In many vertebrates, the enzymatic oxidation of dietary yellow carotenoids generates red keto‐carotenoids giving color to ornaments. The oxidase CYP2J19 is here a key effector. Its purported intracellular location suggests a shared biochemical pathway between trait expression and cell functioning. This might guarantee the reliability of red colorations as individual quality signals independent of production costs. We hypothesize that the ornament type (feathers vs. bare parts) and production costs (probably CYP2J19 activity compromising vital functions) could have promoted tissue‐specific (...) class='Hi'>gene relocation. We review current avian tissue‐specific CYP2J19 expression data. Among the ten red‐billed species showing CYP2J19 bill expression, only one showed strong hepatic expression. Moreover, a phylogenetically‐controlled analysis of 25 red‐colored species shows that those producing red bare parts are less likely to have strong hepatic CYP2J19 expression than species with only red plumages. Thus, both production costs and shared pathways might have contributed to the evolution of red signals. (shrink)

Serial analysis of gene expression (SAGE) is a powerful technique that can be used for global analysis of gene expression. Its chief advantage over other methods is that it does not require prior knowledge of the genes of interest and provides qualitative and quantitative data of potentially every transcribed sequence in a particular cell or tissue type. This is a technique of expression profiling, which permits simultaneous, comparative and quantitative analysis of (...) gene‐specific, 9‐ to 13‐basepair sequences. These short sequences, called SAGE tags, are linked together for efficient sequencing. The sequencing data are then analyzed to identify each gene expressed in the cell and the levels at which each gene is expressed. The main benefit of SAGE includes the digital output and the identification of novel genes. In this review, we present an outline of the method, various bioinformatics methods for data analysis and general applications of this important technology. BioEssays 26:916–922, 2004. © 2004 Wiley Periodicals, Inc. (shrink)

Gene expression network is also a type of complex network. It is challenging to analyze the gene expression network through relevant knowledge and algorithms of a complex network. In this paper, the existing characteristics of genes are analyzed from various indexes of the gene expression network to analyze key genes and TOP genes. Firstly, gene chip data are screened, gene data with obvious characteristics are selected, and relevant clustering characteristics are (...) analyzed. Then, the complex gene network structure is established, and gene networks with different threshold shapes and different sizes are selected. Finally, the relevant indexes and PR values after the PageRank algorithm are analyzed for complex networks under different thresholds, thus establishing the TOP gene and PR sequence. (shrink)

The vast majority (> 95%) of single-gene mutations in yeast affect not only the expression of the mutant gene, but also the expression of many other genes. These data suggest the presence of a previously uncharacterized ‘gene expression network’—a set of interactions between genes which dictate gene expression in the native cell environment. Here, we quantitatively analyze the gene expression network revealed by microarray expression data from 273 (...) different yeast gene deletion mutants.(1) We find that gene expression interactions form a robust, error-tolerant ‘scale-free’ network, similar to metabolic pathways(2) and artificial networks such as power grids and the internet.(3-5) Because the connectivity between genes in the gene expression network is unevenly distributed, a scale-free organization helps make organisms resistant to the deleterious effects of mutation, and is thus highly adaptive. The existence of a gene expression network poses practical considerations for the study of gene function, since most mutant phenotypes are the result of changes in the expression of many genes. Using principles of scale-free network topology, we propose that fragmenting the gene expression network via ‘genome-engineering’ may be a viable and practical approach to isolating gene function. BioEssays 24:267–274, 2002. © 2002 Wiley Periodicals, Inc.; DOI 10.1002/bies.10054. (shrink)

Gene clustering is a useful exploratory technique to group together genes with similar expression levels under distinct cell cycle phases or distinct conditions. It helps the biologist to identify potentially meaningful relationships between genes. In this study, we propose a clustering method based on multivariate normal mixture models, where the number of clusters is predicted via sequential hypothesis tests: at each step, the method considers a mixture model of m components (m = 2 in the first step) and (...) tests if in fact it should be m - 1. If the hypothesis is rejected, m is increased and a new test is carried out. The method continues (increasing m) until the hypothesis is accepted. The theoretical core of the method is the full Bayesian significance test, an intuitive Bayesian approach, which needs no model complexity penalization nor positive probabilities for sharp hypotheses. Numerical experiments were based on a cDNA microarray dataset consisting of expression levels of 205 genes belonging to four functional categories, for 10 distinct strains of Saccharomyces cerevisiae. To analyze the method’s sensitivity to data dimension, we performed principal components analysis on the original dataset and predicted the number of classes using 2 to 10 principal components. Compared to Mclust (model-based clustering), our method shows more consistent results. (shrink)

In the big data era, sequencing technology has produced a large number of biological sequencing data. Different views of the cancer genome data provide sufficient complementary information to explore genetic activity. The identification of differentially expressed genes from multiview cancer gene data is of great importance in cancer diagnosis and treatment. In this paper, we propose a novel method for identifying differentially expressed genes based on tensor robust principal component analysis, which extends the matrix (...) method to the processing of multiway data. To identify differentially expressed genes, the plan is carried out as follows. First, multiview data containing cancer gene expression data from different sources are prepared. Second, the original tensor is decomposed into a sum of a low-rank tensor and a sparse tensor using TRPCA. Third, the differentially expressed genes are considered to be sparse perturbed signals and then identified based on the sparse tensor. Fourth, the differentially expressed genes are evaluated using Gene Ontology and Gene Cards tools. The validity of the TRPCA method was tested using two sets of multiview data. The experimental results showed that our method is superior to the representative methods in efficiency and accuracy aspects. (shrink)

