We argue that the most‐promising area of clinical application of microarrays in the foreseeable future is the diagnostics and monitoring of infectious diseases. Microarrays for the detection and characterization of human pathogens have already found their way into clinical practice in some countries. After discussing the persistent, yet often underestimated, importance of infectious diseases for public health, we consider the technologies that are best suited for the detection and clinical investigation of pathogens. Clinical application of microarray technologies for (...) the detection of mycobacteria, Bacillus anthracis, HIV, hepatitis and influenza viruses, and other major pathogens, as well as the analysis of their drug‐resistance patterns, illustrate our main thesis. BioEssays 30:673–682, 2008. © 2008 Wiley Periodicals, Inc. (shrink)

Detection of genetic aberrations in prenatal samples, obtained through amniocentesis or chorion villus biopsy, is increasingly performed using chromosomal microarray, a technique that can uncover both aneuploidies and copy number variants throughout the genome. Despite the obvious benefits of CMA, the decision on implementing the technology is complicated by ethical issues concerning variant interpretation and reporting. In Belgium, uniform guidelines were composed and a shared database for prenatal CMA findings was established. This Belgian approach sparks discussion: it is evidence-based, prevents (...) inconsistencies and avoids parental anxiety, but can be considered paternalistic. Here, we reflect on the cultural and moral bases of the Belgian reporting system of prenatally detected variants. (shrink)

Although DNA microarrays are now widely used in research settings, they have been slow to penetrate clinical practice in spite of their apparent advantages. This is due to the very different requirements for a clinical test in contrast to a research tool, and to a strict necessity for demonstrated clinical utility. There is a clear differentiation between two types of DNA array tests: “genomic” diagnostics, developed to ascertain the presence or absence of mutations, deletions or duplications, and for which (...) clinical evidence is already established, and tests using expression profiling for prognosis or predictive purposes, in which case the clinical correlate must be proven. Most array diagnostics currently used belong, understandably, to the “genomic” variety. It is to be expected that future improvements in tailored technology, as well as a logical trend towards measuring an ever‐increasing number of parameters, will ensure an important diagnostic role for DNA arrays in the coming decade. BioEssays 29:699–705, 2007. © 2007 Wiley Periodicals, Inc. (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)

In his highly regarded history of the rise of clinical trials in America, HarryMarks describes how their widespread adoption resulted largely fromthe efforts of ‘therapeutic reformers’ who sought to replace the individualexpertise of clinicians with the ‘science of controlled experiment’. Thetransition described by Marks resembles in many respects the transition fromthe ‘truth-to-nature’ objectivity of individual experts to a ‘mechanical’ formof objectivity portrayed by Daston and Galison. In particular,Marks details the passage from a regime of trust in expertise and experts to (...) aregime based on the mechanical generation of data, the elimination ofhuman judgement and the adoption of a ‘view from nowhere’ where individual and group idiosyncrasies are systematically suppressedthrough recourse to quantitative methods.[...]. (shrink)

In his highly regarded history of the rise of clinical trials in America, HarryMarks describes how their widespread adoption resulted largely fromthe efforts of ‘therapeutic reformers’ who sought to replace the individualexpertise of clinicians with the ‘science of controlled experiment’. Thetransition described by Marks resembles in many respects the transition fromthe ‘truth-to-nature’ objectivity of individual experts to a ‘mechanical’ formof objectivity portrayed by Daston and Galison. In particular,Marks details the passage from a regime of trust in expertise and experts to (...) aregime based on the mechanical generation of data, the elimination ofhuman judgement and the adoption of a ‘view from nowhere’ where individual and group idiosyncrasies are systematically suppressedthrough recourse to quantitative methods.[...]. (shrink)

Of the many proposals for inferring genetic regulatory structure from microarray measurements of mRNA transcript hybridization, several aim to estimate regulatory structure from the associations of gene expression levels measured in repeated samples. The repeated samples may be from a single experimental condition, or from several distinct experimental conditions; they may be “equilibrium” measurements or time series; the associations may be estimated by correlation coefficients or by conditional frequencies (for discretized measurements) or by some other statistic. This paper describes two (...) elementary statistical difficulties for all such procedures, no matter whether based on Bayesian updating, conditional independence testing, or other machine learning procedures such as simulated annealing or neural net pruning. One difficulty obtains if large numbers of cells are aggregated in a measurement of expression levels from a common population of cells; the other obtains if small numbers of cells are aggregated or if samples are separately aggregated over different populations of cells. (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)

