Name: array comparative genomic hybridization (array cgh) for detection of genomic copy number variants
Uploaded: 2015-02-21T14:00:00.000+00:00
Duration: 9 min 16 s
Description: Watch this Scientific Journal Video about Array Comparative Genomic Hybridization Array CGH for Detection of Genomic Copy Number Variants at JoVE.com

The authors have no acknowledgements.

1. Labelling Reaction
<ol>
	<li>Prior to use, pre-aliquot cyanine 3 and 5-labeled dUTPs, unlabeled nucleotides and random primers at the manufacturer-recommended concentrations into 96-well plates and store at -20 C ready for use. For the purposes of this protocol, aliquot 10.5 &#181;l of the appropriate labeled dUTP and 10.5 &#181;l unlabeled nucleotides and random primers to each well.</li>
	<li>Thaw the ready-to-use 96-well plate of nucleotides and primers at 4 &#176;C for about 1 hr, protected from light.</li>
	<li>Once thawed, equilibrate this plate at RT for at least 30 min, protected from light.</li>
	<li>Equilibrate DNA samples at 60 &#176;C for at least 15 min.</li>
	<li>Using a liquid handling robot, dispense nuclease-free water to each well of a 96-well plate. 
	NOTE: The volume of water will depend on the concentration of each input DNA sample and should be sufficient to result in a final concentration of 50 ng/ul.</li>
	<li>Using a liquid handling robot, pipette 1 &#181;g of DNA into a well of the 96-well plate (see 1.5) to bring the total volume to 20 &#181;l. 
	NOTE: Smaller quantities of DNA may be used although the quality of resulting data may be compromised (for precious samples, input DNA quantities down to 400 ng can be used).</li>
	<li>Using a liquid handling robot, transfer 20 &#181;l of the equilibrated nucleotides and primers into each well of the plate of diluted DNA.</li>
	<li>Seal the 96-well plate with strip caps (a tight seal is crucial).</li>
	<li>Denature the DNA at 99 &#176;C for 10 min in a PCR machine with a heated lid and then snap cool on ice for 5 min to anneal primers.</li>
	<li>Using a liquid handling robot, add 10 &#181;l of Klenow Exo DNA polymerase enzyme to each DNAs and pipette mix thoroughly. 
	NOTE: The total volume should be 50 &#181;l.</li>
	<li>Seal the 96-well plate and incubate at 37 &#176;C for 16 hr. 
	NOTE: A shorter incubation of 4 hr is sufficient however an O/N incubation can be more convenient.</li>
	<li>Using a liquid handling robot, add 5 &#181;l of stop buffer to each well. 
	NOTE: A summary of the reagents used for the labeling reaction is shown in Table 1.</li>
</ol>
2. Removal of Unincorporated Nucleotides
<ol>
	<li>Remove unincorporated nucleotides using silica-membrane based spin columns and a dedicated spin column processing robot (the spin columns may also be processed manually). Follow the manufacturer&#39;s instructions.
	<ol>
		<li>Transfer the contents of each well to a 2 ml tube; pre-label these with well ID&#8217;s. 
		NOTE: This step can be performed manually or preferably using a liquid handling robot.</li>
		<li>If using a spin column processing robot, then load the robot with 2 ml tubes, DNA purification spin columns and associated buffers .</li>
		<li>Add 250 &#181;l high salt, DNA binding buffer (buffer PB) to the labeling reaction to bind the labeled DNA to the silica membrane.</li>
		<li>Remove impurities by washing the membrane twice with 500 &#181;l wash buffer (buffer PE).</li>
		<li>Add 15 &#181;l low salt elution buffer (buffer EB) to the membrane to recover the purified, labeled DNA in a volume of ~12 &#181;l.</li>
	</ol>
	</li>
</ol>
3. Combine Hyb Pairs
<ol>
	<li>Combine the appropriate pairs of cyanine 3 and 5-labeled DNA, COT-1 DNA, a manufacturer-supplied blocking mix and a manufacturer-supplied hybridization buffer using a liquid handling robot. 
	NOTE: These hyb pairs can be a sample and a reference, or sample vs sample if shared CNVs are not an issue (e.g.,&#160;we routinely pair phenotype-mismatched samples, such as a renal dysplasia patient vs a craniosynostosis patient, as they are very unlikely to carry the same clinically significant CNV). If using a reference DNA, a commercial DNA supply is recommended, and it should be processed alongside the sample.
	<ol>
		<li>Using a liquid handling robot, add COT-1 DNA (3333 ng/&#181;l), the manufacturer-supplied blocking mix and hybridization buffer to each well of a 96-well plate so that each well contains 1.1 &#181;l COT-1 DNA, 4.95 &#181;l blocking mix and 24.75 &#181;l hybridization buffer.</li>
		<li>Add 9.35 &#181;l of the appropriate cyanine 3-labeled DNA to each well. Pre-wet each tip to enhance pipetting accuracy.</li>
		<li>Add 9.35 &#181;l of the appropriate cyanine 5-labeled DNA to each well. Pre-wet each tip to enhance pipetting accuracy.</li>
		<li>Seal the 96-well plate and vortex for 1 min. Spin the 96-well plate to collect contents at the bottom of each well.</li>
	</ol>
	</li>
</ol>
4. Hybridization
<ol>
	<li>Preheat a hybridization oven to 65oC and prewarm one backing slide and one hybridization chamber for each array slide.
	<ol>
		<li>Denature the labeled DNA in a pre-hybridization incubation before being applying to the arrays. Perform hybridization in a rotating oven for 24 hr.</li>
		<li>Incubate the 96-well plate at 70 &#176;C for 30 min and then leave at 37 &#176;C for at least 5 min.</li>
		<li>Working on a heated platform at 42 &#176;C, load each backing slide into a hybridization chamber prior to use. Ensure that the transparent part of the gasket slide aligns with the &#39;windowed&#39; part of the hybridization chamber.</li>
		<li>Pipet 42 &#181;l of the hybridization mix prepared previously (see section 3) onto the appropriate position on the array backing slide. Pre-wet each tip to enhance pipetting accuracy. Pipet slowly onto the center of each position, making sure the liquid does not touch the rubber ring boundary.</li>
		<li>Once all positions on the backing slide are filled, carefully lower the array slide on it and assemble the hybridization chamber. Make sure that the side of the array with writing on it is facing the backing slide. Be sure to tighten the hybridization chamber screw fully.</li>
		<li>Inspect the assembled hybridization chamber. Ensure that there is no leakage of hybridization mix outside the rubber ring boundaries and each air bubble is ~4 mm in height when the hybridization chamber is rested on its end vertically. Rotate the hybridization chamber and check that there are no air bubbles that are stuck in position and not moving. If there are any of these, give the chamber a sharp tap on the bench. Check that all air bubbles are moving.</li>
		<li>Place the hybridization chamber into the rotating oven at 65 &#176;C for 24 hr. Make sure the oven rotor is balanced; use other empty chambers if necessary.</li>
	</ol>
	</li>
</ol>
5. Washing and Scanning Slides
<ol>
	<li>Wash arrays to remove excess labeled DNA and then scan to measure fluorescence of each probe.
	<ol>
		<li>Take hybridization chambers out of oven and disassemble. The array and gasket slides will be stuck together; submerge these in wash buffer 1 and use a pair of plastic, flat edged forceps to pry them apart.</li>
		<li>Discard the gasket slide and place the array slide into a rack submerged in buffer 1.</li>
		<li>Wash the array slide in ~700 ml of fresh wash buffer 1 for 5 min, stirring vigorously (use a flea and a magnetic stirrer).</li>
		<li>Transfer the array slide to ~700 ml wash buffer 2 and wash for 90 sec, stirring vigorously. Gently lift the array slides out of wash buffer 2, they should emerge dry.</li>
		<li>Load the array slide into a slide holder of the scanner, using a slide protector. Load the slide into the array scanner and scan following the array manufacturer&#8217;s instructions.</li>
	</ol>
	</li>
</ol>

