Control of endogenous gene expression timing by introns

Comparison of gene expression from transgenes and endogenous genes with or without introns reveals a time-regulating role of introns in natural biological systems.     

How introns influence and enhance eukaryotic gene expression

Although it has been known since the late 1970s that intron-containing and intronless versions of otherwise identical genes can exhibit dramatically different expression profiles, the underlying molecular mechanisms have only lately come to light. This review summarizes recent progress in our understanding of how introns and the act of their removal by the spliceosome can influence and enhance almost every step of mRNA metabolism. A rudimentary understanding of these effects can prove invaluable to researchers interested in optimizing transgene expression in eukaryotic systems.     

Regulation of picornavirus gene expression

Members of the Picornaviridae are positive- strand RNA viruses that cause a variety of human diseases such as poliomyelitis, the common cold, myocarditis, and hepatitis. Although the diseases caused by picornaviruses are diverse, the genome organization and mechanisms of gene expression are highly conserved among family members. This review will discuss the mechanisms of viral gene expression including cap-independent translation initiation, host cell translation shut off, viral polyprotein processing, and RNA replication.     

Regulation of nodulin gene expression

The expression of plant genes specifically induced during rhizobial infection and the early stages of nodule ontogeny (early nodulin genes) and those induced in the mature, nitrogen-fixing nodule (late nodulin genes) is differentially regulated and tissue/cell specific. We have been interested in the signal transduction pathway responsible for symbiotic, temporal and spatial control of expression of an early (Enod2) and a late (Leghemoglobin;lb) nodulin gene from the stem-nodulated legumeSesbania rostrata, and in identifying thecis-acting elements andtrans-acting factors involved in this process (De Bruijn and Schell, 1992). By introducing chimericS. rostrata lb promoter-gus reporter gene fusions into transgenicLotus corniculatus plants, we have been able to show that thelb promoter directs an infected-cell-specific expression pattern inLotus nodules. We have been able to delimit thecis-acting element responsible for nodule-infected-cell-expression to a 78 pb region of thelb promoter (NICE Element) and have analyzed this element in detail by site-specific mutagenesis. We have studied the interaction of the NICE element, and further upstreamcis-acting elements, withtrans-acting factors of both plant- and rhizobial origin. We have obtained evidence for the involvement of rhizobial proteins in infected-cell-specific plant gene expression (Welters et al., 1993). We have purified one of the bacterial binding proteins from theS. rostrata symbiontAzorhizobium caulinodans (AcBBP1), and cloned and mutated the corresponding gene, in order to examine its symbiotic phenotype. We have also found that theS. rostrata Enod2 gene is rapidly induced by physiologically significant concentrations of cytokinins, suggesting the role of cytokinin as a potential secondary signal involved in nodulation (Dehio and De Bruijn, 1992). We are examining whether the observed cytokinin induction, as well as the nodule-specific expression pattern, are modulated by theSrEnod2 promoter.     

Co-ABC: Correlation artificial bee colony algorithm for biomarker gene discovery using gene expression profile

In this paper, we propose a new hybrid method based on Correlation-based feature selection method and Artificial Bee Colony algorithm,namely Co-ABC to select a small number of relevant genes for accurate classification of gene expression profile. The Co-ABC consists of three stages which are fully cooperated: The first stage aims to filter noisy and redundant genes in high dimensionality domains by applying Correlation-based feature Selection (CFS) filter method. In the second stage, Artificial Bee Colony (ABC) algorithm is used to select the informative and meaningful genes. In the third stage, we adopt a Support Vector Machine (SVM) algorithm as classifier using the preselected genes form second stage. The overall performance of our proposed Co-ABC algorithm was evaluated using six gene expression profile for binary and multi-class cancer datasets. In addition, in order to proof the efficiency of our proposed Co-ABC algorithm, we compare it with previously known related methods. Two of these methods was re-implemented for the sake of a fair comparison using the same parameters. These two methods are: Co-GA, which is CFS combined with a genetic algorithm GA. The second one named Co-PSO, which is CFS combined with a particle swarm optimization algorithm PSO. The experimental results shows that the proposed Co-ABC algorithm acquire the accurate classification performance using small number of predictive genes. This proofs that Co-ABC is a efficient approach for biomarker gene discovery using cancer gene expression profile.     

昆虫基因表达的调控

昆虫的基因表达过程十分复杂,受多种调控因子的调节,随着分子生物学研究新技术在昆虫学上的应用,昆虫基因表达的调控也取得了较快进展,本文以一些特征清楚的系统为例,讨论昆虫基因表达调控的研究现状,旨在为其它昆虫表达的调控研究提供借鉴。