Of the many proposals for inferring genetic regulatory structure from microarray measurements of mRNA transcript hybridization, several aim to estimate regulatory structure from the associations of gene expression levels measured in repeated samples. The repeated samples may be from a single experimental condition, or from several distinct experimental conditions; they may be “equilibrium” measurements or time series; the associations may be estimated by correlation coefficients or by conditional frequencies (for discretized measurements) or by some other statistic. This paper describes two (...) elementary statistical difficulties for all such procedures, no matter whether based on Bayesian updating, conditional independence testing, or other machine learning procedures such as simulated annealing or neural net pruning. One difficulty obtains if large numbers of cells are aggregated in a measurement of expression levels from a common population of cells; the other obtains if small numbers of cells are aggregated or if samples are separately aggregated over different populations of cells. (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)

Edwin Southern developed a blotting technique for DNA in 1973, thereby creating a staple of molecular biology laboratory procedures still used after several decades. It became a seminal technology for studying the structure of DNA. The story of the creation and dissemination of this technology, which was not patented and was freely distributed throughout the scientific community, stands as a case study in open science. The Southern blot was developed at a time when attitudes about commercial intrusion into health research (...) were beginning to change and the practical value of molecular genetics was becoming apparent to industry. Interest from industry in fundamental molecular biological techniques meant that scientists began to think about commercial uses of their work even in otherwise "basic" research. The unpatented Southern blot is contrasted with later patented technologies, particularly microarray methods, which were created in the same environment by many of the same people, but which followed significant changes to UK policies encouraging commercialization of academic research and a norm shift friendlier to such commercialization within academic molecular biology. Professor Southern's personal experience illuminates how the technologies evolved, and his views provide insight into how scientists' attitudes about commercialization have changed. (shrink)

We present evidence of a potentially serious source of error intrinsic to all spotted cDNA microarrays that use IMAGE clones of expressed sequence tags (ESTs). We found that a high proportion of these EST sequences contain 5V-end poly(dT) sequences that are remnants from the oligo(dT)-primed reverse transcription of polyadenylated mRNA templates used to generate EST cDNA for sequence clone libraries. Analysis of expression data from two single-dye cDNA microarray experiments showed that ESTs whose sequences contain repeats of consecutive 5V- (...) end dT residues appeared to be strongly coexpressed, while expression data of all other sequences exhibited no such pattern. Our analysis suggests that expression data from sequences containing 5V poly(dT) tracts are more likely to be due to systematic cross-hybridization of these poly(dT) tracts than to true mRNA coexpression. This indicates that existing data generated by cDNA microarrays containing IMAGE clone ESTs should be filtered to remove expression data containing significant 5V poly(dT) tracts. D 2003 Elsevier Inc. All rights reserved. (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 present evidence of a potentially serious source of error intrinsic to all spotted cDNA microarrays that use IMAGE clones of expressed sequence tags (ESTs). We found that a high proportion of these EST sequences contain 5V-end poly(dT) sequences that are remnants from the oligo(dT)-primed reverse transcription of polyadenylated mRNA templates used to generate EST cDNA for sequence clone libraries. Analysis of expression data from two single-dye cDNA microarray experiments showed that ESTs whose sequences contain repeats of consecutive 5V- (...) end dT residues appeared to be strongly coexpressed, while expression data of all other sequences exhibited no such pattern. Our analysis suggests that expression data from sequences containing 5V poly(dT) tracts are more likely to be due to systematic cross-hybridization of these poly(dT) tracts than to true mRNA coexpression. This indicates that existing data generated by cDNA microarrays containing IMAGE clone ESTs should be filtered to remove expression data containing significant 5V poly(dT) tracts. D 2003 Elsevier Inc. All rights reserved. (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)

After reviewing theoretical reasons for doubting that machine learning methods can accurately infer gene regulatory networks from microarray data, we test 10 algorithms on simulated data from the sea urchin network, and on microarray data for yeast compared with recent experimental determinations of the regulatory network in the same yeast species. Our results agree with the theoretical arguments: most algorithms are at chance for determining the existence of a regulatory connection between gene pairs, and the algorithms that perform better than (...) chance are nonetheless so errorprone as to be of little practical use in these applications. (shrink)

