pattern under drought stress would help for genetic engineering, molecular evolution, and gene prediction in wheat studies for developing varieties that associate with drought tolerance.