This work was supported by grant NIH GM117446 to A.B.

1. Preparation of Cells for Flow Cytometry Sorting
<ol>
	<li>Inoculate 15 mL test tubes containing 8 mL each of YEPD broth such that the cultures reach a density of 5 x 106 to 1.5 x 107 cells per mL after overnight growth (see discussion note 1).</li>
	<li>Spin down yeast cells (1,400 x g, at room temperature or 4 &#176;C) in a 15 mL screw cap centrifuge tube for 5 min, resuspend cells in 1.5 mL 70% ethanol, and transfer to a 1.6 mL microfuge tube, letting this sit for 1 h at room temperature or a...

<ol>
	<li>Fragkos, M., Ganier, O., Coulombe, P., Mechali, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=DNA+replication+origin+activation+in+space+and+time.">DNA replication origin activation in space and time.</a> Nat Rev Mol Cell Biol. 16, 360-374 (2015).</li><li>Santocanale, C., Diffley, J. F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+Mec1-+and+Rad53-dependent+checkpoint+controls+late-firing+origins+of+DNA+replication.">A Mec1- and Rad53-dependent checkpoint controls late-firing origins of DNA replication.</a> Nature. 395, 615-618 (1998).</li><li>Brewer, B. J., Fangman, W. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+replication+fork+barrier+at+the+3'+end+of+yeast+ribosomal+RNA+genes.">A replication fork barrier at the 3' end of yeast ribosomal RNA genes.</a> Cell. 55, 637-643 (1988).</li><li>Raghuraman, M. K., 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=Replication+dynamics+of+the+yeast+genome.">Replication dynamics of the yeast genome.</a> Science. 294, 115-121 (2001).</li><li>Muller, C. A., Nieduszynski, C. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Conservation+of+replication+timing+reveals+global+and+local+regulation+of+replication+origin+activity.">Conservation of replication timing reveals global and local regulation of replication origin activity.</a> Genome Res. 22, 1953-1962 (2012).</li><li>Koren, A., Soifer, I., Barkai, N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=MRC1-dependent+scaling+of+the+budding+yeast+DNA+replication+timing+program.">MRC1-dependent scaling of the budding yeast DNA replication timing program.</a> Genome Res. 20, 781-790 (2010).</li><li>Lang, G. I., Murray, A. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mutation+rates+across+budding+yeast+chromosome+VI+are+correlated+with+replication+timing.">Mutation rates across budding yeast chromosome VI are correlated with replication timing.</a> Genome Biol Evol. 3, 799-811 (2011).</li><li>Durkin, S. G., Glover, T. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Chromosome+fragile+sites.">Chromosome fragile sites.</a> Annu Rev Genet. 41, 169-192 (2007).</li><li>Dillon, L. W., Burrow, A. A., Wang, Y. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=DNA+instability+at+chromosomal+fragile+sites+in+cancer.">DNA instability at chromosomal fragile sites in cancer.</a> Curr Genomics. 11, 326-337 (2010).</li><li>Widrow, R. J., Hansen, R. S., Kawame, H., Gartler, S. M., Laird, C. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Very+late+DNA+replication+in+the+human+cell+cycle.">Very late DNA replication in the human cell cycle.</a> Proc Natl Acad Sci U S A. 95, 11246-11250 (1998).</li><li>Foss, E. 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=SIR2+suppresses+replication+gaps+and+genome+instability+by+balancing+replication+between+repetitive+and+unique+sequences.">SIR2 suppresses replication gaps and genome instability by balancing replication between repetitive and unique sequences.</a> Proc Natl Acad Sci U S A. 114, 552-557 (2017).</li><li>Wu, T. D., Reeder, J., Lawrence, M., Becker, G., Brauer, M. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=GMAP+and+GSNAP+for+Genomic+Sequence+Alignment:+Enhancements+to+Speed,+Accuracy,+and+Functionality.">GMAP and GSNAP for Genomic Sequence Alignment: Enhancements to Speed, Accuracy, and Functionality.</a> Methods Mol Biol. 1418, 283-334 (2016).</li><li>Quinlan, A. R., Hall, I. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=BEDTools:+a+flexible+suite+of+utilities+for+comparing+genomic+features.">BEDTools: a flexible suite of utilities for comparing genomic features.</a> Bioinformatics. 26, 841-842 (2010).</li><li>Langmead, B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Aligning+short+sequencing+reads+with+Bowtie.">Aligning short sequencing reads with Bowtie.</a> Curr Protoc Bioinformatics. , 17 (2010).</li><li>Li, H., Durbin, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Fast+and+accurate+short+read+alignment+with+Burrows-Wheeler+transform.">Fast and accurate short read alignment with Burrows-Wheeler transform.</a> Bioinformatics. 25, 1754-1760 (2009).</li><li>Kellis, M., Birren, B. 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While this technique is robust and relatively straight forward, particular attention should be devoted to the following:
(1) We recommend that cultures grow for at least 12 h before they reach log phase, since differences manifest in cell cycle distributions if cultures are harvested after having reached the desired density just 4 h after inoculation. Our assumption is that a cell cycle distribution that has reached a relatively stable equilibrium better represents a &#34;real&#34; log phase d...