The use of genomic testing in pregnancy is increasing, giving rise to questions over how the information that is generated should be offered and returned in clinical practice. While these tests provide important information for prenatal decision-making, they can also generate information of uncertain significance. This paper critically examines three models for approaching the disclosure of variants of uncertain significance (VUS), which can arise from forms of genomic testing such as prenatal chromosomal microarray analysis (CMA). Contrary to prevailing arguments, we (...) argue that respect for reproductive autonomy does not justify adopting a model on which an offer to disclose VUS is a routine part of genetic counselling. Instead, we contend that a commitment both to solidarity between healthcare providers and pregnant women and to the acceptance of a novel principle of caution under normative uncertainty means that we should instead adopt a model of VUS disclosure that imposes a strong presumption against offering to disclose VUS. The upshot of this is that it should be standard practice to only offer to disclose VUS when this is requested by the woman undergoing CMA. We defend our position against claims that arise from an alleged right to such information and that a presumption against an offer will lead to inequity. (shrink)

The brain is an ever‐changing organ that encodes memories and directs behavior. Neuroanatomical studies have revealed structural plasticity of neural architecture, and advances in gene expression technology and epigenetics have demonstrated new mechanisms underlying the brain's dynamic nature. Stressful experiences challenge the plasticity of the brain, and prolonged exposure to environmental stress redefines the normative transcriptional profile of both neurons and glia, and can lead to the onset of mental illness. A more thorough understanding of normal and abnormal gene expression (...) is needed to define the diseased brain and improve current treatments for psychiatric disorders. The efforts to describe gene expression networks have been bolstered by microarray and RNA‐sequencing technologies. The heterogeneity of neural cell populations and their unique microenvironments, coupled with broad ranging interconnectivity, makes resolving this complexity exceedingly challenging and requires the combined efforts of single cell and systems level expression profiling to identify targets for therapeutic intervention. (shrink)

After a vertebrate dies, many of its organ systems, tissues, and cells remain functional while its body no longer works as a whole. We define this state as the “twilight of death” − the transition from a living body to a decomposed corpse. We claim that the study of the twilight of death is important to ethical, legal and medical science. We examined gene expression at the twilight of death in the zebrafish and mouse reaching the conclusion that apparently thousands (...) of transcripts significantly increase in abundance from life to several hours/days postmortem relative to live controls. Transcript dynamics of different genes provided “proof-of-principle” that models accurately predict an individual's elapsed-time-of-death. While many transcripts were associated with survival and stress compensation, others were associated with epigenetic factors, developmental control, and cancer. Future studies are needed to determine whether the high incidence of cancer in transplant recipients is due to the postmortem processes in donor organs. In organismal death, some organ systems, tissues and cells remain functional while the body no longer works as a whole. In the “twilight of death” − the transition from a living body to a decomposed corpse − thousands of gene transcripts increase in abundance relative to live controls. (shrink)

Prenatal screening pathways, as nowadays offered in most Western countries consist of similar tests. First, a risk-assessment test for major aneuploides is offered to pregnant women. In case of an increased risk, invasive diagnostic tests, entailing a miscarriage risk, are offered. For decades, only conventional karyotyping was used for final diagnosis. Moreover, several foetal ultrasound scans are offered to detect major congenital anomalies, but the same scans also provide relevant information for optimal support of the pregnancy and the delivery. Recent (...) developments in prenatal screening include the application of microarrays that allow for identifying a much broader range of abnomalities than karyotyping, and non-invasive prenatal testing that enables reducing the number of invasive tests for aneuploidies considerably. In the future, broad NIPT may become possible and affordable. This article will briefly address the ethical issues raised by these technological developments. First, a safe NIPT may lead to routinisation and as such challenge the central issue of informed consent and the aim of prenatal screening: to offer opportunity for autonomous reproductive choice. Widening the scope of prenatal screening also raises the question to what extent ‘reproductive autonomy’ is meant to expand. Finally, if the same test is used for two different aims, namely detection of foetal anomalies and pregnancy-related problems, non-directive counselling can no longer be taken as a standard. Our broad outline of the ethical issues is meant as an introduction into the more detailed ethical discussions about prenatal screening in the other articles of this special issue. (shrink)