<ol>
	<li>Miller, D. T., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Consensus+statement:+chromosomal+microarray+is+a+first-tier+clinical+diagnostic+test+for+individuals+with+developmental+disabilities+or+congenital+anomalies.">Consensus statement: chromosomal microarray is a first-tier clinical diagnostic test for individuals with developmental disabilities or congenital anomalies.</a> Am. J. Hum. Genet. 86, 749-764 (2010).</li><li>Ahn, J. W., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Array+CGH+as+a+first+line+diagnostic+test+in+place+of+karyotyping+for+postnatal+referrals+-+results+from+four+years'+clinical+application+for+over+8,700+patients.">Array CGH as a first line diagnostic test in place of karyotyping for postnatal referrals - results from four years' clinical application for over 8,700 patients.</a> Mol. Cytogenet. 6 (16), 1755-8166 (2013).</li><li>Ahn, J. W., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Validation+and+implementation+of+array+comparative+genomic+hybridisation+as+a+first+line+test+in+place+of+postnatal+karyotyping+for+genome+imbalance.">Validation and implementation of array comparative genomic hybridisation as a first line test in place of postnatal karyotyping for genome imbalance.</a> Mol. Cytogenet. 3 (9), 1755-8166 (2010).</li><li>Beaudet, A. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+utility+of+chromosomal+microarray+analysis+in+developmental+and+behavioral+pediatrics.">The utility of chromosomal microarray analysis in developmental and behavioral pediatrics.</a> Child Dev. 84, 121-132 (2013).</li><li>Park, S. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Clinical+implementation+of+whole-genome+array+CGH+as+a+first-tier+test+in+5080+pre+and+postnatal+cases.">Clinical implementation of whole-genome array CGH as a first-tier test in 5080 pre and postnatal cases.</a> Mol. Cytogenet. 4, 12 (2011).</li><li>Iafrate, A. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Detection+of+large-scale+variation+in+the+human+genome.">Detection of large-scale variation in the human genome.</a> Nat. Genet. 36, 949-951 (2004).</li><li>Redon, R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Global+variation+in+copy+number+in+the+human+genome.">Global variation in copy number in the human genome.</a> Nature. 444, 444-454 (2006).</li><li>Cafferkey, M., Ahn, J. W., Flinter, F., Ogilvie, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Phenotypic+features+in+patients+with+15q11.2(BP1-BP2)+deletion:+Further+delineation+of+an+emerging+syndrome.">Phenotypic features in patients with 15q11.2(BP1-BP2) deletion: Further delineation of an emerging syndrome.</a> Am. J. Med. Genet. A. 164, 1916-1922 (2014).</li><li>Molin, A. M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+novel+microdeletion+syndrome+at+3q13.31+characterised+by+developmental+delay,+postnatal+overgrowth,+hypoplastic+male+genitals,+and+characteristic+facial+features.">A novel microdeletion syndrome at 3q13.31 characterised by developmental delay, postnatal overgrowth, hypoplastic male genitals, and characteristic facial features.</a> J. Med. Genet. 49, 104-109 (2012).</li><li>Tropeano, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Male-biased+autosomal+effect+of+16p13.11+copy+number+variation+in+neurodevelopmental+disorders.">Male-biased autosomal effect of 16p13.11 copy number variation in neurodevelopmental disorders.</a> PLoS One. 8, e61365 (2013).</li><li>Bon, B. W., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Further+delineation+of+the+15q13+microdeletion+and+duplication+syndromes:+a+clinical+spectrum+varying+from+non-pathogenic+to+a+severe+outcome.">Further delineation of the 15q13 microdeletion and duplication syndromes: a clinical spectrum varying from non-pathogenic to a severe outcome.</a> J. Med. Genet. 46, 511-523 (2009).</li></ol>

