Thanks to Kenn D. M&#248;ller and Claus Sternberg (DTU) for technical assistance and to Tue S. J&#248;rgensen for quantitative PCR analysis.

NOTE: An overview of the circular DNA purification and sequencing method (Circle-Seq) is illustrated in Figure 1.
1. Cultivation, Cell Harvest and Plasma Membrane Disruption
<ol>
	<li>Inoculate yeast cells (for example&#160;Saccharomyces cerevisiae) from an O/N culture into 50 ml complete nutrient medium of yeast peptone dextrose (YPD). Inoculate at a low initial cell density of 1-3 x 105 cells/ml or an optical density of approximately 0.01 OD600.
	<ol>
		<li>Incubate the cells at 30&#176;C with agitation at 150 rounds per minutes (rpm) until cells reach maximum cell density of approximately 1 x 1010 cells, approximately after 24 to 48 hr or a optical density at OD600 &#62; 10.0. 
		NOTE: The cultivation time is not crucial as lower cell concentrations can be used.</li>
	</ol>
	</li>
	<li>Transfer the outgrown culture to a 50 ml conical tube, pellet the cells by centrifugation at 800 x g for 3 min&#160;and discard the supernatant.</li>
	<li>Wash the pellet with 25 ml buffer solution of 10 mM Tris-Cl, 1 mM EDTA, pH 8.0, re-pellet the cells by centrifugation at 800 x g for 3 min and discard the supernatant.</li>
	<li>Resuspend the cell pellet in 1.2 ml resuspension buffer supplied from a plasmid column-purification kit.</li>
	<li>Optional step: Add highly diluted plasmids as controls for purification of circular DNA elements20. 
	NOTE: In the current dataset, a 7.7 &#181;l plasmid mixture was applied for each sample containing 1010 cells. The plasmid stock mixture consisted of three plasmids in different concentrations; pBR322 at 38 ng/sample, pUC19 at 0.5 ng/sample, and pUG72 at 0.01 ng/sample.</li>
	<li>Transfer the cell suspension into two 2 ml micro-centrifuge tubes, each supplemented with 0.5 mm glass beads at a 1:3 ratio of the total suspension volume.</li>
	<li>Vortex each tube at maximum speed for 10 min to disrupt plasma cell membranes. Pellet the beads by centrifugation at 268 x g for 30 sec&#160;and transfer the 1.2 ml combined supernatant from the two microcentrifuge tubes to a new tube. 
	NOTE: Alternative to step 1.6-1.7, use zymolyase to disrupt cells in 0.6 ml resuspension buffer solution. Ten units of zymolyase can disrupt 5 x 107 cells within 1.5 hr at 35&#176;C.</li>
</ol>
2. EccDNA Enrichment by Column Chromatography
<ol>
	<li>Follow the protocol from a kit for column purification of plasmids. In brief, treat each sample with 1.2 ml alkaline solution, mix gently and incubate 3 min at RT.</li>
	<li>Add 1.2 ml neutralization buffer, mix gently and centrifuge at 9650 x g for 5 min.</li>
	<li>Load the solution onto a column equilibrated with 1 ml equilibration solution and allow the liquid to flow through the column by gravity.</li>
	<li>Wash the column with 4 ml washing solution. When the solution has passed through the resin, carefully add 0.3 ml elution solution to replace most of the 0.35 ml column void volume.</li>
	<li>Elute DNA into a new collection tube with 1 ml elution solution and precipitate the DNA by adding 0.8 ml precipitation mixture. Centrifuge at 9650 x g for 10 min.</li>
	<li>Wash the DNA pellet with 0.5 ml 70% ethanol, centrifuge at 9650 x g for 5 min, air dry for 5 to 15 min and dissolve the purified DNA in 25 &#181;l sterile water. 
	NOTE: Only short term storage of DNA in water is recommended. Preferentially, proceed directly to step 3.</li>
</ol>
3. Digestion of Remaining Linear Chromosomal DNA
<ol>
	<li>Optional step: To facilitate specific digestion of linear DNA by exonuclease, treat the purified DNA with a rare-cutting endonuclease such as NotI. For 5 &#181;g DNA, use 1 unit NotI, 5 &#181;l 10x digestion buffer and sterile water to a total volume of 50 &#181;l. Incubate the reaction at 37&#176;C for 16 hr and heat inactivate the endonuclease at 80&#176;C for 5 min.</li>
	<li>Add 20 units exonuclease (2 &#181;l), 4 &#181;l ATP (25 mM), 34 &#181;l sterile water and 10 &#181;l 10x reaction buffer directly to the 50 &#181;l endonuclease-cleaved DNA to reach a 1x reaction volume of 100 &#181;l, using the ATP-dependent exonuclease kit.</li>
	<li>Perform hydrolysis of linear single-stranded and double-stranded DNA at 37&#176;C for 5 days or more. Add an additional 4 &#181;l ATP (25 mM), 0.6 &#181;l 10x reaction buffer and 20 units exonuclease every 24 hr to continue the enzymatic DNA digestion at a 1x reaction volume.</li>
	<li>After removal of linear DNA, sample 2 &#181;l from the exonuclease treated solution to confirm elimination of chromosomal linear DNA by quantitative polymerase chain reaction (qPCR), using a chromosomal marker such as the actin gene ACT120.
	<ol>
		<li>Each 20 &#181;l qPCR reaction volume contains 2 &#181;l exonuclease-treated sample, 150 nM ACT1 primers 5&#39;-TCCGTCTGGATTGGTGGTTCTA-3&#39; and 5&#39;-TGGACCACTTTCGTCGTATTC-3&#39;, 2% (volume/volume) dimethyl sulfoxide, and 10 &#181;l green fluorescent master mix.</li>
		<li>Use the reaction condition; 3 min at 95&#176;C, followed by 45 cycles of 15 sec at 95&#176;C and 30 sec at 60&#176;C. 
		NOTE: ACT1 is a particularly suitable marker for linear DNA since copy number variations in this gene are deleterious21-23 so eccDNA should not carry ACT1.</li>
		<li>Alternatives to analysis of DNA digestion by qPCR are&#160;standard PCR (4.3) or propidium iodide staining (4.4).
		<ol>
			<li>Use 2 &#181;l exonuclease-treated sample as PCR template with ACT1 primers 5&#39;-TGGATTCTGGTATGTTCTAGC-3&#39; and 5&#39;-GAACGACGTGAGTAACACC-3&#39;. As positive ACT1 control, use 50-100 ng genomic S. cerevisiae DNA as template. PCR reaction conditions; 3 min at 95&#176;C, followed by 35 cycles of 30 sec at 95&#176;C, 30 sec at 56&#176;C and 1 min at 72&#176;C.</li>
			<li>Run PCR reactions by gel electrophoresis on 1% agarose with 0.5 &#181;g/ml ethidium bromide. Look for a 0.8 kb&#160;ACT1 band.&#160;</li>
		</ol>
		</li>
		<li>The absence or presence of linear DNA can also be examined by propidium iodide staining before and after DNA amplification.&#8203;
		<ol>
			<li>Mix each DNA sample in a 1:1 volume with a 1:1,000 H2O-diluted solution of 20 mM propidium iodide stock. Leave solution in darkness for 10-20 min&#160;at RT and analyze DNA staining by fluorescence microscopy at 100x magnification using a red excitation fluorescence filter at 663-738 nm and an exposure-time of 5 to 30 sec. As DNA-staining control, use &#248;29-amplified genomic DNA from yeast and/or &#248;29-amplified plasmid.</li>
		</ol>
		</li>
	</ol>
	</li>
	<li>Heat inactivate the exonuclease solution at 70&#176;C for 30 min.</li>
</ol>
4. DNA Amplification
<ol>
	<li>Amplify the purified and enriched eccDNA from step 3.5) with &#248;29 DNA polymerase24-26 according to the protocol of the polymerase manufacturer.
	<ol>
		<li>In brief, mix 5 &#181;l enriched eccDNA with 5 &#181;l denaturation&#160;buffer.</li>
		<li>After 3 min at RT, add 10 &#181;l neutralization buffer. Mix gently and add 30 &#181;l master mix containing 29 &#181;l reaction buffer and 1 &#181;l &#248;29 DNA polymerase. Incubate the reaction at 30&#176;C for 16 hr or more (up to 72 hr). Heat inactivate the &#248;29 DNA polymerase at 65&#176;C for 3 min.</li>
	</ol>
	</li>
</ol>
5. Sequencing and Data Analysis
<ol>
	<li>Shear the amplified eccDNA with a focused ultrasonicator to an average target peak size of 300 bp. Use the following settings for a 130 &#181;l DNA sample: 450W peak intensity power, 60 sec treatment, 30% duty factor, 200 cycles per burst, temperature 7&#176;C.</li>
	<li>Add barcode index labels and adapters to the fragmented reads for synthesis of libraries for sequencing, using an appropriate method for library preparation.</li>
	<li>Run deep&#160;sequencing, for example as 141-nucleotide single-end reads on a high-throughput sequencing platform.</li>
	<li>Map reads to the yeast reference genome under investigation and allow reads to map to multiple regions. For example, use a freely available workflow system27,28 and short-read aligner mapping software29.</li>
	<li>Identify reads from regions of putative eccDNAs using contiguous reads, for example, more than seven contiguous reads (&#62;1 kb) without gaps20. 
	NOTE: Software is available27,28 for exploring mapped reads at genomic regions of interest.</li>
</ol>