Prenatal screening pathways, as nowadays offered in most Western countries consist of similar tests. First, a risk‐assessment test for major aneuploides is offered to pregnant women. In case of an increased risk, invasive diagnostic tests, entailing a miscarriage risk, are offered. For decades, only conventional karyotyping was used for final diagnosis. Moreover, several foetal ultrasound scans are offered to detect major congenital anomalies, but the same scans also provide relevant information for optimal support of the pregnancy and the delivery.Recent developments (...) in prenatal screening include the application of microarrays that allow for identifying a much broader range of abnomalities than karyotyping, and non‐invasive prenatal testing (NIPT) that enables reducing the number of invasive tests for aneuploidies considerably. In the future, broad NIPT may become possible and affordable.This article will briefly address the ethical issues raised by these technological developments. First, a safe NIPT may lead to routinisation and as such challenge the central issue of informed consent and the aim of prenatal screening: to offer opportunity for autonomous reproductive choice. Widening the scope of prenatal screening also raises the question to what extent ‘reproductive autonomy’ is meant to expand. Finally, if the same test is used for two different aims, namely detection of foetal anomalies and pregnancy‐related problems, non‐directive counselling can no longer be taken as a standard. Our broad outline of the ethical issues is meant as an introduction into the more detailed ethical discussions about prenatal screening in the other articles of this special issue. (shrink)

Statistics play a critical role in biological and clinical research. However, most reports of scientific results in the published literature make it difficult for the reader to reproduce the statistical analyses performed in achieving those results because they provide inadequate documentation of the statistical tests and algorithms applied. The Ontology of Biological and Clinical Statistics (OBCS) is put forward here as a step towards solving this problem. Terms in OBCS, including ‘data collection’, ‘data transformation in statistics’, ‘data visualization’, ‘statistical data (...) analysis’, and ‘drawing a conclusion based on data’, cover the major types of statistical processes used in basic biological research and clinical outcome studies. OBCS is aligned with the Basic Formal Ontology (BFO) and extends the Ontology of Biomedical Investigations (OBI), an OBO (Open Biological and Biomedical Ontologies) Foundry ontology supported by over 20 research communities. We discuss two examples illustrating how the ontology is being applied. In the first (biological) use case, we describe how OBCS was applied to represent the high throughput microarray data analysis of immunological transcriptional profiles in human subjects vaccinated with an influenza vaccine. In the second (clinical outcomes) use case, we applied OBCS to represent the processing of electronic health care data to determine the associations between hospital staffing levels and patient mortality. Our case studies were designed to show how OBCS can be used for the consistent representation of statistical analysis pipelines under two different research paradigms. By representing statistics-related terms and their relations in a rigorous fashion, OBCS facilitates standard data analysis and integration, and supports reproducible biological and clinical research. (shrink)

Technology has outpaced the capacity of researchers performing research on human participants to interpret all data generated and handle those data responsibly. This poses a critical challenge to existing rules governing human subjects research. The technologies used in research to generate images, scans, and data can now produce so much information that there is significant potential for incidental findings, findings generated in the course of research but beyond the aims of the study. Neuroimaging scans may visualize the entire brain and (...) even the entire head; computed tomography colonography research may visualize the entire torso, from the base of the lungs to the pubis; genetics studies may reveal “extra” and sometimes unwanted information about the family, such as misattributed paternity and undisclosed adoption; and genomic microarray research increasingly involves whole-genome analysis revealing an individual’s complete genotype, with enormous potential for uncovering unexpected information about an individual’s genetics and risks of developing future conditions. (shrink)

Long noncoding RNAs have been described in cell lines and various whole tissues, but lncRNA analysis of development in vivo is limited. Here, we comprehensively analyze lncRNA expression for the adult mouse subventricular zone neural stem cell lineage. We utilize complementary genome-wide techniques including RNA-seq, RNA CaptureSeq, and ChIP-seq to associate specific lncRNAs with neural cell types, developmental processes, and human disease states. By integrating data from chromatin state maps, custom microarrays, and FACS purification of the subventricular zone lineage, (...) we stringently identify lncRNAs with potential roles in adult neurogenesis. shRNA-mediated knockdown of two such lncRNAs, Six3os and Dlx1as, indicate roles for lncRNAs in the glial-neuronal lineage specification of multipotent adult stem cells. Our data and workflow thus provide a uniquely coherent in vivo lncRNA analysis and form the foundation of a user-friendly online resource for the study of lncRNAs in development and disease. © 2013 Elsevier Inc. (shrink)

Nonsense‐mediated RNA decay (NMD) is an evolutionary conserved system of RNA surveillance that detects and degrades RNA transcripts containing nonsense mutations. Given that these mutations arise at a relatively low frequency, are there any as yet unknown substrates of NMD in a wild‐type cell? With this question in mind, Mendell et al.1 have used a microarray assay to identify those human genes under NMD regulation. Their results show that, in human cells, NMD regulates hundreds of physiologic transcripts and not just (...) those containing nonsense mutations. Among the NMD targets are a number of non‐functional RNAs expressed from vestigial sequences derived from retroviral and transposable elements. These findings support the notion that NMD is a high profile post‐transcriptional mechanism micromanaging the activity of multiple gene batteries and suppressing the expression of genetic remnants. BioEssays 27:463–466, 2005. © 2005 Wiley Periodicals, Inc. (shrink)

