Applications of Self-Organizing Maps for Ecomorphological Investigations through Early Ontogeny of Fish

We propose a new graphical approach to the analysis of multi-temporal morphological and ecological data concerning the life history of fish, which can typically serves models in ecomorphological investigations because they often undergo significant ontogenetic changes. These changes can be very complex and difficult to describe, so that visualization, abstraction and interpretation of the underlying relationships are often impeded. Therefore, classic ecomorphological analyses of covariation between morphology and ecology, performed by means of multivariate techniques, may result in non-exhaustive models. The Self Organizing map (SOM) is a new, effective approach for pursuing this aim. In this paper, lateral outlines of larval stages of gilthead sea bream (Sparus aurata) and dusky grouper (Epinephelus marginatus) were recorded and broken down using by means of Elliptic Fourier Analysis (EFA). Gut contents of the same specimens were also collected and analyzed. Then, shape and trophic habits data were examined by SOM, which allows both a powerful visualization of shape changes and an easy comparison with trophic habit data, via their superimposition onto the trained SOM. Thus, the SOM provides a direct visual approach for matching morphological and ecological changes during fish ontogenesis. This method could be used as a tool to extract and investigate relationships between shape and other sinecological or environmental variables, which cannot be taken into account simultaneously using conventional statistical methods.     

应用基因芯片技术检测非综合征型耳聋基因突变

目的:应用遗传性耳聋基因芯片对散发性聋患者进行分子病因学检测,评估其在遗传性耳聋快速基因诊断中的可靠性。方法:门诊收集散发性聋患者10例,取外周血,提取基因组DNA,用遗传性耳聋基因芯片检测4个中国人中常见的耳聋相关基因中的9个热点突变,包括GJB2(35delG、176del16bp、235delC及299delAT)、GJB3(C538T)、SLC26A4(IVS7-2AG、A2168G)和线粒体DNA 12S rRNA(A1555G、C1494T)。同时,PCR扩增GJB2、线粒体12S rRNA基因全序列,DNA测序,以验证基因芯片检测结果的准确性。结果:在10名耳聋患者中,基因芯片方法检出1例携带线粒体DNA 12S rRNA C1494T突变;2例GJB2基因235delC纯合突变;2例235delC杂合突变;SLC26A4基因和GJB3基因未检出突变。基因芯片的结果与测序结果完全一致。结论:遗传性耳聋基因芯片技术对中国人常见耳聋相关基因热点突变的检出率高,结果准确、可靠,具有快速、高通量、高准确性、低成本等特点,能够满足临床耳聋基因检测的要求,同时结合产前诊断技术能有效预防耳聋患儿的出生,因而具有广阔的临床应用前景。     

Differential Gene Expression Analysis by DNA Microarray Technology and Its Application in Molecular Oncology

Accumulation of genetic and epigenetic aberrations leads to malignant transformation of normal cells. Functional studies of cancer using genomic and proteomic tools aim to reveal the true complexity of the processes leading to cancer development in humans. Until recently, diagnosis and prognosis of cancer was based on conventional pathologic criteria and epidemiological evidence. Certain tumors were divided only into relatively broad histological and morphological subcategories. Rapidly developing methods of differential gene expression analysis promote the search for clinically relevant genes changing their expression levels during malignant transformation. DNA microarrays offer a unique possibility to rapidly assess the global expression picture of thousands genes in any given time point and compare the results of detailed combinatory analysis of global expression profiles for normal and malignant cells at various functional stages or separate experimental conditions. Acquisition of such genetic portraits allows searching for regularity and difference in expression patterns of certain genes, understanding their function and pathological importance, and ultimately developing the molecular nosology of cancer. This review describes the basis of DNA microarray technology and methodology, and focuses on their application in molecular classification of tumors, drug sensitivity and resistance studies, and identification of biological markers of cancer.     

Rapid Production of Virus Protein Microarray Using Protein Microarray Fabrication through Gene Synthesis (PAGES)

The high genetic variability of RNA viruses is a significant factor limiting the discovery of effective biomarkers, the development of vaccines, and characterizations of the immune response during infection. Protein microarrays have been shown to be a powerful method in biomarker discovery and the identification of novel protein–protein interaction networks, suggesting that this technique could also be very useful in studies of infectious RNA viruses. However, to date, the amount of genetic material required to produce protein arrays, as well as the time- and labor-intensive procedures typically needed, have limited their more widespread application. Here, we introduce a method, protein microarray fabrication through gene synthesis (PAGES), for the rapid and efficient construction of protein microarrays particularly for RNA viruses. Using dengue virus as an example, we first identify consensus sequences from 3,604 different strains and then fabricate complete proteomic microarrays that are unique for each consensus sequence. To demonstrate their applicability, we show that these microarrays can differentiate sera from patients infected by dengue virus, related pathogens, or from uninfected patients. We anticipate that the microarray and expression library constructed in this study will find immediate use in further studies of dengue virus and that, more generally, PAGES will become a widely applied method in the clinical characterization of RNA viruses.     