Eukaryotic genome replication is initiated at multiple discrete sites, called origins of replication, from which replication forks proceed in both directions (reviewed in Fragkos et al., 20151). Origins vary in both their timing and efficiency of firing, and several techniques have been developed to monitor replication origin activity and elucidate the causes of this variation. The activity of individual origins can be inferred from levels of single-stranded DNA2, which forms around active origins, or by using 2D gel electrophoresis to monitor specific replication intermediates3, both of which can be detected with radioactive probes. Both of these techniques are more easily applied in S. cerevisiae than in mammalian cells, because origins are limited to specific known sequences in the former. With the advent of microarrays, it became possible to assess origin firing globally. This was first done by labeling DNA with heavy isotopes, releasing cells from a G1 block into medium containing light isotopes, and then monitoring the formation of heavy-light hybrid DNA across the genome4. The introduction of high throughput sequencing allowed similar genome-wide monitoring of origin activity without the requirement of expensive isotopic labeling. Cells were sorted in a flow cytometer according to DNA content and their DNA subjected to deep sequencing. Because sequence coverage proceeds from 1x to 2x over the course of S phase, relative replication timing can be assessed by comparing read depths of cells in S phase to those in G1 or G25,6. These techniques, particularly applied to yeast, led to a deeper understanding of how DNA sequence, chromatin structure, and DNA replication proteins regulate origin timing and efficiency.
Faithful transmission of genetic information during cellular proliferation requires not only successful initiation of DNA replication, which takes place at origins, but also successful completion of replication, which occurs where replication forks meet. Like initiation of replication, the timing of completion of replication varies across the genome with certain regions remaining unreplicated even late in the cell cycle. Such regions may be particularly distant from active replication origins or may contain sequences or chromatin structures that impede DNA polymerases. Late replicating regions can manifest themselves as fragile sites, which are associated with chromosomal breakage and higher mutation rates, and have been implicated in cancer and aging7,8,9. However, despite the importance of proper completion of DNA replication in maintenance of genome stability, our understanding of where and how this takes place has lagged far behind that of replication initiation. And while individual genes whose late replication has been associated with disease have been studied with, for example, qPCR10, global studies directed at elucidating the locations and underlying causes of late replication have been lacking. Here we describe a technique we refer to as &#34;G2 seq&#34; in which we combine flow cytometry with high throughput sequencing to shed light on the completion of genome replication in yeast11. With minor changes, this protocol can be adapted to any cells that can be flow-sorted according to DNA content.

<table width="722">
	<tbody>
		<tr height="21">
			<td height="21" style="width:301px;height:21px;">YeaStar Genomic DNA kit</td>
			<td style="width:135px;">Genesee Scientific</td>
			<td style="width:119px;">11-323</td>
			<td style="width:167px;"></td>
		</tr>
		<tr height="21">
			<td height="21" style="width:301px;height:21px;">1 &#181;M SYTOX Green</td>
			<td style="width:135px;">ThermoFisher</td>
			<td style="width:119px;">57020</td>
			<td>resuspend in 50 mM sodium citrate, pH 7.2</td>
		</tr>
		<tr height="21">
			<td height="21" style="width:301px;height:21px;">50 mM sodium citrate, pH 7.2</td>
			<td style="width:135px;"></td>
			<td style="width:119px;"></td>
			<td></td>
		</tr>
		<tr height="147">
			<td height="147" style="width:301px;height:147px;">RNase solution (0.25 mg / mL)</td>
			<td style="width:135px;">Sigma</td>
			<td style="width:119px;">R6513</td>
			<td style="width:167px;">0.25 mg / mL RNaseA resuspended in 50 mM sodium citrate, pH 7.2, boil RNase solution for 10 minutes before the first use only, and from then on store at -20&#176;</td>
		</tr>
		<tr height="42">
			<td height="42" style="width:301px;height:42px;">proteinase K solution (20 mg / mL)</td>
			<td style="width:135px;">ThermoFisher / Invitrogen</td>
			<td style="width:119px;">25530-015</td>
			<td>resuspend in 10 mM Tris, pH 7.5, 2 mM CaCl2, 50% glycerol, store at -20&#176;C</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Model 50 Sonic Dismembrator</td>
			<td style="width:135px;">Fisher Scientific</td>
			<td>FB50A220</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="width:301px;height:21px;">BD Biosciences FACSAria II</td>
			<td style="width:135px;">BD Biosciences</td>
			<td>644832</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="width:301px;height:21px;">Zymo-spin III columns</td>
			<td style="width:135px;">Zymo Research</td>
			<td style="width:119px;">C1005</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="width:301px;height:21px;">Qubit dsDNA HS Assay Kit</td>
			<td style="width:135px;">ThermoFisher</td>
			<td style="width:119px;">Q32851</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="width:301px;height:21px;">Qubit 3.0 Fluorometer</td>
			<td style="width:135px;">ThermoFisher</td>
			<td style="width:119px;">Q33216</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Covaris Model LE220 Focused-Ultrasonicator</td>
			<td style="width:135px;">Covaris</td>
			<td style="width:119px;">500219</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="width:301px;height:21px;">Illumina TruSeq DNA LT Sample Prep Kit</td>
			<td style="width:135px;">Illumina</td>
			<td>15026486</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="width:301px;height:21px;">Illumina HiSeq 2500 instrument</td>
			<td style="width:135px;">Illumina</td>
			<td>SY&#8211;401&#8211;2501&#160;</td>
			<td></td>
		</tr>
		<tr height="63">
			<td height="63" style="width:301px;height:63px;">gsnap alignment software</td>
			<td style="width:135px;">open source software / Genentech</td>
			<td style="width:119px;"></td>
			<td style="width:167px;">http://research-pub.gene.com/gmap</td>
		</tr>
	</tbody>
</table>

