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<title>DNA microarray</title>

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<span id="openzim-page-title" class="mw-page-title-main"><span class="mw-page-title-main">DNA microarray</span></span>

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<p>A <b>DNA microarray</b> (also commonly known as a <b>DNA chip</b> or <b><a href="Biochip" title="Biochip">biochip</a></b>) is a collection of microscopic <a href="DNA" title="DNA">DNA</a> spots attached to a solid surface. Scientists use DNA <a href="Microarray" title="Microarray">microarrays</a> to measure the <a href="Gene_expression" title="Gene expression">expression</a> levels of large numbers of genes simultaneously or to <a href="Genotyping" title="Genotyping">genotype</a> multiple regions of a genome. Each DNA spot contains <a href="Pico-" class="mw-redirect" title="Pico-">picomoles</a> (10<sup>−12</sup> <a href="Mole_(unit)" title="Mole (unit)">moles</a>) of a specific DNA sequence, known as <i><a href="Hybridization_probe" title="Hybridization probe">probes</a></i> (or <i>reporters</i> or <i><a href="Oligonucleotide" title="Oligonucleotide">oligos</a></i>). These can be a short section of a <a href="Gene" title="Gene">gene</a> or other DNA element that are used to <a href="Nucleic_acid_hybridization#Hybridization" title="Nucleic acid hybridization">hybridize</a> a <a href="CDNA" class="mw-redirect" title="CDNA">cDNA</a> or cRNA (also called anti-sense RNA) sample (called <i>target</i>) under high-stringency conditions. Probe-target hybridization is usually detected and quantified by detection of <a href="Fluorophore" title="Fluorophore">fluorophore</a>-, silver-, or <a href="Chemiluminescence" title="Chemiluminescence">chemiluminescence</a>-labeled targets to determine relative abundance of nucleic acid sequences in the target. The original nucleic acid arrays were macro arrays approximately 9 cm × 12 cm and the first computerized image based analysis was published in 1981.<sup id="cite_ref-Taub_1-0" class="reference"><a href="#cite_note-Taub-1"><span class="cite-bracket">[</span>1<span class="cite-bracket">]</span></a></sup> It was invented by <a href="Patrick_O._Brown" title="Patrick O. Brown">Patrick O. Brown</a>. An example of its application is in SNPs arrays for polymorphisms in cardiovascular diseases, cancer, pathogens and GWAS analysis. It is also used for the identification of structural variations and the measurement of gene expression.

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<div class="mw-heading mw-heading2"><h2 id="Principle">Principle</h2></div>

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</style><div role="note" class="hatnote navigation-not-searchable">Main article: <a href="Nucleic_acid_hybridization" title="Nucleic acid hybridization">Nucleic acid hybridization</a></div>

<div role="note" class="hatnote navigation-not-searchable">Further information: <a href="#A_typical_protocol">§ A typical protocol</a></div>

<p>The core principle behind microarrays is hybridization between two DNA strands, the property of <a href="Complementarity_(molecular_biology)" title="Complementarity (molecular biology)">complementary</a> nucleic acid sequences to specifically pair with each other by forming <a href="Hydrogen_bond" title="Hydrogen bond">hydrogen bonds</a> between complementary <a href="Nucleotide" title="Nucleotide">nucleotide base pairs</a>. A high number of complementary base pairs in a nucleotide sequence means tighter <a href="Non-covalent" class="mw-redirect" title="Non-covalent">non-covalent</a> bonding between the two strands. After washing off non-specific bonding sequences, only strongly paired strands will remain hybridized. Fluorescently labeled target sequences that bind to a probe sequence generate a signal that depends on the hybridization conditions (such as temperature), and washing after hybridization. Total strength of the signal, from a spot (feature), depends upon the amount of target sample binding to the probes present on that spot. Microarrays use relative quantitation in which the intensity of a feature is compared to the intensity of the same feature under a different condition, and the identity of the feature is known by its position.

</p>

<div class="mw-heading mw-heading2"><h2 id="Uses_and_types">Uses and types</h2></div>

<p>Many types of arrays exist and the broadest distinction is whether they are spatially arranged on a surface or on coded beads:

</p>

<ul><li>The traditional solid-phase array is a collection of orderly microscopic "spots", called features, each with thousands of identical and specific probes attached to a solid surface, such as <a href="Glass" title="Glass">glass</a>, <a href="Plastic" title="Plastic">plastic</a> or <a href="Silicon" title="Silicon">silicon</a> <a href="Biochip" title="Biochip">biochip</a> (commonly known as a <i>genome chip</i>, <i>DNA chip</i> or <i>gene array</i>). Thousands of these features can be placed in known locations on a single DNA microarray.</li>

<li>The alternative bead array is a collection of microscopic polystyrene beads, each with a specific probe and a ratio of two or more dyes, which do not interfere with the fluorescent dyes used on the target sequence.</li></ul>

<p>DNA microarrays can be used to detect DNA (as in <a href="Comparative_genomic_hybridization" title="Comparative genomic hybridization">comparative genomic hybridization</a>), or detect RNA (most commonly as <a href="CDNA" class="mw-redirect" title="CDNA">cDNA</a> after <a href="Reverse_transcription" class="mw-redirect" title="Reverse transcription">reverse transcription</a>) that may or may not be translated into proteins. The process of measuring gene expression via cDNA is called <a href="Gene_expression" title="Gene expression">expression analysis</a> or <a href="Expression_profiling" class="mw-redirect" title="Expression profiling">expression profiling</a>.

</p><p>Applications include:

</p>

<th>Application or technology

</th>

<th>Synopsis

</th></tr>

<tr>

<td><a href="Gene_expression_profiling" title="Gene expression profiling">Gene expression profiling</a>

</td>

<td>In an <a href="MRNA" class="mw-redirect" title="MRNA">mRNA</a> or <a href="Gene_expression_profiling" title="Gene expression profiling">gene expression profiling</a> experiment the <a href="Gene_expression" title="Gene expression">expression</a> levels of thousands of genes are simultaneously monitored to study the effects of certain treatments, <a href="Disease" title="Disease">diseases</a>, and developmental stages on gene expression. For example, microarray-based gene expression profiling can be used to identify genes whose expression is changed in response to <a href="Pathogens" class="mw-redirect" title="Pathogens">pathogens</a> or other organisms by comparing gene expression in infected to that in uninfected cells or tissues.<sup id="cite_ref-Adomas_et_al._2-0" class="reference"><a href="#cite_note-Adomas_et_al.-2"><span class="cite-bracket">[</span>2<span class="cite-bracket">]</span></a></sup>

</td></tr>

<tr>

<td><a href="Comparative_genomic_hybridization" title="Comparative genomic hybridization">Comparative genomic hybridization</a>

</td>

<td>Assessing genome content in different cells or closely related organisms, as originally described by <a href="Patrick_O._Brown" title="Patrick O. Brown">Patrick Brown</a>, Jonathan Pollack, Ash Alizadeh and colleagues at <a href="Stanford_University" title="Stanford University">Stanford</a>.<sup id="cite_ref-Pollack_et_al._3-0" class="reference"><a href="#cite_note-Pollack_et_al.-3"><span class="cite-bracket">[</span>3<span class="cite-bracket">]</span></a></sup><sup id="cite_ref-Moran_et_al._4-0" class="reference"><a href="#cite_note-Moran_et_al.-4"><span class="cite-bracket">[</span>4<span class="cite-bracket">]</span></a></sup>

</td></tr>

<tr>

<td>GeneID

</td>

<td>Small microarrays to check IDs of organisms in food and feed (like <a href="GMO" class="mw-redirect" title="GMO">GMO</a> <a rel="nofollow" class="external autonumber" href="https://web.archive.org/web/20090228210111/http://bgmo.jrc.ec.europa.eu/home/docs.htm">[1]</a>), <a href="Mycoplasms" class="mw-redirect" title="Mycoplasms">mycoplasms</a> in cell culture, or <a href="Pathogens" class="mw-redirect" title="Pathogens">pathogens</a> for disease detection, mostly combining <a href="Polymerase_chain_reaction" title="Polymerase chain reaction">PCR</a> and microarray technology.

</td></tr>

<tr>

<td><a href="ChIP-on-chip" title="ChIP-on-chip">Chromatin immunoprecipitation on Chip</a>

</td>

<td>DNA sequences bound to a particular protein can be isolated by <a href="Immunoprecipitation" title="Immunoprecipitation">immunoprecipitating</a> that protein (<a href="Chromatin_immunoprecipitation" title="Chromatin immunoprecipitation">ChIP</a>), these fragments can be then hybridized to a microarray (such as a <a href="Tiling_array" title="Tiling array">tiling array</a>) allowing the determination of protein binding site occupancy throughout the genome. Example protein to <a href="Chromatin_immunoprecipitation" title="Chromatin immunoprecipitation">immunoprecipitate</a> are histone modifications (<a href="H3K27me3" title="H3K27me3">H3K27me3</a>, H3K4me2, H3K9me3, etc.), <a href="Polycomb-group_protein" class="mw-redirect" title="Polycomb-group protein">Polycomb-group protein</a> (PRC2:Suz12, PRC1:YY1) and <a href="Trithorax-group_protein" class="mw-redirect" title="Trithorax-group protein">trithorax-group protein</a> (Ash1) to study the <a href="Epigenetics" title="Epigenetics">epigenetic landscape</a> or <a href="RNA_polymerase_II" title="RNA polymerase II">RNA polymerase II</a> to study the <a href="Transcription_(genetics)" class="mw-redirect" title="Transcription (genetics)">transcription landscape</a>.