The explosion of multiomics data poses new challenges to existing data mining methods. Joint analysis of multiomics data can make the best of the complementary information that is provided by different types of data. Therefore, they can more accurately explore the biological mechanism of diseases. In this article, two forms of joint nonnegative matrix factorization based on the sparse and graph Laplacian regularization method are proposed. In the method, the graph regularization constraint can preserve the (...) local geometric structure of data. L 2,1 -norm regularization can enhance the sparsity among the rows and remove redundant features in the data. First, SG-jNMF1 projects multiomics data into a common subspace and applies the multiomics fusion characteristic matrix to mine the important information closely related to diseases. Second, multiomics data of the same disease are mapped into the common sample space by SG-jNMF2, and the cluster structures are detected clearly. Experimental results show that SG-jNMF can achieve significant improvement in sample clustering compared with existing joint analysis frameworks. SG-jNMF also effectively integrates multiomics data to identify co-differentially expressed genes. SG-jNMF provides an efficient integrative analysis method for mining the biological information hidden in heterogeneous multiomics data. (shrink)

DNA microarrays are perfectly suited for comparing gene expression in different populations of cells. An important application of microarray techniques is identifying genes which are activated by a particular drug of interest. This process will allow biologists to identify therapies targeted to particular diseases, and, eventually, to gain more knowledge about the biological processes in organisms. Such an application is described in this paper. It is focused on diabetes and obesity, which is a genetically heterogeneous disease, meaning that (...) multiple defective genes are responsible for the diseases. The paper is divided in three parts, each dealing with a different problem addressed to our study. First we validate the data from our microarray experiment. We identified significant systematic sources of variability which are potentially issues for other microarray datasets. Second, we applied multiple hypothesis testing to identify differentially expressed genes. We found a set of genes which appear to change in expression level over time in response to a drug treatment. Third, we tried to address the problem of identification of co-expressed genes using cluster analysis. This last problem is still under discussion. (shrink)

Cancer is fast becoming an alarming cause of human death. However, it has been reported that if the disease is detected at an early stage, diagnosed, treated appropriately, the patient has better chances of survival long life. Machine learning technique with feature-selection contributes greatly to the detecting of cancer, because an efficient feature-selection method can remove redundant features. In this paper, a Fuzzy Preference-Based Rough Set (FPRS) blended with Support Vector Machine (SVM) has been applied in order to predict cancer (...) biomarkers for biological and gene expression datasets. Biomarkers are determined by deploying three models of FPRS, namely, Fuzzy Upward Consistency (FUC), Fuzzy Downward Consistency (FLC), and Fuzzy Global Consistency (FGC). The efficiency of the three models with SVM on five datasets is exhibited, and the biomarkers that have been identified from FUC models have been reported. (shrink)

The power of the application of bioinformatics across multiple publicly available transcriptomic data sets was explored. Using 19 human and mouse circadian transcriptomic data sets, we found that NR1D1 and NR1D2 which encode heme‐responsive nuclear receptors are the most rhythmic transcripts across sleep conditions and tissues suggesting that they are at the core of circadian rhythm generation. Analyzes of human transcriptomic data show that a core set of transcripts related to processes including immune function, glucocorticoid signalling, and (...) lipid metabolism is rhythmically expressed independently of the sleep‐wake cycle. We also identify key transcripts associated with transcription and translation that are disrupted by sleep manipulations, and through network analysis identify putative mechanisms underlying the adverse health outcomes associated with sleep disruption, such as diabetes and cancer. Comparative bioinformatics applied to existing and future data sets will be a powerful tool for the identification of core circadian‐ and sleep‐dependent molecules. (shrink)

Measuring gene expression on a global scale has been one of the vexing problems of cell biology. Velculescu et al.(1) recently proposed a system for identifying gene expression levels based on very short sequence tags – about nine base pairs – located at a specific site within a gene transcript. By coupling the strategy to current automated sequencing machines and the large expressed sequence tag databases, it should be possible to follow changes in gene (...) expression for large numbers of genes economically and accurately. (shrink)

Advances in biochemistry, chemistry and engineering have enabled the development of a new gene expression assay. This ‘chip‐based’ approach utilizes microscopic arrays of cDNAs printed on glass as high‐density hybridization targets. Fluorescent probe mixtures derived from total cellular messenger RNA (mRNA) hybridize to cognate elements on the array, allowing accurate measurement of the expression of the corresponding genes. Array densities of >1,000 cDNAs per cm2 enable quantitative expression monitoring of a large number of genes in a (...) single hybridization. A two‐color fluorescence detection scheme allows rapid and simultaneous differential expression analysis of independent biological samples. Mass‐produced microarrays provide a new tool for genome expression analysis that may revolutionize genetic dissection, drug discovery and human disease diagnostics. (shrink)

We analyzed the expressivity of recombinant proteins by using data mining methods. The expression technique of recombinant protein is a key step towards elucidating the functions of genes discovered through genomic sequence projects. We have studied the productive efficiency of recombinant proteins in fission yeast, Schizosaccharomyces pombe, by mining the expression results. We gathered 57 proteins whose expression levels were known roughly in the host. Correlation analysis, principal component analysis and decision tree analysis (...) were applied to these expression data. Analysis featuring codon usage and amino acid composition clarified that the amino acid composition affected to the expression levels of a recombinant protein strongly than the effect of codon usage. Furthermore, analysis of amino acid composition showed that protein solubility and the metabolism cost of amino acids correlated with a protein expressivity. Codon usage was often interesting in the field of recombinant expressions. However, our analysis found the weak correlation codon features with expressivities. These results indicated that ready-made indices of codon bias were irrelevant ones for modeling the expressivities of recombinant proteins. Our data driven approach was an easy and powerful method to improve recombinant protein expression, and this approach should be concentrated attention with the huge amount of expression data accumulating through the post-genome era. (shrink)

