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 wi...

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 border="0" cellpadding="0" cellspacing="0" width="573">
	<tbody>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">Name of Material/ Equipment</td>
			<td style="width:71px;">Company</td>
			<td style="width:119px;">Catalog Number</td>
			<td style="width:167px;">Comments/Description</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">CGH microarray 8 x 60K</td>
			<td style="width:71px;">Agilent</td>
			<td style="width:119px;">G4126</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Array CGH wash buffers</td>
			<td style="width:71px;">Agilent</td>
			<td style="width:119px;">5188-5226</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Array CGH hybridisation buffer</td>
			<td style="width:71px;">Agilent</td>
			<td style="width:119px;">5188-5380</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Minelute purification kit</td>
			<td style="width:71px;">Qiagen</td>
			<td align="right" style="width:119px;">28006</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Array CGH labelling kit</td>
			<td style="width:71px;">Enzo</td>
			<td style="width:119px;">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 rec...

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

Research

JoVE Journal

Biology

19.4K visualizações.  Guy's & St Thomas' NHS Foundation Trust.  Matriz CGH para a detecção de variantes do número de cópia genômicas substituiu análise do cariótipo G-unida. Este artigo descreve a tecnologia e sua aplicação em um laboratório de serviço de diagnóstico. 

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

Isolation of Genomic DNA from Mouse Tails

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 ...

Micro-drive Array for Chronic in vivo Recording: Drive Fabrication

Chronic recording of large populations of neurons is a valuable technique for studying the function of neuronal circuits in awake behaving rats. Lightweight recording devices carrying a high density array of tetrodes allow for the simultaneous monitoring of the activity of tens to hundreds of individual neurons. Here we describe a protocol for the fabrication of a micro-drive array with twenty one independently movable micro-drives. This device has been used successfully to record from hippocampal and cortical neurons in our lab. We show how to prepare a custom designed, 3-D printed plastic base that will hold the micro-drives. We demonstrate how to construct the individual micro-drives and how to assemble the complete micro-drive array. Further preparation of the drive array for surgical implantation, such as the fabrication of tetrodes, loading of tetrodes into the drive array and gold-plating, is covered in a subsequent video article.

Micro-drive Array for Chronic in vivo Recording: Drive Fabrication

In this protocol we demonstrate how to fabricate a micro-drive array for chronic electrophysiological recordings in rats.

Chronic recording of large populations of neurons is a valuable technique for studying the function of neuronal circuits in awake behaving rats. ...

Large Insert Environmental Genomic Library Production

The vast majority of microbes in nature currently remain inaccessible to traditional cultivation methods. Over the past decade, culture-independent environmental genomic (i.e. metagenomic) approaches have emerged, enabling researchers to bridge this cultivation gap by capturing the genetic content of indigenous microbial communities directly from the environment. To this end, genomic DNA libraries are constructed using standard albeit artful laboratory cloning techniques. Here we describe the construction of a large insert environmental genomic fosmid library with DNA derived from the vertical depth continuum of a seasonally hypoxic fjord. This protocol is directly linked to a series of connected protocols including coastal marine water sampling [1], large volume filtration of microbial biomass [2] and a DNA extraction and purification protocol [3]. At the outset, high quality genomic DNA is end-repaired with the creation of 5 -phosphorylated blunt ends. End-repaired DNA is subjected to pulsed-field gel electrophoresis (PFGE) for size selection and gel extraction is performed to recover DNA fragments between 30 and 60 thousand base pairs (Kb) in length. Size selected DNA is purified away from the PFGE gel matrix and ligated to the phosphatase-treated blunt-end fosmid CopyControl vector pCC1 (EPICENTRE <a href="http://www.epibio.com/item.asp?ID=385">http://www.epibio.com/item.asp?ID=385</a>). Linear concatemers of pCC1 and insert DNA are subsequently headfull packaged into phage particles by lambda terminase, with subsequent infection of phage-resistant E. coli cells. Successfully transduced clones are recovered on LB agar plates under antibiotic selection and archived in 384-well plate format using an automated colony picking robot (Qpix2, GENETIX). The current protocol draws from various sources including the CopyControl Fosmid Library Production Kit from EPICENTRE and the published works of multiple research groups [4-7]. Each step is presented with best practice in mind. Whenever possible we highlight subtleties in execution to improve overall quality and efficiency of library production. The whole process of fosmid library production and automated colony picking takes at least 7-10 days as there are many incubation steps included. However, there are several stopping points possible which are mentioned within the protocol.

