基因芯片技术在甘蔗研究中的应用进展

基因芯片技术是新生代的生物技术,具有大规模平行处理生命信息的能力.基因芯片具有高通量、并行性、微型化与自动化的特点,因此成为探究功能基因组学最有效的方法之一,已引起全世界广泛的关注和重视,在许多领域得到了广泛的应用.甘蔗是世界上急需研发的重要能源作物,基因芯片对甘蔗研究有重要的意义.本文简介了基因芯片技术的原理和制备过程,并着重阐述了在甘蔗抗旱、抗病、基因表达和miR-NA鉴定方面的应用进展.     

基因芯片技术在微生物学研究中的应用

近年来,基因芯片技术的诞生使得在一个实验中就可以同时对成千上万个基因进行转录水平的表达和DNA同源性分析成为可能。该项技术已被应用于揭示许多微生物体的转录表达和基因组的差异,随着越来越多的微生物基因组全序列测定的完成,基因芯片正逐渐成为许多微生物学研究领域中的一项常规技术。归纳了该技术在微生物生理,致病性,流行病学,生态,进化,代谢工程及发酵优化等研究中的应用。     

基因芯片在骨骼肌老龄化相关基因表达谱中的应用

对老龄组大鼠 (30月龄 )和年轻对照组大鼠 (3月龄 )的腓肠肌超微结构进行观察 ,可以看到前者肌肉肌纤维萎缩伴有线粒体空泡变性。并进行总RNA抽提、mRNA纯化、探针制备 ,应用基因芯片筛选老龄化相关基因 ,两组大鼠骨骼肌重复出现的差异表达基因 12 7个 ,下调基因涉及能量代谢、信号转导 ,上调基因涉及蛋白质分解、细胞凋亡     

基因芯片在研究病毒感染宿主基因表达谱中的应用

人类基因组计划提供的海量基因信息以及功能基因组学理论和技术的出现,为研究病毒与宿主相互作用提供了难得的历史机遇。病毒作为一种严格的细胞内寄生物,感染宿主后会引起宿主细胞形态和功能的改变。这些变化主要由于病毒感染导致宿主细胞基因表达变化所引起。通过基因芯片技术研究病毒感染宿主的基因表达谱变化,可以发现病毒感染宿主细胞在分子水平上的应答,从而为病毒性疾病的预防、诊断和临床治疗提供新的策略。     

基因芯片技术在植物研究中的应用

简述了基因芯片的原理、特点、分类及制作方法,同时详细综述了基因芯片技术在植物研究中的应用。     

基因芯片技术与基因表达谱研究

基因芯片技术是近年来出现的分子生物学与微电子技术相结合的最新DNA分析检测技术,该技术将成为信息科学与生命科学之间的联系纽带,为后基因组时代基因功能的分析提供一种最重要的技术手段,目前基因芯片技术已在基因表达谱等研究中得到广泛应用。     

乳酸菌基因芯片应用研究进展

基因芯片技术是上世纪90年代兴起的一种对成百上千甚至上万个基因同时进行检测的新技术,具有高通量、并行化的特点,广泛应用于基因表达谱测定、基因功能预测、基因突变检测和多态性分析等方面。多种乳酸菌基因组全序列以及其大量EST、16S rDNA、16S-23S基因间区和功能基因序列测定的完成,有力地推动了基因芯片技术在乳酸菌研究中的应用。介绍了基因芯片的基本原理及乳酸菌基因芯片在基因表达、种属鉴定等研究中的应用进展,以期更好地利用和开发乳酸菌基因芯片。     

应用基因芯片技术检测肝组织的基因表达

为检测正常肝组织中的基因表达状况,采用cDNA microarray技术对正常肝组织中表达的1500个基因进行定量,结果为97个基因较高表达,1010个基因中度表达,380个基因低表达,结果是cDNA microarray技术是大规模检测基因表达的有效方法。     