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H., 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=Molecular+structure+of+double-minute+chromosomes+bearing+amplified+copies+of+the+epidermal+growth+factor+receptor+gene+in+gliomas.">Molecular structure of double-minute chromosomes bearing amplified copies of the epidermal growth factor receptor gene in gliomas.</a> Proceedings of the National Academy of Sciences of the United States of America. 101 (31), 11368-11373 (2004).</li><li>Ahn, K., Gotay, N., 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=High+rate+of+disease-related+copy+number+variations+in+childhood+onset+schizophrenia.">High rate of disease-related copy number variations in childhood onset schizophrenia.</a> Molecular psychiatry. 19 (5), 568-572 (2013).</li><li>Girirajan, S., Johnson, R. L., 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+increases+in+both+common+and+rare+copy+number+load+associated+with+autism.">Global increases in both common and rare copy number load associated with autism.</a> Human molecular genetics. 22 (14), 2870-2880 (2013).</li><li>Vogt, N., Gibaud, A., Lemoine, F., de la Grange, P., Debatisse, M., Malfoy, B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Amplicon+rearrangements+during+the+extrachromosomal+and+intrachromosomal+amplification+process+in+a+glioma.">Amplicon rearrangements during the extrachromosomal and intrachromosomal amplification process in a glioma.</a> Nucleic Acids Research. , (2014).</li></ol>

The authors declare that they have no competing financial interests.

The Circle-Seq method allows genome-scale detection of eccDNA from yeast cells with sequence-level resolution. The method is a mild eccDNA purification that does not require intensive vortex or pipetting and uses column separation by gravity to limit eccDNA breakage that would lead to exonuclease digestion in the&#160;subsequent step. These features of the method may be crucial for detecting large eccDNAs that contain gene sequences. Circle-Seq detected numerous eccDNAs including full genes (Dataset 1). It also detected the 86-kb yeast mitochondrial DNA. Thus, this protocol&#160;facilitates purification of large circular DNA elements. Keeping the number of DNA extraction steps to a minimum reduces&#160;the risk of eccDNA loss and maximizes&#160;yield. Based on results for control, spiked-in plasmids, Circle-Seq is highly sensitive, detecting a single circular DNA from 2,500 cells. Furthermore, removing abundant endogenous plasmids such as 2&#181; plasmid or mitochondrial DNA might&#160;significantly enhance sensitivity. Curing&#160;of 2&#181; from yeast cultures has been described30. Alternatively, 2&#181; and mitochondrial DNA removal might be achieved with a rare-cutting endonuclease, such as SwaI. However, the restriction enzyme step could target other eccDNAs of interest and limit the total eccDNA yield.
Critical steps for eccDNA detection were removal of linear DNA (step 3) and DNA sequencing (step 5) to a proper depth. To record the majority of eccDNAs from a cell population, deep&#160;sequencing might be required20. Paired-end sequencing should provide&#160;even greater confidence of eccDNA detection, as circular DNA junctions are expected to&#160;yield paired-end reads that map discordantly. These discrepancies support the discovery of circular DNA structures and can potentially be used as an additional eccDNA-detection filter.
The Circle-Seq method was validated using three independent S. cerevisiae CEN.PK populations. Detected sequences included previously reported eccDNAs, endogenous plasmids and spiked-in plasmids and hundreds of putative eccDNAs (Dataset 1). These findings support previous Circle-Seq datasets from S. cerevisiae S288c20. The discovery of several eccDNAs common to CEN.PK and S288c populations indicates that these loci have a propensity to exist as circular elements (Figure 4). We have previously shown that the [GAP1circle] is enriched under nitrogen limited conditions in the CEN.PK background8, though evidence of [GAP1circle] in other strain backgrounds has not been found. Finding of&#160;eccDNA from the CUP1-1 RSC30, ASP3-1, COS111, and HXT6 HXT7 loci in both S288c and CEN.PK suggests that a predisposition for DNA circularization is conserved between the yeast strains. It remains to be shown if [HXT6/7circle],&#160;[ASP3-1circle], [COS111circle], and [CUP1-1 RSC30circle] confer selective advantages to&#160;cells&#160;or if their existence is merely an effect of high rates of DNA circularization.
Taken together, the results indicate that Circle-Seq is well suited for detecting kilobase-sized eccDNAs and has advantages for identifying eccDNAs with complete genes. Circle-Seq is a highly sensitive method that enables whole genome-scale screens of eccDNAs from yeast. The Circle-Seq method could open a new field of research aimed at elucidating the role of eccDNA in generating gene deletions and amplifications. Given that DNA architecture and structure are largely conserved from eukaryotic yeast to higher eukaryotes, the Circle-Seq method should, in principle, be applicable to all eukaryotic cells, with slight modifications. At present, the method does not appear to have any limitations, although its ability to purify megabase-sized eccDNAs has yet to be shown. In addition, the use of &#248;29 DNA polymerase, which uses a rolling-circle amplification method31, creates a bias towards smaller eccDNAs making eccDNA quantification more difficult. Circle-Seq detects eccDNAs large enough to carry full genes, making it suitable for studies on double minutes&#8212;circular DNA from human somatic cells. Double minutes can contribute to cancer when proto-oncogenes are amplified on these elements32-37. Studies of eccDNAs in germline cells could be used to measure germline mutation rates and assess sperm quality, for example in livestock. Thus, Circle-Seq has the potential to yield insights into the rate at which genetic variation arises in the form of copy number variation, and lead to a novel understanding of diseases that involve gene copy-number variation38-40.