The authors have nothing to disclose.

Array CGH will not detect balanced rearrangements or ploidy abnormalities such as triploidy. Furthermore, low level mosaic imbalances may not be detected. However, array CGH has a higher resolution for CNV detection than G-banded chromosome analysis which it has replaced in many cytogenetics laboratories. It is therefore the current gold standard for genome-wide CNV detection. It may be replaced by next-generation sequencing technologies in the future but currently, their cost and the technical complexities associated with using short reads for CNV detection mean that this is not yet a good fit for clinical use.
The protocol described here is in routine use in our clinical service laboratory. Two runs of 96 samples each are processed each week using a liquid handling robot and a dedicated silica membrane spin column processing robot. Automation is highly recommended to improve consistency and maintain quality. DNA extracted from blood, saliva, prenatal samples (e.g., chorionic villi or amniotic fluid) or tissue samples can be, and routinely is, used with this protocol.
Ozone is known to degrade cyanine dyes and therefore ozone monitoring and protection is recommended. Seasonal variation in ozone levels is also common. Our laboratory monitors and records ozone levels continuously. A wall-mounted ozone removal unit is used to reduce ozone levels and particularly sensitive parts of the protocol (i.e.,&#160;washing and scanning arrays) are performed in ozone-free hoods. If possible, ozone levels are kept below 5 ppb.
Most reagents are bought as kits from manufacturers to effectively outsource quality control; this has proved to be an effective strategy. However, this does not mean that quality control is not required. Indeed, quality metrics are carefully monitored for any anomalies: derivative standard deviation of log2 ratios (DLRS) should be below 0.2, cyanine 3 and 5-signal intensities should be greater than 500 and cyanine 3 and 5-signal to noise ratios should be &#62;30. These metrics are generated as part of the scanning protocol by the scanning software and are recorded for long term monitoring.

