Prediction of Cancer Class with Majority Voting Genetic Programming Classifier Using Gene Expression Data

In order to get a better understanding of different types of cancers and to find the possible biomarkers for diseases, recently, many researchers are analyzing the gene expression data using various machine learning techniques. However, due to a very small number of training samples compared to the huge number of genes and class imbalance, most of these methods suffer from overfitting. In this paper, we present a majority voting genetic programming classifier (MVGPC) for the classification of microarray data. Instead of a single rule or a single set of rules, we evolve multiple rules with genetic programming (GP) and then apply those rules to test samples to determine their labels with majority voting technique. By performing experiments on four different public cancer data sets, including multiclass data sets, we have found that the test accuracies of MVGPC are better than those of other methods, including AdaBoost with GP. Moreover, some of the more frequently occurring genes in the classification rules are known to be associated with the types of cancers being studied in this paper.     

Evolving fuzzy rules to model gene expression

This paper develops an algorithm that extracts explanatory rules from microarray data, which we treat as time series, using genetic programming (GP) and fuzzy logic. Reverse polish notation is used (RPN) to describe the rules and to facilitate the GP approach. The algorithm also allows for the insertion of prior knowledge, making it possible to find sets of rules that include the relationships between genes already known. The algorithm proposed is applied to problems arising in the construction of gene regulatory networks, using two different sets of real data from biological experiments on the Arabidopsis thaliana cold response and the rat central nervous system, respectively. The results show that the proposed technique can fit data to a pre-defined precision even in situations where the data set has thousands of features but only a limited number of points in time are available, a situation in which traditional statistical alternatives encounter difficulties, due to the scarcity of time points.     

An Automated System for Skeletal Maturity Assessment by Extreme Learning Machines

Assessing skeletal age is a subjective and tedious examination process. Hence, automated assessment methods have been developed to replace manual evaluation in medical applications. In this study, a new fully automated method based on content-based image retrieval and using extreme learning machines (ELM) is designed and adapted to assess skeletal maturity. The main novelty of this approach is it overcomes the segmentation problem as suffered by existing systems. The estimation results of ELM models are compared with those of genetic programming (GP) and artificial neural networks (ANNs) models. The experimental results signify improvement in assessment accuracy over GP and ANN, while generalization capability is possible with the ELM approach. Moreover, the results are indicated that the ELM model developed can be used confidently in further work on formulating novel models of skeletal age assessment strategies. According to the experimental results, the new presented method has the capacity to learn many hundreds of times faster than traditional learning methods and it has sufficient overall performance in many aspects. It has conclusively been found that applying ELM is particularly promising as an alternative method for evaluating skeletal age.     

Molecular Epidemiology of Cryptosporidiosis in Children in Malawi

ABSTRACT: Few studies have examined the molecular epidemiology of cryptosporidiosis in developing countries. In this study, DNA of 69 microscopy-positive human fecal samples collected from Malawi were examined by multilocus genetic analyses. From 43, 27 and 28 of the samples, the SSU rRNA, 70 kDa heat shock protein (HSP70) and 60 kDa glycoprotein (GP60) genes, respectively, were successfully PCR-amplified. Restriction analysis of the SSU PCR products showed that 41 of the 43 PCR-positive samples had C. hominis and 2 had C. parvum. Sequence analysis of the HSP70 and GP60 gene contirmed the species identification by SSU rRNA PCR-RFLP analysis, but also revealed high intraspecific variations. Altogether, six HSP70 subtypes and six GP60 subtypes (belonging to lour subtype alleles) of C. hominis were found. Linkage diseyuilibrum analysis of the two genetic loci showed possible intraspecitic recombination. Thus, cryptosporidiosis in the study area was largely caused by anthroponotic transmission. The high intraspecitic variation and existence of genetic recombination were probably results of high transmission of cryptosporidiosis in this area.     