Matrices that cannot be handled using conventional clustering, regression or classification methods are often found in every big data research area. In particular, datasets with thousands or millions of rows and less than a hundred columns regularly appear in biological so-called omic problems. The effectiveness of conventional data analysis approaches is hampered by this matrix structure, which necessitates some means of reduction. An evolutionary method called PreCLAS is presented in this article. Its main objective is to find (...) a submatrix with fewer rows that exhibits some group structure. Three stages of experiments were performed. First, a benchmark dataset was used to assess the correct functionality of the method for clustering purposes. Then, a microarray gene expression data matrix was used to analyze the method’s performance in a simple classification scenario, where differential expression was carried out. Finally, several classification methods were compared in terms of classification accuracy using an RNA-seq gene expression dataset. Experiments showed that the new evolutionary technique significantly reduces the number of rows in the matrix and intelligently performs unsupervised row selection, improving classification and clustering methods. (shrink)

The Affymetrix GeneChip is a popular microarray platform for genome‐wide expression profiling and has been widely used in functional genomics especially in the classification of cancers. Due to the updating of genome data, much of the genome information with which the chips were designed is out‐of‐date and it has been reported that many of the genes/transcripts on the chips differ from their original definition when mapping the probes to the new genome information. Dai et al. have reported that (...) the updated definition can cause as much as 30–50% discrepancy in the genes selected as differentially expressed on a heart tissue expression profiling dataset. Understanding the nature of this difference is therefore very important for the utilization of the data. In this work, with a large cancer dataset as an example, we compared two major definitions and investigated their effects on classification, clustering, discovery of differentially expressed genes and gene‐set‐based analysis. Results show that the two definitions agree well on clustering and classification results but genes and gene sets discovered as differentially expressed or enriched can be very different. Discoveries based on the Affymetrix definition can cover most of those based on the new definition, but tend to have more false positives. BioEssays 28: 739–746, 2006. © 2006 Wiley Periodicals, Inc. (shrink)

This report describes the rationale, approaches, organization, and resource development leading to a large-scale deletion bin map of the hexaploid wheat genome. Accompanying reports in this issue detail results from chromosome bin-mapping of expressed sequence tags representing genes onto the seven homoeologous chromosome groups and a global analysis of the entire mapped wheat EST data set. Among the resources developed were the first extensive public wheat EST collection. Described are protocols for sequencing, sequence processing, EST nomenclature, and the (...) assembly of ESTs into contigs. These contigs plus singletons were used for selection of distinct sequence motif unigenes. Selected ESTs were rearrayed, validated by 5′ and 3′ sequencing, and amplified for probing a series of wheat aneuploid and deletion stocks. Images and data for all Southern hybridizations were deposited in databases and were used by the coordinators for each of the seven homoeologous chromosome groups to validate the mapping results. Results from this project have established the foundation for future developments in wheat genomics. (shrink)

The precocious induction in vivo and in culture of insect and amphibian metamorphosis by exogenous ecdysteroids and thyroid hormones, and its retardation or inhibition by juvenile hormone and prolactin, respectively, has allowed the analysis of such diverse processes of post‐embryonic development as morphogenesis, tissue remodelling, functional reorganization, and programmed cell death. Metamorphosis in vertebrates also shares many similarities with mammalian development in the late foetal and perinatal period. This review describes the regulation of expression of some of the (...) ‘adult’ gene products during metamorphosis in invertebrates and vertebrates. Recent studies on metamorphosis have revealed the important role played by auto‐induction of hormone receptor genes, based on which a model will be presented to explain the activation of ‘downstream’ genes which give rise to the adult phenotype. It will also be argued that metamorphosis is an ideal model for analyzing some of the major mechanisms governing post‐embryonic development. (shrink)

Through their transcript products genes regulate the rates at which an immense variety of transcripts and subsequent proteins occur. Understanding the mechanisms that determine which genes are expressed, and when they are expressed, is one of the keys to genetic manipulation for many purposes, including the development of new treatments for disease. Viewing each gene in a genome as a distinct variable that is either on or off, or more realistically as a continuous variable, the values of some of (...) these variables influence the values of others through the regulatory proteins they express, including, of course, the possibility that the rate of expression of a gene at one time may, in various circumstances, influence the rate of expression of that same gene at a later time. If we imagine an arrow drawn from each gene expression variable at a given time to a gene variable whose expression it influences a short while after, the result is a network, technically a directed acyclic graph. For example, the DAG in Figure 1 is a representation of a system in which the expression level of gene G1 at time 1 ) causes the expression level of G2, which in turn causes the expression level of G3. The arrows in Figure 1 which do not have a variable at their tails are “error terms” which represent all of the causes of a variable other than the ones explicitly represented in the DAG. The DAG describes more than associations—it describes causal connections among gene expression rates. A shock to a cell—by mutation, heating, chemical treatment, etc. may alter the DAG describing the relations among gene expressions, for example by activating a gene that was otherwise not expressed, producing a cascade of new expression effects. Although “knockout” experiments can reveal some of the underlying causal network of gene expression levels, unless guided by information from other sources, such experiments are limited in how much of the network structure they can reveal, due to the sheer number of possible combinations of experimental manipulations of genes necessary to reveal the complete causal network. Recent developments have made it possible to compare quantitatively the expression of tens of thousands of genes in cells from different sources in a single experiment, and to trace gene expression over time in thousands of genes simultaneously. cDNA microarrays are already producing extensive data, much of it available on the web. Thus there are calls for analytic software that can be applied to microarray and other data to help infer regulatory networks. In this paper we will review current techniques that are available for searching for the causal relations between variables, describe algorithmic and data gathering obstacles to applying these techniques to gene expression levels, and describe the prospects for overcoming these obstacles. (shrink)