Detecting early or transient chromosomal amplification is difficult because it requires identifying alterations in single DNA molecules in large populations of cells. Chromosomal copy-number variations (CNVs) are generally detected well after their establishment, leaving only the final CNV structure as evidence of the mechanism that generated the variation1,2. Detecting and recovering extrachromosomal circular DNA (eccDNA) in earlier stages of CNV formation might elucidate ongoing processes in genomic rearrangements.
Previously, de novo discovery of eccDNA was by electron micrographs3, Giemsa staining of metaphase chromosomes4, or two-dimensional gel electrophoresis5. These methods provide little or no information about the sequence of the circular DNA. Targeted techniques such as Southern blotting6,7, inverse PCR8, or fluorescence in situ hybridization9 provide evidence only about specific eccDNA elements. None of these methods provide the sequence of all existing eccDNA types in a cell population.
Genomic divergence in a pool of cells can be characterized by genome sequencing and/or tiling arrays10,11. Detecting a deletion or amplification by conventional DNA purification methods usually requires that a mutated allele represent at least 0.1-1% of the cell population12,13. Acentric eccDNAs are expected to be even more transient in a cell culture due to their lack of centromeres and potential absence of DNA synthesis at replication. Thus, since most eccDNAs presumably are in low amounts and their sequences resemble the genome, alternative DNA extraction methods are needed to detect eccDNAs.
Several circular DNA purification techniques exploit the structural differences between chromosomes and circular DNA. For instance, high-speed ultracentrifugation in cesium-chloride gradients is used to isolate 350-3000 basepairs (bp) large eccDNAs from the human HeLa cancer cell line14. However, high-velocity can break or nick the backbone of supercoiled circular DNA structures, altering the sedimentation velocity15 and the eccDNA yield. Dutta and coworkers developed a method for de novo, genome-scale identification of circular DNA from mouse tissues as well as from cultures of chicken and human cells16,17. Their method is extraction of nuclei from homogenized tissue by sucrose ultracentrifugation followed by plasmid purification and several rounds of enzymatic reactions and DNA extractions. Their protocol primarily identifies 200-400 bp eccDNAs, called microDNAs. Dutta and coworkers also attempted purification of microDNAs from Saccharomyces cerevisiae but were unable to record microDNA from this yeast species16.
We have developed a novel method for de novo detection of eccDNA from yeast called Circle-Seq. This method enables genome-scale surveys for circular DNA molecules large enough to carry whole genes and as large as the 86 kilobase (kb) mitochondrial DNA (mtDNA). The Circle-Seq method was developed from a well-established prokaryotic plasmid purification method18,19, optimized for eukaryotic yeast cells and combined with deep&#160;sequencing. Using the Circle-Seq approach, 1756 different eccDNAs, all larger than 1 kb, were detected from ten S. cerevisiae S288c populations20. A size cut-off was chosen to focus on eccDNA that were&#160;large enough to carry whole genes. Circle-Seq was highly sensitive; it detected a single eccDNA within thousands of cells20. In the current study, Circle-Seq was used to isolate and identify 294 eccDNAs from three biological replicates of another S. cerevisiae yeast strain, CEN.PK. The data reveals that eccDNA is a common genetic element in S. cerevisiae strains.