It has been known for many years that deletions or extra copies of chromosomal segments cause intellectual disability, dysmorphism and congentical malformations, and in some cases cause genetic syndromes1. However, the only technology available until the mid-2000s for the genome-wide detection of these changes was G-banded chromosome analysis, which has a resolution of around 5-10Mb, depending on the region and nature of the imbalance, and which cannot detect abnormal chromosomes where material has been replaced by a region from a different chromosome with the same banding pattern. Ancillary cytogenetic techniques such as fluorescence in situ hybridization and multiplex ligation-specific probe amplification have been available for the interrogation of specific loci, in cases of suspected specific syndromic imbalance, but it was not until the introduction of array comparative genomic hybridization (array CGH) into routine clinical diagnostic service2-5 that genome-wide detection of copy number variants (CNVs) became possible at a greatly increased resolution (typically around 120kb). Clinical service work alongside research studies have shown that CNVs for some regions are widespread in the normal population6-7, whilst other CNVs, previously undetectable, are associated with neurodisabilities such as autism and epilepsy8-11.
The protocol described in this paper is used in our UK National Health Service (NHS) clinical diagnostic laboratory; we use novel hybridization strategies, batch testing and robotics to minimize cost in this state-funded service.
Prior to the protocol detailed below, high quality DNA should be extracted from the appropriate starting material, commonly blood, cultured cells or tissue samples. Spectrophotometry can be used to measure concentration (should be &#62;50 ng/ul) and check 260:280 absorbance ratios (should be 1.8-2.0). Gel electrophoresis can be used to check that the DNA is of high molecular weight without significant degradation.
This protocol is designed for higher throughput laboratories that are labeling 96 samples per run using automated liquid handling robotics. However, it may be adapted for lower throughput labs without automation.

<table><tbody><tr><td>CGH microarray 8 x 60K</td><td>Agilent</td><td>G4126</td><td></td></tr><tr><td>Array CGH wash buffers</td><td>Agilent</td><td>5188-5226</td><td></td></tr><tr><td>Array CGH hybridisation buffer</td><td>Agilent</td><td>5188-5380</td><td></td></tr><tr><td>Minelute purification kit</td><td>Qiagen</td><td>28006</td><td></td></tr><tr><td>Array CGH labelling kit</td><td>Enzo</td><td>ENZ-42672-0000</td><td></td></tr></tbody></table>

array comparative genomic hybridization (array cgh) for detection of genomic copy number variants

Array CGH for the detection of genomic copy number variants has replaced G-banded karyotype analysis. This paper describes the technology and its application in a clinical diagnostic service laboratory. DNA extracted from a patient&#8217;s sample (blood, saliva or other tissue types) is labeled with a fluorochrome (either cyanine 5 or cyanine 3). A reference DNA sample is labeled with the opposite fluorochrome. There follows a cleanup step to remove unincorporated nucleotides before the labeled DNAs are mixed and resuspended in a hybridization buffer and applied to an array comprising ~60,000 oligonucleotide probes from loci across the genome, with high probe density in clinically important areas. Following hybridization, the arrays are washed, then scanned and the resulting images are analyzed to measure the red and green fluorescence for each probe. Software is used to assess the quality of each probe measurement, calculate the ratio of red to green fluorescence and detect potential copy number variants.

Each probe on a hybridized array is visualized as a mixture of red and green fluorochromes (see Figure 1). The ratio of red to green fluorescent signal for each probe is quantified by the scanner and the associated software plots these as log2 ratios according to their genomic position, and identifies regions falling outside preset boundaries. The resulting array traces allow interpretation of regions identified as genomically unbalanced. For instance, the trace from a child with Williams syndrome, a recurring microdeletion syndrome mediated by low copy repeats in the proximal region of chromosome 7, is illustrated in Figure 2. This imbalance was identified by the software and indicated by a red line.
Probe fluorescent log ratios should cluster closely around 0, as shown in Figure 2, indicating a green/red ratio of 1:1 for normal regions of the genome. Scattered array traces may result in inaccurate calling of abnormal regions, or failure to identify genomic imbalance (see Figure 3). Such scatter may be caused by a number of factors, including poor DNA quality, or the presence of raised levels of ozone in the atmosphere. Monitoring of ozone levels is recommended, and where elevated ozone levels are problematic, dedicated ozone exclusion cabinets are available; use of these cabinets generally results in markedly improved array quality.
<img alt="Figure 1" fo:content-width="6in" src="/files/ftp_upload/51718/51718fig1highres.jpg" width="600" /> 
Figure 1. Image of an array following hybridization. The white box shows a magnified area, where red probes and green probes can be visualized (indicating imbalance for the regions represented by these probes), against a background of yellow probes (indicating balanced genomic regions).
<img alt="Figure 2" fo:content-width="6in" src="/files/ftp_upload/51718/51718fig2highres.jpg" width="600" /> 
Figure 2. (A) Example trace for chromosome 7 in a sample with a 1.7Mb deletion, shown by an average ratio of -0.8 for 43 consecutive probes. The deleted region in this case is associated with Williams-Beuren syndrome, consistent with the referral indication of dysmorphic features, a heart defect and intellectual disability. (B) The deleted region above displayed in the USCS genome browser, showing the genes within the deleted region. <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/51718/51718fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" fo:content-width="6in" src="/files/ftp_upload/51718/51718fig3highres.jpg" width="600" /> 
Figure 3. Example of a scattered array trace for chromosome 7 in a sample with poor hybridization. <a href="https://www-jove-com.bdigitaluss.remotexs.co/files/ftp_upload/51718/51718fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<table border="0" cellpadding="0" cellspacing="0">
	<tbody>
		<tr>
			<td>Reagent</td>
			<td>Volume (&#181;l)</td>
		</tr>
		<tr>
			<td>Primers &#38; reaction buffer</td>
			<td align="right">20</td>
		</tr>
		<tr>
			<td>DNA (1&#181;g) + water</td>
			<td align="right">20</td>
		</tr>
		<tr>
			<td>Klenow Exonuclease DNA polymerase</td>
			<td align="right">10</td>
		</tr>
	</tbody>
</table>
Table 1. Summary of the reagents used for the labeling reaction.