基因芯片在医学中的应用

本文简述了基因芯片的原理,以及在基因发现、诊断、新药开发、基因组做图、突变和多态性检测方面的应用。     

生物信息学在基因芯片中的应用

生物信息学和基因芯片是生命科学研究领域中的两种新方法和新技术,生物信息学与基因芯片密切相关,生物信息学促进了基因芯片的研究与应用,而基因芯片则丰富了生物信息学的研究内容。本论文探讨生物信息学在基因芯片中的应用,将生物信息学方法运用到高密度基因芯片设计和芯片实验数据管理及分析。从信息学的角度提出基因芯片设计准则,提出寡核苷酸探针的优化设计方法,将该方法运用于再测序型芯片和基因表达型芯片的设计,在此基础上研制出高密度基因芯片设计软件系统和实验结果分析系统。     

Comparison of gene expression microarray data with count-based RNA measurements informs microarray interpretation

Background

Although numerous investigations have compared gene expression microarray platforms, preprocessing methods and batch correction algorithms using constructed spike-in or dilution datasets, there remains a paucity of studies examining the properties of microarray data using diverse biological samples. Most microarray experiments seek to identify subtle differences between samples with variable background noise, a scenario poorly represented by constructed datasets. Thus, microarray users lack important information regarding the complexities introduced in real-world experimental settings. The recent development of a multiplexed, digital technology for nucleic acid measurement enables counting of individual RNA molecules without amplification and, for the first time, permits such a study.

Results

Using a set of human leukocyte subset RNA samples, we compared previously acquired microarray expression values with RNA molecule counts determined by the nCounter Analysis System (NanoString Technologies) in selected genes. We found that gene measurements across samples correlated well between the two platforms, particularly for high-variance genes, while genes deemed unexpressed by the nCounter generally had both low expression and low variance on the microarray. Confirming previous findings from spike-in and dilution datasets, this “gold-standard” comparison demonstrated signal compression that varied dramatically by expression level and, to a lesser extent, by dataset. Most importantly, examination of three different cell types revealed that noise levels differed across tissues.

Conclusions

Microarray measurements generally correlate with relative RNA molecule counts within optimal ranges but suffer from expression-dependent accuracy bias and precision that varies across datasets. We urge microarray users to consider expression-level effects in signal interpretation and to evaluate noise properties in each dataset independently.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-649) contains supplementary material, which is available to authorized users.     

A simple and robust algorithm for microarray data clustering based on gene population-variance ratio metric

With the advent of the microarray technology, the field of life science has been greatly revolutionized, since this technique allows the simultaneous monitoring of the expression levels of thousands of genes in a particular organism. However, the statistical analysis of expression data has its own challenges, primarily because of the huge amount of data that is to be dealt with, and also because of the presence of noise, which is almost an inherent characteristic of microarray data. Clustering is one tool used to mine meaningful patterns from microarray data. In this paper, we present a novel method of clustering yeast microarray data, which is robust and yet simple to implement. It identifies the best clusters from a given dataset on the basis of the population of the clusters as well as the variance of the feature values of the members from the cluster-center. It has been found to yield satisfactory results even in the presence of noisy data.     

冰片提取物对沙眼衣原体感染HeLa细胞CT703及CT259表达的影响

目的:探究冰片提取物对沙眼衣原体感染后的He La细胞模型CT703和CT259表达的影响。方法:将成功建立的40例感染L2血清型沙眼衣原体的人宫颈癌上皮(He La)细胞模型随机分成A、B两组,分别添加冰片提取物和等剂量生理盐水。观察感染后He La细胞模型的包涵体数目及大小、RNA抽提结果完整性以及CT70与CT259的表达变化。结果:染色后的40例受沙眼衣原体感染的He La细胞模型体内均发现包涵体,在同一时间点B组细胞内包涵体比A组大,且数目比A组多(P0.05);两组提取的总RNA的OD值均在1.8~2.0之间,通过RNA凝胶电泳结果可清楚发现28S、18S及5S条带;同一时间点CT259和CT703扩增产物的平均灰度值比较,A组感染后He La细胞模型样本基因表达量低于B组,差异具有统计学意义(P0.05)。结论:冰片提取物能够有效降低经沙眼衣原体感染的He La细胞模型中CT703与CT259基因表达量。     