<table>
	<tbody>
		<tr>
			<td>Bacto peptone</td>
			<td>BD Difco</td>
			<td>211677</td>
			<td>Alternative product can be used.</td>
		</tr>
		<tr>
			<td>Brilliant III SYBR Green PCR Master Mix&#160;</td>
			<td>Agilent Technologies</td>
			<td>600882</td>
			<td>For qPCR analysis. Alternative product can be used.</td>
		</tr>
		<tr>
			<td>Dextrose (D-glucose)</td>
			<td>Carl Roth</td>
			<td>HN06.4</td>
			<td>Alternative product can be used.</td>
		</tr>
		<tr>
			<td>Disruptor Beads, 0.5 mm</td>
			<td>Scientific Industries, Inc.</td>
			<td>SI-BG05</td>
			<td>Glass beads to disrupt plasma cell membranes. Alternative product can be used.</td>
		</tr>
		<tr>
			<td>Ethidium bromide</td>
			<td>Carl Roth</td>
			<td>2218.2</td>
			<td>Agarose gel stain for detecting DNA/RNA.</td>
		</tr>
		<tr>
			<td>GeneJet plasmid miniprep kit</td>
			<td>Thermo Fisher</td>
			<td>K0502</td>
			<td>Plasmid purifcation from bacteria. Alternative product can be used&#160;</td>
		</tr>
		<tr>
			<td>NotI, FastDigest</td>
			<td>Life Technologies -&#160; Thermo Fisher Scientific, USA</td>
			<td>FD0594</td>
			<td>Endonuclease. Alternative product can be used.&#160;</td>
		</tr>
		<tr>
			<td>Plasmid Mini AX kit&#160;</td>
			<td>A&#38;A Biotechnology, Poland</td>
			<td>010-50</td>
			<td>Plasmid purifcation kit used to purify eccDNA.&#160;&#160;</td>
		</tr>
		<tr>
			<td>Plasmid-Safe ATP-dependent DNase kit</td>
			<td>Epicentre, USA</td>
			<td>E3105K</td>
			<td>ATP-dependent exonuclease kit. Alternative product can be used.</td>
		</tr>
		<tr>
			<td>Propidium iodide&#160;</td>
			<td>Sigma-Aldrich, USA</td>
			<td>81845</td>
			<td>Alternative product can be used.</td>
		</tr>
		<tr>
			<td>pUG6 plasmid</td>
			<td>EUROSCARF, Germany</td>
			<td>P30114</td>
			<td>Marker gene: loxP-PAgTEF1-kanMX-TAgTEF1-loxP. Plasmid requests: Please contact Dr. Peter Philippsen@unibas.ch</td>
		</tr>
		<tr>
			<td>QIAGEN genomic-tip 100/G&#160;</td>
			<td>Qiagen, USA</td>
			<td>13343</td>
			<td>Genomic DNA purifcation from yeast. Alternative product can be used.</td>
		</tr>
		<tr>
			<td>REPLI-g Mini Kit protocol&#160;</td>
			<td>Qiagen, USA</td>
			<td>150023</td>
			<td>Amplification of eccDNA by the phi29 polymerase&#160;</td>
		</tr>
		<tr>
			<td>Yeast extract</td>
			<td>BD Difco</td>
			<td>210929</td>
			<td>Alternative product can be used.</td>
		</tr>
		<tr>
			<td>Zymolyase 100T (Lyticase, Yeast Lytic Enzyme)</td>
			<td>Nordic BioSite, Sweden</td>
			<td>Z1004-3</td>
			<td>Alternative product can be used.</td>
		</tr>
		<tr>
			<td></td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Data access to sequence files</td>
			<td>European Nucleotide Archive&#160;</td>
			<td></td>
			<td>EccDNA dataset from Saccharomyces cerevisiae CEN.PK113-7D. Study accession number PRJEB9684. 2nd accession number is ERP010820. Locus tag prefix is BN2032.&#160;</td>
		</tr>
		<tr>
			<td></td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Strains</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td colspan="2">Saccharomyces cerevisiae CEN.PK113-7D</td>
			<td></td>
			<td>Genotype MATa MAL2-8c SUC2</td>
		</tr>
		<tr>
			<td>Saccharomyces cerevisiae yeast deletion library pool</td>
			<td>EUROSCARF, Germany</td>
			<td></td>
			<td>S288c BY4741 pool of 4400 viable single-gene deletion mutants disrubted by KanMX module. Genotypes MATa his3&#8710;1 leu2&#8710;0 met15&#8710;0 ura3&#8710;0 genexxx::KanMX.</td>
		</tr>
		<tr>
			<td></td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Equipments</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>DNA Spectrophotometer&#160;</td>
			<td colspan="2">NanoDrop 1000 Spectrophotometer, Thermo Fisher</td>
			<td>Measuring DNA concentration. Alternative product can be used.</td>
		</tr>
		<tr>
			<td>Fluorescence microscopy</td>
			<td>Nikon Optronics Magnafire. Red excitation fluorescence filter, 663-738 nm.</td>
			<td></td>
			<td>Alternative product can be used.</td>
		</tr>
		<tr>
			<td>Robotic library-build system</td>
			<td>Apollo 324, IntegenX Inc.</td>
			<td></td>
			<td>DNA library preparation. Alternative product can be used.</td>
		</tr>
		<tr>
			<td>Sequencing platform</td>
			<td colspan="2">Illumina HiSeq 2000 platform, Illumina Inc.</td>
			<td>DNA sequencing. Alternative product can be used.</td>
		</tr>
		<tr>
			<td>Ultrasonicator</td>
			<td colspan="2">Covaris LE220, microTUBE AFA Fiber tubes</td>
			<td>Alternative product can be used.</td>
		</tr>
		<tr>
			<td></td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td></td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Methods</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>2% YPD media&#160;</td>
			<td></td>
			<td></td>
			<td>Mix 10 g Dextrose, 10 g Yeast extract, 20 g Bacto peptone and add H2O to a total volume of 1000 ml and autoclave.</td>
		</tr>
		<tr>
			<td>Circle-Seq test on genomic DNA</td>
			<td></td>
			<td></td>
			<td>Genomic DNA was purified (Qiagen) from a pool of the yeast deletion library (Euroscarf). The DNA concentration was measured by nanodrop and 30 &#181;g genomic DNA was pipetted into two micro centrifuge tubes. One micro centrifuge tube was supplemented with 100 nanogram plasmid (pUG6). The DNA samples were purified by Circle-Seq, omitting the protocol steps 1.1-1.3 and 1.5-1.7. The eluted DNA concentrations were measured by nanodrop and the entire DNA yield from sample GD and GD+P was treated with exonuclease for a period of 29 hours. A 10% fraction was collected for phi29-amplification and PCR analysis, while the remaining DNA was subjected to 72 hour exonuclease treatment. The samples were analyzed for linear DNA content by PCR, using the ACT1 gene as chromosomal marker. A 5% fraction of each of the exonuclease treated samples was amplified by the phi29 DNA polymerase for 16 hours (Qiagen). The presence of DNA in each sample was examined by loading an equal amount (7 &#181;l) in wells on an 0.5 &#181;g/ml ethidium-bromide 0.9% agarose gel after running gel-electrophoresis.&#160;</td>
		</tr>
		<tr>
			<td>Mapping software</td>
			<td>Bowtie2 aligner, John Hopkins University</td>
			<td></td>
			<td>Ultrafast short read alignment. Reference: Langmead B, Salzberg S. Fast gapped-read alignment with Bowtie 2. Nature Methods. 2012, 9:357-359.</td>
		</tr>
		<tr>
			<td>Propidium iodide stain</td>
			<td></td>
			<td></td>
			<td>Images of propidium iodine stained DNA were captured by fluorescence microscopy at 100x magnification (100x/1.30 oil, Nikon) in the RFP channel (red excitation fluorescence filter, 663-738 nm) using identical exposition time (5 seconds).&#160;</td>
		</tr>
		<tr>
			<td>Workflow bioinformatic system</td>
			<td>Galaxy, Open source.</td>
			<td></td>
			<td>A free web-based platform for data intensive biomedical research. References: Goecks, J, Nekrutenko, A, Taylor, J and The Galaxy Team. Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences. Genome Biol. 2010 Aug 25;11(8):R86. Blankenberg D, Von Kuster G, Coraor N, Ananda G, Lazarus R, Mangan M, Nekrutenko A, Taylor J. &#34;Galaxy: a web-based genome analysis tool for experimentalists&#34;. Current Protocols in Molecular Biology. 2010 Jan; Chapter 19:Unit 19.10.1-21. Giardine B, Riemer C, Hardison RC, Burhans R, Elnitski L, Shah P, Zhang Y, Blankenberg D, Albert I, Taylor J, Miller W, Kent WJ, Nekrutenko A. &#34;Galaxy: a platform for interactive large-scale genome analysis.&#34; Genome Research. 2005 Oct; 15(10):1451-5.</td>
		</tr>
	</tbody>
</table>

genome-wide purification of extrachromosomal circular dna from eukaryotic cells

Extrachromosomal circular DNAs (eccDNAs) are common genetic elements in Saccharomyces cerevisiae and are reported in other eukaryotes as well. EccDNAs contribute to genetic variation among somatic cells in multicellular organisms and to evolution of unicellular eukaryotes. Sensitive methods for detecting eccDNA are needed to clarify how these elements affect genome stability and how environmental and biological factors&#160;induce their formation in eukaryotic cells. This video presents a sensitive eccDNA-purification method called Circle-Seq. The method encompasses column purification of circular DNA, removal of remaining linear chromosomal DNA, rolling-circle amplification of eccDNA, deep sequencing, and mapping. Extensive exonuclease treatment&#160;was&#160;required for sufficient linear chromosomal DNA degradation. The rolling-circle amplification step by &#966;29 polymerase enriched for circular DNA over linear DNA. Validation of the Circle-Seq method on three S. cerevisiae CEN.PK populations of 1010 cells detected hundreds of eccDNA profiles in sizes larger than 1 kilobase. Repeated findings of ASP3-1, COS111, CUP1, RSC30,&#160;HXT6, HXT7 genes on circular DNA in both S288c and CEN.PK suggests that DNA circularization is conserved between strains at these loci. In sum, the Circle-Seq method has broad applicability for genome-scale screening for eccDNA in eukaryotes as well as for detecting specific eccDNA types.

