Micro Array

This is a short review of the mixing techniques used in microarray binding reactions. Current micro-fluidic mixing technologies that are being implemented in the microarray industry include, Turbulent Flow, Rotary Mixing with air bubbles, Laminar flow, Acoustic waves, Surface Acoustic Waves, and Chaotic Mixing. The goal of mixing a microarray binding reaction is to assure that every molecule in solution finds its binding partner immobilized on the microarray as quickly as possible. In other words, the most desirable binding reaction has fast and complete diffusion of all biomolecules in solution over all microarray spots and remains a homogeneous mixture until the reaction is complete. Sound microarray data can be achieved using inexpensive hybridization cassettes, however, in certain cases active mixing has been shown to speed up binding reactions, improve data quality, and reduce the number of molecules required in solution for the binding or hybridization reaction. Reasons to use automated machines for microarray binding reactions include: • • • • •

Save time and money by performing tests faster with less test sample Minimize handling of microarrays, which reduces the possibility of human error. Get better control over the experimental variables, resulting in increased reproducibility Empower users to define, edit and store individual methods and protocols Save and link experimental or testing procedures to database

In a turbulent flow system, the hybridization cocktail is mixed by the using random contact with the physical structure of a reaction chamber. One challenge of this type of system is obtaining homogeneity of the reaction mixture. Rotary mixing with air bubbles is performed inside a sealed reaction cassette by rotating a trapped air bubble over the microarray. Binding reactions cannot take place in air, only in solution. Therefore a challenge of this approach is minimizing air bubble-based oxidization of the fluorescent dyes commonly used in microarray reactions, which would lead to lower signals and elevated background. Another challenge is that if an air bubble were to become trapped, the reaction in the trapped area would not proceed. Laminar Flow is generated by using a small diaphragm pumping system at each end of the microarray to move the binding reaction sample back and forth across the microarray. Recent micro-fluidic studies show that laminar flow mixing can produce layers of liquid that flow over top of each other, thus one challenge of this approach is to obtain fully homogeneous and complete mixing of sample during the laminar flow process. Surface Acoustic Waves generated by piezoelectric transducers are used to cause streaming of the hybridization reactions under cover slips or lifter slips. Some of the same challenges that apply to laminar flow also apply to systems that use surface acoustic waves. Chaotic Advection Mixing is accomplished using micro fluidic pumps and a mixing loop. The overall movement of liquid in properly configured systems is “chaotic” due to the extremely complex direction and speed of fluids provided by the mixing loop. This type of system provides the most complete mixing of low volumes of liquid in the shortest amount of time.

Microarray-based Comparative Genomic Hybridization (aCGH) By: Aaron Theisen, Ph.D. © 2008 Nature Education Citation: Theisen, A. (2008) Microarray-based comparative genomic hybridization (aCGH). Nature Education 1(1)

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* Required Many human genetic disorders result from unbalanced chromosomal abnormalities, in which there is net gain or loss of genetic material. Traditionally, cytologists have detected such abnormalities by generating a karyotype of a person's chromosomes and analyzing the banding patterns therein. Indeed, since its development in the 1970s, cytogenetic analysis of banding patterns has been the primary tool for the clinical assessment of patients with a variety of congenital anomalies. Under ideal conditions, aberrations as small as approximately 5 megabases (Mb) can be detected with banding analysis; such chromosome rearrangements are termed "microscopic." In recent years, however, researchers have increasingly turned to newer cytogenetic techniques. One such method is fluorescence in situ hybridization (FISH), a technique that uses fluorescently labeled probes to locate the positions of specific DNA sequences on chromosomes. Yet another popular technique is comparative genomic hybridization (CGH), which provides an alternative means of genome-wide screening for copy number variations. First developed to detect copy number changes in solid tumors, CGH uses two genomes, a test and a control, which are differentially labeled and competitively hybridized to metaphase chromosomes. The fluorescent signal intensity of the labeled test DNA relative to that of the reference DNA can then be linearly plotted across each chromosome, allowing the identification of copy number changes (Kallioniemi et al., 1992). Unlike traditional techniques used to detect copy number gains and losses, which rely on the examination of a single target and prior knowledge of the region under investigation, CGH can be used to quickly scan an entire genome for imbalances. In addition, CGH does not require cells that are undergoing division (Speicher et al., 1993). However, as with earlier cytogenetic methods, the resolution of CGH has been limited to alterations of approximately 5-10 Mb for most clinical applications (Lichter et al., 2000; Kirchhoff et al., 1998).