The human genome contains about 30,000 genes, each creating several transcripts per gene. Transcript structures and expression are studied by high‐throughput transcriptomic techniques using microarrays. Generally, transcripts are not directly operating molecules, but are translated into functional proteins, post‐translationally modified by proteolysis, glycosylation, phosphorylation, etc., sometimes with great functional impact. Proteins need to be analyzed by proteomic techniques, less suited for high‐throughput. Two‐dimensional polyacrylamide gel electrophoresis (2D‐PAGE), separating thousands of proteins has developed slowly over the past quarter of a (...) century. This technique is now quite reproducible and suitable for differential proteomics, comparing normal and diseased cells/tissues revealing differentially regulated proteins. 2D‐PAGE is combined with protein‐identification methods, currently mass spectrometry (MS), which has been significantly improved over the last decade. Other proteomic techniques studying protein–protein interactions are now either established or still being developed, such as peptide or protein arrays, phage display, and the yeast two‐hybrid system. The strengths and weaknesses of these techniques are discussed. BioEssays 26:901–915, 2004. © 2004 Wiley Periodicals, Inc. (shrink)

Females and males often exhibit conspicuous morphological, physiological and behavioral differences. Similarly, gene expression profiles indicate that a large portion of the genome is sex‐differentially deployed, particularly in the germ line. Because males and females are so fundamentally different, each sex is likely to have a different optimal gene expression profile that is never fully achieved in either sex because of antagonistic selection in females versus males. Males are hemizygous for the X chromosome, which means that recessive male‐favorable de novo (...) mutations on the X chromosome are subject to immediate selection. In females, a recessive female‐favorable mutation on one of two X chromosomes is not available for selection until it becomes frequent enough in the local population to result in homozygous individuals. Given that most mutations are recessive, one would expect that genes or alleles favoring males should accumulate on the X chromosome. Recent microarray work in Drosophila and C. elegans clearly shows the opposite. Why is the X chromosome a highly disfavored location for genes with male‐biased expression in these animals? BioEssays 26:543–548, 2004. Published 2004 Wiley Periodicals, Inc. (shrink)

A flurry of technological advances in molecular, cellular and developmental biology during the past decade has provided a clearer understanding of mechanisms underlying phenotypic diversification. Building upon such momentum, a recent paper tackles one of the foremost topics in evolution, that is the origin of species‐specific beak morphology in Darwin's finches.1 Previous work involving both domesticated and wild birds implicated a well‐known signaling pathway (i.e. bone morphogenetic proteins) and one population of progenitor cells in particular (i.e. cranial neural crest), as (...) primary factors for establishing beak size and shape. But these results were limited in their ability to explain fully the morphogenetic bases of patterned outgrowth. So in a quest to identify novel genes whose expression correlated with differences in beak anatomy among Darwin's finches, a DNA microarray approach was undertaken using tissues harvested from the Galápagos Islands. The results are striking and point to a protein called calmodulin, which is a mediator of cellular calcium signaling, as a key determinant of beak length. BioEssays 29: 1–6, 2007. © 2006 Wiley Periodicals, Inc. (shrink)

The ethically controversial option of genetic population screening used to be restricted to a small number of rather rare diseases by methodological limitations which are now about to be overcome. With the new technology of DNA microarrays ("DNA chip"), emerging from the synthesis of microelectronics and molecular biology, methods are now at hand for the development of mass screening programmes for a wide spectrum of genetic traits. Thus, the DNA chip may be the key technology for a refined preventive (...) medicine as well as a new dimension of eugenics. The forthcoming introduction of the DNA chip technology into medical practice urgently requires an internationally consistent framework of ethical standards and legal limitations if we do not want it to become a new Pandora's box. (shrink)

In this paper we will offer a few examples to illustrate the orientation of contemporary research in data analysis and we will investigate the corresponding role of mathematics. We argue that the modus operandi of data analysis is implicitly based on the belief that if we have collected enough and sufficiently diverse data, we will be able to answer most relevant questions concerning the phenomenon itself. This is a methodological paradigm strongly related, but not limited to, biology, and we label (...) it the microarray paradigm. In this new framework, mathematics provides powerful techniques and general ideas which generate new computational tools. But it is missing any explicit isomorphism between a mathematical structure and the phenomenon under consideration. This methodology used in data analysis suggests the possibility of forecasting and analyzing without a structured and general understanding. This is the perspective we propose to call agnostic science, and we argue that, rather than diminishing or flattening the role of mathematics in science, the lack of isomorphisms with phenomena liberates mathematics, paradoxically making more likely the practical use of some of its most sophisticated ideas. (shrink)