Construction of a fosmid library with environmental genomic DNA isolated from the vertical depth continuum of a seasonally hypoxic fjord is described. The resulting clone library is picked into 384-well plates and archived for downstream sequencing and functional screening by the application of an automated colony picking system.

The vast majority of microbes in nature currently remain inaccessible to traditional cultivation methods. Over the past decade, culture-independent ...

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, ...

Genomic MRI - a Public Resource for Studying Sequence Patterns within Genomic DNA

Non-coding genomic regions in complex eukaryotes, including intergenic areas, introns, and untranslated segments of exons, are profoundly non-random in their nucleotide composition and consist of a complex mosaic of sequence patterns. These patterns include so-called Mid-Range Inhomogeneity (MRI) regions -- sequences 30-10000 nucleotides in length that are enriched by a particular base or combination of bases (e.g. (G+T)-rich, purine-rich, etc.). MRI regions are associated with unusual (non-B-form) DNA structures that are often involved in regulation of gene expression, recombination, and other genetic processes (Fedorova &amp; Fedorov 2010). The existence of a strong fixation bias within MRI regions against mutations that tend to reduce their sequence inhomogeneity additionally supports the functionality and importance of these genomic sequences (Prakash et al. 2009).
Here we demonstrate a freely available Internet resource -- the Genomic MRI program package -- designed for computational analysis of genomic sequences in order to find and characterize various MRI patterns within them (Bechtel et al. 2008). This package also allows generation of randomized sequences with various properties and level of correspondence to the natural input DNA sequences. The main goal of this resource is to facilitate examination of vast regions of non-coding DNA that are still scarcely investigated and await thorough exploration and recognition.

We present a public computational web site for the analysis of genomic sequences. It detects DNA sequence patterns with various non-random nucleotide compositions. This resource also generates randomized sequences with diverse levels of complexity.

Non-coding genomic regions in complex eukaryotes, including intergenic areas, introns, and untranslated segments of exons, are profoundly non-random in ...

Competitive Genomic Screens of Barcoded Yeast Libraries

By virtue of advances in next generation sequencing technologies, we have access to new genome sequences almost daily. The tempo of these advances is accelerating, promising greater depth and breadth. In light of these extraordinary advances, the need for fast, parallel methods to define gene function becomes ever more important. Collections of genome-wide deletion mutants in yeasts and E. coli have served as workhorses for functional characterization of gene function, but this approach is not scalable, current gene-deletion approaches require each of the thousands of genes that comprise a genome to be deleted and verified. Only after this work is complete can we pursue high-throughput phenotyping. Over the past decade, our laboratory has refined a portfolio of competitive, miniaturized, high-throughput genome-wide assays that can be performed in parallel. This parallelization is possible because of the inclusion of DNA 'tags', or 'barcodes,' into each mutant, with the barcode serving as a proxy for the mutation and one can measure the barcode abundance to assess mutant fitness. In this study, we seek to fill the gap between DNA sequence and barcoded mutant collections. To accomplish this we introduce a combined transposon disruption-barcoding approach that opens up parallel barcode assays to newly sequenced, but poorly characterized microbes. To illustrate this approach we present a new Candida albicans barcoded disruption collection and describe how both microarray-based and next generation sequencing-based platforms can be used to collect 10,000 - 1,000,000 gene-gene and drug-gene interactions in a single experiment.

We have developed comprehensive, unbiased genome-wide screens to understand gene-drug and gene-environment interactions. Methods for screening these mutant collections are presented.