GP2/THP gene family of self-binding, GPI-anchored proteins forms a cluster at chromosome 7F1 region in mouse genome

We investigated the genomic organization of pancreatic zymogen granule membrane-associated protein GP2, a GPI-anchored protein exhibiting self-aggregation at acidic pH, in order to construct a gene-knockout mouse. Cloning and analysis of lambda clones encoding GP2 from 129 Svj mouse genomic DNA libraries showed that the GP2 gene spans about 16.8 kb and includes 11 exons. Identifiable functional domains including a signal sequence, an EGF-like motif, a putative condensing ZP domain, a GPI-anchor attachment site, and a transmembrane sequence for GPI anchoring are encoded in separate exons. Using FISH, the GP2 gene was mapped to mouse chromosome 7F1 near the gene for THP, a GP2 homolog expressed in the cells of thick ascending loop of Henle (TALH) in the kidney. Further analysis of the mouse genome revealed that the THP and GP2 genes are adjacent to one another and are separated by only 3.5 kb in the 7F1 locus. Additionally, the overall structure of the THP gene, 16.2kb with 11 exons, was strikingly similar to that of GP2. This finding suggests that the GP2 and THP genes were generated by gene duplication and evolved separately to acquire regulatory elements leading to tissue-specific expression. Comparative analysis revealed that the 5' flanking region of the THP gene is similar to the first intron of NKCC2, a TALH cell-specific ion-transporter gene. The promoter region of the GP2 gene shares cis-elements found in other pancreas-specific genes. Using this genetic information, a GP2 null mutation was successfully introduced into an ES cell line, and an animal model was established without disruption of THP expression.     

表达猪繁殖与呼吸综合征病毒GP3基因的重组伪狂犬病病毒的构建

猪繁殖与呼吸综合征 (porcinereproductiveandrespiratorysyndrome ,PRRS)是引起怀孕母猪早产、流产、死胎及仔猪呼吸系统疾病的一种新发现的病毒性传染病[1] .该病毒的基因组为单股正链RNA ,约15kb ,含有 8个开放阅读框架 (ORFs) ,ORF1编码病毒非结构蛋白 (依赖RNA的RNA聚合酶 ) ,ORF2 ORF7编码病毒的结构蛋白 .其中ORF3含有 2 6 5个氨基酸 ,编码的GP3蛋白为高度糖基化的结构蛋白 ,有 7个糖基化位点 ,具有免疫原性[2 ,3 ] .目前 ,用于预防PRRS的疫苗主要是弱毒苗和灭活苗 ,虽然都有一定的免疫效果 ,但由于PRRS抗体依赖性…     

Synthetic biology and genetic causation

Synthetic biology research is often described in terms of programming cells through the introduction of synthetic genes. Genetic material is seemingly attributed with a high level of causal responsibility. We discuss genetic causation in synthetic biology and distinguish three gene concepts differing in their assumptions of genetic control. We argue that synthetic biology generally employs a difference-making approach to establishing genetic causes, and that this approach does not commit to a specific notion of genetic program or genetic control. Still, we suggest that a strong program concept of genetic material can be used as a successful heuristic in certain areas of synthetic biology. Its application requires control of causal context, and may stand in need of a modular decomposition of the target system. We relate different modularity concepts to the discussion of genetic causation and point to possible advantages of and important limitations to seeking modularity in synthetic biology systems.     

Evolution of pleiotropy: epistatic interaction pattern supports a mechanistic model underlying variation in genotype-phenotype map

The genotype-phenotype (GP) map consists of developmental and physiological mechanisms mapping genetic onto phenotypic variation. It determines the distribution of heritable phenotypic variance on which selection can act. Comparative studies of morphology as well as of gene regulatory networks show that the GP map itself evolves, yet little is known about the actual evolutionary mechanisms involved. The study of such mechanisms requires exploring the variation in GP maps at the population level, which presently is easier to quantify by statistical genetic methods rather than by regulatory network structures. We focus on the evolution of pleiotropy, a major structural aspect of the GP map. Pleiotropic genes affect multiple traits and underlie genetic covariance between traits, often causing evolutionary constraints. Previous quantitative genetic studies have demonstrated population-level variation in pleiotropy in the form of loci, at which genotypes differ in the genetic covariation between traits. This variation can potentially fuel evolution of the GP map under selection and/or drift. Here, we propose a developmental mechanism underlying population genetic variation in covariance and test its predictions. Specifically, the mechanism predicts that the loci identified as responsible for genetic variation in pleiotropy are involved in trait-specific epistatic interactions. We test this prediction for loci affecting allometric relationships between traits in an advanced intercross between inbred mouse strains. The results consistently support the prediction. We further find a high degree of sign epistasis in these interactions, which we interpret as an indication of adaptive gene complexes within the diverged parental lines.     