It has long been thought that gene expression is tightly regulated in multicellular eukaryotes, so that expression profiles match functional profiles. This conception emerged from the assumption that gene activity is synonymous with gene function. This paradigm was first challenged by comparative protein electrophoresis studies showing extensive differences in expression patterns among related species. The paradigm is now being challenged by evolutionary transcriptomics using microarray technologies. Most gene expression profiles display features that lack any obvious functional significance. The so‐called “ectopic” (...) expression refers to the expression of genes at times and locations where the target gene is not known to have a function. However, ectopic expression might be associated with genuine function even if this function is not essential or has yet to be ascertained. Alternatively, ectopic expression might come about as a superfluous by‐product of regulatory systems, which would call for a revision of prevailing ideas about the specificity of gene regulation. We herein review available evidence for ectopic expression and the hypotheses proposed for its origin and evolution. We propose that ectopic expression must be regarded as part of an integrated phenotypic whole. It seems likely that ectopic expression represents a leak in the evolution of regulatory systems, but one that is endowed with considerable evolutionary possibilities. BioEssays 27:592–601, 2005. © 2005 Wiley Periodicals, Inc. (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)

In this article we examine the history of the production of microarray technologies and their role in constructing and operationalizing views of human genetic difference in contemporary genomics. Rather than the “turn to difference” emerging as a post-Human Genome Project phenomenon, interest in individual and group differences was a central, motivating concept in human genetics throughout the twentieth century. This interest was entwined with efforts to develop polymorphic “genetic markers” for studying human traits and diseases. We trace the technological, methodological (...) and conceptual strategies in the late twentieth century that established single nucleotide polymorphisms as key focal points for locating difference in the genome. By embedding SNPs in microarrays, researchers created a technology that they used to catalog and assess human genetic variation. In the process of making genetic markers and array-based technologies to track variation, scientists also made commitments to ways of describing, cataloging and “knowing” human genetic differences that refracted difference through a continental geographic lens. We show how difference came to matter in both senses of the term: difference was made salient to, and inscribed on, genetic matter, as a result of the decisions, assessments and choices of collaborative and hybrid research collectives in medical genomics research. (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)

CtBP family proteins predominantly function as transcriptional corepressors. Studies with mutant mouse suggest that the two mouse genes, Ctbp1 and Ctbp2, play unique and redundant gene regulatory roles during development.1 Ctbp1-deficient mice are viable, but are small and die early, while Ctbp2 deficiency leads to embryonic lethality. Ctbp2-null mutation causes defects in axial patterning, heart morphogenesis and neural development. The Ctbp2 mutant phenotype is more severe in the absence of Ctbp1. The studies with Ctbp2 mutant embryos suggest that CtBP can (...) also activate transcription. A plant CtBP homolog, Angustifolia (AN), has recently been identified.2, 3 AN controls polar elongation of leaf cells via the microtubule cytoskeleton. Microarray analysis suggests that AN also functions as a transcriptional repressor. Thus, the CtBP family proteins control cellular processes by serving as transcriptional activators and regulators of the cytoskeleton as well as transcriptional corepressors. BioEssays 25:9–12, 2003. © 2002 Wiley Periodicals, Inc. (shrink)

Motivation: One approach to inferring genetic regulatory structure from microarray measurements of mRNA transcript hybridization is to estimate the associations of gene expression levels measured in repeated samples. The associations may be estimated by correlation coefficients or by conditional frequencies or by some other statistic. Although these procedures have been successfully applied to other areas, their validity when applied to microarray measurements has yet to be tested. Results: This paper describes an elementary statistical difficulty for all such procedures, no matter (...) whether based on Bayesian updating, conditional independence testing, or other machine learning procedures such as simulated annealing or neural net pruning. The difficulty obtains if a number of cells from a common population are aggregated in a measurement of expression levels. Although there are special cases where the conditional associations are preserved under aggregation, in general inference of genetic regulatory structure based on conditional association is unwarranted. Contact: tchu@ andrew.cmu.edu. (shrink)

