Variations on a Chip: Technologies of Difference in Human Genetics Research.

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 (HGP) 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 (SNPs) 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(s), as a result of the decisions, assessments and choices of collaborative and hybrid research collectives in medical genomics research.

Microarrays for identifying binding sites and probing structure of RNAs.

Oligonucleotide microarrays are widely used in various biological studies. In this review, application of oligonucleotide microarrays for identifying binding sites and probing structure of RNAs is described. Deep sequencing allows fast determination of DNA and RNA sequence. High-throughput methods for determination of secondary structures of RNAs have also been developed. Those methods, however, do not reveal binding sites for oligonucleotides. In contrast, microarrays directly determine binding sites while also providing structural insights. Microarray mapping can be used over a wide range of experimental conditions, including temperature, pH, various cations at different concentrations and the presence of other molecules. Moreover, it is possible to make universal microarrays suitable for investigations of many different RNAs, and readout of results is rapid. Thus, microarrays are used to provide insight into oligonucleotide sequences potentially able to interfere with biological function. Better understanding of structure-function relationships of RNA can be facilitated by using microarrays to find RNA regions capable to bind oligonucleotides. That information is extremely important to design optimal sequences for antisense oligonucleotides and siRNA because both bind to single-stranded regions of target RNAs.

Overview of DNA microarrays: types, applications, and their future.

This unit provides an overview of DNA microarrays. Microarrays are a technology in which thousands of nucleic acids are bound to a surface and are used to measure the relative concentration of nucleic acid sequences in a mixture via hybridization and subsequent detection of the hybridization events. This overview first discusses the history of microarrays and the antecedent technologies that led to their development. This is followed by discussion of the methods of manufacture of microarrays and the most common biological applications. The unit ends with a brief description of the limitations of microarrays and discusses how microarrays are being rapidly replaced by DNA sequencing technologies.

Single nucleotide polymorphism arrays: a decade of biological, computational and technological advances.

Array manufacturers originally designed single nucleotide polymorphism (SNP) arrays to genotype human DNA at thousands of SNPs across the genome simultaneously. In the decade since their initial development, the platform's applications have expanded to include the detection and characterization of copy number variation--whether somatic, inherited, or de novo--as well as loss-of-heterozygosity in cancer cells. The technology's impressive contributions to insights in population and molecular genetics have been fueled by advances in computational methodology, and indeed these insights and methodologies have spurred developments in the arrays themselves. This review describes the most commonly used SNP array platforms, surveys the computational methodologies used to convert the raw data into inferences at the DNA level, and details the broad range of applications. Although the long-term future of SNP arrays is unclear, cost considerations ensure their relevance for at least the next several years. Even as emerging technologies seem poised to take over for at least some applications, researchers working with these new sources of data are adopting the computational approaches originally developed for SNP arrays.

[Development and application of gene chip technology].

Gene chip technology, featured by large information capacity, easy performance, and rapid response, has became a research hotspot in recent years. Along with the further research in molecular biology and genomics, a large number of gene chip technologies have been developed and applied. This article describes the history, status quo, and future trends of gene chip technology.

[Biochips in the laboratory of A. D. Mirzabekov: 1988-2007].

The article reviews the last period of A. D. Mirzabekov's scientific career. During this time, gel-based biochips were invented, studied, and introduced to practical applications in his laboratory. This work began at the early stages of the "Human Genome" project and is continuing today, including recent development of diagnostic oligonucleotide and protein biochips. This research is discussed in the context of the worldwide development of microarray technologies.

Options available for profiling small samples: a review of sample amplification technology when combined with microarray profiling.

The possibility of performing microarray analysis on limited material has been demonstrated in a number of publications. In this review we approach the technical aspects of mRNA amplification and several important implicit consequences, for both linear and exponential procedures. Amplification efficiencies clearly allow profiling of extremely small samples. The conservation of transcript abundance is the most important issue regarding the use of sample amplification in combination with microarray analysis, and this aspect has generally been found to be acceptable, although demonstrated to decrease in highly diluted samples. The fact that variability and discrepancies in microarray profiles increase with minute sample sizes has been clearly documented, but for many studies this does appear to have affected the biological conclusions. We suggest that this is due to the data analysis approach applied, and the consequence is the chance of presenting misleading results. We discuss the issue of amplification sensitivity limits in the light of reports on fidelity, published data from reviewed articles and data analysis approaches. These are important considerations to be reflected in the design of future studies and when evaluating biological conclusions from published microarray studies based on extremely low input RNA quantities.

The emergence of toxicogenomics: a case study of molecularization.

This paper described the efforts of scientists at the National Institute of Environmental Health Sciences (NIEHS) and their allies in the National Toxicology Program to molecularize toxicology by fostering the emergence of a new discipline: toxicogenomics. I demonstrate that the molecularization of toxicology at the NIEHS began in a process of 'co-construction'. However, the subsequent emergence of the discipline of toxicogenomics has required the deliberate development of communication across the myriad disciplines necessary to produce toxicogenomic knowledge; articulation of emergent forms, standards, and practices with extant ones; management of the tensions generated by grounding toxicogenomics in traditional toxicological standards and work practices even it transforms those standards and practices; and identification and stabilization of roles for toxicogenomic knowledge in markets and service sites, such as environmental health risk assessment and regulation. This paper describes the technological, institutional, and inter-sectoral strategies that scientists have pursued in order to meet these challenges. In so doing, this analysis offers a vista into both the means and meanings of molecularization.

Historical background and anticipated developments.

Expression profiling using DNA arrays is often believed to have appeared during the second half of the 1990s, and to be based exclusively on nonisotopic methods. In fact, the first article describing the application of cDNA arrays to expression analysis was published in 1992, relied on radioactive labeling, and was a new development of "high-density" membranes used until then essentially for efficient screening of libraries. Several papers described the use of this technology for simultaneous expression measurement of thousands of genes at the time when the first glass microarrays were published. Simultaneously, oligonucleotide chips, originally developed for resequencing and mutation detection applications, were shown to be capable of expression measurement as well. The three approaches have developed over the years and still coexist, as each of them has specific advantages (and drawbacks); the major issues have become those of data quality, data analysis and storage (ideally in a common public database). Meanwhile, the technology continues to evolve. The most obvious trend is a shift towards using arrays of relatively long oligonucleotides that combine most of the advantages of very long (cDNA) and very short (25-mer) DNA segments. The search for better detection methods, ideally without labeling of the sample, is continuing, although it seems difficult to reach the required sensitivity. New materials for microarray manufacture and new implementations of existing methods have appeared. In addition, the field is progressively becoming segmented into high gene number, low volume (research) applications on the one hand, and low gene number, high throughput (diagnostic) uses on the other.