Combining CGH with Microarrays: The Development of Array CGH

Figure 1: Diagram of the microarray-based comparative genomic hybridization (aCGH) process. In an attempt to overcome some of the aforementioned limitations associated with traditional CGH, investigators have developed a newer method that combines the principles of CGH with the use of microarrays (Schena et al., 1995). Instead of using metaphase chromosomes, this method—which is known as array CGH, or simply aCGH—uses slides arrayed with small segments of DNA as the

targets for analysis (Lucito et al., 2003). These microarrays are created by the deposit and immobilization of small amounts of DNA (known as probes) on a solid support, such as a glass slide, in an ordered fashion. Probes vary in size from oligonucleotides manufactured to represent areas of interest (25–85 base pairs) to genomic clones such as bacterial artificial chromosomes (80,000–200,000 base pairs). Because probes are several orders of magnitude smaller than metaphase chromosomes, the theoretical resolution of aCGH is proportionally higher than that of traditional CGH. The level of resolution is determined by considering both probe size and the genomic distance between DNA probes. For example, a microarray with probes selected from regions across the genome that are 1 Mb apart will be unable to detect copy number changes of the intervening sequence. Regardless of the type of probe, the basic methodology for aCGH analysis is consistent (Figure 1). First, DNA is extracted from a test sample (e.g., blood, skin, fetal cells). The test DNA is then labeled with a fluorescent dye of a specific color, while DNA from a normal control (reference) sample is labeled with a dye of a different color. The two genomic DNAs, test and reference, are then mixed together and applied to a microarray. Because the DNAs have been denatured, they are single strands; thus, when applied to the slide, they attempt to hybridize with the arrayed singlestrand probes. Next, digital imaging systems are used to capture and quantify the relative fluorescence intensities of the labeled DNA probes that have hybridized to each target. The fluorescence ratio of the test and reference hybridization signals is determined at different positions along the genome, and it provides information on the relative copy number of sequences in the test genome as compared to the normal genome. The recent sequencing of the human genome and development of high-throughput methods of robotically arraying genetic material on a solid surface have enabled the detection of submicroscopic chromosomal deletions and duplications at an unprecedented level (DeRisi et al., 1996; Schena et al., 1995; Shaffer et al., 2007).

Advantages of aCGH Technology The primary advantage of aCGH is the ability to simultaneously detect aneuploidies, deletions, duplications, and/or amplifications of any locus represented on an array; in fact, one assay using this technique is equivalent to thousands of FISH experiments, with the attendant savings in labor and expense. In addition, aCGH has proven to be a powerful tool for the detection of submicroscopic chromosomal abnormalities in individuals with idiopathic mental retardation and various birth defects. Indeed, several large-scale studies demonstrate that aCGH has a 10%–20% detection rate of chromosomal abnormalities in children with mental retardation/developmental delay with or without congenital anomalies; only 3%–5% of these abnormalities would be detectable by other means. For example, in a study of 8,789 cases analyzed by aCGH, 1,049 (11.9%) had a clinically relevant chromosomal abnormality (Shaffer et al., 2007).

Studying Specific Chromosomal Regions with aCGH Because aCGH facilitates simultaneous detection of multiple abnormalities and offers higher resolution than traditional cytogenetic methods, it has allowed investigators to focus on various types of rearrangements in particular regions of chromosomes. In recent years, aCGH has been particularly useful in the study of subtelomeric and pericentromeric rearrangements.

