Comparative genomics and experimental promoter analysis reveal functional liver-specific elements in mammalian hepatic lipase genes

Background

Array-based comparative genomic hybridization (aCGH) is a high-throughput method for measuring genome-wide DNA copy number changes. Current aCGH methods have limited resolution, sensitivity and reproducibility. Microarrays for aCGH are available only for a few organisms and combination of aCGH data with expression data is cumbersome.

Results

We present a novel method of using commercial oligonucleotide expression microarrays for aCGH, enabling DNA copy number measurements and expression profiles to be combined using the same platform. This method yields aCGH data from genomic DNA without complexity reduction at a median resolution of approximately 17,500 base pairs. Due to the well-defined nature of oligonucleotide probes, DNA amplification and deletion can be defined at the level of individual genes and can easily be combined with gene expression data.

Conclusion

A novel method of gene resolution analysis of copy number variation (graCNV) yields high-resolution maps of DNA copy number changes and is applicable to a broad range of organisms for which commercial oligonucleotide expression microarrays are available. Due to the standardization of oligonucleotide microarrays, graCNV results can reliably be compared between laboratories and can easily be combined with gene expression data using the same platform.     

Applications of DNA and protein microarrays in comparative physiology

DNA microarrays have revolutionized gene expression studies and made large-scale parallel measurement of whole genome expression a feasible technique in model species where genomes are well characterized. Such studies are perfectly suited to unraveling the complex regulation and/or interaction of both genes and proteins likely involved in most physiological processes. Gene expression profiles are currently being used to identify genes underlying a range of physiological responses. Characterization of these genes will help to elucidate the pathways and processes regulating physiological processes. Expanding the use of DNA microarrays to non-model species that have been critical in elucidating certain physiological pathways will be valuable in determining the genes associated with these processes. Approaches that do not require complete genome information have recently been applied to "non-model" organisms. As whole genomes are sequenced for non-model organisms, the application of DNA microarrays to comparative physiology will expand even further. The recent development of protein microarrays will be critical in understanding the regulation of physiological processes not accounted for at the genomic level. Together, DNA and protein microarrays provide the most thorough and efficient method of understanding the molecular basis of physiological processes to date. In turn, classical physiological approaches will be vital in characterizing and verifying the function of the novel genes identified by microarray experiments. Ultimately, DNA and protein microarray expression profiles may be used to predict physiological responses.     

Genome-wide expression analysis of plant cell cycle modulated genes

Genome-wide expression analysis is rapidly becoming an essential tool for identifying and analysing genes involved in, or controlling, various biological processes ranging from development to responses to environmental cues. The control of cell division involves the temporal expression of different sets of genes, allowing the dividing cell to progress through the different phases of the cell cycle. A landmark study using DNA microarrays to follow the patterns of gene expression in synchronously dividing yeast cells has allowed the identification of several hundreds of genes that are involved in the cell cycle. Although DNA microarrays provide a convenient tool for genome-wide expression analysis, their use is limited to organisms for which the complete genome sequence or a large cDNA collection is available. For other organisms, including most plant species, DNA fragment analysis based methods, such as cDNA-AFLP, provide a more appropriate tool for genome-wide expression analysis. Furthermore, cDNA-AFLP exhibits properties that complement DNA microarrays and, hence, constitutes a useful tool for gene discovery.     

Current status of protein chip development in terms of fabrication and application

Sequencing of the human genome revealed that more than 30 000 genes encode proteins comprising the human proteome. "Proteomics" can be defined as a field of research studying proteins in terms of their function, expression, structure, modification and their interaction in physiological and in pathological states. The concentration, modification and interaction of proteins in cells, plasma, and in tissues are crucial in determining the phenotype of living organisms. Although fluctuation of protein concentration is essential to maintain homeostasis, protein expression levels are also pathognomonic features. Estimating protein concentration by analyzing the quantity of mRNA in cells through conventional technologies, such as DNA chips, does not provide precise values since the half-life and translation efficacy of mRNA is variable. In addition, polypeptides undergo post-translational modification. For these reasons, novel techniques are needed to analyze multiple proteins simultaneously using protein microarrays. In the near future, protein chips may allow construction of complete relational databases for metabolic and signal transduction pathways. This article reviews the current status of technologies for fabricating protein microarrays and their applications.     

Human genomics and microarrays: implications for the plastic surgeon

The Human Genome Project was launched in 1989 in an effort to sequence the entire span of human DNA. Although coding sequences are important in identifying mutations, the static order of DNA does not explain how a cell or organism may respond to normal and abnormal biological processes. By examining the mRNA content of a cell, researchers can determine which genes are being activated in response to a stimulus.Traditional methods in molecular biology generally work on a "one gene: one experiment" basis, which means that the throughput is very limited and the "whole picture" of gene function is hard to obtain. To study each of the 60,000 to 80,000 genes in the human genome under each biological circumstance is not practical. Recently, microarrays (also known as gene or DNA chips) have emerged; these allow for the simultaneous determination of expression for thousands of genes and analysis of genome-wide mRNA expression.The purpose of this article is twofold: first, to provide the clinical plastic surgeon with a working knowledge and understanding of the fields of genomics, microarrays, and bioinformatics and second, to present a case to illustrate how these technologies can be applied in the study of wound healing.     