Watch this Scientific Journal Video about Array Comparative Genomic Hybridization Array CGH for Detection of Genomic Copy Number Variants at JoVE.com

Array Comparative Genomic Hybridization Array CGH for Detection of Genomic Copy Number Variants

Array CGH for the detection of genomic copy number variants has replaced G-banded karyotype analysis. This paper describes the technology and its application in a diagnostic service laboratory.

Array Comparative Genomic Hybridization (Array CGH) for Detection of Genomic Copy Number Variants

Array CGH for the detection of genomic copy number variants has replaced G-banded karyotype analysis. This paper describes the technology and its ...

array-comparative-genomic-hybridization-array-cgh-for-detection

Universidad San Sebastian

Research

JoVE Journal

Biology

19.5K Views.  Guy's & St Thomas' NHS Foundation Trust. Array CGH for the detection of genomic copy number variants has replaced G-banded karyotype analysis. This paper describes the technology and its application in a diagnostic service laboratory.

Video: Array Comparative Genomic Hybridization Array CGH for Detection of Genomic Copy Number Variants

Detection of Copy Number Alterations Using Single Cell Sequencing

Detection of genomic changes at single cell resolution is important for characterizing genetic heterogeneity and evolution in normal tissues, cancers, and microbial populations. Traditional methods for assessing genetic heterogeneity have been limited by low resolution, low sensitivity, and/or low specificity. Single cell sequencing has emerged as a powerful tool for detecting genetic heterogeneity with high resolution, high sensitivity and, when appropriately analyzed, high specificity. Here we provide a protocol for the isolation, whole genome amplification, sequencing, and analysis of single cells. Our approach allows for the reliable identification of megabase-scale copy number variants in single cells. However, aspects of this protocol can also be applied to investigate other types of genetic alterations in single cells.

Single cell sequencing is an increasingly popular and accessible tool for addressing genomic changes at high resolution. We provide a protocol that uses single cell sequencing to identify copy number alterations in single cells.

Detection of genomic changes at single cell resolution is important for characterizing genetic heterogeneity and evolution in normal tissues, cancers, and ...

Genetics

Serum and Plasma Copy Number Detection Using Real-time PCR

Serum and plasma cell free DNA (cfDNA) has been shown as an informative, non-invasive source of biomarkers for cancer diagnosis, prognosis, monitoring, and prediction of treatment resistance. Starting from the hypothesis that androgen receptor (AR) gene copy number (CN) gain is a frequent event in metastatic castration resistance prostate cancer (mCRPC), we propose to analyze this event in cfDNA as a potential predictive biomarker.
We evaluated AR CN in cfDNA using 2 different real-time PCR assays and 2 reference genes (RNaseP and AGO1). DNA amount of 60 ng was used for each assay combination. AR CN gain was confirmed using Digital PCR as a more accurate method. CN variation analysis has already been demonstrated to be informative for the prediction of treatment resistance in the setting of mCRPC, but it could be useful also for other purposes in different patient settings. CN analysis on cfDNA has several advantages: it is non-invasive, rapid and easy to perform, and it starts from a small volume of serum or plasma material.

This manuscript describes the copy number variation analysis performed in serum or plasma DNA using real-time PCR approach. This method is suitable for the prediction of drug resistance in castration resistant prostate cancer patients, but it could be informative also for other diseases.