To validate the Circle-Seq method, three S. cerevisiae CEN.PK populations of 1 x 1010 cells were screened after cells were grown separately in YPD for ten generations. Chromosomal linear DNA elimination was confirmed by the absence of a qPCR ACT1 signal as described previously20 (data not shown). Purified and enriched eccDNA was sequenced up to 68 million reads (141-nucleotide single-end reads) and mapped to the CEN.PK113-7D reference genome (version 19 June 2012). Recordings of putative eccDNAs from the three samples named C1, C2 and C4 were assigned to genomic regions mapped by contiguous reads longer than 1 kb. Based on 10,000 Monte Carlo simulations, the significance of each region mapped by contiguous reads longer than 1 kb was estimated. From this 79, 159 and 56 regions were annotated as likely eccDNA sequences (p &#60; 0.1, Dataset 1). The number of recorded contiguous reads &#62; 1 kb increased as a function of sequence depth suggesting that even more eccDNA elements would have been recorded if samples had been sequenced further (Figure&#160;2). As expected, the Circle-Seq method extracted numerous reads from a number of known circular DNA elements including the 2&#181; plasmid, mitochondrial DNA, ribosomal RNA genes on chromosome XII, and the three internal control plasmids pBR322, pUC19 and pUG72 that were spiked into samples just before column purification (Figure 3).
The video shows an example of contiguous reads that mapped to the HXT7_ARS432_HXT6 locus on chromosome IV. Previously, the [HXT6/7circle] was detected by Circle-Seq in ten S288c populations (each with 1 x 1010 cells) and the circular DNA structure was confirmed by inverse PCR analysis20. The [HXT6/7circle] was also recorded in each of the three CEN.PK populations (Figure 4A). Moreover, most of the common eccDNA genes among replicate samples of CEN.PK overlapped eccDNA genes from the S288c datasets (Figure 4B).
To test the specificity of the Circle-Seq protocol for circular DNA purification, two samples, each with 30 &#181;g genomic DNA, were tested. One sample was supplemented with 100 ng plasmid DNA and eccDNA from both&#160;samples were purified by the Circle-Seq protocol. After column separation, the DNA yield was 1.27% (380 ng) for the sample without plasmid (GD) and 1.60% (480 ng) for the sample with plasmid (GD+P). The efficiency of exonuclease treatment was tested for linear DNA content after 29 hr&#160;and 72 hr&#160;using PCR against ACT1. No samples contained amplified ACT1 (data not shown). A fraction of each exonuclease-treated sample was further amplified by the &#248;29 polymerase and the products of enzymatic reactions were analyzed by propidium iodide staining (Figure 5A-F) and agarose gel electrophoresis (Figure 5G). Samples after exonuclease treatment showed minimal propidium iodine-stain (Figure 5A-B). The &#248;29-amplified sample with only genomic DNA revealed thread-like structures (Figure 5C) similar to the control sample (Figure 5E). The &#248;29-amplified sample that had added plasmid revealed foci (Figure 5D)&#160;resembling the plasmid control (Figure 5F). The images indicated that &#248;29 polymerase enriched for circular DNA over linear DNA. Most linear chromosomal DNA was removed from samples after 29 hr exonuclease treatment (Figure 5A-B, G). However, extensive exonuclease treatment for more than 100 hr and using more than 100 units&#160;was needed to remove all chromosomal linear DNA, as &#248;29-amplified&#160;samples still showed a background of thread-like structures after 72 hr exonuclease treatment (Figure 5C-D).
<img alt="Figure 1" src="/files/ftp_upload/54239/54239fig1.jpg" /> 
Figure 1. Outline of the Circle-Seq method. The protocol has 5 steps: 1) cell culturing, 2) purification and enrichment of eccDNA by column chromatography, 3) digestion of remaining linear chromosomal DNA in the eluate fraction, 4) amplification of DNA by &#248;29 DNA polymerase, and 5) sequencing of highly enriched eccDNA and mapping of reads to the S. cerevisiae reference genome. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54239/54239fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" src="/files/ftp_upload/54239/54239fig2.jpg" /> 
Figure 2. Contiguous reads &#62; 1 kb as function of sequence depth. EccDNA from 1 x 1010 cells increase as a function of sequence depth (in millions of mapped reads). Shown: biological triplicates from haploid CEN.PK S. cerevisiae populations (C1, C2, C4) separated by 1010 cell divisions. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54239/54239fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" src="/files/ftp_upload/54239/54239fig3.jpg" /> 
Figure 3. Detection of known circular DNA elements.&#160;(A-B) Scatter plots of read coverage (read density) in percent for plasmids in CEN.PK biological replicates C1, C2 and C4. (A) Mapped reads to the endogenous yeast plasmids were: 2&#181;; [rDNAcircle] (ribosomal RNA genes from chromosome XII); and mtDNA (the mitochondrial DNA). (B) Unique reads mapped to control plasmids. Control plasmids were spiked into samples before column purification. Plasmid ratios per cell were: pBR322 (plus signs) 1:1, pUC19 (circles) 1:50, and pUG72 (triangles) 1:2,500.
<img alt="Figure 4" src="/files/ftp_upload/54239/54239fig4.jpg" /> 
Figure 4. Common eccDNA elements in CEN.PK and S288c. (A) Venn diagram displaying overlap among the 476 genes on 294 eccDNA elements in the three CEN.PK samples (C1, C2, C4). The 16 common overlapping eccDNA genes/plasmids are annotated (all gene names are in Dataset 1). (B) Venn diagram of all recorded genes on putative eccDNAs from the three CEN.PK samples (C1, C2, C4), compared to all recorded genes on putative eccDNAs from 10 S288c samples: S1-S2, R1-R4, Z1-Z4 (see reference20). Shown are 13 biological replicates (S1-S2, R1-R4, Z1-Z4, C1-C3) with genes/plasmids and putative eccDNA regions that overlapped a minimum of 2 strain backgrounds and either 3 or more experimental setups. C samples, CEN.PK; R and Z samples, S288c BY4741; S samples, S288c M3750. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54239/54239fig4large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 5" src="/files/ftp_upload/54239/54239fig5.jpg" /> 
Figure 5. Visualization of DNA samples after exonuclease and &#248;29 treatment. (A-F) Propidium iodide staining of DNA. Scale bar, 10 &#181;m. (A, C and E) Samples with genomic DNA (GD); (B and D)&#160;samples with GD plus plasmid (GD+P). (A-B) After 29 hr exonuclease treatment (EXO 29 h); (C-D) after 72 hr exonuclease treatment followed by &#248;29 polymerase amplification (EXO 72 h + &#248;29). (E) Genomic DNA control after e: &#248;29 polymerase amplification; (F) plasmid control (5.5 kb) after 29 polymerase amplification; (G&#248;) agarose gel-eletrophoresis. From left: L, 1 kb&#160;markers; P, plasmid control (5.5 kb) after EXO 29 hr; GD, after EXO 29 hr (sample as in A); GD+P, after EXO 29 hr (sample as B); GD and GD+P, after EXO 29 hr + &#248;29; GD and GD+P, after EXO 72 hr + &#248;29 (sample as in C-D). See Table S1 for extra details. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54239/54239fig5large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Dataset 1" src="/files/ftp_upload/54239/54239dataset1.jpg" /> 
Dataset 1. Potential DNA circularization regions in CEN.PK. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/54239/DATASET1-CENPK.xlsx">Please click here to download this file.</a> 
Shown are sequence data and analyses for 348 regions. Columns are A-D, eccDNA mapping. A (first column from left), sample from which putative eccDNA was identified; B, chromosome; C-D, start and end coordinates of putative eccDNAs. E-H, eccDNA content. E, autonomously replicating sequence (ARS) in the region; F, complete gene in the region; G, part of gene included in the region; H, BLASTN-identified gene. I-O, EccDNA coverage and p-values. I, longest region with a uniquely annotated sequence in bp; J, number of all mapped reads; K, coverage of all mapped reads by fragments per kb from a million mapped reads (FPKM); L, p-value for putative eccDNA compared to occurrence by chance from Monte Carlo simulations; M, number of uniquely mapped reads; N-O; as K and L using only uniquely mapped reads (UFPKM). Parameters for mapping of reads and Monte Carlo simulations were as described20.