</td></tr>

<tr>

<td><a href="DNA_adenine_methyltransferase_identification" title="DNA adenine methyltransferase identification">DamID</a>

</td>

<td>Analogously to <a href="ChIP" class="mw-redirect" title="ChIP">ChIP</a>, genomic regions bound by a protein of interest can be isolated and used to probe a microarray to determine binding site occupancy. Unlike ChIP, DamID does not require antibodies but makes use of adenine methylation near the protein's binding sites to selectively amplify those regions, introduced by expressing minute amounts of protein of interest fused to bacterial <a href="Dam_(methylase)" class="mw-redirect" title="Dam (methylase)">DNA adenine methyltransferase</a>.

</td></tr>

<tr>

<td><a href="SNP_array" title="SNP array">SNP detection</a>

</td>

<td>Identifying <a href="Single_nucleotide_polymorphism" class="mw-redirect" title="Single nucleotide polymorphism">single nucleotide polymorphism</a> among <a href="Alleles" class="mw-redirect" title="Alleles">alleles</a> within or between populations.<sup id="cite_ref-Hacia_et_al._5-0" class="reference"><a href="#cite_note-Hacia_et_al.-5"><span class="cite-bracket">[</span>5<span class="cite-bracket">]</span></a></sup> Several applications of microarrays make use of SNP detection, including <a href="Genotyping" title="Genotyping">genotyping</a>, <a href="Forensic" class="mw-redirect" title="Forensic">forensic</a> analysis, measuring <a href="Genetic_predisposition" title="Genetic predisposition">predisposition</a> to disease, identifying drug-candidates, evaluating <a href="Germline" title="Germline">germline</a> mutations in individuals or <a href="Somatic_(biology)" title="Somatic (biology)">somatic</a> mutations in cancers, assessing <a href="Loss_of_heterozygosity" title="Loss of heterozygosity">loss of heterozygosity</a>, or <a href="Genetic_linkage" title="Genetic linkage">genetic linkage</a> analysis.

</td></tr>

<tr>

<td><a href="Alternative_splicing" title="Alternative splicing">Alternative splicing</a> detection

</td>

<td>An <i>exon junction array</i> design uses probes specific to the expected or potential splice sites of predicted <a href="Exon" title="Exon">exons</a> for a gene. It is of intermediate density, or coverage, to a typical gene expression array (with 1–3 probes per gene) and a genomic tiling array (with hundreds or thousands of probes per gene). It is used to assay the expression of alternative splice forms of a gene. Exon arrays have a different design, employing probes designed to detect each individual exon for known or predicted genes, and can be used for detecting different splicing isoforms.

</td></tr>

<tr>

<td><a href="Fusion_gene" title="Fusion gene">Fusion genes</a> microarray

</td>

<td>A fusion gene microarray can detect fusion transcripts, <i>e.g.</i> from cancer specimens. The principle behind this is building on the <a href="Alternative_splicing" title="Alternative splicing">alternative splicing</a> microarrays. The oligo design strategy enables combined measurements of chimeric transcript junctions with exon-wise measurements of individual fusion partners.

</td></tr>

<tr>

<td><a href="Tiling_array" title="Tiling array">Tiling array</a>

</td>

<td>Genome tiling arrays consist of overlapping probes designed to densely represent a genomic region of interest, sometimes as large as an entire human chromosome. The purpose is to empirically detect expression of <a href="MRNA" class="mw-redirect" title="MRNA">transcripts</a> or <a href="Alternative_splicing" title="Alternative splicing">alternatively spliced forms</a> which may not have been previously known or predicted.

</td></tr>

<tr>

<td>Double-stranded B-DNA microarrays

</td>

<td>Right-handed double-stranded B-DNA microarrays can be used to characterize novel drugs and biologicals that can be employed to bind specific regions of immobilized, intact, double-stranded DNA. This approach can be used to inhibit gene expression.<sup id="cite_ref-Gagna_895–914_6-0" class="reference"><a href="#cite_note-Gagna_895–914-6"><span class="cite-bracket">[</span>6<span class="cite-bracket">]</span></a></sup><sup id="cite_ref-Gagna_381–401_7-0" class="reference"><a href="#cite_note-Gagna_381–401-7"><span class="cite-bracket">[</span>7<span class="cite-bracket">]</span></a></sup> They also allow for characterization of their structure under different environmental conditions.

</td></tr>

<tr>

<td>Double-stranded Z-DNA microarrays

</td>

<td>Left-handed double-stranded Z-DNA microarrays can be used to identify short sequences of the alternative Z-DNA structure located within longer stretches of right-handed B-DNA genes (e.g., transcriptional enhancement, recombination, RNA editing).<sup id="cite_ref-Gagna_895–914_6-1" class="reference"><a href="#cite_note-Gagna_895–914-6"><span class="cite-bracket">[</span>6<span class="cite-bracket">]</span></a></sup><sup id="cite_ref-Gagna_381–401_7-1" class="reference"><a href="#cite_note-Gagna_381–401-7"><span class="cite-bracket">[</span>7<span class="cite-bracket">]</span></a></sup> The microarrays also allow for characterization of their structure under different environmental conditions.

</td></tr>

<tr>

<td>Multi-stranded DNA microarrays (triplex-DNA microarrays and quadruplex-DNA microarrays)

</td>

<td>Multi-stranded DNA and RNA microarrays can be used to identify novel drugs that bind to these multi-stranded nucleic acid sequences. This approach can be used to discover new drugs and biologicals that have the ability to inhibit gene expression.<sup id="cite_ref-Gagna_895–914_6-2" class="reference"><a href="#cite_note-Gagna_895–914-6"><span class="cite-bracket">[</span>6<span class="cite-bracket">]</span></a></sup><sup id="cite_ref-Gagna_381–401_7-2" class="reference"><a href="#cite_note-Gagna_381–401-7"><span class="cite-bracket">[</span>7<span class="cite-bracket">]</span></a></sup><sup id="cite_ref-8" class="reference"><a href="#cite_note-8"><span class="cite-bracket">[</span>8<span class="cite-bracket">]</span></a></sup><sup id="cite_ref-9" class="reference"><a href="#cite_note-9"><span class="cite-bracket">[</span>9<span class="cite-bracket">]</span></a></sup> These microarrays also allow for characterization of their structure under different environmental conditions.

</td></tr></tbody></table>

<p>Specialised arrays tailored to particular <a href="Crop" title="Crop">crops</a> are becoming increasingly popular in <a href="Molecular_breeding" title="Molecular breeding">molecular breeding</a> applications. In the future they could be used to screen <a href="Seedling" title="Seedling">seedlings</a> at early stages to lower the number of unneeded seedlings tried out in breeding operations.<sup id="cite_ref-Rasheed-et-al-2017_10-0" class="reference"><a href="#cite_note-Rasheed-et-al-2017-10"><span class="cite-bracket">[</span>10<span class="cite-bracket">]</span></a></sup>

</p>

<div class="mw-heading mw-heading3"><h3 id="Fabrication">Fabrication</h3></div>

<p>Microarrays can be manufactured in different ways, depending on the number of probes under examination, costs, customization requirements, and the type of scientific question being asked. Arrays from commercial vendors may have as few as 10 probes or as many as 5 million or more micrometre-scale probes.

</p>

<div class="mw-heading mw-heading3"><h3 id="Spotted_vs._in_situ_synthesised_arrays">Spotted vs. <i>in situ</i> synthesised arrays</h3></div>

<p>Microarrays can be fabricated using a variety of technologies, including printing with fine-pointed pins onto glass slides, <a href="Photolithography" title="Photolithography">photolithography</a> using pre-made masks, photolithography using dynamic micromirror devices, ink-jet printing,<sup id="cite_ref-11" class="reference"><a href="#cite_note-11"><span class="cite-bracket">[</span>11<span class="cite-bracket">]</span></a></sup><sup id="cite_ref-12" class="reference"><a href="#cite_note-12"><span class="cite-bracket">[</span>12<span class="cite-bracket">]</span></a></sup> or <a href="Electrochemistry" title="Electrochemistry">electrochemistry</a> on microelectrode arrays.

</p><p>In <i>spotted microarrays</i>, the probes are <a href="Oligonucleotide_synthesis" title="Oligonucleotide synthesis">oligonucleotides</a>, <a href="CDNA" class="mw-redirect" title="CDNA">cDNA</a> or small fragments of <a href="Polymerase_chain_reaction" title="Polymerase chain reaction">PCR</a> products that correspond to <a href="MRNA" class="mw-redirect" title="MRNA">mRNAs</a>. The probes are <a href="Oligonucleotide_synthesis" title="Oligonucleotide synthesis">synthesized</a> prior to deposition on the array surface and are then "spotted" onto glass. A common approach utilizes an array of fine pins or needles controlled by a robotic arm that is dipped into wells containing DNA probes and then depositing each probe at designated locations on the array surface. The resulting "grid" of probes represents the nucleic acid profiles of the prepared probes and is ready to receive complementary cDNA or cRNA "targets" derived from experimental or clinical samples.

