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Gene, Genomics And DNA Arrays

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To take complete advantage of the large and rapidly increasing body of sequence information, advanced technologies are very much required. Among the most powerful tools for genomics are high-density arrays of oligonucleotides or cDNAs. Exploration of the genome using DNA microarray should narrow the gap in our knowledge between gene function and molecular biology. Nucleic acid arrays or simply DNA arrays work by hybridisation of labelled RNA or DNA in a solution to DNA molecules attached to a unique location on the surface.


Scientists know that a mutation or any kind of alteration in a particular gene’s DNA may lead to a specific disease. However, it can be very difficult to develop a test to detect these mutations because most of the large genes have several regions for mutations to occur. Microarray is a technology where thousands of nucleic acids are bound to a surface and are used to measure the relative concentration of the nucleic acid sequence in a mixture via subsequent hybridisation events. A DNA array is used to probe a soln. of a mixture of labelled nucleic acids and the binding of these targets to the probes on the array is used to measure the relative concentration of nucleic acid species in a soln. DNA microarrays allow for the comparison of thousands of gene at a go. It is most powerful when used on species with sequenced genome. Gene expression data can provide the information of the function or expression of those uncharacterized genes. They are used to study the extent to which certain genes are turned on or off in cells. They are also used in certain clinical diagnostic tests for some diseases.


Genomic tools such as arrays or microarrays do not preclude hypthothesis driven research. For fully sequenced organisms, arrays containing probes for every annotated gene in the entire genome have been produced. Full genome arrays allow the chromosomal landscape of silencing to be mapped and make it possible to test whether what is true for a handful of well studied genes near the telomeres is true for all telomeric genes and whether any centromere-proximal genes are also transcriptionally silenced.


They are a group of technologies in which specific DNA sequences are deposited or synthesized in a 2-D array in such a way that the DNA is covalently or non covalently attached to the surface. In the array analysis, a nucleic acid-containing sample is labelled then they are allowed to hybridise with the gene specific targets on the array. Based on the amount of probe hybridised to each of the target spots, information is gained against a specific nucleic acid composition. Major advantages of gene arrays include providing information on thousands of targets in single experiment only.

Many terms exist for these DNA arrays like gene arrays, biochip, DNA chip, gene chip, micro and macroarrays. When biochip or gene chip or DNA chip is used, it refers to arrays on glass support. Microarrays and macroarrays are used to differentiate the spot size or the no. of spots on the support. Gene arrays used for sequence identification (for ex. Mutation analysis). Microarrays have been used in cancer research to address three main objectives: determining the molecular differences between normal and malignant cells; improving the classification of tumours to increase the effectiveness of therapeutics; and identifying mutations in genes that are implicated in tumour formation or progression. DNA arrays can also offer potential and prognostic information regarding the breast cancers in today’s world.


Advances in cancer research can be facilitated by studies that use microarrays to explore the function of genes implicated in tumour progression or genetic susceptibility. For example, women with a germ-line mutation in BRCA1 are predisposed to breast and ovarian cancer Researchers believe that mutations in the genes BRCA1 and BRCA2 cause as many as 60% of all cases of hereditary breast and ovarian cancers. Researchers have already discovered over 800 different mutations in BRCA1 alone About 90% breast cancer is always due to genetic abnormalities such as variations in high-penetrance genes such as BRCA1, BRCA2, p53, PTEN, ATM, NBS1, LKB1, etc. In addition, the AR, ATM, BARD1, BRIP1, RAD50, and RAD51 genes are associated with breast cancer. The DNA microarray is a tool used to determine whether the DNA from a particular individual contains a mutation in genes like BRCA1 and BRCA2. This technique has identified single base insertions, deletions, and substitutions in three different tumour suppressor genes, BRCA1, BRCA2, and p53. Various microarray-based online tools have been developed with promises of assistance to the treatment decisions for breast cancer patients. Gene expression-based Outcome for Breast cancer Online (GOBO) is one of newly developed online tool which has three main applications: Gene Set Analysis (GSA), Co-expressed Genes (CG), and Sample Prediction (SP).

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Microarrays have also been used in combination with chromatin immunoprecipitation (Solomon et al., 1988) to determine the binding sites of transcription factors (Horak and Snyder, 2002; Iyer et al., 2001). In brief, transcription factors (TFs) are cross linked to DNA with formaldehyde and the DNA is fragmented. The TF(s) of interest (with the DNA to which they were bound still attached) are affinity purified using either an antibody to the TF or by tagging the transcription factor with peptide that’s amenable to affinity chromatography (for example a FLAG-, HIS-, myc or HA-tag). After purification, the DNA is released from the TF, amplified, labelled and hybridized to the array. This technique is commonly referred to as “ChIP-chip” for Chromatin Immuno-Precipitation on a “chip” or microarray.