Serum and plasma cell free DNA (cfDNA) has been shown as an informative, non-invasive source of biomarkers for cancer diagnosis, prognosis, monitoring, ...

Cancer Research

An Array-based Comparative Genomic Hybridization Platform for Efficient Detection of Copy Number Variations in Fast Neutron-induced Medicago truncatula Mutants

Mutants are invaluable genetic resources for gene function studies. To generate mutant collections, three types of mutagens can be utilized, including biological such as T-DNA or transposon, chemical such as ethyl methanesulfonate (EMS), or physical such as ionization radiation. The type of mutation observed varies depending on the mutagen used. For ionization radiation induced mutants, mutations include deletion, duplication, or rearrangement. While T-DNA or transposon-based mutagenesis is limited to species that are susceptible to transformation, chemical or physical mutagenesis can be applied to a broad range of species. However, the characterization of mutations derived from chemical or physical mutagenesis traditionally relies on a map-based cloning approach, which is labor intensive and time consuming. Here, we show that a high-density genome array-based comparative genomic hybridization (aCGH) platform can be applied to efficiently detect and characterize copy number variations (CNVs) in mutants derived from fast neutron bombardment (FNB) mutagenesis in Medicago truncatula, a legume species. Whole genome sequence analysis shows that there are more than 50,000 genes or gene models in M. truncatula. At present, FNB-induced mutants in M. truncatula are derived from more than 150,000 M1 lines, representing invaluable genetic resources for functional studies of genes in the genome. The aCGH platform described here is an efficient tool for characterizing FNB-induced mutants in M. truncatula.

An Array-based Comparative Genomic Hybridization Platform for Efficient Detection of Copy Number Variations in Fast Neutron-induced Medicago truncatula Mutants

This protocol provides experimental steps and information about reagents, equipment, and analysis tools for researchers who are interested in carrying out whole genome array-based comparative genomic hybridization (CGH) analysis of copy number variations in plants.

Mutants are invaluable genetic resources for gene function studies. To generate mutant collections, three types of mutagens can be utilized, including ...

Detection of a CDH1 Rare Transcript Variant in Fresh-frozen Gastric Cancer Tissues by Chip-based Digital PCR

CDH1a, a non-canonical transcript of the CDH1 gene, has been found to be expressed in some gastric cancer (GC) cell lines, whereas it is absent in normal gastric mucosa. Recently, we detected CDH1a transcript variant in fresh-frozen tumor tissues obtained from patients with GC. The expression of this variant in tissue samples was investigated by the chip-based digital PCR (dPCR) approach presented here. dPCR offers the potential for an accurate, robust, and highly sensitive measurement of nucleic acids and is increasingly utilized for many applications in different fields. dPCR is capable of detecting rare targets; in addition, dPCR offers the possibility for absolute and precise quantification of nucleic acids without the need for calibrators and standard curves. In fact, the reaction partitioning enriches the target from the background, which improves amplification efficiency and tolerance to inhibitors. Such characteristics make dPCR an optimal tool for the detection of the CDH1a rare transcript.

Detection of a CDH1 Rare Transcript Variant in Fresh-frozen Gastric Cancer Tissues by Chip-based Digital PCR

The manuscript describes a chip-based digital PCR assay to detect a rare CDH1 transcript variant (CDH1a) in fresh-frozen normal and tumor tissues obtained from patients with gastric cancer.

CDH1a, a non-canonical transcript of the CDH1 gene, has been found to be expressed in some gastric cancer (GC) cell lines, whereas it is absent in normal ...

Technical Demonstration of Whole Genome Array Comparative Genomic Hybridization

Array comparative genomic hybridization (array CGH) is a method for detecting gains and losses of DNA segments or gene dosage in the genome 1. Recent advances in this technology have enabled high resolution comparison of whole genomes for the identification of genetic alterations in cancer and other genetic diseases 2. The Sub-Megabase Resolution Tiling-set array (or SMRT) array is comprised of a set of approximately thirty thousand overlapping bacterial artificial chromosome (BAC) clones that span the human genome in ~100 kilobase pair (kb) segments 2. These BAC targets are individually synthesized and spotted in duplicate on a single glass slide 2-4. Array CGH is based on the principle of competitive hybridization. Sample and reference DNA are differentially labeled with Cyanine-3 and Cyanine-5 fluorescent dyes, and co-hybridized to the array. After an incubation period the unbound samples are washed from the slide and the array is imaged. A freely available custom software package called SeeGH (www.flintbox.ca) is used to process the large volume of data collected - a single experiment generates 53,892 data points. SeeGH visualizes the log2 signal intensity ratio between the 2 samples at each BAC target which is vertically aligned with chromosomal position 5,6. The SMRT array can detect alterations as small as 50 kb in size 7. The SMRT array can detect a variety of DNA rearrangement events including DNA gains, losses, amplifications and homozygous deletions. A unique advantage of the SMRT array is that one can use DNA isolated from formalin fixed paraffin embedded samples. When combined with the low input requirements of unamplified DNA (25-100ng) this allows profiling of precious samples such as those produced by microdissection 7,8. This is attributed to the large size of each BAC hybridization target that allows the binding of sufficient labeled samples to produce signals for detection. Another advantage of this platform is the tolerance of tissue heterogeneity, decreasing the need for tedious tissue microdissection 8. This video protocol is a step-by-step tutorial from labeling the input DNA through to signal acquisition for the whole genome tiling path SMRT array.