g2-seq: a high throughput sequencing-based technique for identifying late replicating regions of the genome

Numerous techniques have been developed to follow the progress of DNA replication through the S phase of the cell cycle. Most of these techniques have been directed toward elucidation of the location and timing of initiation of genome duplication rather than its completion. However, it is critical that we understand regions of the genome that are last to complete replication, because these regions suffer elevated levels of chromosomal breakage and mutation, and they have been associated with both disease and aging. Here we describe how we have extended a technique that has been used to monitor replication initiation to instead identify those regions of the genome last to complete replication. This approach is based on a combination of flow cytometry and high throughput sequencing. Although this report focuses on the application of this technique to yeast, the approach can be used with any cells that can be sorted in a flow cytometer according to DNA content.

We have used the procedure described above to identify late replicating sites in budding yeast. Testing this approach using a known late replicating region on an artificial chromosome proved the technique to be accurate and reliable. Our results have also demonstrated the biological importance of timely completion of replication by showing that a late replicating region on chromosome 7, which we identified as late replicating on the basis of our G2-seq results, was lost approximately thre...

Watch this Scientific Journal Video about G2-seq: A High Throughput Sequencing-based Technique for Identifying Late Replicating Regions of the Genome at JoVE.com

G2-seq: A High Throughput Sequencing-based Technique for Identifying Late Replicating Regions of the Genome

We describe a technique for combining flow cytometry and high throughput sequencing to identify late replicating regions of the genome.

Numerous techniques have been developed to follow the progress of DNA replication through the S phase of the cell cycle. Most of these techniques have ...