By virtue of advances in next generation sequencing technologies, we have access to new genome sequences almost daily.  The tempo of these advances is ...

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

As DNA sequencing technology has markedly advanced in recent years2, it has become increasingly evident that the amount of genetic variation between any two individuals is greater than previously thought3. In contrast, array-based genotyping has failed to identify a significant contribution of common sequence variants to the phenotypic variability of common disease4,5. Taken together, these observations have led to the evolution of the Common Disease / Rare Variant hypothesis suggesting that the majority of the "missing heritability" in common and complex phenotypes is instead due to an individual's personal profile of rare or private DNA variants6-8. However, characterizing how rare variation impacts complex phenotypes requires the analysis of many affected individuals at many genomic loci, and is ideally compared to a similar survey in an unaffected cohort. Despite the sequencing power offered by today's platforms, a population-based survey of many genomic loci and the subsequent computational analysis required remains prohibitive for many investigators.
To address this need, we have developed a pooled sequencing approach1,9 and a novel software package1 for highly accurate rare variant detection from the resulting data. The ability to pool genomes from entire populations of affected individuals and survey the degree of genetic variation at multiple targeted regions in a single sequencing library provides excellent cost and time savings to traditional single-sample sequencing methodology. With a mean sequencing coverage per allele of 25-fold, our custom algorithm, SPLINTER, uses an internal variant calling control strategy to call insertions, deletions and substitutions up to four base pairs in length with high sensitivity and specificity from pools of up to 1 mutant allele in 500 individuals. Here we describe the method for preparing the pooled sequencing library followed by step-by-step instructions on how to use the SPLINTER package for pooled sequencing analysis (<a href="http://www.ibridgenetwork.org/wustl/splinter" target="_blank">http://www.ibridgenetwork.org/wustl/splinter</a>). We show a comparison between pooled sequencing of 947 individuals, all of whom also underwent genome-wide array, at over 20kb of sequencing per person. Concordance between genotyping of tagged and novel variants called in the pooled sample were excellent. This method can be easily scaled up to any number of genomic loci and any number of individuals. By incorporating the internal positive and negative amplicon controls at ratios that mimic the population under study, the algorithm can be calibrated for optimal performance. This strategy can also be modified for use with hybridization capture or individual-specific barcodes and can be applied to the sequencing of naturally heterogeneous samples, such as tumor DNA.

Pooled DNA sequencing is a fast and cost-effective strategy to detect rare variants associated with complex phenotypes in large cohorts. Here we describe the computational analysis of pooled, next-generation sequencing of 32 cancer-related genes using the SPLINTER software package. This method is scalable, and applicable to any phenotype of interest.

As DNA sequencing technology has markedly advanced in recent years2, it has become increasingly evident that the amount of genetic variation between any ...

Genomic Transformation of the Picoeukaryote Ostreococcus tauri

Common problems hindering rapid progress in Plant Sciences include cellular, tissue and whole organism complexity, and notably the high level of genomic redundancy affecting simple genetics in higher plants. The novel model organism Ostreococcus tauri is the smallest free-living eukaryote known to date, and possesses a greatly reduced genome size and cellular complexity1,2, manifested by the presence of just one of most organelles (mitochondrion, chloroplast, golgi stack) per cell, and a genome containing only ~8000 genes. Furthermore, the combination of unicellularity and easy culture provides a platform amenable to chemical biology approaches. Recently, Ostreococcus has been successfully employed to study basic mechanisms underlying circadian timekeeping3-6. Results from this model organism have impacted not only plant science, but also mammalian biology7. This example highlights how rapid experimentation in a simple eukaryote from the green lineage can accelerate research in more complex organisms by generating testable hypotheses using methods technically feasible only in this background of reduced complexity. Knowledge of a genome and the possibility to modify genes are essential tools in any model species. Genomic1, Transcriptomic8, and Proteomic9 information for this species is freely available, whereas the previously reported methods6,10 to genetically transform Ostreococcus are known to few laboratories worldwide.
In this article, the experimental methods to genetically transform this novel model organism with an overexpression construct by means of electroporation are outlined in detail, as well as the method of inclusion of transformed cells in low percentage agarose to allow selection of transformed lines originating from a single transformed cell. Following the successful application of Ostreococcus to circadian research, growing interest in Ostreococcus can be expected from diverse research areas within and outside plant sciences, including biotechnological areas. Researchers from a broad range of biological and medical sciences that work on conserved biochemical pathways may consider pursuing research in Ostreococcus, free from the genomic and organismal complexity of larger model species.