The transcriptional profile of the entire Caulobacter crescentus genome over a synchronous cell cycle was recently described.(1) The analysis reveals a stunning 553 cell-cycle-regulated genes or orfs, nearly 19% of the genome, including putative functions in virtually all biological activities. Over a quarter of these genes/orfs respond to the Caulobacter master regulator, CtrA, most of them apparently indirectly. The analysis confirms and extends earlier observations showing that many proteins involved in cell cycle functions are expressed at the cell (...) age when they are needed. Conversely, the data suggest that proteins specifically expressed at a particular age may be involved in a process taking place then. BioEssays 23:563–565, 2001. © 2001 John Wiley & Sons, Inc. (shrink)

Hidden among the myriad nucleotide variants that constitute each species' gene pool are a few variants that contribute to phenotypic variation. Many of these differences that make a difference are non‐coding cis‐regulatory variants, which, unlike coding variants, can only be identified through laborious experimental analysis. Recently, Cowles et al.1 described a screening method that does an end‐run around this problem by searching for genes whose cis regulation varies without having to find the polymorphic nucleotides that influence transcription. While (...) we will continue to require a diverse arsenal of experimental methods, this versatile method will speed the identification of functional genetic variation. BioEssays 25:421–424, 2003. © 2003 Wiley Periodicals, Inc. (shrink)

Auxin, a class of plant hormones which affects a wide array of growth and developmental processes including cell elongation and cell division, alters gene expression in a very rapid, selective, and dramatic way. The relative level of some mRNAs decreases several fold, while that of other mRNAs increases many fold. These changes are mediated, at least in some cases, by very fast (within 5–10 min) modulation by auxin of transcription as measured by run‐off transcription assays using nuclei isolated (...) from control and auxin‐treated tissues. Rapid turnover of mRNAs following auxin treatment also contributes to large changes in steady state concentration in some cases. The data are suggestive of multiple and complex mechanisms of regulation of expression of those genes which have been studied, using cloned cDNAs for direct quantitation of mRNA steady state levels and relative transcription rates. While there is no definitive evidence that auxin‐regulated gene expression mediates any of the growth responses effected by auxin, several lines of evidence are supportive of a very close relationship between these processes. The working hypothesis is that there is a causal relationship between the effects of auxin on gene expression and at least some of the physiological and growth responses to auxin. (shrink)

RNA polymerase II (RNAP II) non‐coding transcription is now known to cover almost the entire eukaryotic genome, a phenomenon referred to as pervasive transcription. As a consequence, regions previously thought to be non‐transcribed are subject to the passage of RNAP II and its associated proteins for histone modification. This is the case for the nucleosome‐depleted regions (NDRs), which provide key sites of entry into the chromatin for proteins required for the initiation of coding gene transcription and DNA replication. In (...) this review, recent data on the effects of pervasive transcription through NDRs are summarized and a model is proposed to explain how RNAP II‐driven transcription is able to modify the nucleosomes flanking the NDRs, leading to nucleosome repositioning and NDR closure. Even though much of the mechanistic detail underlying these events remains to be elucidated, such a model provides a basis to explain how non‐coding transcription through NDRs can regulate the initiation of coding gene expression and DNA replication. (shrink)

Emerging evidence suggests that DNA topology plays an instructive role in cell fate control through regulation of gene expression. Transcription produces torsional stress, and the resultant supercoiling of the DNA molecule generates an array of secondary structures. In turn, local DNA architecture is harnessed by the cell, acting within sensory feedback mechanisms to mediate transcriptional output. MYC is a potent oncogene, which is upregulated in the majority of cancers; thus numerous studies have focused on detailed understanding of its (...) regulation. Dissection of regulatory regions within the MYC promoter provided the first hint that intimate feedback between DNA topology and associated DNA remodeling proteins is critical for moderating transcription. As evidence of such regulation is also found in the context of many other genes, here we expand on the prototypical example of the MYC promoter, and also explore DNA architecture in a genome-wide context as a global mechanism of transcriptional control. Torsional stress, and supercoiling generated by transcription, shape the topology of DNA. Furthermore, the resultant secondary DNA structures and their interacting partners provide feedback to regulate gene expression. Emerging evidence suggests these mechanisms, identified through analysis of the MYC promoter, are applicable genome-wide. (shrink)

Skin is one of the most thoroughly studied epithelia and can be used as a model for transcriptional control of epithelial differentiation. In particular, the stages of epidermal development and differentiation from a simple epithelium are well characterized. Temporal gene expression during development can be used to assign roles for transcription factors in epidermal differentiation. Approaches to understanding transcriptional regulation in epidermis include extensive promoter analysis and expression studies, in some cases coupled to functional studies. This (...) work has not produced any consensus about the importance of any particular factor or class of factors in epidermal specification. There is, as yet, nothing similar to the myo D family of tissue‐specific and cell‐type determining factors in epidermis. These studies, however, have revealed much about control of the differentiation process in epidermis. Most recently, there has been a suggestion that epithelial transcription can be influenced directly by the status of the adhesion complexes at the cell surface, providing a direct link between one of the distinguishing features of the epithelial state and gene transcription. (shrink)

