Tumor-specific gene expression patterns with gene expression profiles

Gene expression profiles of 14 common tumors and their counterpart normal tissues were analyzed with machine learning methods to address the problem of selection of tumor-specific genes and analysis of their differential expressions in tumor tissues. First, a variation of the Relief algorithm, “RFE_Relief algorithm” was proposed to learn the relations between genes and tissue types. Then, a support vector machine was employed to find the gene subset with the best classification performance for distinguishing cancerous tissues and their counterparts. After tissue-specific genes were removed, cross validation experiments were employed to demonstrate the common deregulated expressions of the selected gene in tumor tissues. The results indicate the existence of a specific expression fingerprint of these genes that is shared in different tumor tissues, and the hallmarks of the expression patterns of these genes in cancerous tissues are summarized at the end of this paper.     

Tumor-specific gene expression patterns with gene expression profiles

Gene expression profiles of 14 common tumors and their counterpart normal tissues were analyzed with machine learning methods to address the problem of selection of tumor-specific genes and analysis of their differential expressions in tumor tissues. First, a variation of the Relief algorithm, "RFE_Relief algorithm" was proposed to learn the relations between genes and tissue types. Then, a support vector machine was employed to find the gene subset with the best classification performance for distinguishing cancerous tissues and their counterparts. After tissue-specific genes were removed, cross validation experiments were employed to demonstrate the common deregulated expressions of the selected gene in tumor tissues. The results indicate the existence of a specific expression fingerprint of these genes that is shared in different tumor tissues, and the hallmarks of the expression patterns of these genes in cancerous tissues are summarized at the end of this paper.     

Site-specific gene targeting for gene expression in eukaryotes

Major advances in the use of site-specific recombinases to facilitate sustained gene expression via chromosomal targeting have been made during the past year. New tools for genomic manipulations using this technology include the discovery of epitopes in recombinases that confer nuclear localization, crystal structures that show the precise topology of recombinase-DNA-substrate synaptic complexes, manipulations of the DNA recognition sequences that select for integration over excision of DNA, and manipulations that make changes in gene expression inducible by drug administration. In addition, endogenous eukaryotic and mammalian DNA sequences have been discovered that can support site-specific recombinase-mediated manipulations.     

Transient gene expression and influence of promoters on foreign gene expression in Arabidopsis thaliana

Summary The influence of a variety of parameters was investigated on polyethylene glycol (PEG)-mediated transient nptII and gus gene expression in mesophyll protoplasts of Arabidopsis thaliana ecotype, Estland, in order to develop a suitable transient gene expression system. The investigation revealed that a combination of 20% PEG, incubation time of 15 min, 20–30 μg plasmid concentration per ml along with 50 μg carrier DNA m/l, and inclusion of calcium and magnesium ions during transfection followed by a culture period of 24 h registered maximum NPTII activity. Of the various promoters used for driving expression of the gus gene, the ubiquitin promoter from A. thaliana was the most efficient followed by 35S promoter of the CaMV and the actin promoter of rice. For comparison, similar studies in protoplasts of rice, wheat, and Brassica also revealed the differences in strength of these promoters. Arabidopsis ubiquitin promoter was the most effective in Brassica, and the rice actin1 promoter was the most effective in rice and wheat.     

Developmentally regulated gene expression in Artemia: Histone gene expression in newly hatched larvae

The synthesis of histones and presence of histone mRNA sequences in embryos and larvae of the brine shrimp, Artemia, were investigated. Radiolabeling of proteins synthesized in vivo followed by electrophoretic and fluorographic analysis confirmed the prediction that histone synthesis is coordinated with the wave of DNA replication in newly hatched larvae. No histone synthesis occurs during development of encysted embryos. Hybridization of cloned Artemia histone gene DNA to total cell RNA indicated that dormant encysted embryos do not contain “masked” messenger RNA.     

Tuning noise in gene expression

The relative contribution of promoter architecture and the associated chromatin environment in regulating gene expression noise has remained elusive. In their recent work, Arkin, Schaffer and colleagues (Dey et al, 2015) show that mean expression and noise for a given promoter at different genomic loci are uncorrelated and influenced by the local chromatin environment.     

Monoallelic gene expression in mammals

Three systems of monoallelic gene expression in mammals are known, namely, X-chromosome inactivation, imprinting, and allelic exclusion. In all three systems, monoallelic expression is regulated epigenetically and is frequently directed by long non-coding RNAs (ncRNAs). This review briefs all three systems of monoallelic gene expression in mammals focusing on chromatin modifications, spatial chromosome organization in the nucleus, and the functioning of ncRNAs.     

Mechanoregulation of gene expression in fibroblasts

Mechanical loads placed on connective tissues alter gene expression in fibroblasts through mechanotransduction mechanisms by which cells convert mechanical signals into cellular biological events, such as gene expression of extracellular matrix components (e.g., collagen). This mechanical regulation of ECM gene expression affords maintenance of connective tissue homeostasis. However, mechanical loads can also interfere with homeostatic cellular gene expression and consequently cause the pathogenesis of connective tissue diseases such as tendinopathy and osteoarthritis. Therefore, the regulation of gene expression by mechanical loads is closely related to connective tissue physiology and pathology. This article reviews the effects of various mechanical loading conditions on gene regulation in fibroblasts and discusses several mechanotransduction mechanisms. Future research directions in mechanoregulation of gene expression are also suggested.