DNA microarray analyses in higher plants

DNA microarrays were originally devised and described as a convenient technology for the global analysis of plant gene expression. Over the past decade, their use has expanded enormously to cover all kingdoms of living organisms. At the same time, the scope of applications of microarrays has increased beyond expression analyses, with plant genomics playing a leadership role in the on-going development of this technology. As the field has matured, the rate-limiting step has moved from that of the technical process of data generation to that of data analysis. We currently face major problems in dealing with the accumulating datasets, not simply with respect to how to archive, access, and process the huge amounts of data that have been and are being produced, but also in determining the relative quality of the different datasets. A major recognized concern is the appropriate use of statistical design in microarray experiments, without which the datasets are rendered useless. A vigorous area of current research involves the development of novel statistical tools specifically for microarray experiments. This article describes, in a necessarily selective manner, the types of platforms currently employed in microarray research and provides an overview of recent activities using these platforms in plant biology.     

FunnyBase: a systems level functional annotation of Fundulus ESTs for the analysis of gene expression

Background  

While studies of non-model organisms are critical for many research areas, such as evolution, development, and environmental biology, they present particular challenges for both experimental and computational genomic level research. Resources such as mass-produced microarrays and the computational tools linking these data to functional annotation at the system and pathway level are rarely available for non-model species. This type of "systems-level" analysis is critical to the understanding of patterns of gene expression that underlie biological processes.     

Microarray studies of gene expression in fish

The use of microarrays for the study of various aspects of fish physiology has seen a spectacular increase in recent years. From early studies with model species, such as zebrafish, to current studies with commercially important species, such as salmonids, catfish, carp, and flatfish, microarray technology has emerged as a key tool for understanding developmental processes as well as basic physiology. In addition, microarrays are being applied to the fields of ecotoxicology and nutrigenomics. A number of different platforms are now available, ranging from microarrays containing cDNA amplicons to oligomers of various sizes. High-density microarrays containing hundreds of thousands of distinct oligomers have been developed for zebrafish and catfish. As this exciting technology advances, so will our understanding of global gene expression in fish. Furthermore, lessons learned from this experimentally tractable group of organisms can also be applied to more advanced organisms such as humans.     

Use of expressed sequence tag analysis and cDNA microarrays of the filamentous fungus Aspergillus nidulans

The use of microarrays in the analysis of gene expression is becoming widespread for many organisms, including yeast. However, although the genomes of a number of filamentous fungi have been fully or partially sequenced, microarray analysis is still in its infancy in these organisms. Here, we describe the construction and validation of microarrays for the fungus Aspergillus nidulans using PCR products from a 4092 EST conidial germination library. An experiment was designed to validate these arrays by monitoring the expression profiles of known genes following the addition of 1% (w/v) glucose to wild-type A. nidulans cultures grown to mid-exponential phase in Vogel's minimal medium with ethanol as the sole carbon source. The profiles of genes showing statistically significant differential expression following the glucose up-shift are presented and an assessment of the quality and reproducibility of the A. nidulans arrays discussed.     

Microarray methods in Drosophila neurobiology

In the relatively short period since their development, DNA microarrays have been used increasingly in the study of genetic and cellular processes, thereby offering a genome-wide approach to gene expression studies. With the advent of genome sequencing programs for organisms from yeast to man, the number of organisms which now have ready-made commercial arrays continues to increase. Here, the principle of DNA microarrays is introduced, with particular attention being given to the role of this technology in studies of the nervous system of the fruitfly Drosophila melanogaster. The importance of experimental design and sample preparation, in line with minimum information about microarray experiment (MIAME) compliance, is emphasised. The technical platforms available to the Drosophila neurobiologist have been illustrated and a brief number of data analysis tools that are readily available reviewed.     

Optimal design of genetic studies of gene expression with two-color microarrays in outbred crosses

Combining global gene-expression profiling and genetic analysis of natural allelic variation (genetical genomics) has great potential in dissecting the genetic pathways underlying complex phenotypes. Efficient use of microarrays is paramount in experimental design as the cost of conducting this type of study is high. For those organisms where recombinant inbred lines are available for mapping, the “distant pair design” maximizes the number of informative contrasts over all marker loci. Here, we describe an extension of this design, named the “optimal pair design,” for use with F₂ crosses between outbred lines. The performance of this design is investigated by simulation and compared to several other two-color microarray designs. We show that, for a given number of microarrays, the optimal pair design outperforms all other designs considered for detection of expression quantitative trait loci (eQTL) with additive effects by linkage analysis. We also discuss the suitability of this design for outbred crosses in organisms with large genomes and for detection of dominance.     

DNA microarrays in parasitology: strengths and limitations

Genome sequencing efforts have provided a wealth of new biological information that promises to have a major impact on our understanding of parasites. Microarrays provide one of the major high-throughput platforms by which this information can be exploited in the laboratory. Many excellent reviews and technique articles have recently been published on applying microarrays to organisms for which fully annotated genomes are at hand. However, many parasitologists work on organisms whose genomes have been only partially sequenced and where little, if any, annotation is available. The focus of this review is on how to use and apply microarrays to these situations.     

A model of base-call resolution on broad-spectrum pathogen detection resequencing DNA microarrays

Oligonucleotide microarrays offer the potential to efficiently test for multiple organisms, an excellent feature for surveillance applications. Among these, resequencing microarrays are of particular interest, as they possess additional unique capabilities to track pathogens’ genetic variations and perform detailed discrimination of closely related organisms. However, this potential can only be realized if the costs of developing the detection microarray are kept at a manageable level. Selection and verification of the probes are key factors affecting microarray design costs that can be reduced through the development and use of in silico modeling. Models created for other types of microarrays do not meet all the required criteria for this type of microarray. We describe here in silico methods for designing resequencing microarrays targeted for multiple organism detection. The model development presented here has focused on accurate base-call prediction in regions that are applicable to resequencing microarrays designed for multiple organism detection, a variation from other uses of a predictive model in which perfect prediction of all hybridization events is necessary. The model will assist in simplifying the design of resequencing microarrays and in reduction of the time and costs required for their development for new applications.