DNA微阵列在药物研究中的应用

DNA微阵列是传统分子生物学向后基因组学过渡中发展起来的新技术,具有高通量,速度快的优点,并能够在药物和基因之间架起一座桥梁.从基因水平上来解释药物的作用机理,因此在新型药物开发和分析中具有广泛的应用前景.本文着重介绍了该技术的概况和在药物开发和分析中的应用,并提出了该技术在药物开发和分析的前景和展望.     

DNA微阵列在结核分枝杆菌研究中的应用

高密度DNA微阵列技术可以通过一次杂交获得大量的基因组信息,广泛用于基因组结构和基因表达谱分析。本文简介DNA微阵列技术在结核分枝杆菌的功能基因组学,致病机理以及耐药机制,诊断等方面的应用。     

基因芯片技术在病原细菌检测中的应用

基因芯片技术具有快速、高通量、平行化等优点,在病原细菌检测中有广泛的应用前景,选择细菌适宜的靶基因是芯片制备的关键之一。用细菌核糖体基因做靶基因的芯片技术,虽然应用广泛,但仍存在一些不足,随着基因组信息及基因功能的深入研究,包括毒力基因、耐药基因等具有较好种属特异性的细菌基因不断被发现,为芯片技术检测病原细菌提供了更多特异的靶基因,使检测结果更加灵敏、准确,在病原细菌研究中将发挥更大的作用。     

Self-Organizing Feature Maps Identify Proteins Critical to Learning in a Mouse Model of Down Syndrome

Down syndrome (DS) is a chromosomal abnormality (trisomy of human chromosome 21) associated with intellectual disability and affecting approximately one in 1000 live births worldwide. The overexpression of genes encoded by the extra copy of a normal chromosome in DS is believed to be sufficient to perturb normal pathways and normal responses to stimulation, causing learning and memory deficits. In this work, we have designed a strategy based on the unsupervised clustering method, Self Organizing Maps (SOM), to identify biologically important differences in protein levels in mice exposed to context fear conditioning (CFC). We analyzed expression levels of 77 proteins obtained from normal genotype control mice and from their trisomic littermates (Ts65Dn) both with and without treatment with the drug memantine. Control mice learn successfully while the trisomic mice fail, unless they are first treated with the drug, which rescues their learning ability. The SOM approach identified reduced subsets of proteins predicted to make the most critical contributions to normal learning, to failed learning and rescued learning, and provides a visual representation of the data that allows the user to extract patterns that may underlie novel biological responses to the different kinds of learning and the response to memantine. Results suggest that the application of SOM to new experimental data sets of complex protein profiles can be used to identify common critical protein responses, which in turn may aid in identifying potentially more effective drug targets.     

基因芯片技术在新基因发现中的应用

基因芯片技术是20世纪90年代中期在生命科学领域中发展起来的一种分子生物学新兴技术,是多学科的交叉融合。简要概述了基因芯片技术的产生、原理、特点、制作方法和类型,及其在新基因发现中的应用。     

DNA微阵列在猪遗传育种中的应用

DNA微阵列是高通量﹑微型化﹑自动化研究生物大分子功能的高新技术,目前已经广泛应用于动植物生物学过程的基因表达研究中。猪既是重要的经济动物,又是常用的实验动物,应用DNA微阵列对其重要经济性状主效基因的寻找和各种疾病遗传机制的探索已经成为今后该领域的一个十分重要的发展方向。     

Interpreting 16S rDNA T-RFLP Data: Application of Self-Organizing Maps and Principal Component Analysis to Describe Community Dynamics and Convergence