Ethical Issues of Using CRISPR Technologies for Research on Military Enhancement

This paper presents an overview of the key ethical questions of performing gene editing research on military service members. The recent technological advance in gene editing capabilities provided by CRISPR/Cas9 and their path towards first-in-human trials has reinvigorated the debate on human enhancement for non-medical purposes. Human performance optimization has long been a priority of military research in order to close the gap between the advancement of warfare and the limitations of human actors. In spite of this focus on temporary performance improvement, biomedical enhancement is an extension of these endeavours and the ethical issues of such research should be considered. In this paper, we explore possible applications of CRISPR to military human gene editing research and how it could be specifically applied towards protection of service members against biological or chemical weapons. We analyse three normative areas including risk–benefit analysis, informed consent, and inequality of access as it relates to CRISPR applications for military research to help inform and provide considerations for military institutional review boards and policymakers.     

Commonly conserved genetic fragments revealed by genome profiling can serve as tracers of evolution

We developed a method to produce, identify and analyze DNA fragments for the purpose of taxonomic classification. Genome profiling (GP) is a strategy that identifies genomic DNA fragments common to closely related species without prior knowledge of the DNA sequence. Random PCR, one of the key technologies of GP, is used to produce fragments and may be used even when there are mutations at the priming site. These fragments can then be distinguished based on the information of mobility and melting pattern when subjected to temperature gradient gel electrophoresis (TGGE). Corresponding fragments among several species, designated as commonly conserved genetic fragments (CCGFs), likely have the same genetic origin or correspond to the same gene. The criteria for identification of CCGFs has been defined and presented here. To assess this prediction, some of the fragments were sequenced and were confirmed to be CCGFs. We show that genome profiles bearing evolutionarily conserved CCGFs can be used to classify organisms and trace evolutionary pathways, among other profound applications.     

Toward predictive engineering of gene circuits

Many synthetic biology applications rely on programming living cells using gene circuits – the assembly and wiring of genetic elements to control cellular behaviors. Extensive progress has been made in constructing gene circuits with diverse functions and applications. For many circuit functions, however, it remains challenging to ensure that the circuits operate in a predictable manner. Although the notion of predictability may appear intuitive, close inspection suggests that it is not always clear what constitutes predictability. We dissect this concept and how it can be confounded by the complexity of a circuit, the complexity of the context, and the interplay between the two. We discuss circuit engineering strategies, in both computation and experiment, that have been used to improve the predictability of gene circuits.     

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。     

表达猪繁殖与呼吸综合征病毒修饰型GP5m蛋白的重组伪狂犬病毒的构建及其在小鼠的免疫反应

猪伪狂犬病毒（PRV）是一种良好的兽用活病毒疫苗载体。但以PRV基因缺失疫苗株TK^-/gE^-/LacZ⁺为载体表达PRRSV GP5的重组病毒TK^-/gE^-/GP5⁺免疫实验动物后难以激发抗PRRSV的中和抗体。为了进一步增强这种重组病毒的免疫效力,用具有更好免疫原性的修饰的ORF5基因（ORF5m）代替天然ORF5基因,构建了表达PRRSV的修饰型GP5m蛋白的重组伪狂犬病毒TK^-/gE^-/GP5m⁺。经PCR、Southern blot、Western blot 证实构建正确,并能表达具有活性的GP5m蛋白。将TK^-/gE^-/GP5m⁺与TK^-/gE^-/GP5⁺分别免疫Balb/c小鼠,结果TK^-/gE^-/GP5m⁺免疫小鼠不仅产生了较高水平的抗PRRSV的中和抗体(3/6只达到了1∶16),而且在诱导PRRSV特异性细胞免疫方面也显著优于TK^-/gE^-/GP5⁺,表明TK^-/gE^-/GP5m⁺是一种极有希望的PRRSV和PRV二价基因工程候选疫苗。     