Circadian rhythms are responsible for 24‐hour oscillations in diverse biological processes. While the central genes governing circadian pacemaker rhythmicity have largely been identified, clock‐controlled output molecules responsible for regulating rhythmic behaviors remain largely unknown. Two recent reports from McDonald and Rosbash1 and Claridge‐Chang et al.2 address this issue. By identifying a large number of genes whose mRNA levels show circadian oscillations, the reports provide important new information on the biology of circadian rhythm. In addition, the reports illustrate both the power (...) and limitations of microarray‐based methods for profiling mRNA expression on a genomic scale. BioEssays 24:494–498, 2002. © 2002 Wiley Periodicals, Inc. (shrink)

DNA arrays have become the preferred method for large-scale expression measurement. Such data are needed in view of the large amounts of sequence data available: expression levels in a number of different tissues or situations provide a first step toward functional characterisation of new entities revealed by DNA sequencing. Although the basic principle of measurement is in all cases based on hybridisation of a mixed probe derived from tissue RNA to large sets of DNA fragments representing many genes, a number (...) of different forms of implementation of this principle are at hand. They are briefly described and compared, emphasizing the important issue of sensitivity and sample requirements and the accessibility of the methods to academic scientists. When these factors are taken into account, it appears that, contrary to a largely prevalent impression, the “best” approach is not necessarily always provided by the widely advertised glass microarrays or oligonucleotide chips. BioEssays 21:781–790, 1999. © 1999 John Wiley & Sons, Inc. (shrink)

This paper calls fresh attention to ethical problems surrounding prenatal testing by focusing on genetic knowledge gained through evolving testing procedures. Advances in reproductive and prenatal genetic testing include non-invasive tests, such as Verifi and Materniti21, designed to gather detailed information regarding fetal DNA as early as 10 weeks. Meanwhile, a new method of chromosomal microarray has proved more reliable than karyotyping in detecting fetal abnormality. This method detects abnormalities in 1 out of every 60 pregnancies in which karyotyping identified (...) the fetus as “normal.” Chromosomal microarray directly compares fetal DNA to DNA from a presumptively “healthy person” to identify genetic deviations. The chromosomal microarray method thus assumes a human genetic blueprint—that is, a normal genotype, deviance from which is risky and open to medical diagnosis. But, according to philosopher and geneticist Jackie Leach Scully, there is no genetic blueprint for human beings. Rather, genetic variation is constant. Thus, notes Scully, genetic discourse could free medical discourse from the dictates of the binary between normal and abnormal, although mistaken belief in a genetic blueprint can foil this alternative way of speaking and thinking. Prenatal testing has received critical philosophical attention from both disability theorists and feminists. Adrienne Asch suggests that prenatal testing and diagnosis stigmatizes already-existing persons with disabilities by suggesting that bodily deviance is intolerable. Licia Carlson coined the phrase “prenatal prototypes” to describe the obfuscating results of genetic profiling carried out on the fetus. The philosophical conversation Asch and Carlson stimulate involves higher stakes now that testing uncovers fetal genotype and reveals mere genetic deviation in order to aid reproductive decision-making. I argue that prenatal testing, and especially the most recently developed testing procedures described above, forecloses Scully’s alternative discourse of genetic variation by supporting an ideal of a singular “healthy genotype,” deviance from which is to be uncovered and avoided. Mobilizing this insight by drawing on the work of feminist disability scholars like Asch and Carlson, I seek to foreground the play between norm and deviance. I expose the normalizing field of statistical risk, operating in excess of medical diagnosis, which requires potential parents to manage and avoid deviance itself. (shrink)

nature of modern data collection and storage techniques, and the increases in the speed and storage capacities of computers. Statistics books from 30 years ago often presented examples with fewer than 10 variables, in domains where some background knowledge was plausible. In contrast, in new domains, such as climate research where satellite data now provide daily quantities of data unthinkable a few decades ago, fMRI brain imaging, and microarray measurements of gene expression, the number of variables can range into the (...) tens of thousands, and there is often limited background knowledge to reduce the space of alternative causal hypotheses. In such domains, non-automated causal discovery techniques appear to be hopeless, while the availability of faster computers with larger memories and disc space allow for the practical implementation of computationally intensive automated search algorithms over large search spaces. Contemporary science is not your grandfather’s science, or Karl Popper’s. Causal inference without experimental controls has long seemed as if it must somehow be capable of being cast as a kind of statistical inference involving estimators with some kind of convergence and accuracy properties under some kind of assumptions. Until recently, the statistical literature said not. While parameter estimation and experimental design for the effective use of data developed throughout the 20th century, as recently as 20 years ago the methodology of causal inference without experimental controls remained relatively primitive. Besides a cessation of hostilities from the majority of the statistical and philosophical communities (which has still only partially happened), several things were needed for theories of causal estimation to appear and to flower: well defined mathematical objects to represent causal relations; well defined connections between aspects of these objects and sample data; and a way to compute those connections. A sequence of studies beginning with Dempster’s work on the factorization of probability distributions [Dempster 1972] and culminating with Kiiveri and Speed’s [Kiiveri & Speed 1982] study of linear structural equation models, provided the first, in the form of directed acyclic graphs, and the second, in the form of the “local” Markov condition.. (shrink)