This paper addresses the issue of the stability of lists of genes identified as differentially expressed in microarray experiments. The similarities be- tween gene rankings yielded by various gene selection methods performed with resampled datasets were assessed. The mean percentage of overlapping genes for two rankings varied from 10 to 90% depending on the applied gene selection method and the size of the list. The assessment of the stability of obtained gene rankings seems to be relevant (...) in the analysis of microarray data. (shrink)

We review a recent paper in Genome Research by Guantes et al. showing that nuclear gene expression is influenced by the bioenergetic status of the mitochondria. The amount of energy that mitochondria make available for gene expression varies considerably. It depends on: the energetic demands of the tissue; the mitochondrial DNA (mtDNA) mutant load; the number of mitochondria; stressors present in the cell. Hence, when failing mitochondria place the cell in energy crisis there are major effects (...) on gene expression affecting the risk of degenerative diseases, cancer and ageing. In 2015 the UK parliament approved a change in the regulation of IVF techniques, allowing “Mitochondrial replacement therapy” to become a reproductive choice for women at risk of transmitting mitochondrial disease to their children. This is the first time that this technique will be available. Therefore understanding the interaction between mitochondria and the nucleus has never been more important. (shrink)

The nuclear envelope shapes the functional organization of the nucleus. Increasing evidence indicates that one of its main components, the nuclear lamina, dynamically interacts with the genome, including the promoter region of specific genes. This seems to occur in a manner that accords developmental significance to these interactions. This essay addresses key issues raised by recent data on the association of nuclear lamins with the genome. We discuss how lamins interact with large chromatin domains and with spatially restricted regions (...) on gene promoters. We address the relationship between these interactions, chromatin modifications and gene expression outcomes. Lamin‐genome contacts are redistributed after cell division and during stem cell differentiation, with evidence of lineage specificity. Thus, we also speculate on a developmental role of lamin interactions with specific genes. Finally, we highlight how concepts arising from this recent work lay the foundations of future challenges and investigations. (shrink)

The apolipoprotein E gene plays an important role in the pathogenesis of Alzheimer's disease , and amyloid plaque comprised mostly of the amyloid-beta peptide ) is one of the major hallmarks of AD. However, the relationship between these two important molecules is poorly understood. We examined how A treatment affects APOE expression in cultured cells and tested the role of the transcription factor NF-B in APOE gene regulation. To delineate NF-B's role, we have characterized a 1098 nucleotide (...) segment containing the 5'-flanking region of the human APOE gene . Sequence analysis of this region suggests the presence of two potential NF-B elements. To demonstrate promoter activity, the region was cloned upstream of a promoterless luciferase gene. This segment was able to drive expression of luciferase in transient transfections of human fetal glial cells. Promoter activity was stimulated twofold by A treatment. Pretreatment with double-stranded DNA decoy oligonucleotides against NF-B reduced A stimulation. Deletion and mutagenetic analyses demonstrated that the distal NF-B element was functional and showed a strong DNA-protein complex band in gel shift analysis, similar to that from control NF-B consensus element. An anti-inflammatory and anti-NF-B drug, sodium salicylate, significantly blocked A-induced APOE promoter function. Our data provide evidence that upregulation of APOE by A in astroglial cells is mediated by an NF-B-element present in the 5'-flanking region of the APOE gene. (shrink)

The multifunctional zinc‐finger protein CCCTC‐binding factor (CTCF) is a very strong candidate for the role of coordinating the expression level of coding sequences with their three‐dimensional position in the nucleus, apparently responding to a “code” in the DNA itself. Dynamic interactions between chromatin fibers in the context of nuclear architecture have been implicated in various aspects of genome functions. However, the molecular basis of these interactions still remains elusive and is a subject of intense debate. Here we discuss the (...) nature of CTCF‐DNA interactions, the CTCF‐binding specificity to its binding sites and the relationship between CTCF and chromatin, and we examine data linking CTCF with gene regulation in the three‐dimensional nuclear space. We discuss why these features render CTCF a very strong candidate for the role and propose a unifying model, the “CTCF code,” explaining the mechanistic basis of how the information encrypted in DNA may be interpreted by CTCF into diverse nuclear functions. (shrink)

Honeybees display a fascinating social behavior. The structural basis for this behavior, which made the bee a model organism for the study of communication, learning and memory formation, is the tiny insect brain. Neurons of the brain communicate via messenger molecules. Among these molecules, neuropeptides represent the structurally most‐diverse group and occupy a high hierarchic position in the modulation of behavior. A recent analysis of the honeybee genome revealed a considerable number of predicted (200) and confirmed (100) neuropeptides in (...) this insect.1 Is this quantity merely the result of advanced mass spectrometric techniques and bioinformatic tools or does it reflect the expression of more of these important messenger molecules, more than known from other insects studied so far? Our analysis of the data suggests that the social behavior is by no means correlated with a specific increase in the number of neuropeptides. Indeed, the honeybee genome is likely to contain fewer neuropeptide genes, neuropeptide paralogues and neuropeptide receptor genes than the solitary fruitfly Drosophila. BioEssays 29:416–421, 2007. © 2007 Wiley Periodicals, Inc. (shrink)