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Genome-wide Purification of Extrachromosomal Circular DNA from Eukaryotic Cells

This paper presents a sensitive method called Circle-Seq for purifying extrachromosomal circular DNA (eccDNA). The method encompasses column purification, removal of remaining linear chromosomal DNA, rolling-circle amplification and high-throughput sequencing. Circle-Seq is applicable to genome-scale screening of eukaryotic eccDNA and studying genome instability and copy-number variation.

Extrachromosomal circular DNAs (eccDNAs) are common genetic elements in Saccharomyces cerevisiae and are reported in other eukaryotes as well. EccDNAs ...

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25.0K Views.  University of Copenhagen. This paper presents a sensitive method called Circle-Seq for purifying extrachromosomal circular DNA (eccDNA). The method encompasses column purification, removal of remaining linear chromosomal DNA, rolling-circle amplification and high-throughput sequencing. Circle-Seq is applicable to genome-scale screening of eukaryotic eccDNA and studying genome instability and copy-number variation. 

Video: Genome-wide Purification of Extrachromosomal Circular DNA from Eukaryotic Cells

Staining of Proteins in Gels with Coomassie G-250 without Organic Solvent and Acetic Acid

In classical protein staining protocols using Coomassie Brilliant Blue (CBB), solutions with high contents of toxic and flammable organic solvents (Methanol, Ethanol or 2-Propanol) and acetic acid are used for fixation, staining and destaining of proteins in a gel after SDS-PAGE. To speed up the procedure, heating the staining solution in the microwave oven for a short time is frequently used. This usually results in evaporation of toxic or hazardous Methanol, Ethanol or 2-Propanol and a strong smell of acetic acid in the lab which should be avoided due to safety considerations. In a protocol originally published in two patent applications by E.M. Wondrak (US2001046709 (A1), US6319720 (B1)), an alternative composition of the staining solution is described in which no organic solvent or acid is used. The CBB is dissolved in bidistilled water (60-80mg of CBB G-250 per liter) and 35 mM HCl is added as the only other compound in the staining solution. The CBB staning of the gel is done after SDS-PAGE and thorough washing of the gel in bidistilled water. By heating the gel during the washing and staining steps, the process can be finished faster and no toxic or hazardous compunds are evaporating. The staining of proteins occurs already within 1 minute after heating the gel in staining solution and is fully developed after 15-30 min with a slightly blue background that is destained completely by prolonged washing of the stained gel in bidistilled water, without affecting the stained protein bands.

A short protocol for protein staining with Coomassie Brilliant Blue (CBB) G-250 in polyacrylamide gels is described without using organic solvents or acetic acid as in the classical staining procedures with CBB.

In classical protein staining protocols using Coomassie Brilliant Blue (CBB), solutions with high contents of toxic and flammable organic solvents ...

Purification of Mitochondria from Yeast Cells

Mitochondria are the main site of ATP production during aerobic metabolism in eukaryotic non-photosynthetic cells1. These complex organelles also play essential roles in apoptotic cell death2, cell survival3, mammalian development4, neuronal development and function4, intracellular signalling5, and longevity regulation6. Our understanding of these complex biological processes controlled by mitochondria relies on robust methods for assessing their morphology, their protein and lipid composition, the integrity of their DNA, and their numerous vital functions. The budding yeast Saccharomyces cerevisiae, a genetically and biochemically manipulable unicellular eukaryote with annotated genome and well-defined proteome, is a valuable model for studying the molecular and cellular mechanisms underlying essential biological functions of mitochondria. For these types of studies, it is crucial to have highly pure mitochondria. Here we present a detailed description of a rapid and effective method for purification of yeast mitochondria. This method enables the isolation of highly pure mitochondria that are essentially free of contamination by other organelles and retain their structural and functional integrity after their purification. Mitochondria purified by this method are suitable for cell-free reconstitution of essential mitochondrial processes and can be used for the analysis of mitochondrial structure and functions, mitochondrial proteome and lipidome, and mitochondrial DNA.

We describe a rapid and effective method for purification of mitochondria from the yeast Saccharomyces cerevisiae. This method enables the high-yield isolation of pure mitochondria that are essentially free of contamination by other organelles and retain their structural and functional integrity after their purification.

Mitochondria are the main site of ATP production during aerobic metabolism in eukaryotic non-photosynthetic cells1. These complex organelles also play ...

Genome-wide Analysis of Aminoacylation (Charging) Levels of tRNA Using Microarrays

tRNA aminoacylation, or charging, levels can rapidly change within a cell in response to the environment[1]. Changes in tRNA charging levels in both prokaryotic and eukaryotic cells lead to translational regulation which is a major cellular mechanism of stress response. Familiar examples are the stringent response in E. coli and the Gcn2 stress response pathway in yeast ([2-6]). Recent work in E. coli and S. cerevisiae have shown that tRNA charging patterns are highly dynamic and depends on the type of stress experienced by cells [1, 6, 7]. The highly dynamic, variable nature of tRNA charging makes it essential to determine changes in tRNA charging levels at the genomic scale, in order to fully elucidate cellular response to environmental variations. In this review we present a method for simultaneously measuring the relative charging levels of all tRNAs in S. cerevisiae . While the protocol presented here is for yeast, this protocol has been successfully applied for determining relative charging levels in a wide variety of organisms including E. coli and human cell cultures[7, 8].

Genome-wide Analysis of Aminoacylation Charging Levels of tRNA Using Microarrays

We describe a method for microarray analysis to determine relative aminoacylation levels of all tRNAs from S. cerivisiae.

tRNA aminoacylation, or charging, levels can rapidly change within a cell in response to the environment[1]. Changes in tRNA charging levels in both ...

