In silico identification of short nucleotide sequences associated with gene expression of pollen development in rice

Microarray analysis of tiny amounts of RNA extracted from plant section samples prepared by laser microdissection (LM) can provide high-quality information on gene expression in specified plant cells at various stages of development. Having joined the LM-microarray analysis project, we utilized such genome-wide gene expression data from developing rice pollen cells to identify candidates for cis-regulatory elements for specific gene expression in these cells. We first found a few clusters of gene expression patterns based on the data from LM-microarrays. On one gene cluster in which the members were specifically expressed at the bicellular and mature pollen mitotic stages, we identified gene cluster fingerprints (GCFs), each of which consists of a short nucleotide representing the gene cluster. We expected that these GCFs would contain cis-regulatory elements for stage- and tissue-specific gene expression, and we further identified groups of GCFs with common core sequences. Some criteria, such as frequency of occurrence in the gene cluster in contrast to the total tested gene set, flanking sequence preference and distribution of combined GCF sets in the gene regions, allowed us to limit candidates for cis-regulatory sequences for specific gene expression in rice pollen cells to at least 20 sets of combined GCFs. This approach should provide a general purpose algorithm for identifying short nucleotides associated with specific gene expression.     

Large-scale analysis of gene expression profiles

The accumulation of DNA microarray data has now made it possible to use gene expression profiles to analyse expression data. A gene expression profile contains the expression data for a given gene over various samples, and can be contrasted with an expression signature, which contains the expression data for a single sample. Gene expression profiles are most revealing when samples are grouped appropriately, either by standard clinical or pathological categories or by categories discovered through cluster analysis techniques. Expression profiles can exist at various levels of abstraction, yielding information across various tissues or across diseases within a particular tissue. Hypothesis tests may be applied to expression profiles on a large scale to identify candidate genes of interest.     

In silico analysis of PHB gene family in maize

Prohibitins (PHBs) are highly conserved proteins in species ranging from prokaryotes to eukaryotes. Plant PHBs have been implicated in various cellular processes including development, senescence and stress responses. Although PHBs have been investigated in several plant species including Arabidopsis and tobacco, no systematic gene family analysis has been carried in maize. In the present study, 16 putative PHB genes have been identified. Analysis of the conserved protein motifs and gene structures has revealed high levels of conservation within the phylogenetic subgroups. Published microarray database showed that most maize PHB genes exhibited different expression levels in different tissues and developmental stages. Cis-elements analysis showed that ZmPHB2 and ZmPHB12 may play important roles in plant development. Taken together, we provide a comprehensive bioinformatics analysis of the PHB gene family in maize genome and our data provide an important foundation for further functional study of this gene family in maize.     

A comparative MudPIT analysis identifies different expression profiles in heart compartments

Cardiomyopathies indistinctly affect atrial and ventricular cardiac compartments with alterations of their mechanical and/or electrical activity. To understand the main mechanisms involved in these pathological alterations, a detailed knowledge of the physiology of the healthy heart is critical. In the present work, we utilize multidimensional protein identification technology to characterize the murine left ventricle (LV), right ventricle (RV), and atria (A) proteomes, identifying thousands of distinct proteins. Moreover, using multidimensional algorithm protein map tool, relative abundances of proteins among the heart chambers were investigated. In sum, we found 16 and 55 proteins were more abundant in LV compared to RV and A, respectively; 47 and 60 proteins were more abundant in RV than LV and A, respectively; and, 81 and 74 proteins were more abundant in A than LV and RV, respectively. This detailed characterization of myocardial compartment proteome represents an important advancement in the knowledge of heart physiology, and may contribute to the identification of key features underlying the onset of cardiomyopathy.     

In silico feedback for in vivo regulation of a gene expression circuit

We show that difficulties in regulating cellular behavior with synthetic biological circuits may be circumvented using in silico feedback control. By tracking a circuit's output in Saccharomyces cerevisiae in real time, we precisely control its behavior using an in silico feedback algorithm to compute regulatory inputs implemented through a genetically encoded light-responsive module. Moving control functions outside the cell should enable more sophisticated manipulation of cellular processes whenever real-time measurements of cellular variables are possible.     