© The Author 2016. Published by Oxford University Press on behalf of Japanese Society of Plant Physiologists. All rights reserved.Cell walls of grasses, including cereal crops and biofuel grasses, comprise the majority of plant biomass and intimately influence plant growth, development and physiology. However, the functions of many cell wall synthesis genes, and the relationships among and the functions of cell wall components remain obscure. To better understand the patterns of cell wall accumulation and identify genes that act in grass (...) cell wall biosynthesis, we characterized 30 samples from aerial organs of rice at 10 developmental time points, 3-100 d post-germination. Within these samples, we measured 15 cell wall chemical components, enzymatic digestibility and 18 cell wall polysaccharide epitopes/ligands. We also used quantitative reverse transcription-PCR to measure expression of 50 glycosyltransferases, 15 acyltransferases and eight phenylpropanoid genes, many of which had previously been identified as being highly expressed in rice. Most cell wall components vary significantly during development, and correlations among them support current understanding of cell walls. We identified 92 significant correlations between cell wall components and gene expression and establish nine strong hypotheses for genes that synthesize xylans, mixed linkage glucan and pectin components. This work provides an extensive analysis of cell wall composition throughout rice development, identifies genes likely to synthesize grass cell walls, and provides a framework for development of genetically improved grasses for use in lignocellulosic biofuel production and agriculture. (shrink)

Honey bees are eusocial insects and the workers inform their nestmates of information regarding the location of food source using symbolic communication, called ‘dance communication’, that are based on their highly advanced learning abilities. Mushroom bodies (MBs), a higher-order center in the honey bee brain, comprise some subtypes/populations of interneurons termed Kenyon cells (KCs) that are distinguished by their cell body size and location in the MBs, as well as their gene expression profiles. Although the role of MBs (...) in learning ability has been studied extensively in the honey bee, the roles of each KC subtype and their evolution in hymenopteran insects remain mostly unknown. This mini-review describes recent progress in the analysis of gene/protein expression profiles and possible functions of KC subtypes/populations in the honey bee. Especially, the discovery of novel KC subtype/population, ‘middle-type KCs’ and ‘KC population expressing FoxP’, necessitated a redefinition of the KC subtype/population. Analysis of the effects of inhibiting gene function in a KC subtype-preferential manner revealed the function of the gene product as well as of the subtype where it is expressed. Genes expressed in a KC subtype/population-preferential manner can be used to trace the differentiation of KC subtypes during the honey bee ontogeny and the possible evolution of KC subtypes in hymenopteran insects. Current findings suggest that the three KC subtypes are unique characteristics to the aculeate hymenopteran insects. Finally, recent application of genome editing for the study of KC subtype functions in the honey bee is described. Genes expressed in a KC subtype-preferential manner can be good candidate target genes for genome editing, because they are likely related to highly advanced brain functions and some of them are dispensable for normal development and sexual maturation in honey bees. (shrink)

Many common human traits are believed to be a composite reflection of multiple genetic and non‐genetic factors and the genetic contribution is consequently often difficult to characterise. Recent advances suggest that subtle variation in the regulation of gene expression may contribute to complex human traits. In two reports,1,2 Cheung and colleagues scale up human genetics analysis to an impressive level in a genome‐wide search for the regulators of gene expression. They perform linkage analysis on (...) expression profiles for over 3,500 genes and then employ the HapMap resource3 to take positive findings through to association studies at the genome‐wide level. This work gives new insights into the complexities of gene regulation and the plausibility of genome‐wide study design. BioEssays 28: 968–972, 2006. © 2006 Wiley Periodicals, Inc. (shrink)

Mechanisms involved in the regulation of development and its genetic control are receiving ever‐increasing attention in studies of mammalian developmental genetics. The potential success of such studies is strongly enhanced by the availability of suitable systems of analysis. Such a system was identified in a series of radiation‐induced chromosomal deletions at and around the albino (c) locus of the mouse associated with cell type‐specific effects on liver differentiation. Their detailed study has aided the analysis of possible machanisms of (...) cell type‐specific gene expression. As summarized in this review, the experimental results strongly suggest that specific trans‐acting developmental regulatory genes are concerned with the differentiation of hormone‐inducible expression of a cluster of hepatocyte specific structural genes mapping in different parts of the genome. (shrink)

A similarity index allowing comparisons of human populations has been defined as the common “Percentage of Isoactive Genes” or PIG, which can be calculated from any gene frequency distribution characterizing two populations. The complement to one of this value has been proved to be a distance, a measure which can be used in most techniques of cluster analysis as well as in usual representations of multivariated data (dendrograms, etc...). Furthermore, the formula can be generalized to a set (...) of populations. From a biological point of vue, PIG values are particularly meaningful, whereas other previously defined indices which tend to measure similarity or difference between populations neither have such an advantage, nor can they be expressed by a single and clear number like a percentage. Moreover,comparisons using PIG indices depend at first on the fluctuations of the most frequent genes of a distribution; on the other hand, different measures principally reflect the variations of low frequency genes, which unfortunately are nearly always poorly estimated, due to weak samples of populations.Interestingly, PIG values can be applied to any frequency distribution of any kind of objects. They can also extend to a whole set of distributions by using a mean value. When applying these measures to a series of polymorphic genetical systems such as ABO, Rhesus, MNSs, Gm and HLA, one can account for the variability or the homogeneity particular to the different human groups, with simple and objective criteria. (shrink)