This technique is used by research scientists around the world to produce "in-house" printed microarrays in their own labs. These arrays may be easily customized for each experiment, because researchers can choose the probes and printing locations on the arrays, synthesize the probes in their own lab (or collaborating facility), and spot the arrays. They can then generate their own labeled samples for hybridization, hybridize the samples to the array, and finally scan the arrays with their own equipment. This provides a relatively low-cost microarray that may be customized for each study, and avoids the costs of purchasing often more expensive commercial arrays that may represent vast numbers of genes that are not of interest to the investigator.

Publications exist which indicate in-house spotted microarrays may not provide the same level of sensitivity compared to commercial oligonucleotide arrays,<sup id="cite_ref-TRC_Standardization_13-0" class="reference"><a href="#cite_note-TRC_Standardization-13"><span class="cite-bracket">[</span>13<span class="cite-bracket">]</span></a></sup> possibly owing to the small batch sizes and reduced printing efficiencies when compared to industrial manufactures of oligo arrays.

</p><p>In <i>oligonucleotide microarrays</i>, the probes are short sequences designed to match parts of the sequence of known or predicted <a href="Open_reading_frame" title="Open reading frame">open reading frames</a>. Although oligonucleotide probes are often used in "spotted" microarrays, the term "oligonucleotide array" most often refers to a specific technique of manufacturing. Oligonucleotide arrays are produced by printing short oligonucleotide sequences designed to represent a single gene or family of gene splice-variants by <a href="Oligonucleotide_synthesis" title="Oligonucleotide synthesis">synthesizing</a> this sequence directly onto the array surface instead of depositing intact sequences. Sequences may be longer (60-mer probes such as the <a href="Agilent" class="mw-redirect" title="Agilent">Agilent</a> design) or shorter (25-mer probes produced by <a href="Affymetrix" title="Affymetrix">Affymetrix</a>) depending on the desired purpose; longer probes are more specific to individual target genes, shorter probes may be spotted in higher density across the array and are cheaper to manufacture.

One technique used to produce oligonucleotide arrays include <a href="Photolithographic" class="mw-redirect" title="Photolithographic">photolithographic</a> synthesis (Affymetrix) on a silica substrate where light and light-sensitive masking agents are used to "build" a sequence one nucleotide at a time across the entire array.<sup id="cite_ref-Affy_PNAS_Paper_14-0" class="reference"><a href="#cite_note-Affy_PNAS_Paper-14"><span class="cite-bracket">[</span>14<span class="cite-bracket">]</span></a></sup> Each applicable probe is selectively "unmasked" prior to bathing the array in a solution of a single nucleotide, then a masking reaction takes place and the next set of probes are unmasked in preparation for a different nucleotide exposure. After many repetitions, the sequences of every probe become fully constructed. More recently, Maskless Array Synthesis from NimbleGen Systems has combined flexibility with large numbers of probes.<sup id="cite_ref-NimbleGen_Genome_Res_Paper_15-0" class="reference"><a href="#cite_note-NimbleGen_Genome_Res_Paper-15"><span class="cite-bracket">[</span>15<span class="cite-bracket">]</span></a></sup>

</p>

<div class="mw-heading mw-heading3"><h3 id="Two-channel_vs._one-channel_detection">Two-channel vs. one-channel detection</h3></div>

<p><i>Two-color microarrays</i> or <i>two-channel microarrays</i> are typically <a href="DNA_hybridization" class="mw-redirect" title="DNA hybridization">hybridized</a> with cDNA prepared from two samples to be compared (e.g. diseased tissue versus healthy tissue) and that are labeled with two different <a href="Fluorophore" title="Fluorophore">fluorophores</a>.<sup id="cite_ref-Shalon_et_al._16-0" class="reference"><a href="#cite_note-Shalon_et_al.-16"><span class="cite-bracket">[</span>16<span class="cite-bracket">]</span></a></sup> <a href="Fluorescence" title="Fluorescence">Fluorescent</a> dyes commonly used for cDNA labeling include <a href="Cyanine" title="Cyanine">Cy</a>3, which has a fluorescence emission wavelength of 570 nm (corresponding to the green part of the light spectrum), and <a href="Cyanine" title="Cyanine">Cy</a>5 with a fluorescence emission wavelength of 670 nm (corresponding to the red part of the light spectrum). The two Cy-labeled cDNA samples are mixed and hybridized to a single microarray that is then scanned in a microarray scanner to visualize fluorescence of the two fluorophores after <a href="Excited_state" title="Excited state">excitation</a> with a <a href="Laser" title="Laser">laser</a> beam of a defined wavelength. Relative intensities of each fluorophore may then be used in ratio-based analysis to identify up-regulated and down-regulated genes.<sup id="cite_ref-Tang_et_al._17-0" class="reference"><a href="#cite_note-Tang_et_al.-17"><span class="cite-bracket">[</span>17<span class="cite-bracket">]</span></a></sup>

</p><p>Oligonucleotide microarrays often carry control probes designed to hybridize with <a href="RNA_spike-in" title="RNA spike-in">RNA spike-ins</a>. The degree of hybridization between the spike-ins and the control probes is used to <a href="Normalization_(statistics)" title="Normalization (statistics)">normalize</a> the hybridization measurements for the target probes. Although absolute levels of gene expression may be determined in the two-color array in rare instances, the relative differences in expression among different spots within a sample and between samples is the preferred method of <a href="Data_analysis" title="Data analysis">data analysis</a> for the two-color system. Examples of providers for such microarrays includes <a href="Agilent" class="mw-redirect" title="Agilent">Agilent</a> with their Dual-Mode platform, <a href="Eppendorf_(company)" title="Eppendorf (company)">Eppendorf</a> with their DualChip platform for colorimetric <a href="Silverquant" title="Silverquant">Silverquant</a> labeling, and TeleChem International with Arrayit.

</p><p>In <i>single-channel microarrays</i> or <i>one-color microarrays</i>, the arrays provide intensity data for each probe or probe set indicating a relative level of hybridization with the labeled target. However, they do not truly indicate abundance levels of a gene but rather relative abundance when compared to other samples or conditions when processed in the same experiment. Each RNA molecule encounters protocol and batch-specific bias during amplification, labeling, and hybridization phases of the experiment making comparisons between genes for the same microarray uninformative. The comparison of two conditions for the same gene requires two separate single-dye hybridizations. Several popular single-channel systems are the Affymetrix "Gene Chip", Illumina "Bead Chip", Agilent single-channel arrays, the Applied Microarrays "CodeLink" arrays, and the Eppendorf "DualChip & Silverquant". One strength of the single-dye system lies in the fact that an aberrant sample cannot affect the raw data derived from other samples, because each array chip is exposed to only one sample (as opposed to a two-color system in which a single low-quality sample may drastically impinge on overall data precision even if the other sample was of high quality). Another benefit is that data are more easily compared to arrays from different experiments as long as batch effects have been accounted for.

</p><p>One channel microarray may be the only choice in some situations. Suppose <span class="mwe-math-element mwe-math-element-inline"><span class="mwe-math-mathml-inline mwe-math-mathml-a11y" style="display: none;"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="{\displaystyle i}">

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</p>

<th>number of samples

</th>

<th>one-channel microarray

</th>

<th>two channel microarray

</th>

<th>

<p>two channel microarray (with reference)

</p>

</th></tr>

<tr>

<td>1

</td>

<td>1

</td>

<td>1

</td>

<td>1

</td></tr>

<tr>

<td>2

</td>

<td>2

</td>

<td>1

</td>

<td>1

</td></tr>

<tr>

<td>3

</td>

<td>3

</td>

<td>3

</td>

<td>2

</td></tr>

<tr>

<td>4

</td>

<td>4

</td>

<td>6

</td>

<td>3

</td></tr>

<tr>

</mstyle>

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</semantics>

</td>

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</td>

</mrow>

</mstyle>

</mrow>

<annotation encoding="application/x-tex">{\displaystyle i(i-1)/2}</annotation>

</semantics>

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</td>

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<annotation encoding="application/x-tex">{\displaystyle i-1}</annotation>

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</math></span><img src="./9d2ca5c639f26340e0e80f5883cc93a00254513c.svg" class="mwe-math-fallback-image-inline mw-invert skin-invert" aria-hidden="true" style="vertical-align: -0.505ex; width:4.805ex; height:2.343ex;" alt="{\displaystyle i-1}" loading="lazy"></span>

</td></tr></tbody></table>

<div class="mw-heading mw-heading3"><h3 id="A_typical_protocol">A typical protocol</h3></div>

<p>This is an example of a <b>DNA microarray experiment</b> which includes details for a particular case to better explain DNA microarray experiments, while listing modifications for RNA or other alternative experiments.