Subtelomeric Rearrangements

Figure 2: aCGH analysis and FISH combined can identify small subtelomeric regions associated with clinical phenotypes. a) aCGH analysis of the genome of "Patient 5" revealed a deletion in the subtelomeric region of chromosome 17. This deletion was confirmed using FISH in the patient (b) Chromosome 17 from the mother and father of the patient is shown in (c) and (d). Copyright 2004 BMJ Publishing Group Ltd., Shaw-Smith, C. et al., Microarray based comparative genomic hybridisation (array-CGH) detects submicroscopic chromosomal deletions and duplications in patients with learning disability/mental retardation and dysmorphic features, Journal of Medical Genetics 41, 241-248 Studies of subtelomeric rearrangements illustrate how aCGH has revealed an unprecedented amount of information about the complexity of the human genome. Present on all but the short arms of acrocentric chromosomes 13, 14, 15, 21, and 22, subtelomeric regions have been the subject of a great deal of study because they are relatively gene-rich (Saccone et al., 1992) and are prone to rearrangement by a number of mechanisms (Ballif et al., 2003, 2004). Moreover, rearrangement of subtelomeric regions has been suggested to represent a high proportion of abnormalities in individuals with idiopathic mental retardation. The largest study of subtelomeric abnormalities to date examined 11,688 cases with subtelomeric FISH and detected pathogenic abnormalities in 2.6% (Ravnan et al., 2006). Interestingly, recent large-scale prospective studies using aCGH on similar populations show that interstitial deletions (which are caused by two breaks in the chromosome arm, the loss of the intervening segment, and the rejoining of the chromosome segments) are two to three times more frequent than terminal imbalances in subtelomeric regions (Shaw-Smith et al., 2007). It is important to note that aCGH data can be verified using FISH analysis (Figure 2). For instance, Ballif and others (2007b) recently characterized 169 cases with subtelomeric abnormalities identified by aCGH. Although the coverage was sufficient to define the breakpoints in over half (56%) of the subtelomeric abnormalities, 44% of the abnormalities extended outside the coverage, suggesting that many such abnormalities are greater than 5 Mb in size. Of these 169 cases, 42 had interstitial deletions. These deletions would have been missed or incorrectly characterized by subtelomeric FISH panels that use a single clone to the most distal unique sequence for each region. In addition, six (3.5%) of the individuals had complex rearrangements that showed deletions along with duplications or additional deletions. The identification of these sorts of complex rearrangements suggests that chromosomal abnormalities are often more complex than previously thought.

Pericentromeric Rearrangements aCGH has also allowed for the detection of rearrangements in the pericentromeric regions directly adjacent to the repetitive centromeric regions in all chromosomes. The pericentromeric regions are known to be prone to instability because numerous microdeletions, including those causing Williams, DiGeorge, and Prader-Willi syndromes, occur in these regions. Because of the high levels of repetitive sequences present in the pericentromeric regions and the variability in presentation associated with traditional G-banding, rearrangements in these regions are inherently difficult to assess by chromosome analysis. However, the recent construction of microarrays targeted to the