In recent years, sequencing technologies have enabled the identification of a wide range of non-coding RNAs (ncRNAs). Unfortunately, annotation and integration of ncRNA data has lagged behind their identification. Given the large quantity of information being obtained in this area, there emerges an urgent need to integrate what is being discovered by a broad range of relevant communities. To this end, the Non-Coding RNA Ontology (NCRO) is being developed to provide a systematically structured and precisely defined controlled vocabulary for (...) the domain of ncRNAs, thereby facilitating the discovery, curation, analysis, exchange, and reasoning of data about structures of ncRNAs, their molecular and cellular functions, and their impacts upon phenotypes. The goal of NCRO is to serve as a common resource for annotations of diverse research in a way that will significantly enhance integrative and comparative analysis of the myriad resources currently housed in disparate sources. It is our belief that the NCRO ontology can perform an important role in the comprehensive unification of ncRNA biology and, indeed, fill a critical gap in both the Open Biological and Biomedical Ontologies (OBO) Library and the National Center for Biomedical Ontology (NCBO) BioPortal. Our initial focus is on the ontological representation of small regulatory ncRNAs, which we see as the first step in providing a resource for the annotation of data about all forms of ncRNAs. (shrink)

Background Population based genetics studies are dependent on large numbers of individuals in the pursuit of small effect sizes. Recruiting and consenting a large number of participants is both costly and time consuming. We explored whether an online consent process for large-scale genetics studies is acceptable for prospective participants using an example online genetics study. Methods We conducted semi-structured interviews with 42 members of the public stratified by age group, gender and newspaper readership (a measure of social status). Respondents were (...) asked to use a website designed to recruit for a large-scale genetic study. After using the website a semi-structured interview was conducted to explore opinions and any issues they would have. Responses were analysed using thematic content analysis. Results The majority of respondents said they would take part in the research (32/42). Those who said they would decline to participate saw fewer benefits from the research, wanted more information and expressed a greater number of concerns about the study. Younger respondents had concerns over time commitment. Middle aged respondents were concerned about privacy and security. Older respondents were more altruistic in their motivation to participate. Common themes included trust in the authenticity of the website, security of personal data, curiosity about their own genetic profile, operational concerns and a desire for more information about the research. Conclusions Online consent to large-scale genetic studies is likely to be acceptable to the public. The online consent process must establish trust quickly and effectively by asserting authenticity and credentials, and provide access to a range of information to suit different information preferences. (shrink)

This study is the most comprehensive account to date of modern treatments of the love commandment. Gene Outka examines the literature on agape from Nygren's Agape and Eros in 1930. Both Roman Catholic and Protestant writings are considered, including those of D'Arcy, Niebuhr, Ramsey, Tillich, and above all, Karl Barth. The first seven chapters focus on the principal treatments in the theological literature as they relate to major topics in ethical theory. The last chapter explores further the basic normative (...) content of agape and discusses some of the most characteristic problems. "The book is in my judgment the best recent work in religious ethics. Outka brings together analytic moral philosophy and theological ethics, providing a masterly survey of views and issues arising in the past forty years.... I can think of few books of interest to scholars in both philosophy and theology, but Outka's is one. Unlike some scholars who are at home in continental theology, Outka is also at home in secular analytic philosophy; he brings them together in a mutually illuminating way."--Donald Evans "Outka has mastered this vast literature on love, and has brought a critical and clarifying analysis to bear upon it. This is a most important book on a most important subject, and brings the whole discussion into a new phase."--John Macquarrie "The first thing to be said about Outka's book quite simply is that it is excellent; in fact, it is probably the very best available book about contemporary Christian ethical theory."--The Humanities Association Review. (shrink)

In mice, dosage compensation of X‐linked gene expression is achieved through the inactivation of one of the two X‐chromosomes in XX female cells. The complex epigenetic process leading to X‐inactivation is largely controlled by Xist and Tsix, two non‐coding genes of opposing function. Xist RNA triggers X‐inactivation by coating the inactive X, while Tsix is critical for the designation of the active X‐chromosome through cis‐repression of Xist RNA accumulation. Recently, a plethora of trans‐acting factors and cis‐regulating elements have (...) been suggested to act as key regulators of either Xist, Tsix or both; these include ubiquitous factors such as Yy1 and Ctcf, developmental proteins such as Nanog, Oct4 and Sox2, and X‐linked regulators such as Rnf12. In this paper we summarise recent advances in our knowledge of the regulation of Xist and Tsix in embryonic stem (ES) and differentiating ES cells. (shrink)

While self-report data is a staple of modern psychological studies, they rely on participants accurately self-reporting. Two constructs that impede accurate results are insufficient effort responding and response styles. These constructs share conceptual underpinnings and both utilized to reduce cognitive effort when responding to self-report scales. Little research has extensively explored the relationship of the two constructs. The current study explored the relationship of the two constructs across even-point and odd-point scales, as well as before and after data (...) cleaning procedures. We utilized IRTrees, a statistical method for modeling response styles, to examine the relationship between IER and response styles. To capture the wide range of IER metrics available, we employed several forms of IER assessment in our analyses and generated IER factors based on the type of IER being detected. Our results indicated an overall modest relationship between IER and response styles, which varied depending on the type of IER metric being considered or type of scale being evaluated. As expected, data cleaning also changed the relationships of some of the variables. We posit the difference between the constructs may be the degree of cognitive effort participants are willing to expend. Future research and applications are discussed. (shrink)