In silico diagnosis of inherently inhibited gene expression focusing on initial codon combinations

The translation start site, immediately downstream from the start codon, is a dominant factor for gene expression in Escherichia coli. At present, no method exists to improve the expression level of cloned genes, since it remains difficult to find the best codon combination within the region. We determined the expression parameters that correspond to all sense codons within the first four codons using GFPuv which encodes a derivative of green fluorescent protein. Using a genetic algorithm (GA)-based computer program, these parameters were incorporated in a simple, static model for the prediction of translation efficiency, and optimized to the expression level for 137 randomly isolated GFPuv genes. The calculated initial translation index (ITI), also proven for the DsRed2 gene that encodes a red fluorescent protein, should provide a solution to overcome the gene expression problem in cloned genes whose expression is often inherently blocked at the translation process. The proposed method facilitates heterologous protein production in E. coli, the most commonly used host in biological and industrial fields.     

油菜蔗糖转化酶基因的电子克隆和生物信息学分析

运用电子克隆技术获得油菜中一个蔗糖转化酶基因eDNA序列,同时根据此段序列设计引物以油菜eDNA为模板进行扩增。经测序得到证实。采用生物信息学方法,对该基因编码蛋白从氨基酸组成、基本理化性质、跨膜结构域、信号肽导肽、疏水性／亲水性、二级结构、亚细胞定位等方面进行了预测和分析。结果表明：该基因eDNA序列长度为2150bp,包含一个1779bp开放阅读框,编码592个氨基酸;该编码蛋白含有蔗糖转化酶的多个典型的保守结构域。同源比对分析显示,该基因编码的氨基酸序列与拟南芥等植物的蔗糖转化酶基因具有高度的相似性,进一步确定该蛋白为蔗糖蛋白酶。研究结果为该基因进一步的实验克隆,表达分析,功能鉴定奠定基础。     

In silico prioritisation of candidate genes for prokaryotic gene function discovery: an application of phylogenetic profiles

Background  

In silico candidate gene prioritisation (CGP) aids the discovery of gene functions by ranking genes according to an objective relevance score. While several CGP methods have been described for identifying human disease genes, corresponding methods for prokaryotic gene function discovery are lacking. Here we present two prokaryotic CGP methods, based on phylogenetic profiles, to assist with this task.     

Genome-wide analysis of gene expression profiles associated with cell cycle transitions in growing organs of Arabidopsis

Organ growth results from the progression of component cells through subsequent phases of proliferation and expansion before reaching maturity. We combined kinematic analysis, flowcytometry, and microarray analysis to characterize cell cycle regulation during the growth process of leaves 1 and 2 of Arabidopsis (Arabidopsis thaliana). Kinematic analysis showed that the epidermis proliferates until day 12; thereafter, cells expand until day 19 when leaves reach maturity. Flowcytometry revealed that endoreduplication occurs from the time cell division rates decline until the end of cell expansion. Analysis of 10 time points with a 6k-cDNA microarray showed that transitions between the growth stages were closely reflected in the mRNA expression data. Subsequent genome-wide microarray analysis on the three main stages allowed us to categorize known cell cycle genes into three major classes: constitutively expressed, proliferative, and inhibitory. Comparison with published expression data obtained from root zones corresponding to similar developmental stages and from synchronized cell cultures supported this categorization and enabled us to identify a high confidence set of 131 proliferation genes. Most of those had an M phase-dependent expression pattern and, in addition to many known cell cycle-related genes, there were at least 90 that were unknown or previously not associated with proliferation.     

In silico identification and expression analysis of Rare Cold Inducible 2 (RCI2) gene family in cucumber

Journal of Plant Biochemistry and Biotechnology - Rare Cold Inducible 2 (RCI2), also known as plasma membrane protein 3, is a group of low molecular weight proteins that play crucial roles in plant...     

In silico analysis of the EPS8 gene family: genomic organization,expression profile,and protein structure

EPS8 codes for a protein essential in Ras to Rac signaling leading to actin remodeling. Three genes highly homologous to EPS8 were discovered, thereby defining a novel gene family. Here, we report the genomic structure of EPS8 and the EPS8-related genes in human and mouse. We performed BLASTN searches against the Celera Human Genome and Mouse Fragments Database. The mouse fragments were manually assembled, and the organization of both human and mouse genes was reconstructed. The gene structures in Celera annotations of the human and mouse genomes were compared to outline correspondences and divergences. We also compared the EPS8 family gene structures predicted by Celera with those predicted by NCBI. Moreover, we performed a virtual analysis of the expression of the EPS8 gene family members by using the SAGEmap Database in NCBI. Finally, we analyzed the domain organization of the gene products and their evolutionary conservation to define novel putative domains, thereby helping to predict novel modality of action for the members of this gene family. The data obtained will be instrumental in directing further experimental functional characterization of these genes.