Interpreting the large amount of data generated by rapid profiling techniques, such as T-RFLP, DGGE, and DNA arrays, is a difficult problem facing microbial ecologists. This study compares the ability of two very different ordination methods, principal component analysis (PCA) and self-organizing map neural networks (SOMs), to analyze 16S-DNA terminal restriction-fragment length polymorphism (T-RFLP) profiles from microbial communities in glucose-fed methanogenic bioreactors during startup and changes in operational parameters. Our goal was not only to identify which samples were similar, but also to decipher community dynamics and describe specific phylotypes, i.e., phylogenetically similar organisms, that behaved similarly in different reactors. Fifteen samples were taken over 56 volume changes from each of two bioreactors inoculated from river sediment (S2) and anaerobic digester sludge (M3) and from a well-established control reactor (R1). PCA of bacterial T-RFLP profiles indicated that both the S2 and M3 communities changed rapidly during the first nine volume changes, and then became relatively stable. PCA also showed that an HRT of 8 or 6 days had no effect on either reactor communtity, while an HRT of 2 days changed community structure significantly in both reactors. The SOM clustered the terminal restriction fragments according to when each fragment was most abundant in a reactor community, resulting in four clearly discernible groups. Thirteen fragments behaved similarly in both reactors, eight of which composed a significant proportion of the microbial community as judged by the relative abundance of the fragment in the T-RFLP profiles. Six Bacteria terminal restriction fragments shared between the two communities matched cloned 16S rDNA sequences from the reactors related to Spirochaeta, Aminobacterium, Thermotoga, and Clostridium species. Convergence also occurred within the acetoclastic methanogen community, resulting in a predominance of Methanosarcina siciliae-related organisms. The results demonstrate that both PCA and SOM analysis are useful in the analysis of T-RFLP data; however, the SOM was better at resolving patterns in more complex and variable data than PCA ordination.     

DNA芯片技术在食品病原体检测中的应用

病原体的存在,尤其是食品中的病原体,给人类健康带来了威胁。DNA芯片技术是一种非常有效的病原体检测工具,具有众多传统检测方法所不具备的优势,受到广泛关注。我们简要论述了DNA芯片在细菌病原体、寄生虫、病毒病原体、微生物耐药性等的检测中的应用,并进一步综述了DNA芯片技术在食品检测中存在的问题、解决方法及发展方向。     

N-Cadherin Gene Maps to Human Chromosome 18 and Is Not Linked to the E-Cadherin Gene

cDNA clones encoding the human N-cadherin cell adhesion molecule have been isolated from an embryonic muscle library by screening with an oligonucleotide probe complementary to the chick brain sequence and chick brain cDNA probe lambda N2. Comparison of the predicted protein sequences revealed greater than 91% homology between chick brain, mouse brain, and human muscle N-cadherin cDNAs over the 748 amino acids of the mature, processed protein. A single polyadenylation site in the chick clone was also present and duplicated in the human muscle sequence. Immediately 3' of the recognition site in chick a poly(A) tail ensued; however, in human an additional 800 bp of 3' untranslated sequence followed. Northern analysis identified a number of major N-cadherin mRNAs. These were of 5.2, 4.3, and 4.0 kb in C6 glioma, 4.3 and 4.0 kb in human foetal muscle cultures, and 4.3 kb in human embryonic brain and mouse brain with minor bands of 5.2 kb in human muscle and embryonic brain. Southern analysis of a panel of somatic cell hybrids allowed the human N-cadherin gene to be mapped to chromosome 18. This is distinct from the E-cadherin locus on chromosome 16. Therefore, it is likely that the cadherins have evolved from a common precursor gene that has undergone duplication and migration to other chromosomal locations.     

随机矩阵理论在肝癌基因功能模块识别中的应用

采用随机矩阵理论方法研究了肝癌的基因表达网络。通过标准误差分析,得到了从富含噪声的肝癌基因网络中分离出真实肝癌基因网络的、去躁最充分的关联系数,分析了由此获得的基因表达网络的13个基因功能模块,发现这些模块与肝癌的产生和发展有密切关系。基于随机矩阵理论的方法克服了以往模块识别方法带有主观因素且不能去除噪声因子的缺陷,是一种有效去除随机噪声、识别基因模块、简化基因网络的方法。由于基因数目的众多及细胞生物过程的复杂性,从整体的角度系统研究肝癌基因表达谱,对理解肝癌分子机制和探索新的治疗方法有重要的现实意义。     

寡核苷酸芯片在微生物检测中的应用

近几年来发展起来的基因组研究技术———基因芯片技术为微生物检测提供了一种强有力的手段。目前国内外已广泛地开展了利用寡核苷酸芯片对多种微生物 (主要是病毒和细菌 ,少量有真菌 )进行相关检测的研究 ,并在对微生物病原体检测、种类鉴定、功能基因检测、基因分型、突变检测、基因组监测等方面获得了成功。由于寡核苷酸探针具有可根据研究需要任意设计、特异性高等特点 ,寡核苷酸芯片在微生物检测中有着巨大的应用价值 ,具有广阔的应用前景。