</p>

<ol><li>The two samples to be compared (pairwise comparison) are grown/acquired. In this example treated sample (<a href="Case-control" class="mw-redirect" title="Case-control">case</a>) and untreated sample (<a href="Case-control" class="mw-redirect" title="Case-control">control</a>).</li>

<li>The <a href="Nucleic_acid" title="Nucleic acid">nucleic acid</a> of interest is purified: this can be <a href="RNA" title="RNA">RNA</a> for <a href="Expression_profiling" class="mw-redirect" title="Expression profiling">expression profiling</a>, <a href="DNA" title="DNA">DNA</a> for <a href="Comparative_hybridization" class="mw-redirect" title="Comparative hybridization">comparative hybridization</a>, or DNA/RNA bound to a particular <a href="Protein" title="Protein">protein</a> which is <a href="Chromatin_immunoprecipitation" title="Chromatin immunoprecipitation">immunoprecipitated</a> (<a href="ChIP-on-chip" title="ChIP-on-chip">ChIP-on-chip</a>) for <a href="Epigenetics" title="Epigenetics">epigenetic</a> or regulation studies. In this example total RNA is isolated (both nuclear and <a href="Cytoplasm" title="Cytoplasm">cytoplasmic</a>) by <a href="Guanidinium_thiocyanate-phenol-chloroform_extraction" class="mw-redirect" title="Guanidinium thiocyanate-phenol-chloroform extraction">guanidinium thiocyanate-phenol-chloroform extraction</a> (e.g. <a href="Trizol" title="Trizol">Trizol</a>) which isolates most RNA (whereas column methods have a cut off of 200 nucleotides) and if done correctly has a better purity.</li>

<li>The purified RNA is analysed for quality (by <a href="Capillary_electrophoresis" title="Capillary electrophoresis">capillary electrophoresis</a>) and quantity (for example, by using a NanoDrop or NanoPhotometer <a href="Spectrometer" title="Spectrometer">spectrometer</a>). If the material is of acceptable quality and sufficient quantity is present (e.g., >1<a href="%CE%9Cg" class="mw-redirect" title="Μg">μg</a>, although the required amount varies by microarray platform), the experiment can proceed.</li>

<li>The labeled product is generated via <a href="Reverse_transcription" class="mw-redirect" title="Reverse transcription">reverse transcription</a> and followed by an optional <a href="Polymerase_chain_reaction" title="Polymerase chain reaction">PCR</a> amplification. The RNA is reverse transcribed with either polyT primers (which amplify only <a href="MRNA" class="mw-redirect" title="MRNA">mRNA</a>) or random primers (which amplify all RNA, most of which is <a href="RRNA" class="mw-redirect" title="RRNA">rRNA</a>). <a href="MicroRNA" title="MicroRNA">miRNA</a> microarrays ligate an oligonucleotide to the purified small RNA (isolated with a fractionator), which is then reverse transcribed and amplified.

<ul><li>The label is added either during the reverse transcription step, or following amplification if it is performed. The <a href="Sense_(molecular_biology)" title="Sense (molecular biology)">sense</a> labeling is dependent on the microarray; e.g. if the label is added with the RT mix, the <a href="CDNA" class="mw-redirect" title="CDNA">cDNA</a> is antisense and the microarray probe is sense, except in the case of negative controls.</li>

<li>The label is typically <a href="Fluorescent" class="mw-redirect" title="Fluorescent">fluorescent</a>; only one machine uses <a href="Radioactivity_in_biology" class="mw-redirect" title="Radioactivity in biology">radiolabels</a>.</li>

<li>The labeling can be direct (not used) or indirect (requires a coupling stage). For two-channel arrays, the coupling stage occurs before hybridization, using <a href="Aminoallyl" class="mw-redirect" title="Aminoallyl">aminoallyl</a> <a href="Uridine" title="Uridine">uridine</a> <a href="Triphosphate" class="mw-redirect" title="Triphosphate">triphosphate</a> (aminoallyl-UTP, or aaUTP) and <a href="N-hydroxysuccinimide" class="mw-redirect" title="N-hydroxysuccinimide">NHS</a> amino-reactive dyes (such as <a href="Cyanine" title="Cyanine">cyanine dyes</a>); for single-channel arrays, the coupling stage occurs after hybridization, using <a href="Biotin#Use_in_biotechnology" title="Biotin">biotin</a> and labeled <a href="Streptavidin#Uses_in_biotechnology" title="Streptavidin">streptavidin</a>. The modified nucleotides (usually in a ratio of 1 aaUTP: 4 TTP (<a href="Thymidine_triphosphate" title="Thymidine triphosphate">thymidine triphosphate</a>)) are added enzymatically in a low ratio to normal nucleotides, typically resulting in 1 every 60 bases. The aaDNA is then purified with a <a href="DNA_separation_by_silica_adsorption" title="DNA separation by silica adsorption">column</a> (using a phosphate buffer solution, as <a href="Tris" title="Tris">Tris</a> contains amine groups). The aminoallyl group is an amine group on a long linker attached to the nucleobase, which reacts with a reactive dye.

<ul><li>A form of replicate known as a dye flip can be performed to control for dye <a href="Artifact_(error)" title="Artifact (error)">artifacts</a> in two-channel experiments; for a dye flip, a second slide is used, with the labels swapped (the sample that was labeled with Cy3 in the first slide is labeled with Cy5, and vice versa). In this example, <a href="Aminoallyl" class="mw-redirect" title="Aminoallyl">aminoallyl</a>-UTP is present in the reverse-transcribed mixture.</li></ul></li></ul></li>

<li>The labeled samples are then mixed with a proprietary <a href="Nucleic_acid_hybridization" title="Nucleic acid hybridization">hybridization</a> solution which can consist of <a href="Sodium_dodecyl_sulfate" title="Sodium dodecyl sulfate">SDS</a>, <a href="Citrate" class="mw-redirect" title="Citrate">SSC</a>, <a href="Dextran" title="Dextran">dextran sulfate</a>, a blocking agent (such as <a href="Comparative_genomic_hybridization#Blocking" title="Comparative genomic hybridization">Cot-1 DNA</a>, salmon sperm DNA, calf thymus DNA, <a href="PolyA" class="mw-redirect" title="PolyA">PolyA</a>, or PolyT), Denhardt's solution, or <a href="Methylamine" title="Methylamine">formamine</a>.</li>

<li>The mixture is denatured and added to the pinholes of the microarray. The holes are sealed and the microarray hybridized, either in a hyb oven, where the microarray is mixed by rotation, or in a mixer, where the microarray is mixed by alternating pressure at the pinholes.</li>

<li>After an overnight hybridization, all nonspecific binding is washed off (SDS and SSC).</li>

<li>The microarray is dried and scanned by a machine that uses a laser to excite the dye and measures the emission levels with a detector.</li>

<li>The image is gridded with a template and the intensities of each feature (composed of several pixels) is quantified.</li>

<li>The raw data is normalized; the simplest normalization method is to subtract background intensity and scale so that the total intensities of the features of the two channels are equal, or to use the intensity of a reference gene to calculate the <a href="T-value" class="mw-redirect" title="T-value">t-value</a> for all of the intensities. More sophisticated methods include <a href="Z-score" class="mw-redirect" title="Z-score">z-ratio</a>, <a href="Local_regression" title="Local regression">loess and lowess regression</a> and RMA (robust multichip analysis) for Affymetrix chips (single-channel, silicon chip, <i>in situ</i> synthesized short oligonucleotides).</li></ol>

<div class="mw-heading mw-heading2"><h2 id="Microarrays_and_bioinformatics">Microarrays and bioinformatics</h2></div>

<p>The advent of inexpensive microarray experiments created several specific bioinformatics challenges:<sup id="cite_ref-19" class="reference"><a href="#cite_note-19"><span class="cite-bracket">[</span>19<span class="cite-bracket">]</span></a></sup> the multiple levels of replication in experimental design (<a href="#Experimental_design">Experimental design</a>); the number of platforms and independent groups and data format (<a href="#Standardization">Standardization</a>); the statistical treatment of the data (<a href="#Data_analysis">Data analysis</a>); mapping each probe to the <a href="MRNA" class="mw-redirect" title="MRNA">mRNA</a> transcript that it measures (<a href="#Annotation">Annotation</a>); the sheer volume of data and the ability to share it (<a href="#Data_warehousing">Data warehousing</a>).

</p>

<div class="mw-heading mw-heading3"><h3 id="Experimental_design">Experimental design</h3></div>

<p>Due to the biological complexity of gene expression, the considerations of experimental design that are discussed in the <a href="Expression_profiling" class="mw-redirect" title="Expression profiling">expression profiling</a> article are of critical importance if statistically and biologically valid conclusions are to be drawn from the data.