This video is a technical demonstration of the hybridization protocol for whole genome tiling path array CGH, which scans the entire human genome using only 25-100 ng of DNA that can be isolated from a variety of sources, including archival formalin fixed material.

Array comparative genomic hybridization (array CGH) is a method for detecting gains and losses of DNA segments or gene dosage in the genome 1.  Recent ...

Pre-Implantation Genetic Testing for Aneuploidy on a Semiconductor Based Next-Generation Sequencing Platform

Next-generation sequencing has gained increasing importance in the clinical application in the determination of genetic variants. In the pre-implantation genetic test, this technique has its unique advantages in scalability, throughput, and cost. For the pre-implantation genetic test for aneuploidy analysis, the semiconductor-based next-generation sequencing (NGS) system presented here provides a comprehensive approach to determine structural genetic variants at a minimum resolution of 8 Mb. From sample acquisition to the final report, the working process requires multiple steps with close adherence to protocols. Since various critical steps could determine the outcome of amplification, quality of the library, coverage of reads, and output of data, descriptive information with visual demonstration other than words could offer more detail to the operation and manipulation, which may have a great impact on the results of all critical steps. The methods presented herein will display the procedures involved in whole genome amplification (WGA) of biopsied Trophectoderm (TE) cells, genomic library construction, sequencer management, and finally, generating copy number variants' reports.

The protocol presents the overall in-lab procedures required in pre-implantation genetic testing for aneuploidy on a semiconductor-based next-generation sequencing platform. Here we present the detailed steps of whole genome amplification, DNA fragment selection, library construction, template preparation, and sequencing working flow with representative results.

Next-generation sequencing has gained increasing importance in the clinical application in the determination of genetic variants. In the pre-implantation ...

Comparative Lesions Analysis Through a Targeted Sequencing Approach

Assessing intra-tumoral heterogeneity (ITH) is of paramount importance to anticipate failure of targeted therapies and design accordingly effective anti-tumor strategies. Although concerns are frequently raised due to differences in sample processing and depth of coverage, next-generation sequencing of solid tumors have unraveled a highly variable degree of ITH across tumor types. Capturing the genetic relatedness between primary and metastatic lesions through the identification of clonal and subclonal populations is critical to the design of therapies for advance-stage diseases. Here, we report a method for comparative lesions analysis that allows for the identification of clonal and subclonal populations among different specimens from the same patient. The experimental approach described here integrates three well-established approaches: histological analysis, high-coverage multi-lesion sequencing, and immunophenotypic analyses. In order to minimize the effects on the detection of subclonal events by inappropriate sample processing, we subjected tissues to careful pathological examination and neoplastic cell enrichment. Quality controlled DNA from neoplastic lesions and normal tissues was then subjected to high coverage sequencing, targeting the coding regions of 409 relevant cancer genes. While only looking at a limited genomic space, our approach enables evaluating the extent of heterogeneity among somatic alterations (single-nucleotide mutations and copy-number variations) in distinct lesions from a given patient. Through comparative analysis of sequencing data, we were able to distinguish clonal vs. subclonal alterations. The majority of ITH is often ascribed to passenger mutations; therefore, we also used immunohistochemistry to predict functional consequences of mutations. While this protocol has been applied to a specific tumor type, we anticipate that the methodology described here is broadly applicable to other solid tumor types.

This article describes a method to identify clonal and subclonal alterations among different specimens from a given patient. Although the experiments described here focus on a specific tumor type, the approach is broadly applicable to other solid tumors.

Assessing intra-tumoral heterogeneity (ITH) is of paramount importance to anticipate failure of targeted therapies and design accordingly effective ...