Identification of environmental carcinogens and other hazards constitutes a major challenge in the field of toxicology. One must identify trans-species, chemical-specific biomarkers that result from quantified exposures to drugs or toxic chemicals. The potential of DNA microarray technology to identify gene expression changes associated with toxic or pharmacologic processes has been the focus of several studies. For example, the biochemical and molecular mechanisms of lead neurotoxicity revealed that lead has been shown to interfere with several signal transduction pathways. Changes in gene expression in target cells are hypothesized to be a mechanism by which this chemical interferes with normal brain development. (Hossain et al.) studied the mechanisms underlying lead neurotoxicity using cDNA microarray gene expression analysis and identified lead-sensitive genes in immortalized human fetal astrocytes (SVFHA). Their findings indicated that lead induces vascular endothelial growth factor (VEGF) expression in SV-FHAs via a pathway involving protein kinase C and the AP-1 transcription factor. This report highlights the potential of DNA microarrays for the discovery of novel toxicant-induced gene expression alterations and the ability to dissect the second messenger pathways and transcription factors mediating these changes. Microarray experiments using pharmacologic agents have focused on identification of mechanisms for drug action as well as isolation of potential drug targets. A study described a method for drug target validation and identification of secondary drug target effects based on genome-wide gene expression patterns. Researchers generated mutations in yeast genes encoding targets of the immunosuppressant drugs cyclosporin A or FK506. Expression profiles were then identified for both mutant and wild-type cells after drug treatment to verify essential components of the drug’s molecular mechanism. The described method permitted direct confirmation of drug targets and recognition of drug-dependent changes in gene expression, including those mediated through pathways distinct from the drug’s intended target. This parallel approach in comparison of wild-type and mutant cells may help improve the efficiency of the drug development process.

SNP (Single Nucleotide Polymorphism) ARRAYS

It is a useful tool for studying slight amount of variations in a whole genome. The most important clinical applications for the SNP arrays are for determining disease susceptibility and for measuring the efficacy of drug therapies designed specifically for individuals. It can be used to detect constitutional imbalances, loss of heterozygocity (LOH), etc. They can be used to map disease loci, determine disease susceptibility genes in individuals. For example diseases such as rheumatoid arthritis, prostate cancer, type 2 diabetes.

Cancer development is accompanied by multiple genetic alterations including chromosomal copy number and structural changes. Identification of all genetic alterations is essential for a full understanding of the etiology of human cancer. Genetic analysis using a genome-wide detection tool is an essential approach to uncover all abnormalities and is also an efficient way to identify key genetic events, such as activation of oncogenes and inactivation of tumour suppressor genes in cancer development and progression. Such an approach can lead to quick discovery of genetic markers for cancer risk assessment, diagnosis and prognosis. SNP arrays are used to study the genetic abnormalities in cancer. It can be used to study LOH which occurs very commonly in oncogenesis. For example, tumour suppressor genes prevent the cancer from developing. If an individual has one mutated dysfunctional copy of the tumour suppressor gene and his second, functional copy of the gene gets damaged anyhow, they may become more likely to develop cancer. High density SNP arrays help identify patterns of allelic imbalance. Because LOH is so common in many human cancers, SNP arrays have great potential in cancer diagnostics. Recent studies showed that solid tumours such as gastric cancers and liver cancers show LOH. Due to the complexity of genetic alterations in cancer cells, high density SNP array analysis is a very demanding technique in the field of cancer research. The initial purpose of SNP array development was to genotype multiple SNPs simultaneously. Therefore they were first used in cancer research for LOH and AI analyses which are important for tumour suppressor gene identification. In 2000, Lindblad-Toh et al. first applied SNPs array in a LOH study of human cancers. Analyzing small-cell lung cancer and control DNA samples, they found that the SNP arrays detected the same patterns of LOH as simple sequence length polymorphism (SSLPs or micro-satellites) analysis. In breast cancer, SNP array analysis detected LOH patterns associated with tumour subgroups which were also partially defined by gene expression patterns.

Compared with other array technology, the high density resolution of SNP arrays is clearly an advantage. It is estimated that there are over 20 million SNPs in the entire human genome, on average every 150 base pair per SNP. The whole-genome genotyping SNP array technology under current development has the potential to comprise almost all existing SNPs into a single experiment. The resolution of genetic abnormalities picked up by high density SNP array analysis will be more than sufficient for direct PCR and sequencing analysis. The unique feature of SNP arrays and the concurrent analysis of both genotype and DNA copy number changes, make SNP arrays irreplaceable by any other high throughput technology.


Although the next big thing in genomics which is Next generation sequencing (NGS), has already made its place in this area, microarrays will continue to be used on a wide scale because of various factors like:

  1. Microarray technology is cheaper as compared to establishing the complete pipeline for next generation sequencing(NGS).
  2. Since, NGS is still new for many users, researchers across the globe would continue using microarrays until they learn enough of NGS to replace microarray workflow.
  3. Many hospitals, especially those working on cancer samples, still use microarrays at a large scale because they analyze thousands of samples on a daily basis per patient. The analysis/patient/day is cost effective.


  1. High Noise due to Cross Hybridization : Since this is essentially a hybridization experiment, binding of 2 molecules that are not completely complementary is a problem and gives out false results.
  2. Requires a well annotated genome: This is essential for designing the probes. This is a limiting step since the genome of an organism may not always be available.
  3. Limited range of signal detection : Due to high noise affecting the lower range of detection and saturation in detecting high signals, the actual range of detection is small.


For these array-based methods to become truly revolutionary, they must become an integral part of the daily activities of the typical molecular biology laboratory. Despite their impressive and rapidly growing résumé, these technologies are still in their infancy, with plenty of room for technical improvements, further development, and more widespread acceptance and accessibility. Nucleic acid array-based methods that previously seemed exotic, and too expensive, are becoming routine as indicated by the huge increase in the number of publications that incorporate data obtained in this way.

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Gene, Genomics And DNA Arrays. (2022, February 17). Edubirdie. Retrieved February 4, 2023, from
“Gene, Genomics And DNA Arrays.” Edubirdie, 17 Feb. 2022,
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Gene, Genomics And DNA Arrays [Internet]. Edubirdie. 2022 Feb 17 [cited 2023 Feb 4]. Available from:
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