</p><p>There are three main elements to consider when designing a microarray experiment. First, replication of the biological samples is essential for drawing conclusions from the experiment. Second, technical replicates (e.g. two RNA samples obtained from each experimental unit) may help to quantitate precision. The biological replicates include independent RNA extractions. Technical replicates may be two <a href="https://en.wiktionary.org/wiki/Special:Search/aliquot" class="extiw external" title="wikt:Special:Search/aliquot">aliquots</a> of the same extraction. Third, spots of each cDNA clone or oligonucleotide are present as replicates (at least duplicates) on the microarray slide, to provide a measure of technical precision in each hybridization. It is critical that information about the sample preparation and handling is discussed, in order to help identify the independent units in the experiment and to avoid inflated estimates of <a href="Statistical_significance" title="Statistical significance">statistical significance</a>.<sup id="cite_ref-20" class="reference"><a href="#cite_note-20"><span class="cite-bracket">[</span>20<span class="cite-bracket">]</span></a></sup>

</p>

<div class="mw-heading mw-heading3"><h3 id="Standardization">Standardization</h3></div>

<p>Microarray data is difficult to exchange due to the lack of standardization in platform fabrication, assay protocols, and analysis methods. This presents an <a href="Interoperability" title="Interoperability">interoperability</a> problem in <a href="Bioinformatics" title="Bioinformatics">bioinformatics</a>. Various <a href="Grass-roots" class="mw-redirect" title="Grass-roots">grass-roots</a> <a href="Open-source_model" class="mw-redirect" title="Open-source model">open-source</a> projects are trying to ease the exchange and analysis of data produced with non-proprietary chips:

</p><p>For example, the "Minimum Information About a Microarray Experiment" (<a href="MIAME" class="mw-redirect" title="MIAME">MIAME</a>) checklist helps define the level of detail that should exist and is being adopted by many <a href="Scientific_journal" title="Scientific journal">journals</a> as a requirement for the submission of papers incorporating microarray results. But MIAME does not describe the format for the information, so while many formats can support the MIAME requirements, as of 2007 no format permits verification of complete semantic compliance. The "MicroArray Quality Control (MAQC) Project" is being conducted by the US <a href="Food_and_Drug_Administration" title="Food and Drug Administration">Food and Drug Administration</a> (FDA) to develop standards and quality control metrics which will eventually allow the use of MicroArray data in drug discovery, clinical practice and regulatory decision-making.<sup id="cite_ref-21" class="reference"><a href="#cite_note-21"><span class="cite-bracket">[</span>21<span class="cite-bracket">]</span></a></sup> The <a href="MGED_Society" class="mw-redirect" title="MGED Society">MGED Society</a> has developed standards for the representation of gene expression experiment results and relevant annotations.

</p>

<div class="mw-heading mw-heading3"><h3 id="Data_analysis">Data analysis</h3></div>

<div role="note" class="hatnote navigation-not-searchable">Main article: <a href="Microarray_analysis_techniques" title="Microarray analysis techniques">Microarray analysis techniques</a></div>

<div role="note" class="hatnote navigation-not-searchable">See also: <a href="Gene_chip_analysis" class="mw-redirect" title="Gene chip analysis">Gene chip analysis</a></div>

<p>Microarray data sets are commonly very large, and analytical precision is influenced by a number of variables. <a href="Statistics" title="Statistics">Statistical</a> challenges include taking into account effects of background noise and appropriate <a href="Normalization_(statistics)" title="Normalization (statistics)">normalization</a> of the data. Normalization methods may be suited to specific platforms and, in the case of commercial platforms, the analysis may be proprietary.<sup id="cite_ref-22" class="reference"><a href="#cite_note-22"><span class="cite-bracket">[</span>22<span class="cite-bracket">]</span></a></sup> Algorithms that affect statistical analysis include:

</p>

<ul><li>Image analysis: gridding, spot recognition of the scanned image (segmentation algorithm), removal or marking of poor-quality and low-intensity features (called <i>flagging</i>).</li>

<li>Data processing: background subtraction (based on global or local background), determination of spot intensities and intensity ratios, visualisation of data (e.g. see <a href="MA_plot" title="MA plot">MA plot</a>), and log-transformation of ratios, global or <a href="Local_regression" title="Local regression">local</a> normalization of intensity ratios, and segmentation into different copy number regions using <a href="Step_detection" title="Step detection">step detection</a> algorithms.<sup id="cite_ref-23" class="reference"><a href="#cite_note-23"><span class="cite-bracket">[</span>23<span class="cite-bracket">]</span></a></sup></li>

<li>Class discovery analysis: This analytic approach, sometimes called unsupervised classification or knowledge discovery, tries to identify whether microarrays (objects, patients, mice, etc.) or genes cluster together in groups. Identifying naturally existing groups of objects (microarrays or genes) which cluster together can enable the discovery of new groups that otherwise were not previously known to exist. During knowledge discovery analysis, various unsupervised classification techniques can be employed with DNA microarray data to identify novel clusters (classes) of arrays.<sup id="cite_ref-Peterson_24-0" class="reference"><a href="#cite_note-Peterson-24"><span class="cite-bracket">[</span>24<span class="cite-bracket">]</span></a></sup> This type of approach is not hypothesis-driven, but rather is based on iterative pattern recognition or statistical learning methods to find an "optimal" number of clusters in the data. Examples of unsupervised analyses methods include self-organizing maps, neural gas, k-means cluster analyses,<sup id="cite_ref-25" class="reference"><a href="#cite_note-25"><span class="cite-bracket">[</span>25<span class="cite-bracket">]</span></a></sup> hierarchical cluster analysis, Genomic Signal Processing based clustering and model-based cluster analysis. For some of these methods the user also has to define a distance measure between pairs of objects. Although the Pearson correlation coefficient is usually employed, several other measures have been proposed and evaluated in the literature.<sup id="cite_ref-26" class="reference"><a href="#cite_note-26"><span class="cite-bracket">[</span>26<span class="cite-bracket">]</span></a></sup> The input data used in class discovery analyses are commonly based on lists of genes having high informativeness (low noise) based on low values of the coefficient of variation or high values of Shannon entropy, etc. The determination of the most likely or optimal number of clusters obtained from an unsupervised analysis is called cluster validity. Some commonly used metrics for cluster validity are the silhouette index, Davies-Bouldin index,<sup id="cite_ref-27" class="reference"><a href="#cite_note-27"><span class="cite-bracket">[</span>27<span class="cite-bracket">]</span></a></sup> Dunn's index, or Hubert's <span class="mwe-math-element mwe-math-element-inline"><span class="mwe-math-mathml-inline mwe-math-mathml-a11y" style="display: none;"><math xmlns="http://www.w3.org/1998/Math/MathML" alttext="{\displaystyle \Gamma }">

</mstyle>

</mrow>

<annotation encoding="application/x-tex">{\displaystyle \Gamma }</annotation>

</semantics>

</math></span><img src="./4cfde86a3f7ec967af9955d0988592f0693d2b19.svg" class="mwe-math-fallback-image-inline mw-invert skin-invert" aria-hidden="true" style="vertical-align: -0.338ex; width:1.453ex; height:2.176ex;" alt="{\displaystyle \Gamma }" loading="lazy"></span> statistic.</li>

<li>Class prediction analysis: This approach, called supervised classification, establishes the basis for developing a predictive model into which future unknown test objects can be input in order to predict the most likely class membership of the test objects. Supervised analysis<sup id="cite_ref-Peterson_24-1" class="reference"><a href="#cite_note-Peterson-24"><span class="cite-bracket">[</span>24<span class="cite-bracket">]</span></a></sup> for class prediction involves use of techniques such as linear regression, k-nearest neighbor, learning vector quantization, decision tree analysis, random forests, naive Bayes, logistic regression, kernel regression, artificial neural networks, support vector machines, <a href="Mixture_of_experts" title="Mixture of experts">mixture of experts</a>, and supervised neural gas. In addition, various metaheuristic methods are employed, such as <a href="Genetic_algorithm" title="Genetic algorithm">genetic algorithms</a>, covariance matrix self-adaptation, <a href="Particle_swarm_optimization" title="Particle swarm optimization">particle swarm optimization</a>, and <a href="Ant_colony_optimization" class="mw-redirect" title="Ant colony optimization">ant colony optimization</a>. Input data for class prediction are usually based on filtered lists of genes which are predictive of class, determined using classical hypothesis tests (next section), Gini diversity index, or information gain (entropy).</li>

<li>Hypothesis-driven statistical analysis: Identification of statistically significant changes in gene expression are commonly identified using the <a href="T-test" class="mw-redirect" title="T-test">t-test</a>, <a href="ANOVA" class="mw-redirect" title="ANOVA">ANOVA</a>, <a href="Bayesian_method" class="mw-redirect" title="Bayesian method">Bayesian method</a><sup id="cite_ref-Ben-GalShani2005_28-0" class="reference"><a href="#cite_note-Ben-GalShani2005-28"><span class="cite-bracket">[</span>28<span class="cite-bracket">]</span></a></sup> <a href="Mann%E2%80%93Whitney_test" class="mw-redirect" title="Mann–Whitney test">Mann–Whitney test</a> methods tailored to microarray data sets, which take into account <a href="Multiple_comparisons" class="mw-redirect" title="Multiple comparisons">multiple comparisons</a><sup id="cite_ref-29" class="reference"><a href="#cite_note-29"><span class="cite-bracket">[</span>29<span class="cite-bracket">]</span></a></sup> or <a href="Cluster_analysis" title="Cluster analysis">cluster analysis</a>.<sup id="cite_ref-Priness2007_30-0" class="reference"><a href="#cite_note-Priness2007-30"><span class="cite-bracket">[</span>30<span class="cite-bracket">]</span></a></sup> These methods assess statistical power based on the variation present in the data and the number of experimental replicates, and can help minimize <a href="Type_I_and_type_II_errors" title="Type I and type II errors">type I and type II errors</a> in the analyses.<sup id="cite_ref-Wei_31-0" class="reference"><a href="#cite_note-Wei-31"><span class="cite-bracket">[</span>31<span class="cite-bracket">]</span></a></sup></li>

<li>Dimensional reduction: Analysts often reduce the number of dimensions (genes) prior to data analysis.<sup id="cite_ref-Peterson_24-2" class="reference"><a href="#cite_note-Peterson-24"><span class="cite-bracket">[</span>24<span class="cite-bracket">]</span></a></sup> This may involve linear approaches such as principal components analysis (PCA), or non-linear manifold learning (distance metric learning) using kernel PCA, diffusion maps, Laplacian eigenmaps, local linear embedding, locally preserving projections, and Sammon's mapping.</li>