Genomic Transformation of the Picoeukaryote Ostreococcus tauri

This article describes genetic transformation of the unicellular marine alga Ostreococcus tauri by electroporation. This eukaryotic organism is an effective model platform for higher plants, possesing greatly reduced genomic and cellular complexity and being readily amenable to both cell culture and chemical biology.

Common problems hindering rapid progress in Plant Sciences include cellular, tissue and whole organism complexity, and notably the high level of genomic ...

Selective Capture of 5-hydroxymethylcytosine from Genomic DNA

5-methylcytosine (5-mC) constitutes ~2-8% of the total cytosines in human genomic DNA and impacts a broad range of biological functions, including gene expression, maintenance of genome integrity, parental imprinting, X-chromosome inactivation, regulation of development, aging, and cancer1. Recently, the presence of an oxidized 5-mC, 5-hydroxymethylcytosine (5-hmC), was discovered in mammalian cells, in particular in embryonic stem (ES) cells and neuronal cells2-4. 5-hmC is generated by oxidation of 5-mC catalyzed by TET family iron (II)/&alpha;-ketoglutarate-dependent dioxygenases2, 3. 5-hmC is proposed to be involved in the maintenance of embryonic stem (mES) cell, normal hematopoiesis and malignancies, and zygote development2, 5-10. To better understand the function of 5-hmC, a reliable and straightforward sequencing system is essential. Traditional bisulfite sequencing cannot distinguish 5-hmC from 5-mC11. To unravel the biology of 5-hmC, we have developed a highly efficient and selective chemical approach to label and capture 5-hmC, taking advantage of a bacteriophage enzyme that adds a glucose moiety to 5-hmC specifically12.
Here we describe a straightforward two-step procedure for selective chemical labeling of 5-hmC. In the first labeling step, 5-hmC in genomic DNA is labeled with a 6-azide-glucose catalyzed by &beta;-GT, a glucosyltransferase from T4 bacteriophage, in a way that transfers the 6-azide-glucose to 5-hmC from the modified cofactor, UDP-6-N3-Glc (6-N3UDPG). In the second step, biotinylation, a disulfide biotin linker is attached to the azide group by click chemistry. Both steps are highly specific and efficient, leading to complete labeling regardless of the abundance of 5-hmC in genomic regions and giving extremely low background. Following biotinylation of 5-hmC, the 5-hmC-containing DNA fragments are then selectively captured using streptavidin beads in a density-independent manner. The resulting 5-hmC-enriched DNA fragments could be used for downstream analyses, including next-generation sequencing.
Our selective labeling and capture protocol confers high sensitivity, applicable to any source of genomic DNA with variable/diverse 5-hmC abundances. Although the main purpose of this protocol is its downstream application (i.e., next-generation sequencing to map out the 5-hmC distribution in genome), it is compatible with single-molecule, real-time SMRT (DNA) sequencing, which is capable of delivering single-base resolution sequencing of 5-hmC.

Described is a two-step labeling process using &beta;-glucosyltransferase (&beta;-GT) to transfer an azide-glucose to 5-hmC, followed by click chemistry to transfer a biotin linker for easy and density-independent enrichment. This efficient and specific labeling method enables enrichment of 5-hmC with extremely low background and high-throughput epigenomic mapping via next-generation sequencing.

5-methylcytosine (5-mC) constitutes ~2-8% of the total cytosines in human genomic DNA and impacts a broad range of biological functions, including gene ...