Improving cluster visualization in self-organizing maps: application in gene expression data analysis

Cluster analysis is one of the crucial steps in gene expression pattern (GEP) analysis. It leads to the discovery or identification of temporal patterns and coexpressed genes. GEP analysis involves highly dimensional multivariate data which demand appropriate tools. A good alternative for grouping many multidimensional objects is self-organizing maps (SOM), an unsupervised neural network algorithm able to find relationships among data. SOM groups and maps them topologically. However, it may be difficult to identify clusters with the usual visualization tools for SOM. We propose a simple algorithm to identify and visualize clusters in SOM (the RP-Q method). The RP is a new node-adaptive attribute that moves in a two dimensional virtual space imitating the movement of the codebooks vectors of the SOM net into the input space. The Q statistic evaluates the SOM structure providing an estimation of the number of clusters underlying the data set. The SOM-RP-Q algorithm permits the visualization of clusters in the SOM and their node patterns. The algorithm was evaluated in several simulated and real GEP data sets. Results show that the proposed algorithm successfully displays the underlying cluster structure directly from the SOM and is robust to different net sizes.     

Gene expression profile class prediction using linear Bayesian classifiers

Due to recent advances in DNA microarray technology, using gene expression profiles, diagnostic category of tissue samples can be predicted with high accuracy. In this study, we discuss shortcomings of some existing gene expression profile classification methods and propose a new approach based on linear Bayesian classifiers. In our approach, we first construct gene-level linear classifiers to identify genes that provide high class-prediction accuracies, i.e., low error rates. After this screening phase, starting with the gene that offers the lowest error rate, we construct a multi-dimensional linear classifier by incorporating next best-performing genes, until the prediction error becomes minimum or 0, if possible. When we compared classification performance of our approach against prediction analysis of microarrays (PAM) and support vector machines (SVM) based approaches, we found that our method outperforms PAM and produces comparable results with SVM. In addition, we observed that the gene selection scheme of PAM could be misleading. Albeit SVM achieves relatively higher prediction performance, it has two major disadvantages: Complexity and lack of insight about important genes. Our intuitive approach offers competing performance and also an efficient means for finding important genes.     

Characterization of de novo microdeletions involving 17q11.2q12 identified through chromosomal comparative genomic hybridization

High-resolution array-comparative genome hybridization (CGH) is a powerful tool for detection of submicroscopic chromosome deletions and duplications. We describe two patients with mild mental retardation (MR) and de novo microdeletions of 17q11.2q12. Although the deletions did not involve the neurofibromatosis type 1 (NF1) gene, they overlap with long-range deletions of the NF1 region which have been encountered in a small group of NF1 patients with more severe MR. Given the overlap of the deletions in our two patients with the large-sized NF1 microdeletions but not with the more frequent and smaller NF1 deletions, we hypothesize that more than one gene in the 17q11.2q12 region may be involved in MR. We discuss candidate genes for MR within this interval that was precisely defined through array-CGH analysis.     

儿童肾上腺皮质癌表达谱时序分析用于筛选相关靶点的研究

目的 探讨肾上腺皮质癌（ACT）潜在致病机制,并筛选出可能作为相关生物靶标的基因。方法 从基因表达数据库Gene Expression Omnibus（GEO）中选取儿童ACT相关RNA芯片数据集（GSE75415）,利用R语言的相关函数包对其中的18个ACT组织样本（实验组）以及7个正常肾上腺皮质组织样本（对照组）中的mRNA表达数据进行预处理差异表达分析,对ACT各分级（stage1~4）的差异表达基因（DEGs）和重合差异基因（OLDEGs）,采用功能富集分析（GO功能富集和KEGG通路）,并筛选出中心基因。同时对TCGA数据库包括79个ACT样本的二代测序数据进 行分析,筛选出对ACT患者生存时间有影响的基因。结果 Stage1～4分别有248、334、315和561个基因发生了差异表达,各分级样本组间存在73个重合基因（OLDEGs）,中心基因HSPA13、GARS、STXBP1、AKIRIN1、TUBB3在各分级中均表达上调,中心基因ADH1B、DCN、RASSF2、PDGFRA、PLAT、C3、FOS在各分级中均表达下调,它们通过影响免疫反应、细胞周期、磷酸化、凝血及相应的信号通路,对ACT的发生与发展发挥作用。另外,OLDEGs在79个TCGA数据库ACT样本生存期分析发现,基因XPO1、RACGAP1、PDGFD、NR4A2、MXRA5、VPS51、TMED3、NDFIP1和CDKN1C与ACT的生存期密切相关。结论 在各级中均差异表达的基因和生存期相关基因可以作为ACT治疗的新靶点,这将有助于进一步理解肾上腺皮质癌的病因和预后治疗。     