<li>Network-based methods: Statistical methods that take the underlying structure of gene networks into account, representing either associative or causative interactions or dependencies among gene products.<sup id="cite_ref-Emmert_32-0" class="reference"><a href="#cite_note-Emmert-32"><span class="cite-bracket">[</span>32<span class="cite-bracket">]</span></a></sup> <a href="Weighted_correlation_network_analysis" title="Weighted correlation network analysis">Weighted gene co-expression network analysis</a> is widely used for identifying co-expression modules and intramodular hub genes. Modules may corresponds to cell types or pathways. Highly connected intramodular hubs best represent their respective modules.</li></ul>

<p>Microarray data may require further processing aimed at reducing the dimensionality of the data to aid comprehension and more focused analysis.<sup id="cite_ref-33" class="reference"><a href="#cite_note-33"><span class="cite-bracket">[</span>33<span class="cite-bracket">]</span></a></sup> Other methods permit analysis of data consisting of a low number of biological or technical <a href="Replication_(statistics)" title="Replication (statistics)">replicates</a>; for example, the Local Pooled Error (LPE) test pools <a href="Standard_deviation" title="Standard deviation">standard deviations</a> of genes with similar expression levels in an effort to compensate for insufficient replication.<sup id="cite_ref-34" class="reference"><a href="#cite_note-34"><span class="cite-bracket">[</span>34<span class="cite-bracket">]</span></a></sup>

</p>

<div class="mw-heading mw-heading3"><h3 id="Annotation">Annotation</h3></div>

<p>The relation between a probe and the <a href="MRNA" class="mw-redirect" title="MRNA">mRNA</a> that it is expected to detect is not trivial.<sup id="cite_ref-35" class="reference"><a href="#cite_note-35"><span class="cite-bracket">[</span>35<span class="cite-bracket">]</span></a></sup> Some mRNAs may cross-hybridize probes in the array that are supposed to detect another mRNA. In addition, mRNAs may experience amplification bias that is sequence or molecule-specific. Thirdly, probes that are designed to detect the mRNA of a particular gene may be relying on genomic <a href="Expressed_sequence_tag" title="Expressed sequence tag">EST</a> information that is incorrectly associated with that gene.

</p>

<div class="mw-heading mw-heading3"><h3 id="Data_warehousing">Data warehousing</h3></div>

<p>Microarray data was found to be more useful when compared to other similar datasets. The sheer volume of data, specialized formats (such as <a href="MIAME" class="mw-redirect" title="MIAME">MIAME</a>), and curation efforts associated with the datasets require specialized databases to store the data. A number of open-source data warehousing solutions, such as <a href="InterMine" title="InterMine">InterMine</a> and <a href="BioMart" title="BioMart">BioMart</a>, have been created for the specific purpose of integrating diverse biological datasets, and also support analysis.

</p>

<div class="mw-heading mw-heading2"><h2 id="Alternative_technologies">Alternative technologies</h2></div>

<p>Advances in massively parallel sequencing has led to the development of <a href="RNA-Seq" title="RNA-Seq">RNA-Seq</a> technology, that enables a whole transcriptome shotgun approach to characterize and quantify gene expression.<sup id="cite_ref-mortazavi2008_36-0" class="reference"><a href="#cite_note-mortazavi2008-36"><span class="cite-bracket">[</span>36<span class="cite-bracket">]</span></a></sup><sup id="cite_ref-wang2009_37-0" class="reference"><a href="#cite_note-wang2009-37"><span class="cite-bracket">[</span>37<span class="cite-bracket">]</span></a></sup> Unlike microarrays, which need a reference genome and transcriptome to be available before the microarray itself can be designed, RNA-Seq can also be used for new model organisms whose genome has not been sequenced yet.<sup id="cite_ref-wang2009_37-1" class="reference"><a href="#cite_note-wang2009-37"><span class="cite-bracket">[</span>37<span class="cite-bracket">]</span></a></sup>

</p>

<div class="mw-heading mw-heading2"><h2 id="Glossary">Glossary</h2></div>

<ul><li>An <i>array</i> or <i>slide</i> is a collection of <i><a href="Glossary_of_gene_expression_terms" class="mw-redirect" title="Glossary of gene expression terms">features</a></i> spatially arranged in a two dimensional grid, arranged in columns and rows.</li>

<li><i>Block</i> or <i>subarray</i>: a group of spots, typically made in one print round; several subarrays/ blocks form an array.</li>

<li><i>Case/control</i>: an experimental design paradigm especially suited to the two-colour array system, in which a condition chosen as control (such as healthy tissue or state) is compared to an altered condition (such as a diseased tissue or state).</li>

<li><i><a href="Channel_(digital_image)" title="Channel (digital image)">Channel</a></i>: the <a href="Fluorescence" title="Fluorescence">fluorescence</a> output recorded in the scanner for an individual <a href="Fluorophore" title="Fluorophore">fluorophore</a> and can even be ultraviolet.</li>

<li><i>Dye flip</i> or <i>dye swap</i> or <i><a href="Fluorophore" title="Fluorophore">fluor</a> reversal</i>: reciprocal labelling of DNA targets with the two dyes to account for dye bias in experiments.</li>

<li><i>Scanner</i>: an instrument used to detect and quantify the intensity of fluorescence of spots on a microarray slide, by selectively exciting fluorophores with a <a href="Laser" title="Laser">laser</a> and measuring the fluorescence with a <a href="Filtered" class="mw-redirect" title="Filtered">filter (optics)</a> <a href="Photomultiplier" title="Photomultiplier">photomultiplier</a> system.</li>

<li><i>Spot</i> or <i>feature</i>: a small area on an array slide that contains picomoles of specific DNA samples.</li>

<li>For other relevant terms see:

<ul><li><a href="Glossary_of_gene_expression_terms" class="mw-redirect" title="Glossary of gene expression terms">Glossary of gene expression terms</a></li>

<li><a href="Protocol_(natural_sciences)" class="mw-redirect" title="Protocol (natural sciences)">Protocol (natural sciences)</a></li></ul></li></ul>

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<ul><li><a href="Transcriptomics_technologies" title="Transcriptomics technologies">Transcriptomics technologies</a>

<ul><li><a href="Serial_analysis_of_gene_expression" title="Serial analysis of gene expression">Serial analysis of gene expression</a></li>

<li><a href="MAGIChip" title="MAGIChip">MAGIChip</a></li>

<li><a href="Microarray_analysis_techniques" title="Microarray analysis techniques">Microarray analysis techniques</a></li>

<li><a href="Microarray_databases" title="Microarray databases">Microarray databases</a></li>

<li><a href="Cyanine" title="Cyanine">Cyanine</a> dyes, such as Cy3 and Cy5, are commonly used <a href="Fluorophores" class="mw-redirect" title="Fluorophores">fluorophores</a> with microarrays</li>

<li><a href="Gene_chip_analysis" class="mw-redirect" title="Gene chip analysis">Gene chip analysis</a></li>

<li><a href="Significance_analysis_of_microarrays" class="mw-redirect" title="Significance analysis of microarrays">Significance analysis of microarrays</a></li>

<li><a href="Methylation_specific_oligonucleotide_microarray" title="Methylation specific oligonucleotide microarray">Methylation specific oligonucleotide microarray</a></li>

<li><a href="Microfluidics" title="Microfluidics">Microfluidics</a> or <a href="Lab-on-chip" class="mw-redirect" title="Lab-on-chip">lab-on-chip</a></li>

<li><a href="Pathogenomics" title="Pathogenomics">Pathogenomics</a></li>

<li><a href="Phenotype_microarray" title="Phenotype microarray">Phenotype microarray</a></li>

<li><a href="Systems_biology" title="Systems biology">Systems biology</a></li>

<li><a href="Whole_genome_sequencing" title="Whole genome sequencing">Whole genome sequencing</a></li></ul>

</div>

<div class="mw-heading mw-heading2"><h2 id="References">References</h2></div>

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<li id="cite_note-wang2009-37"><span class="mw-cite-backlink">^ <a href="#cite_ref-wang2009_37-0"><sup><i><b>a</b></i></sup></a> <a href="#cite_ref-wang2009_37-1"><sup><i><b>b</b></i></sup></a></span> <span class="reference-text"><cite id="CITEREFWangMark_GersteinMichael_Snyder2009" class="citation journal cs1">Wang, Zhong; Mark Gerstein; Michael Snyder (January 2009). <a rel="nofollow" class="external text" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2949280">"RNA-Seq: a revolutionary tool for transcriptomics"</a>. <i>Nat Rev Genet</i>. <b>10</b> (1): <span class="nowrap">57–</span>63. <a href="Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<a rel="nofollow" class="external text" href="https://doi.org/10.1038%2Fnrg2484">10.1038/nrg2484</a>. <a href="ISSN_(identifier)" class="mw-redirect" title="ISSN (identifier)">ISSN</a> <a rel="nofollow" class="external text" href="https://search.worldcat.org/issn/1471-0056">1471-0056</a>. <a href="PMC_(identifier)" class="mw-redirect" title="PMC (identifier)">PMC</a> <span class="id-lock-free" title="Freely accessible"><a rel="nofollow" class="external text" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2949280">2949280</a></span>. <a href="PMID_(identifier)" class="mw-redirect" title="PMID (identifier)">PMID</a> <a rel="nofollow" class="external text" href="https://pubmed.ncbi.nlm.nih.gov/19015660">19015660</a>.</cite></span>