Cytogenetic research has had a major impact on the field of reproductive medicine, providing an insight into the frequency of chromosomal abnormalities that occur during gametogenesis, embryonic development and pregnancy. In humans, aneuploidy has been found to be relatively common during fetal life, necessitating prenatal screening of high‐risk pregnancies. Aneuploidy rates are higher still during the preimplantation stage of development. An increasing number of IVF laboratories have attempted to improve pregnancy rates by using preimplantation genetic diagnosis (PGD) to ensure that (...) the embryos transferred to the mother are chromosomally normal. This paper reviews some of the techniques that are key to the detection of aneuploidy in reproductive samples including comparative genomic hybridization (CGH). CGH has provided an unparalleled insight into the nature of chromosome imbalance in human embryos and polar bodies. The clinical application of CGH for the purposes of PGD and the future extensions of the methodology, including DNA microarrays, are discussed. BioEssays 25:289–300, 2003. © 2003 Wiley Periodicals, Inc. (shrink)

Increasingly, genomic analysis is being utilized to diagnose children with developmental delay or dysmorphic facial features suggestive of a congenital disorder. Genetic testing has rapidly evolved, and the genome-wide tests that we use today are significantly different from the more targeted single-gene tests of the last decade. Chromosomal microarray analysis is now a first line test for children with multiple birth defects, children with intellectual impairment, and children with an unusual constellation of symptoms that do not fit with a known (...) disease. There are three types of CMA that are currently clinically available. CMA by oligonucleotide array-based comparative genomic hybridization compares the hybridization signal from the patient's DNA to that of a reference DNA sample for each oligonucleotide on the array. Depending on the specific array, this can range from tens of thousands to hundreds of thousands of oligonucleotides. (shrink)

Increasingly, genomic analysis is being utilized to diagnose children with developmental delay or dysmorphic facial features suggestive of a congenital disorder. Genetic testing has rapidly evolved, and the genome-wide tests that we use today are significantly different from the more targeted single-gene tests of the last decade. Chromosomal microarray analysis is now a first line test for children with multiple birth defects, children with intellectual impairment, and children with an unusual constellation of symptoms that do not fit with a known (...) disease. There are three types of CMA that are currently clinically available. CMA by oligonucleotide array-based comparative genomic hybridization compares the hybridization signal from the patient's DNA to that of a reference DNA sample for each oligonucleotide on the array. Depending on the specific array, this can range from tens of thousands to hundreds of thousands of oligonucleotides. (shrink)

At the beginning of the 21st century, biology will try to address the function of a large number of new genes. From the perspective of technologies applied today to functional genomics, this task appears to be more complex than the effort invested in the sequencing of the human genome. Conceptually, a high-throughput approach permitting correlation between newly discovered genes and functional properties of their protein products has yet to be developed. To address relationships between tens of thousands of genes and (...) their cognate proteins, novel interdisciplinary technologies need to emerge. In this paper, a new idea of immunomics is presented and an experimental strategy is outlined to circumvent some of the restrictions associated with methodologies currently in use. It is proposed that cloned segments of genomic DNA are used for genetic immunization to obtain a large collection of antibodies, and to generate microarrays of these antibodies for tracing differentially expressed cellular proteins. (shrink)

The vertebrate body is organized in segments, easily visible in the consecutive vertebrae of the skeleton. These are first defined in the embryo by the formation of somites. Somites are generated at regular intervals from the presomitic mesoderm by a combination of oscillating signals, known as the segmentation clock, which establish the pace at which new somites are formed, and signaling gradients that set the location of new intersomitic borders. Using a microarray approach, Dequéant et al.1 have now shown that (...) the segmentation clock is more complex than previously thought and includes oscillating expression of genes from at least three signaling pathways organized in coordinated networks. BioEssays 29:412–415, 2007. © 2007 Wiley Periodicals, Inc. (shrink)