Musical performance is a multimodal experience, for performers and listeners alike. This paper reports on a pilot study which constitutes the first step toward a comprehensive approach to the experience of music as performed. We aim at bridging the gap between qualitative and quantitative approaches, by combining methods for data collection. The purpose is to build a data corpus containing multimodal measures linked to high-level subjective observations. This will allow for a systematic inclusion of the knowledge of music (...) professionals in an analytic framework, which synthesizes methods across established research disciplines. We outline the methods we are currently developing for the creation of a multimodal data corpus dedicated to the analysis and exploration of instrumental music performance from the perspective of embodied music cognition. This will enable the study of the multiple facets of instrumental music performance in great detail, as well as lead to the development of music creation techniques that take advantage of the cross-modal relationships and higher-level qualities emerging from the analysis of this multi-layered, multimodal corpus. The results of the pilot project suggest that qualitative analysis through stimulated recall is an efficient method for generating higher-level understandings of musical performance. Furthermore, the results indicate several directions for further development, regarding observational movement analysis, and computational analysis of coarticulation, chunking, and movement qualities in musical performance. We argue that the development of methods for combining qualitative and quantitative data are required to fully understand expressive musical performance, especially in a broader scenario in which arts, humanities, and science are increasingly entangled. The future work in the project will therefore entail an increasingly multimodal analysis, aiming to become as holistic as is music in performance. (shrink)

A number of social theorists have contended that the essence of historical analysis is the employment of ideal types to comprehend past goings-on. But, while acknowledging that the study of history through ideal types can yield genuine insight, we may still ask if it represents the full emancipation of historical understanding from other modes of conceiving the past. This paper follows Michael Oakeshott's work on the philosophy of history in arguing that explaining the historical past by means of ideal (...) types, even though offering a coherent and fruitful enterprise, nevertheless falls short of fully embodying the characteristics that differentiate historical understanding. -/- This dispute involves fundamental issues regarding the nature of the social sciences. Furthermore, I suggest that it is of more than purely theoretical interest, in that social theorists who have accepted the Weberian view of historical inquiry will tend to be unaware of the defects inherent in all attempts to capture the nature of past events in a net of generalizations, and thus may be lead to ignore the inherent partiality of the understanding of historical happenings provided by ideal typification. (shrink)

The advance of technology has influenced marketing in a number of ways that have ethical implications. Growth in use of the Internetand e-commerce has placed electronic “cookies,” spyware, spam, RFIDs, and data mining at the forefront of the ethical debate. Some marketers have minimized the significance of these trends. This overview paper examines these issues and introduces the two articles that follow. It is hoped that these entries will further the important “marketing and technology” ethical debate.

The advance of technology has influenced marketing in a number of ways that have ethical implications. Growth in use of the Internetand e-commerce has placed electronic “cookies,” spyware, spam, RFIDs, and data mining at the forefront of the ethical debate. Some marketers have minimized the significance of these trends. This overview paper examines these issues and introduces the two articles that follow. It is hoped that these entries will further the important “marketing and technology” ethical debate.

Research findings on addiction are contradictory. According to biographical records and widely used diagnostic manuals, addicts use drugs compulsively, meaning that drug use is out of control and independent of its aversive consequences. This account is supported by studies that show significant heritabilities for alcoholism and other addictions and by laboratory experiments in which repeated administration of addictive drugs caused changes in neural substrates associated with reward. Epidemiological and experimental data, however, show that the consequences of drug consumption can (...) significantly modify drug intake in addicts. The disease model can account for the compulsive features of addiction, but not occasions in which price and punishment reduced drug consumption in addicts. Conversely, learning models of addiction can account for the influence of price and punishment, but not compulsive drug taking. The occasion for this target article is that recent developments in behavioral choice theory resolve the apparent contradictions in the addiction literature. The basic argument includes the following four statements: First, repeated consumption of an addictive drug decreases its future value and the future value of competing activities. Second, the frequency of an activity is a function of its relative (not absolute) value. This implies that an activity that reduces the values of competing behaviors can increase in frequency even if its own value also declines. Third, a recent experiment (Heyman & Tanz 1995) shows that the effective reinforcement contingencies are relative to a frame of reference, and this frame of reference can change so as to favor optimal or suboptimal choice. Fourth, if the frame of reference is local, reinforcement contingencies will favor excessive drug use, but if the frame of reference is global, the reinforcement contingencies will favor controlled drug use. The transition from a global to a local frame of reference explains relapse and other compulsive features of addiction. (shrink)

The advance of technology has influenced marketing in a number of ways that have ethical implications. Growth in use of the Internetand e-commerce has placed electronic “cookies,” spyware, spam, RFIDs, and data mining at the forefront of the ethical debate. Some marketers have minimized the significance of these trends. This overview paper examines these issues and introduces the two articles that follow. It is hoped that these entries will further the important “marketing and technology” ethical debate.

Introduction of human plasma protein genes into the mouse genome to produce transgenic mice furnishes an in vivo model for correlating chromosomal DNA sequences with developmental and tissue‐specific expression. The liver produces an array of plasma proteins that circulate throughout the body contributing to homeostasis. Non‐hepatic tissue sites of synthesis have been identified where a local provision of plasma proteins in needed. Analysis of expression of human plasma protein genes in ageing transgenic mice appears especialy promising in (...) identifying DNA sequences that respond to environmental adversities such as inflammatory factors, hormonal changes and metal toxicity. The results indicate that human genes encoding and controlling liver plasma proteins serve as useful models for studying genetic regulation in the background of development and ageing. (shrink)