</li>

</ol></div></div>

<div class="mw-heading mw-heading2"><h2 id="External_links">External links</h2></div>

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<ul><li><a rel="nofollow" class="external text" href="https://web.archive.org/web/20161017012107/http://1lec.com/microarray/">Microarray Animation</a> 1Lec.com</li>

<li><a rel="nofollow" class="external text" href="https://pubmed.ncbi.nlm.nih.gov/14551912/">PLoS Biology Primer: Microarray Analysis</a></li>

<li><a rel="nofollow" class="external text" href="https://web.archive.org/web/20150924040600/http://www.genome.gov/page.cfm?pageID=10000533">Rundown of microarray technology</a></li>

<li><a rel="nofollow" class="external text" href="http://www.arraymining.net">ArrayMining.net</a> – a free web-server for online microarray analysis</li>

<li><a rel="nofollow" class="external text" href="https://web.archive.org/web/20090223111750/http://www.unsolvedmysteries.oregonstate.edu/microarray_07">Microarray – How does it work?</a></li>

<li><a rel="nofollow" class="external text" href="https://www.pnas.org/doi/abs/10.1073/pnas.0607650103">PNAS Commentary: Discovery of Principles of Nature from Mathematical Modeling of DNA Microarray Data</a></li>

<li><a rel="nofollow" class="external text" href="https://learn.genetics.utah.edu/content/labs/microarray/">DNA microarray virtual experiment</a></li></ul>

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</style><div id="Molecular_biology462" style="font-size:114%;margin:0 4em"><a href="Molecular_biology" title="Molecular biology">Molecular biology</a></div></th></tr><tr><td class="navbox-abovebelow" colspan="2"><div>

<ul><li><a href="History_of_molecular_biology" title="History of molecular biology">History</a></li>

<li><a href="Index_of_molecular_biology_articles" title="Index of molecular biology articles">Index</a></li>

<li><a href="Glossary_of_genetics" class="mw-redirect" title="Glossary of genetics">Glossary</a></li></ul>

</div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%">Overview</th><td class="navbox-list-with-group navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em"></div><table class="nowraplinks navbox-subgroup" style="border-spacing:0"><tbody><tr><th scope="row" class="navbox-group" style="width:1%"><a href="Central_dogma_of_molecular_biology" title="Central dogma of molecular biology">Central dogma</a></th><td class="navbox-list-with-group navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em">

<ul><li><a href="DNA_replication" title="DNA replication">DNA replication</a> (<a href="DNA" title="DNA">DNA</a>)</li>

<li><a href="Transcription_(biology)" title="Transcription (biology)">Transcription</a> (<a href="RNA" title="RNA">RNA</a>)</li>

<li><a href="Translation_(biology)" title="Translation (biology)">Translation</a> (<a href="Protein" title="Protein">protein</a>)</li></ul>

</div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%">Element</th><td class="navbox-list-with-group navbox-list navbox-even" style="width:100%;padding:0"><div style="padding:0 0.25em">

<ul><li><span style="font-size: 85%;">Genetic</span></li>

<li><span style="font-size: 85%;">Heredity</span></li></ul></li></ul>

<ul><li><a href="Promoter_(genetics)" title="Promoter (genetics)">Promoter</a>

<ul><li><a href="Pribnow_box" title="Pribnow box">Pribnow box</a></li>

<li><a href="Operon" title="Operon">Operon</a>

<ul><li><a href="Gal_operon" title="Gal operon">gal operon</a></li>

<li><a href="Lac_operon" title="Lac operon">lac operon</a></li>

<li><a href="Trp_operon" title="Trp operon">trp operon</a></li></ul></li>

<li><a href="Intron" title="Intron">Intron</a></li>

<li><a href="Terminator_(genetics)" title="Terminator (genetics)">Terminator</a></li>

<li><a href="Enhancer_(genetics)" title="Enhancer (genetics)">Enhancer</a></li>

<li><a href="Repressor" title="Repressor">Repressor</a>

<ul><li><a href="Lac_repressor" title="Lac repressor">lac repressor</a></li>

<li><a href="Tryptophan_repressor" title="Tryptophan repressor">trp repressor</a></li></ul></li>

<li><a href="Silencer_(genetics)" title="Silencer (genetics)">Silencer</a></li>

<li><a href="Histone_methylation" title="Histone methylation">Histone methylation</a></li></ul>

</div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%">Linked life</th><td class="navbox-list-with-group navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em">

<ul><li><a href="Cell_biology" title="Cell biology">Cell biology</a></li>

<li><a href="Biochemistry" title="Biochemistry">Biochemistry</a></li>

<li><a href="Computational_biology" title="Computational biology">Computational biology</a></li>

<li><a href="Developmental_biology" title="Developmental biology">Developmental biology</a></li>

<li><a href="Medicine" title="Medicine">Functional biology/medicine</a></li>

<li><a href="Genetics" title="Genetics">Genetics</a></li></ul>

</div></td></tr></tbody></table><div></div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%">Engineering</th><td class="navbox-list-with-group navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em"></div><table class="nowraplinks navbox-subgroup" style="border-spacing:0"><tbody><tr><th scope="row" class="navbox-group" style="width:1%">Concepts</th><td class="navbox-list-with-group navbox-list navbox-even" style="width:100%;padding:0"><div style="padding:0 0.25em">

<ul><li><a href="Cultured_meat" title="Cultured meat">Cultured meat</a></li>

<li><a href="Mitosis" title="Mitosis">Mitosis</a></li>

<li><a href="Cell_signaling" title="Cell signaling">Cell signalling</a></li>

<li><a href="Post-transcriptional_modification" title="Post-transcriptional modification">Post-transcriptional modification</a></li>

<li><a href="Post-translational_modification" title="Post-translational modification">Post-translational modification</a></li>

</div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%">Techniques</th><td class="navbox-list-with-group navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em">

<ul><li><a href="Cell_culture" title="Cell culture">Cell culture</a></li>

<li><a href="Model_organism" title="Model organism">Model organisms</a> (such as <a href="C57BL/6" title="C57BL/6">C57BL/6 mice</a>)</li>

<li>Methods

<ul><li><a href="Nucleic_acid_methods" title="Nucleic acid methods">Nucleic acid</a></li>

<li><a href="Protein_methods" title="Protein methods">Protein</a></li></ul></li>

<li><a href="Fluorescence_in_the_life_sciences" title="Fluorescence in the life sciences">Fluorescence</a>, <a href="Pigment" title="Pigment">Pigment</a> & <a href="Radioactivity_in_the_life_sciences" title="Radioactivity in the life sciences">Radioactivity</a></li></ul>

<dl><dt><span class="nobold">High-throughput technique ("<a href="Omics" title="Omics">-omics</a>")</span></dt>

<dd><a href="Mass_spectrometry" title="Mass spectrometry">Mass spectrometry</a></dd>

</div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%"><a href="Regulation_of_gene_expression" title="Regulation of gene expression">Gene regulation</a></th><td class="navbox-list-with-group navbox-list navbox-even" style="width:100%;padding:0"><div style="padding:0 0.25em">

<ul><li><a href="Epigenetics" title="Epigenetics">Epigenetic</a></li>

<li><a href="Regulation_of_gene_expression" title="Regulation of gene expression">Genetic</a></li>

<li><a href="Post-transcriptional_regulation" title="Post-transcriptional regulation">Post-transcriptional</a></li>

<li><a href="Post-translational_regulation" title="Post-translational regulation">Post-translational regulation</a></li></ul>

</div></td></tr></tbody></table><div></div></td></tr><tr><td class="navbox-abovebelow" colspan="2"><div>

<ul><li><span class="noviewer" typeof="mw:File"><span title="Category"></span></span><b>Molecular biology</b></li>

<li><span class="noviewer" typeof="mw:File"><span title="WikiProject"></span></span> <b>WikiProject</b></li></ul>

</div></td></tr></tbody></table></div>

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<ul><li><a href="Glass" title="Glass">Glass</a></li>

<li><a href="Glass_transition" title="Glass transition">Glass transition</a></li>

<li><a href="Supercooling" title="Supercooling">Supercooling</a></li></ul>

</div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%">Formulation</th><td class="navbox-list-with-group navbox-list navbox-even hlist" style="width:100%;padding:0"><div style="padding:0 0.25em">

<ul><li><a href="AgInSbTe" title="AgInSbTe">AgInSbTe</a></li>

<li><a href="Bioglass" class="mw-redirect" title="Bioglass">Bioglass</a></li>

<li><a href="Borophosphosilicate_glass" title="Borophosphosilicate glass">Borophosphosilicate glass</a></li>

<li><a href="Borosilicate_glass" title="Borosilicate glass">Borosilicate glass</a></li>

<li><a href="Ceramic_glaze" title="Ceramic glaze">Ceramic glaze</a></li>

<li><a href="Chalcogenide_glass" title="Chalcogenide glass">Chalcogenide glass</a></li>

<li><a href="Cobalt_glass" title="Cobalt glass">Cobalt glass</a></li>

<li><a href="Cranberry_glass" title="Cranberry glass">Cranberry glass</a></li>

<li><a href="Crown_glass_(optics)" title="Crown glass (optics)">Crown glass</a></li>