Factors influencing cDNA microarray hybridization on silylated glass slides

cDNA microarray technology is becoming the technique of choice for studying gene expression and gene expression patterns. Although experimental protocols are available, only limited methodological information on microarray manufacture, hybridization, and signal interpretation has been published. The aim of this paper is to provide more insight into the practical aspects of microarray construction and hybridization. The influence of the size, composition, and concentration of the spotted DNA fragments on the final hybridization signal and the effect of hybridization volume, sample concentration, and sample depletion have been tested and are discussed.     

Using ANOVA for gene selection from microarray studies of the nervous system

Methods are presented for detecting differential expression using statistical hypothesis testing methods including analysis of variance (ANOVA). Practicalities of experimental design, power, and sample size are discussed. Methods for multiple testing correction and their application are described. Instructions for running typical analyses are given in the R programming environment. R code and the sample data set used to generate the examples are available at http://microarray.cpmc.columbia.edu/pavlidis/pub/aovmethods/.     

Comparison of commercial probe labeling kits for microarray: towards quality assurance and consistency of reactions

Microarray technology is readily available to scientists interested in gene expression. Commensurate with this availability is the growing market in accessory products offering convenience but potentially variable performance. Here we evaluate seven commercial kits for probe labeling against a human apoptosis oligonucleotide array. All kits were found to label probes successfully using the manufacturers' instructions. The Stratagene Fairplay Microarray Labeling Kit was the most sensitive, with an overall call rate of 74% and the lowest rate of indeterminant calls for the HEK and HepG2 cell lines. The Invitrogen SuperScript Indirect cDNA Labeling System showed the most reproducible gene expression pattern and the least technical variation, both in terms of signal strength and between replicates on each array. The Promega Pronto! Plus System showed the least dye bias however, a higher level of variation between replicates was observed. Pairwise comparisons revealed that the Promega Pronto! Plus System and Invitrogen SuperScript Indirect cDNA Labeling System had the most similarity in their patterns of gene expression. Results obtained suggest variability in the performance of commercial kits between different manufacturers. This study supports the need to conduct comparative evaluations of commercial microarray probe labeling kits and the need for validation prior to use.     

DNA microarray unravels rapid changes in transcriptome of MK-801 treated rat brain

AIM:To investigate the impact of MK-801 on gene expression patterns genome wide in rat brain regions. METHODS:Rats were treated with an intraperitoneal injection of MK-801 [0.08(low-dose) and 0.16(highdose) mg/kg] or NaC l(vehicle control). In a first series of experiment,the frontoparietal electrocorticogram was recorded 15 min before and 60 min after injection. In a second series of experiments,the whole brain of each animal was rapidly removed at 40 min post-injection,and different regions were separated:amygdala,cerebral cortex,hippocampus,hypothalamus,midbrain and ventral striatum on ice followed by DNA microarray(4 × 44 K whole rat genome chip) analysis.RESULTS:Spectral analysis revealed that a single systemic injection of MK-801 significantly and selectively augmented the power of baseline gamma frequency(30-80 Hz) oscillations in the frontoparietal electroencephalogram. DNA microarray analysis showed the largest number(up- and down- regulations) of gene expressions in the cerebral cortex(378),midbrain(376),hippocampus(375),ventral striatum(353),amygdala(301),and hypothalamus(201) under low-dose(0.08 mg/kg) of MK-801. Under high-dose(0.16 mg/kg),ventral striatum(811) showed the largest number of gene expression changes. Gene expression changes were functionally categorized to reveal expression of genes and function varies with each brain region.CONCLUSION:Acute MK-801 treatment increases synchrony of baseline gamma oscillations,and causes very early changes in gene expressions in six individual rat brain regions,a first report.