兰花抗病毒基因工程研究进展(综述)

兰花病毒病严重影响兰花产业的发展,研究和探索防治兰花病毒病的新技术、新途径已成为众多研究者普遍关注的焦点。本文综述目前抗兰花病毒研究中应用的各种抗病毒基因工程策略,包括病毒来源基因中的外壳蛋白基因和运动蛋白基因介导的抗性策略,RNA介导的抗病毒策略,植物自身的抗病毒基因介导的抗性策略,利用多基因介导的抗性策略,以及抗体基因介导的抗性策略等。最后对兰花抗病毒基因工程的发展及应用进行了展望。     

Gene transfer into chicken embryos by retrovirus vectors

While chickens have many properties that are advantageous for embryological studies, their genetic analysis has been restricted. However, by using retrovirus vector systems in combination with classical techniques of experimental developmental biology, it has recently become possible to analyze the function of genes involved in the development of this organism. Avian retrovirus vectors are unique in that they can be divided into two categories: replication-competent and replication-defective (replication-incompetent). By choosing the vectors correctly, there are many experimental applications of these vectors such as induction of constitutive (or regulated) gene expression in a restricted region of tissues, organs and embryos; cell lineage analysis; and formation of concentration gradients of morphogens in micromass cultures. In this paper, several retrovirus vectors available for the chicken will be introduced and their applications in developmental biology will be reviewed.     

Component Object Based Single System Image for Dependable Implementation of Genetic Programming on Clusters

We present a distributed component-object model (DCOM) based single system image (SSI) for dependable parallel implementation of genetic programming (DPIGP). DPIGP is aimed to significantly and reliably improve the computational performance of genetic programming (GP) exploiting the inherent parallelism in GP among the evaluation of individuals. It runs on cost-effective clusters of commodity, non-dedicated, heterogeneous workstations or PCs. Developed SSI represents the pool of heterogeneous workstations as a single, unified virtual resource – a metacomputer, and addresses the issues of locating and allocating the physical resources, communicating between the entities of DPIGP, scheduling and load balancing. In addition, addressing the issue of fault tolerance, SSI allows for building a highly available metacomputer in which the cases of workstation failure result only in a corresponding partial degradation of the overall performance characteristics of DPIGP. Adopting DCOM as a communicating paradigm offers the benefits of software platform- and network protocol neutrality of proposed approach; and the generic support for the issues of locating, allocating and security of the distributed entities of DPIGP.     

The role of the charged residues of the GP2 helical regions in Ebola entry

The glycoprotein (GP) of Ebola is the sole structural protein that forms the spikes on the viral envelope. The GP contains two subunits, GP1 and GP2, linked by a disulfide bond, which are responsible for receptor binding and membrane fusion, respectively. In this study, the full length of GP gene of Ebola Zaire species, 2028 base pairs in length, was synthesized using 38 overlapping oligonucleotides by multiple rounds of polymerase chain reaction (PCR). The synthesized GP gene was shown to be efficiently expressed in mammalian cells. Furthermore, an efficient HIV-based pseudotyping system was developed using the synthetic GP gene, providing a safe approach to dissecting the entry mechanism of Ebola viruses. Using this pseudotyping system and mutational analysis, the role of the charged residues in the GP2 helical regions was examined. It was found that substitutions of the most charged residues in the regions did not adversely affect GP expression, processing, or viral incorporation, however, most of the mutations greatly impaired the ability of GP to mediate efficient viral infection. These results demonstrate that these charged residues of GP2 play an important role in GP-mediated Ebola entry into its host cells. We propose that these charged residues are involved in forming the intermediate conformation(s) of GP in membrane fusion and Ebola entry.     

紫菜色素突变体研究进展

色素变异是紫菜常见的突变性状。发生色素突变的紫菜可以为其遗传育种提供优秀的种质资源,并为其生理及基因功能研究提供理想的实验材料。结合色素突变体在育种工作和遗传基础研究等领域逐步显示出的广阔应用前景,本文重点论述了紫菜色素突变体的诱变、遗传特征、突变分子机制及应用等方面的研究进展。