<li><a href="Flint_glass" title="Flint glass">Flint glass</a></li>

<li><a href="Fluorosilicate_glass" title="Fluorosilicate glass">Fluorosilicate glass</a></li>

<li><a href="Fused_quartz" title="Fused quartz">Fused quartz</a></li>

<li><a href="GeSbTe" title="GeSbTe">GeSbTe</a></li>

<li><a href="Cranberry_glass" title="Cranberry glass">Gold ruby glass</a></li>

<li><a href="Lead_glass" title="Lead glass">Lead glass</a></li>

<li><a href="Milk_glass" title="Milk glass">Milk glass</a></li>

<li><a href="Phosphosilicate_glass" title="Phosphosilicate glass">Phosphosilicate glass</a></li>

<li><a href="Photochromic_lens" title="Photochromic lens">Photochromic lens glass</a></li>

<li><a href="Glass#Silicate_glass" title="Glass">Silicate glass</a></li>

<li><a href="Soda%E2%80%93lime_glass" title="Soda–lime glass">Soda–lime glass</a></li>

<li><a href="Sodium_hexametaphosphate" title="Sodium hexametaphosphate">Sodium hexametaphosphate</a></li>

<li><a href="Sodium_silicate" title="Sodium silicate">Soluble glass</a></li>

<li><a href="Tellurite_glass" title="Tellurite glass">Tellurite glass</a></li>

<li><a href="Thoriated_glass" title="Thoriated glass">Thoriated glass</a></li>

<li><a href="Ultra_low_expansion_glass" title="Ultra low expansion glass">Ultra low expansion glass</a></li>

<li><a href="Uranium_glass" title="Uranium glass">Uranium glass</a></li>

<li><a href="Vitreous_enamel" title="Vitreous enamel">Vitreous enamel</a></li>

<li><a href="Wood's_glass" title="Wood's glass">Wood's glass</a></li>

<li><a href="ZBLAN" title="ZBLAN">ZBLAN</a></li></ul>

</div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%"><a href="Glass-ceramic" title="Glass-ceramic">Glass-ceramics</a></th><td class="navbox-list-with-group navbox-list navbox-odd hlist" style="width:100%;padding:0"><div style="padding:0 0.25em">

<ul><li><a href="Bioactive_glass" title="Bioactive glass">Bioactive glass</a></li>

<li><a href="CorningWare" title="CorningWare">CorningWare</a></li>

<li><a href="Glass-ceramic-to-metal_seals" title="Glass-ceramic-to-metal seals">Glass-ceramic-to-metal seals</a></li>

<li><a href="Macor" title="Macor">Macor</a></li>

<li><a href="Zerodur" title="Zerodur">Zerodur</a></li></ul>

</div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%">Preparation</th><td class="navbox-list-with-group navbox-list navbox-even hlist" style="width:100%;padding:0"><div style="padding:0 0.25em">

<ul><li><a href="Annealing_(glass)" title="Annealing (glass)">Annealing</a></li>

<li><a href="Chemical_vapor_deposition" title="Chemical vapor deposition">Chemical vapor deposition</a></li>

<li><a href="Glass_batch_calculation" title="Glass batch calculation">Glass batch calculation</a></li>

<li><a href="Glass_production" title="Glass production">Glass forming</a></li>

<li><a href="Glass_production#Hot_end" title="Glass production">Glass melting</a></li>

<li><a href="Calculation_of_glass_properties" title="Calculation of glass properties">Glass modeling</a></li>

<li><a href="Ion_implantation" title="Ion implantation">Ion implantation</a></li>

<li><a href="Liquidus" class="mw-redirect" title="Liquidus">Liquidus temperature</a></li>

<li><a href="Sol%E2%80%93gel_process" title="Sol–gel process">sol–gel technique</a></li>

<li><a href="Viscosity#Viscosity_of_amorphous_materials" title="Viscosity">Viscosity</a></li>

<li><a href="Vitrification" title="Vitrification">Vitrification</a></li></ul>

</div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%"><a href="Optics" title="Optics">Optics</a></th><td class="navbox-list-with-group navbox-list navbox-odd hlist" style="width:100%;padding:0"><div style="padding:0 0.25em">

<ul><li><a href="Achromatic_lens" title="Achromatic lens">Achromat</a></li>

<li><a href="Dispersion_(optics)" title="Dispersion (optics)">Dispersion</a></li>

<li><a href="Gradient-index_optics" title="Gradient-index optics">Gradient-index optics</a></li>

<li><a href="Hydrogen_darkening" title="Hydrogen darkening">Hydrogen darkening</a></li>

<li><a href="Optical_amplifier" title="Optical amplifier">Optical amplifier</a></li>

<li><a href="Optical_fiber" title="Optical fiber">Optical fiber</a></li>

<li><a href="Optical_lens_design" title="Optical lens design">Optical lens design</a></li>

<li><a href="Photochromic_lens" title="Photochromic lens">Photochromic lens</a></li>

<li><a href="Photosensitive_glass" title="Photosensitive glass">Photosensitive glass</a></li>

<li><a href="Refraction" title="Refraction">Refraction</a></li>

<li><a href="Transparency_and_translucency" title="Transparency and translucency">Transparent materials</a></li></ul>

</div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%">Surface<br>modification</th><td class="navbox-list-with-group navbox-list navbox-even hlist" style="width:100%;padding:0"><div style="padding:0 0.25em">

<ul><li><a href="Anti-reflective_coating" title="Anti-reflective coating">Anti-reflective coating</a></li>

<li><a href="Chemically_strengthened_glass" title="Chemically strengthened glass">Chemically strengthened glass</a></li>

<li><a href="Corrosion#Corrosion_of_glasses" title="Corrosion">Corrosion</a></li>

<li><a href="Dealkalization" title="Dealkalization">Dealkalization</a></li>

<li><a href="Hydrogen_darkening" title="Hydrogen darkening">Hydrogen darkening</a></li>

<li><a href="Insulated_glazing" title="Insulated glazing">Insulated glazing</a></li>

<li><a href="Porous_glass" title="Porous glass">Porous glass</a></li>

<li><a href="Self-cleaning_glass" title="Self-cleaning glass">Self-cleaning glass</a></li>

<li><a href="Sol%E2%80%93gel_process" title="Sol–gel process">sol–gel technique</a></li>

<li><a href="Tempered_glass" title="Tempered glass">Tempered glass</a></li></ul>

</div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%">Diverse<br>topics</th><td class="navbox-list-with-group navbox-list navbox-odd hlist" style="width:100%;padding:0"><div style="padding:0 0.25em">

<ul><li><a href="Conservation_and_restoration_of_glass_objects" title="Conservation and restoration of glass objects">Conservation and restoration of glass objects</a></li>

<li><a href="Glass-coated_wire" title="Glass-coated wire">Glass-coated wire</a></li>

<li><a href="Safety_glass" title="Safety glass">Safety glass</a></li>

<li><a href="Glass_databases" title="Glass databases">Glass databases</a></li>

<li><a href="Glass_electrode" title="Glass electrode">Glass electrode</a></li>

<li><a href="Glass_fiber_reinforced_concrete" title="Glass fiber reinforced concrete">Glass fiber reinforced concrete</a></li>

<li><a href="Glass_ionomer_cement" title="Glass ionomer cement">Glass ionomer cement</a></li>

<li><a href="Glass_microsphere" title="Glass microsphere">Glass microspheres</a></li>

<li><a href="Fiberglass" title="Fiberglass">Glass-reinforced plastic</a></li>

<li><a href="Glass_cloth" title="Glass cloth">Glass cloth</a></li>

<li><a href="Glass-to-metal_seal" title="Glass-to-metal seal">Glass-to-metal seal</a></li>

<li><a href="Porous_glass" title="Porous glass">Porous glass</a></li>

<li><a href="Prince_Rupert's_drop" title="Prince Rupert's drop">Prince Rupert's drops</a></li>

<li><a href="Radioactive_waste#Vitrification" title="Radioactive waste">Radioactive waste vitrification</a></li>

<li><a href="Windshield" title="Windshield">Windshield</a></li>

<li><a href="Glass_fiber" title="Glass fiber">Glass fiber</a></li></ul>

</div></td></tr></tbody></table></div>

<div class="navbox-styles"></div><div role="navigation" class="navbox authority-control" aria-label="Navbox397" style="padding:3px"><table class="nowraplinks hlist navbox-inner" style="border-spacing:0;background:transparent;color:inherit"><tbody><tr><th scope="row" class="navbox-group" style="width:1%">Authority control databases: National </th><td class="navbox-list-with-group navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em"><ul><li><span class="uid"><a rel="nofollow" class="external text" href="https://id.ndl.go.jp/auth/ndlna/01066497">Japan</a></span></li></ul></div></td></tr></tbody></table></div></div><div><div class="zim-footer">

This article is issued from <a class="external text" title="Last edited on 2025-07-19" href="https://en.wikipedia.org/wiki/?title=DNA_microarray&oldid=1301376104">Wikipedia</a>. The text is available under <a class="external text" href="https://creativecommons.org/licenses/by-sa/4.0/deed.en">Creative Commons Attribution-Share Alike 4.0</a> unless otherwise noted. Additional terms may apply for the media files.

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