pericentromeric regions has allowed for the assessment of copy number imbalances in these regions. For example, in one study of 8,789 individuals with mental retardation and/or birth defects (Shaffer et al., 2007), 94 individuals were found to have a microdeletion in a pericentromeric region, and 42 individuals were found to have reciprocal duplications in these regions. In addition, 22 individuals had novel deletions, while 11 individuals had novel duplications of other pericentromeric regions that were found in two or more patients. Among these individuals were four with recurrent de novo interstitial deletion in band p11.2p12.2 on the short arm of chromosome 16. The common clinical features of these patients suggest that deletion of 16p11.2p12.2 constitutes a novel microdeletion syndrome (Bailif et al., 2007a). Two other individuals with recurrent interstitial deletions on the long arm of chromosome 16 (16q11.2q12.2) were also identified (Bailif et al., 2008b), and their common clinical features, as well as those of individuals in another report (Borozdin et al., 2006), suggest that microdeletions of the pericentromeric region of the long arm of chromosome 16 represent another underappreciated syndrome. Many such microdeletion syndromes are caused by nonallelic homologous recombination (NAHR) mediated by flanking segmental duplications (Shaffer et al., 2001). This mechanism predicts that reciprocal duplications of these deletions should occur with equal frequency (Lupski, 1998). However, duplications have been reported more rarely than expected. One explanation for this finding is that individuals with duplications usually have milder phenotypes than individuals with deletions, and these mild phenotypes may not lead to clinical investigation (Ensenauer et al., 2003; Yobb et al., 2005). Furthermore, duplications involving segments smaller than 1.5 Mb may be routinely missed even by FISH of interphase nuclei (Shaffer et al., 1997). However, recent largepopulation studies of individuals tested by aCGH have shown that the frequency of reciprocal duplications is higher than detected in previous studies that used other cytogenetic technologies (Shaffer et al., 2007; Lu et al., 2007). For example, duplications of the common Rett syndrome gene MECP2 have been identified in males with developmental delay (del Gaudio et al., 2006). In addition, the reciprocal duplications of microdeletion syndromes such as 3q29 microdeletion syndrome (Ballif et al., 2008a), Williams-Beuren syndrome (Kriek et al., 2006), and 22q11.21 microdeletion syndrome (Ensenauer et al., 2003) have also been identified by aCGH. The clinical significance of some of these reciprocal duplications is not yet known. For instance, only two individuals had de novo microduplications of 3q29, whereas the remaining cases were inherited from a carrier parent. Thus, the clinical significance of these duplications is unclear, and any phenotype may be modulated by an as-yet unidentified genetic modifier.

The Future of aCGH Array CGH has propelled cytogenetics from the microscope to the computer, combining CGH with high-throughput microarrays to simultaneously analyze hundreds or thousands of discrete regions of the genome and identify unbalanced karyotypes. Array CGH combines the locus-specific nature of FISH with the global genome view of high-resolution chromosomes; thus, this method represents the integration of traditional and molecular cytogenetic techniques and will continue to enable the clinical diagnosis of chromosomal abnormalities at an unprecedented resolution in the years to come. Hybridization is the process of combining complementary, single-stranded nucleic acids into a single molecule. Nucleotides will bind to their complement under normal conditions, so two perfectly complementary strands will bind to each other readily. This is called annealing. However, due to the different molecular geometries of the nucleotides, a single inconsistency between the two strands will make binding between them more energetically unfavorable. Measuring the effects of base incompatibility by quantifying the rate at which two strands anneal can provide information as to the similarity in base sequence between the two strands being annealed. Annealing may be

reversed by heating the double stranded molecule of DNA (or RNA or DNA:RNA) to break the hydrogen bonds between bases and separate the two strands. This is called melting or denaturation. The process of hybridization is a major force in the evolution of plants - much more so than in the animal kingdom. Plants of related species often cross-pollinate to produce fertile hybrids, which can reproduce themselves or back-cross with the ‘parent’ species to produce hybrid swarms. Some hybrids do not reproduce sexually, but can effectively clone themselves to produce new microspecies. And some hybridization events produce entirely new species, often by doubling their chromosome number, in which case the offspring contain all the DNA of both parents. The process of hybridization often occurs when plants find themselves growing near related species that they would not normally be found with in the wild. Introducing exotic species, disturbing natural ecosystems and altering the distribution of plants through climate change are all ways in which human activity can facilitate hybridization. The responses of plants to these changes are well worth studying. Hybrids, despite often being difficult to identify, should not be ignored. They may reflect subtle changes in the environment, or they may be the best possible adaptation of wild plants to climate change. Hybridization is neither good nor bad, but it is inevitable. The hybridization project is funded by the BSBI and is the only strategic initiative on this subject in the UK, despite its importance for conservation, land management and ecology.