Genome-wide Analysis using ChIP to Identify Isoform-specific Gene Targets

Recruitment of transcriptional and epigenetic factors to their targets is a key step in their regulation. Prominently featured in recruitment are the protein domains that bind to specific histone modifications. One such domain is the plant homeodomain (PHD), found in several chromatin-binding proteins. The epigenetic factor RBP2 has multiple PHD domains, however, they have different functions (Figure 4). In particular, the C-terminal PHD domain, found in a RBP2 oncogenic fusion in human leukemia, binds to trimethylated lysine 4 in histone H3 (H3K4me3)1. The transcript corresponding to the RBP2 isoform containing the C-terminal PHD accumulates during differentiation of promonocytic, lymphoma-derived, U937 cells into monocytes2. Consistent with both sets of data, genome-wide analysis showed that in differentiated U937 cells, the RBP2 protein gets localized to genomic regions highly enriched for H3K4me33. Localization of RBP2 to its targets correlates with a decrease in H3K4me3 due to RBP2 histone demethylase activity and a decrease in transcriptional activity. In contrast, two other PHDs of RBP2 are unable to bind H3K4me3. Notably, the C-terminal domain PHD of RBP2 is absent in the smaller RBP2 isoform4. It is conceivable that the small isoform of RBP2, which lacks interaction with H3K4me3, differs from the larger isoform in genomic location. The difference in genomic location of RBP2 isoforms may account for the observed diversity in RBP2 function. Specifically, RBP2 is a critical player in cellular differentiation mediated by the retinoblastoma protein (pRB). Consistent with these data, previous genome-wide analysis, without distinction between isoforms, identified two distinct groups of RBP2 target genes: 1) genes bound by RBP2 in a manner that is independent of differentiation; 2) genes bound by RBP2 in a differentiation-dependent manner.
To identify differences in localization between the isoforms we performed genome-wide location analysis by ChIP-Seq. Using antibodies that detect both RBP2 isoforms we have located all RBP2 targets. Additionally we have antibodies that only bind large, and not small RBP2 isoform (Figure 4). After identifying the large isoform targets, one can then subtract them from all RBP2 targets to reveal the targets of small isoform. These data show the contribution of chromatin-interacting domain in protein recruitment to its binding sites in the genome.

Here we are presenting a chromatin immunoprecipitation (ChIP) procedure for genome-wide location analysis of protein isoforms that differ in a histone-binding domain. We are applying it to ChIP-Seq analysis to identify the targets of the KDM5A/JARID1A/RBP2 histone demethylase.

Recruitment of transcriptional and epigenetic factors to their targets is a key step in their regulation. Prominently featured in recruitment are the ...

Streamlined Purification of Plasmid DNA From Prokaryotic Cultures

We describe the complete process of AcroPrep Advance Filter Plates for 96 plasmid preparations, starting from prokaryotic culture and ending with high purity DNA. Based on multi-well filtration for bacterial lysate clearance and DNA purification, this method creates a streamlined process for plasmid preparation. Filter plates containing silica-based media can easily be processed by vacuum filtration or centrifuge to yield appreciable quantities of plasmid DNA. Quantitative analyses determine the purified plasmid DNA is consistently of high quality with average OD260/280 ratios of 1.97. Overall, plasmid yields offer more pure DNA for downstream applications, such as sequencing and cloning. This streamlined method of using AcroPrep Advance Filter Plates allows for manual, semi-automated or fully-automated processing.

This protocol is a cost effective alternative for efficient parallel clarification and plasmid DNA purification from E. coli cultures. The AcroPrep Advance process starts with an optimized lysate clarification filter plate followed by purification on a high binding capacity DNA binding filter plate.

We describe the complete process of AcroPrep Advance Filter Plates for 96 plasmid preparations, starting from prokaryotic culture and ending with high ...

Genome-wide Screen for miRNA Targets Using the MISSION Target ID Library

The Target ID Library is designed to assist in discovery and identification of microRNA (miRNA) targets. The Target ID Library is a plasmid-based, genome-wide cDNA library cloned into the 3'UTR downstream from the dual-selection fusion protein, thymidine kinase-zeocin (TKzeo). The first round of selection is for stable transformants, followed with introduction of a miRNA of interest, and finally, selecting for cDNAs containing the miRNA's target. Selected cDNAs are identified by sequencing (see Figure 1-3 for Target ID Library Workflow and details).
To ensure broad coverage of the human transcriptome, Target ID Library cDNAs were generated via oligo-dT priming using a pool of total RNA prepared from multiple human tissues and cell lines. Resulting cDNA range from 0.5 to 4 kb, with an average size of 1.2 kb, and were cloned into the p3&#900;TKzeo dual-selection plasmid (see Figure 4 for plasmid map). The gene targets represented in the library can be found on the Sigma-Aldrich webpage. Results from Illumina sequencing (Table 3), show that the library includes 16,922 of the 21,518 unique genes in UCSC RefGene (79%), or 14,000 genes with 10 or more reads (66%).

The Target ID Library is a plasmid-based, genome-wide collection of cloned cDNA used to identify miRNA targets. Here we demonstrate its use and application.

The Target ID Library is designed to assist in discovery and identification of microRNA (miRNA) targets. The Target ID Library is a plasmid-based, ...

Quantitative and Automated High-throughput Genome-wide RNAi Screens in C. elegans

RNA interference is a powerful method to understand gene function, especially when conducted at a whole-genome scale and in a quantitative context. In C. elegans, gene function can be knocked down simply and efficiently by feeding worms with bacteria expressing a dsRNA corresponding to a specific gene 1. While the creation of libraries of RNAi clones covering most of the C. elegans genome 2,3 opened the way for true functional genomic studies (see for example 4-7), most established methods are laborious. Moy and colleagues have developed semi-automated protocols that facilitate genome-wide screens 8. The approach relies on microscopic imaging and image analysis. 
	Here we describe an alternative protocol for a high-throughput genome-wide screen, based on robotic handling of bacterial RNAi clones, quantitative analysis using the COPAS Biosort (Union Biometrica (UBI)), and an integrated software: the MBioLIMS (Laboratory Information Management System from Modul-Bio) a technology that provides increased throughput for data management and sample tracking. The method allows screens to be conducted on solid medium plates. This is particularly important for some studies, such as those addressing host-pathogen interactions in C. elegans, since certain microbes do not efficiently infect worms in liquid culture.
	We show how the method can be used to quantify the importance of genes in anti-fungal innate immunity in C. elegans. In this case, the approach relies on the use of a transgenic strain carrying an epidermal infection-inducible fluorescent reporter gene, with GFP under the control of the promoter of the antimicrobial peptide gene nlp 29 and a red fluorescent reporter that is expressed constitutively in the epidermis. The latter provides an internal control for the functional integrity of the epidermis and nonspecific transgene silencing9. When control worms are infected by the fungus they fluoresce green. Knocking down by RNAi a gene required for nlp 29 expression results in diminished fluorescence after infection. Currently, this protocol allows more than 3,000 RNAi clones to be tested and analyzed per week, opening the possibility of screening the entire genome in less than 2 months.

Quantitative and Automated High-throughput Genome-wide RNAi Screens in C. elegans

We describe a protocol using C. elegans and RNAi feeding libraries that allows automated measurement of multiple parameters such as fluorescence, size and opacity of individual worms in a population. We give one example of a screen to identify genes involved in anti-fungal innate immunity in C. elegans.

RNA interference is a powerful method to understand gene function, especially when conducted at a whole-genome scale and in a quantitative context. In C. ...

