Scientists know that a mutation - or alteration - in a particular gene's DNA may contribute to a certain disease. However, it can be very difficult to develop a test to detect these mutations, because most large genes have many regions where mutations can occur. For example, researchers believe that mutations in the genes BRCA1 and BRCA2 cause as many as 60 percent of all cases of hereditary breast and ovarian cancers.
But there is not one specific mutation responsible for all of these cases. Researchers have already discovered over different mutations in BRCA1 alone. The chip consists of a small glass plate encased in plastic. Subsequently, many other sequence-based applications have been developed, including genotyping, detection of point mutations, single nucleotide polymorphisms, and insertions and deletions, as well as the detection, identification, and enumeration of microorganisms.
Microarray technology has revolutionized studies of gene expression. A cDNA or oligonucleotide array complementary to expressed mRNA provides a means to simultaneously assess the expression of thousands of genes. Two-color labeling strategies introduce an additional degree of sophistication because they facilitate simultaneous comparison between gene expression in control and test cells on the same array.
A goal in expression analysis is to place all of the genes for an organism on a single chip and then use that microarray to monitor changes in gene expression in cells.
Already, there are chips with arrays representing all or many of the genes of the human and other species, such as rat, mouse, dog, monkey, honey bee, Arabidopis , Drosophila , and Escherichia coli. CGH is used as a molecular cytogenetic technique that permits quantitative analysis of gains and losses of whole or portions of chromosomes.
The ratio of fluorescence intensities at a given chromosomal location is approximately proportional to the sequence copy number. Searching for small deletions requires DNA microarray technology in which the labeled test and reference genomes are hybridized directly on DNA microarrays on glass slides. The ratio of the test and reference fluorescence intensities hybridized to the probes on the array reflects the relative copy number of genomic segments in the target genome. Theoretically, the resolution of microarray-based CGH is limited only by the density of the probe sequences placed onto the array.
Tissue microarrays are produced by organizing small sections of formalin-fixed tissue e. It is then a simple matter to simultaneously probe all of the tissue sections with antibody- or DNA-probe reagents. This type of array has found numerous applications in the study of cancer, including molecular profiling of tumor specimens, amplification surveys, determining gene copy number, and investigating hormone therapy failures. Drug discovery has evolved to become a large-scale and highly sophisticated endeavor.
The massively parallel analytical capabilities of microarrays makes them ideally suited to various aspects of drug discovery, such as drug-target validation and pharmacogenomics studies. Arrays of antigens and antibodies have been produced and used for multianalyte immunoassays microspot immunoassays, microarray ELISAs and to assess protein—protein, protein—DNA, protein—RNA, and protein—ligand interactions.
Arrays of single-stranded oligonucleotides on a surface can be used for surface-based DNA computing as a means of solving certain intractable computational problems. The internal sequence of an oligonucleotide e. The collection of oligonucleotides is arrayed, and locations on the array are interrogated by successive hybridization with a set of molecules and exonuclease digestion steps that remove single-stranded oligonucleotides.
Molecules remaining on the surface yield the answer to the computational problem. Microarray experiments produce enormous amounts of data, leading to new requirements and challenges for bioinformatics. Numerous approaches to data analysis have been developed on the basis of different algorithms and Bayesian networks, as well as neural, multivariate, clustering, and knowledge-based analysis.
Information retrieval, data mining, the development of tools for mining data, and database development are now critical issues for the effective use of microarray technology. The list of patents and published patent applications covers a broad range of microarray technology. The commercial potential of microarrays has led to aggressive protection of intellectual property in this area 6. Phimster B. Going global. Nat Genet ; 21 Suppl 1 : 1.
Schena M eds. Multiple authors. The chipping forecast. The data gathered through microarrays can be used to create gene expression profiles, which show simultaneous changes in the expression of many genes in response to a particular condition or treatment. Related Concepts 6.
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A signal resulting from hybridization of the labeled target with the specific immobilized probe identifies which RNAs are present in the unknown target sample.
Prevention, diagnosis, and treatment in dental practice are based on an understanding of the biology of underlying oral health and disease. Few aspects of patient care will remain untouched by today's rapid advances in biological research. In the future, dentists may use inexpensive but remarkably sophisticated diagnostic tests to diagnose infection, oral lesions, and symptoms of temporomandibular dysfunction TMD.
The small variations in the DNA sequence that lead to different characteristics such as skin color, facial features, or height are known as polymorphisms, which also can cause or contribute to the development of many syndromes and diseases. Microarray provides a basis to genotype thousands of different loci at a time, which is useful for association and linkage studies to isolate chromosomal regions related to a particular disease. This array also can be used to locate chromosomal aberrations related to cancer, such as segments of allelic imbalance, which can be identified by loss of heterozygosity.
The different DNA fragments are arranged in rows and columns such that the identity of each fragment is known through its location on the array.
Two types of microarrays are gene expression microarray and tissue microarray TMA. Techniques like Northern blot and reverse transcriptase-polymerase chain reaction RT-PCR allow testing for only a few genes per experiment. Whenever some genes are expressed or are in their active state, many copies of mRNA corresponding to the particular genes are produced by a process called transcription.
These mRNAs synthesize the corresponding protein by translation. So, indirectly by assessing the various mRNAs, we can assess the genetic information or the gene expression. This helps in the understanding of various processes behind every altered genetic expression. Thus, mRNA acts as a surrogate marker.
The principle behind microarrays is that complementary sequences will bind to each other. The unknown DNA molecules are cut into fragments by restriction endonucleases; fluorescent markers are attached to these DNA fragments. These are then allowed to react with probes of the DNA chip.
The remaining DNA fragments are washed away. The target DNA pieces can be identified by their fluorescence emission by passing a laser beam. A computer is used to record the pattern of fluorescence emission and DNA identification. This technique of employing DNA chips is very rapid, besides being sensitive and specific for the identification of several DNA fragments simultaneously.
TMAs are similar to gene expression microarrays in having samples arrayed in rows and columns on a glass slide; they differ in that each element on the TMA slide corresponds to a single patient sample, allowing multiple patient samples to be assessed for a single molecular marker in one experiment, while gene expression arrays allow assessment of thousands of molecular markers on a single patient sample per experiment.
Tumor formation involves simultaneous changes in hundreds of cells and variations in genes. Microarray can be a boon to researchers as it provides a platform for simultaneous testing of a large set of genetic samples. It helps especially in the identification of single-nucleotide polymorphisms SNPs and mutations, classification of tumors, identification of target genes of tumor suppressors, identification of cancer biomarkers, identification of genes associated with chemoresistance, and drug discovery.
For example, we can compare the different patterns of gene expression levels between a group of cancer patients and a group of normal patients and identify the gene associated with that particular cancer.
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