海洋青铜小单孢菌FIM 02-523全基因组测序及分析

青铜小单孢菌(Micromonospora chalcea, M. chalcea)FIM 02-523能够合成对乏氧肿瘤细胞、艰难梭菌等具有活性的环脂肽类化合物rakicidins。利用Illumina HiSeq高通量测序平台,本研究首次对M. chalcea FIM 02-523进行全基因组测序,得到总长约6.74Mb的序列信息。分析表明基因组GC含量为72.89%,包含了6167个蛋白编码序列。利用AntiSMASH预测基因组中存在19个生物合成基因簇。结合PKS/NRPS生物合成特征和rakicidins化学结构特点,定位到了rakicidins的生物合成基因簇,并初步推测其生物合成途径。研究为M. chalcea FIM 02-523的功能基因组学研究和代谢调控提供了理论基础。     

甲氨蝶呤代谢酶基因多态性在类风湿关节炎治疗中的研究进展

甲氨蝶呤（MTX）是治疗类风湿关节炎的一线药物。然而,MTX的有效性和不良反应在患者间具有显著的差异,研究提示MTX的代谢及叶酸通路中关键酶的基因多态性可能影响细胞中MTX多聚谷氨酸的浓度和对叶酸通路的拮抗作用,从而影响了MTX的疗效发挥或患者对药物不良反应的差异。本文综述了近年来关于MTX治疗RA涉及基因多态性的研究进展。     

冠脉介入术患者CYP2C19基因多态性与氯吡格雷应用后心血管事件的相关性研究

目的：研究中国淮海地区汉族人群中冠心病并行支架植入术患者CYP2C19基因多态性与氯吡格雷应用后心血管事件发生的相关性。方法：选取我院拟行冠脉介入术治疗的冠心病患者225例,采用芯片杂交法进行CYP2C19基因分型。观察患者在服用氯吡格雷等药物治疗1年内各种心脑血管事件和出血事件的发生情况。结果：所有患者中CYP2C19基因慢代谢型比例为13.33%,中间代谢型比例为40.89%,快代谢型比例为45.78%。CYP2C19基因慢代谢型患者中发生心血管事件5例,快代谢型患者无心血管事件发生,差异有统计学意义（P＜0.05）。Logistic多元回归分析,发生心血管事件的相关因素为CYP2C19突变杂合及纯合基因型、吸烟、低密度脂蛋白过高（P＜0.05）。结论：淮海地区PCI术患者CYP2C19基因突变与氯吡格雷应用后再发生心血管事件相关。     

Antibody profiling using a recombinant protein–based multiplex ELISA array accelerates recombinant vaccine development: Case study on red sea bream iridovirus as a reverse vaccinology model

Predicting antigens that would be protective is crucial for the development of recombinant vaccine using genome based vaccine development, also known as reverse vaccinology. High-throughput antigen screening is effective for identifying vaccine target genes, particularly for pathogens for which minimal antigenicity data exist. Using red sea bream iridovirus (RSIV) as a research model, we developed enzyme-linked immune sorbent assay (ELISA) based RSIV-derived 72 recombinant antigen array to profile antiviral antibody responses in convalescent Japanese amberjack (Seriola quinqueradiata). Two and three genes for which the products were unrecognized and recognized, respectively, by antibodies in convalescent serum were selected for recombinant vaccine preparation, and the protective effect was examined in infection tests using Japanese amberjack and greater amberjack (S. dumerili). No protection was provided by vaccines prepared from gene products unrecognized by convalescent serum antibodies. By contrast, two vaccines prepared from gene products recognized by serum antibodies induced protective immunity in both fish species. These results indicate that ELISA array screening is effective for identifying antigens that induce protective immune responses. As this method does not require culturing of pathogens, it is also suitable for identifying protective antigens to un-culturable etiologic agents.     

Ischemic tau protein gene induction as an additional key factor driving development of Alzheimer’s phenotype changes in CA1 area of hippocampus in an ischemic model of Alzheimer’s disease

Background

Tauopathies are a class of neurodegenerative illnesses associated with the aberrant accumulation of the tau protein in the brain. The best known out of these diseases is Alzheimer’s disease, a disorder where the microtubule associated tau protein becomes hyperphosphorylated (which lowers its binding affinity to microtubules) and accumulates inside neurons in the form of tangles. In this study, we attempt to find out whether brain ischemia may play an important role in tau protein gene alterations.