Behavior

DNA Microarrays: Sample Quality Control, Array Hybridization and Scanning

Microarray expression profiling of the nervous system provides a powerful approach to identifying gene activities in different stages of development, different physiological or pathological states, response to therapy, and, in general, any condition that is being experimentally tested1. Expression profiling of neural tissues requires isolation of high quality RNA, amplification of the isolated RNA and hybridization to DNA microarrays. In this article we describe protocols for reproducible microarray experiments from brain tumor tissue2. We will start by performing a quality control analysis of isolated RNA samples with Agilent's 2100 Bioanalyzer "lab-on-a-chip" technology. High quality RNA samples are critical for the success of any microarray experiment, and the 2100 Bioanalyzer provides a quick, quantitative measurement of the sample quality. RNA samples are then amplified and labeled by performing reverse transcription to obtain cDNA, followed by in vitro transcription in the presence of labeled nucleotides to produce labeled cRNA. By using a dual-color labeling kit, we will label our experimental sample with Cy3 and a reference sample with Cy5. Both samples will then be combined and hybridized to Agilent's 4x44 K arrays. Dual-color arrays offer the advantage of a direct comparison between two RNA samples, thereby increasing the accuracy of the measurements, in particular for small changes in expression levels, because the two RNA samples are hybridized competitively to a single microarray. The arrays will be scanned at the two corresponding wavelengths, and the ratio of Cy3 to Cy5 signal for each feature will be used as a direct measurement of the relative abundance of the corresponding mRNA. This analysis identifies genes that are differentially expressed in response to the experimental conditions being tested.

We demonstrate the use of DNA microarrays for expression profiling of the nervous system. We describe RNA quality control, sample labeling, and array hybridization and scanning.

Microarray expression profiling of the nervous system provides a powerful approach to identifying gene activities in different stages of development, ...

Detecting Somatic Genetic Alterations in Tumor Specimens by Exon Capture and Massively Parallel Sequencing

Efforts to detect and investigate key oncogenic mutations have proven valuable to facilitate the appropriate treatment for cancer patients. The establishment of high-throughput, massively parallel "next-generation" sequencing has aided the discovery of many such mutations. To enhance the clinical and translational utility of this technology, platforms must be high-throughput, cost-effective, and compatible with formalin-fixed paraffin embedded (FFPE) tissue samples that may yield small amounts of degraded or damaged DNA. Here, we describe the preparation of barcoded and multiplexed DNA libraries followed by hybridization-based capture of targeted exons for the detection of cancer-associated mutations in fresh frozen and FFPE tumors by massively parallel sequencing. This method enables the identification of sequence mutations, copy number alterations, and select structural rearrangements involving all targeted genes. Targeted exon sequencing offers the benefits of high throughput, low cost, and deep sequence coverage, thus conferring high sensitivity for detecting low frequency mutations.

We describe the preparation of barcoded DNA libraries and subsequent hybridization-based exon capture for detection of key cancer-associated mutations in clinical tumor specimens by massively parallel "next generation" sequencing. Targeted exon sequencing offers the benefits of high throughput, low cost, and deep sequence coverage, thus yielding high sensitivity for detecting low frequency mutations.

Efforts  to detect and investigate key oncogenic mutations have proven valuable to  facilitate the appropriate treatment for cancer patients. The ...

DNA Microarrays

Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica surfaces.
While DNA microarrays are used to monitor gene expression, protein microarrays detect biologically relevant interactions of a fluorescently labeled protein with other proteins, DNA, or small molecules.
DNA microarray slides are often called gene chips or DNA chips. DNA chips are widely used to profile thousands of genes parallelly. Other than gene expression, they are also used in studying microRNA expression, DNA copy numbers, and single-nucleotide polymorphism detection. Commercially, these chips are used in biotechnology, forensics, toxicology, drug discovery, and targeted therapy for infectious and genetic diseases.
The chemically stable nature of DNA probes makes DNA chips the most popular of the microarray technologies. The covalently bound single-stranded DNA probe retains its native interactions despite harsh chemicals and temperatures that are used during probe loading and chip preparation.
The most obvious shortcoming of DNA microarrays is the prerequisite of a known target sequence. Because DNA microarray probes are designed to complement the target cDNA sequence, the sequence of the mRNA from which the cDNA is copied must be known. This makes the technology unusable while looking for novel mRNA sequences. For such purposes, RNASeq is the preferred albeit expensive option.

DNA Microarrays: High-throughput Gene Expression Profiling

Mikromacierze DNA

Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in ...

Array Comparative Genomic Hybridization (Array CGH) for Detection of Genomic Copy Number Variants

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DNA Microarrays: Sample Quality Control, Array Hybridization and Scanning

Detecting Somatic Genetic Alterations in Tumor Specimens by Exon Capture and Massively Parallel Sequencing

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