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types

ChIPseq is a widely used technique for investigating protein-DNA interactions. Read density profiles are generated by using next-sequencing of protein-bound DNA and aligning the short reads to a reference genome. Enriched regions are revealed as peaks, which often differ dramatically in shape, depending on the target protein1. For example, transcription factors often bind in a site- and sequence-specific manner and tend to produce punctate peaks, while histone modifications are more pervasive and are characterized by broad, diffuse islands of enrichment2. Reliably identifying these regions was the focus of our work.
Algorithms for analyzing ChIPseq data have employed various methodologies, from heuristics3-5 to more rigorous statistical models, e.g. Hidden Markov Models (HMMs)6-8. We sought a solution that minimized the necessity for difficult-to-define, ad hoc parameters that often compromise resolution and lessen the intuitive usability of the tool. With respect to HMM-based methods, we aimed to curtail parameter estimation procedures and simple, finite state classifications that are often utilized.
Additionally, conventional ChIPseq data analysis involves categorization of the expected read density profiles as either punctate or diffuse followed by subsequent application of the appropriate tool. We further aimed to replace the need for these two distinct models with a single, more versatile model, which can capably address the entire spectrum of data types.
To meet these objectives, we first constructed a statistical framework that naturally modeled ChIPseq data structures using a cutting edge advance in HMMs9, which utilizes only explicit formulas-an innovation crucial to its performance advantages. More sophisticated then heuristic models, our HMM accommodates infinite hidden states through a Bayesian model. We applied it to identifying reasonable change points in read density, which further define segments of enrichment. Our analysis revealed how our Bayesian Change Point (BCP) algorithm had a reduced computational complexity-evidenced by an abridged run time and memory footprint. The BCP algorithm was successfully applied to both punctate peak and diffuse island identification with robust accuracy and limited user-defined parameters. This illustrated both its versatility and ease of use. Consequently, we believe it can be implemented readily across broad ranges of data types and end users in a manner that is easily compared and contrasted, making it a great tool for ChIPseq data analysis that can aid in collaboration and corroboration between research groups. Here, we demonstrate the application of BCP to existing transcription factor10,11 and epigenetic data12 to illustrate its usefulness.

Our Bayesian Change Point (BCP) algorithm builds on state-of-the-art advances in modeling change-points via Hidden Markov Models and applies them to chromatin immunoprecipitation sequencing (ChIPseq) data analysis. BCP performs well in both broad and punctate data types, but excels in accurately identifying robust, reproducible islands of diffuse histone enrichment.

ChIPseq is a widely used technique for investigating protein-DNA interactions. Read density profiles are generated by using next-sequencing of ...

Genome-wide Gene Deletions in Streptococcus sanguinis by High Throughput PCR

Transposon mutagenesis and single-gene deletion are two methods applied in genome-wide gene knockout in bacteria 1,2. Although transposon mutagenesis is less time consuming, less costly, and does not require completed genome information, there are two weaknesses in this method: (1) the possibility of a disparate mutants in the mixed mutant library that counter-selects mutants with decreased competition; and (2) the possibility of partial gene inactivation whereby genes do not entirely lose their function following the insertion of a transposon. Single-gene deletion analysis may compensate for the drawbacks associated with transposon mutagenesis. To improve the efficiency of genome-wide single gene deletion, we attempt to establish a high-throughput technique for genome-wide single gene deletion using Streptococcus sanguinis as a model organism. Each gene deletion construct in S. sanguinis genome is designed to comprise 1-kb upstream of the targeted gene, the aphA-3 gene, encoding kanamycin resistance protein, and 1-kb downstream of the targeted gene. Three sets of primers F1/R1, F2/R2, and F3/R3, respectively, are designed and synthesized in a 96-well plate format for PCR-amplifications of those three components of each deletion construct. Primers R1 and F3 contain 25-bp sequences that are complementary to regions of the aphA-3 gene at their 5' end. A large scale PCR amplification of the aphA-3 gene is performed once for creating all single-gene deletion constructs. The promoter of aphA-3 gene is initially excluded to minimize the potential polar effect of kanamycin cassette. To create the gene deletion constructs, high-throughput PCR amplification and purification are performed in a 96-well plate format. A linear recombinant PCR amplicon for each gene deletion will be made up through four PCR reactions using high-fidelity DNA polymerase. The initial exponential growth phase of S. sanguinis cultured in Todd Hewitt broth supplemented with 2.5% inactivated horse serum is used to increase competence for the transformation of PCR-recombinant constructs. Under this condition, up to 20% of S. sanguinis cells can be transformed using ~50 ng of DNA. Based on this approach, 2,048 mutants with single-gene deletion were ultimately obtained from the 2,270 genes in S. sanguinis excluding four gene ORFs contained entirely within other ORFs in S. sanguinis SK36 and 218 potential essential genes. The technique on creating gene deletion constructs is high throughput and could be easy to use in genome-wide single gene deletions for any transformable bacteria.

Genome-wide Gene Deletions in Streptococcus sanguinis by High Throughput PCR

An efficient genome-wide single gene mutation method has been established using Streptococcus sanguinis as a model organism. This method has achieved via high throughput recombinant PCRs and transformations.

Transposon  mutagenesis and single-gene deletion are two methods applied in genome-wide  gene knockout in bacteria 1,2. Although transposon mutagenesis is ...

Polysome Fractionation and Analysis of Mammalian Translatomes on a Genome-wide Scale

mRNA translation plays a central role in the regulation of gene expression and represents the most energy consuming process in mammalian cells. Accordingly, dysregulation of mRNA translation is considered to play a major role in a variety of pathological states including cancer. Ribosomes also host chaperones, which facilitate folding of nascent polypeptides, thereby modulating function and stability of newly synthesized polypeptides. In addition, emerging data indicate that ribosomes serve as a platform for a repertoire of signaling molecules, which are implicated in a variety of post-translational modifications of newly synthesized polypeptides as they emerge from the ribosome, and/or components of translational machinery. Herein, a well-established method of ribosome fractionation using sucrose density gradient centrifugation is described. In conjunction with the in-house developed &#8220;anota&#8221; algorithm this method allows direct determination of differential translation of individual mRNAs on a genome-wide scale. Moreover, this versatile protocol can be used for a variety of biochemical studies aiming to dissect the function of ribosome-associated protein complexes, including those that play a central role in folding and degradation of newly synthesized polypeptides.

Ribosomes play a central role in protein synthesis. Polyribosome (polysome) fractionation by sucrose density gradient centrifugation allows direct determination of translation efficiencies of individual mRNAs on a genome-wide scale. In addition, this method can be used for biochemical analysis of ribosome- and polysome-associated factors such as chaperones and signaling molecules.

Genome-wide Purification of Extrachromosomal Circular DNA from Eukaryotic Cells

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Staining of Proteins in Gels with Coomassie G-250 without Organic Solvent and Acetic Acid

Purification of Mitochondria from Yeast Cells

Genome-wide Analysis of Aminoacylation (Charging) Levels of tRNA Using Microarrays

Genome-wide Analysis using ChIP to Identify Isoform-specific Gene Targets

Streamlined Purification of Plasmid DNA From Prokaryotic Cultures

Genome-wide Screen for miRNA Targets Using the MISSION Target ID Library

Quantitative and Automated High-throughput Genome-wide RNAi Screens in C. elegans

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types

Genome-wide Gene Deletions in Streptococcus sanguinis by High Throughput PCR

Polysome Fractionation and Analysis of Mammalian Translatomes on a Genome-wide Scale