The overall goal of this procedure for deep sequencing DNA from cells that have been flow sorted according to cell cycle phase is to identify regions of the genome that replicate extremely late in the cell cycle. This method can help answer key questions in the DNA replication field such as which regions of the genome have trouble completing DNA replication and are therefore particularly vulnerable to genome rearrangements. The main advantage of this technique is that even though it is very simple from an experimental standpoint, it provides a surprisingly rich view into the dynamics of genomic replication.To begin, inoculate 15 milliliter test tubes containing eight milliliters of YEPD with yeast cells of interest. Synthetic or rich medium is acceptable. Culture the cells overnight for at least 12 hours to collect them during their real log phase distribution.The following day when the cultures are at a density of five to 15 million cells per milliliter, spin down the cells and resuspend them in 1.5 milliliters of 70%ethanol. Then transfer the suspension to a 1.6 milliliter microfuge tube and let the cells incubate at room temperature for an hour or for at least three hours on ice. After the inoculation, spin down the cells and resuspend them in one milliliter of sodium citrate.Finally, briefly sonicate the cells twice. Then repeat the centrifugation cycle and resuspend the yeast in one milliliter of sodium citrate containing RNase. Allow the RNase to react with the yeast at 50 degrees Celsius for an hour or overnight at 37 degrees Celsius in a heat block or a water bath.After the RNase treatment, add 50 microliters of proteinase K solution to the mixture and continue the reaction for an hour at 50 degrees Celsius. Then spin down the cells and resuspend the cells in one milliliter of sodium citrate. Next, centrifuge the cells and aspirate the supernatant using a vacuum.Then in dim light resuspend the cells in one milliliter of sodium citrate with green nucleic acid stain. Now incubate in the yeast in the dark for an hour at room temperature. To proceed, count the cells using a cell sorter using 530 nanometer emission data.Sort them according to their DNA content into their cell cycle phases, G1 S, early G2, and late G2.Collect at least 1.6 million haploid cells from each phase. Promptly after sorting the cells, spin them down for 20 minutes. Aspirate the supernatant and freeze the pellet at negative 20 degrees Celsius for storage.We have found that the single most critical step for this procedure is simply spinning the cells down promptly after collecting them, an hour the most after sorting. This extraction is based on a yeast genomic DNA extraction kit. Begin with adding 120 microliters of digestion buffer and five microliters of yeast lytic enzyme.Then blend the cells into the reaction mixture using a vortex and incubate the mixture at 37 degrees Celsius for 40 to 60 minutes. Next, add 120 microliters of lysis buffer and vortex the mixture at high speed for 10 to 20 seconds. Then add 250 microliters of chloroform and for one minute thoroughly mix the tube contents.Next, spin down the tube at maximum speed for two minutes. Then transfer the supernatant onto the DNA-binding column. Spin the supernatant through the column using a one-minute maximum speed centrifugation cycle.To wash the DNA on the column membrane, transfer the column to a new collection tube and apply 300 microliters of DNA washing buffer. Then repeat the centrifugation at maximum speed for one minute. Repeat this wash step one more time.To collect the DNA, transfer the spin column to a fresh tube. Add 60 microliters of water and wait one to three minutes. Then centrifuge the column at maximum speed for 10 seconds to isolate the water containing the eluted DNA.Now add between five and 195 microliters of double-stranded DNA high-sensitivity buffer containing reagent at a one to 200 concentration. Then measure the sample's fluorescence to calculate the yield. Expect to collect between 10 and 50 nanograms of DNA.Now use sonication to break up the DNA into fragments that are between 250 and 350 base pairs. Then use a standard kit to prepare a DNA library and sequence it using at least 10 million 50 base pairs single-end reads. The described procedure was used to identify late replicating sites in budding yeast.Normal cells were compared with those lacking Sir2, a deacetylase protein. The raw data contained large spikes mostly due to the presence of TY elements. These spikes were removed by capping the read depths to 2.5 times the median red depth for each sample.The de-spiked data was then smoothed with a 20 kb sliding window. Finally, the data was normalized and plotted as ratios to levels in G1.A completely unreplicated cell would appear at 0.5 and a completely replicated cell would appear at one. In this data from chromosome seven, there was evidence of a known late replicating region in the Sir2 mutant.After watching this video, you should have a good understanding of how to identify those regions of the genome that are last to complete DNA replication and that are therefore particularly vulnerable to DNA breaks and other problems that are associated with late replication.

g2-seq-high-throughput-sequencing-based-technique-for-identifying

Research

JoVE Journal

Genetics

5.7K ビュー.  Fred Hutchinson Cancer Research Center. The overall goal of this procedure for deep sequencing DNA from cells that have been flow sorted according to cell cycle phase is to identify regions of the genome that replicate extremely late in the cell cycle. This method can help answer key questions in the DNA replication field such as which regions of the genome have trouble completing DNA replication and are therefore particularly vulnerable to genome rearrangements. The main advantage of this technique is that even though it is very s...

ビデオ: G2-seq: A High Throughput Sequencing-based Technique for Identifying Late Replicating Regions of the Genome

We describe a technique for combining flow cytometry and high throughput sequencing to identify late replicating regions of the...

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We describe herein an assay by coupling DNA adenine methyltransferase identification (DamID) to high throughput sequencing (DamID-seq). This improved method provides a higher resolution and a wider dynamic range, and allows analyzing DamID-seq data in conjunction with other high throughput sequencing data such as ChIP-seq, RNA-seq,...

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InSET: A Novel Tool for Unbiased Genome-Wide Functional Element Discovery

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highly efficient ligation of small rna molecules for microrna quantitation by high-throughput sequencing

Highly Efficient Ligation of Small RNA Molecules for MicroRNA Quantitation by High-Throughput Sequencing

MicroRNAs (miRNAs) are a widely conserved class of regulatory molecules. Here we describe a miRNA cloning method that relies upon two potent ligation steps followed by high-throughput sequencing. Our method permits accurate genome-wide quantitation of miRNAs.

ribo-seq in bacteria: a sample collection and library preparation protocol for ngs sequencing

RIBO-seq in Bacteria: a Sample Collection and Library Preparation Protocol for NGS Sequencing

Here we describe the stages of sample collection and preparation for RIBO-seq in bacteria. Sequencing of the libraries prepared according to these guidelines results in sufficient data for comprehensive bioinformatic analysis. The protocol we present is simple, uses standard laboratory equipment and takes seven days from lysis to obtaining libraries.

A Robotic Platform for High-throughput Protoplast Isolation and Transformation

Over the last decade there has been a resurgence in the use of plant protoplasts that range from model species to crop species, for analysis of signal transduction pathways, transcriptional regulatory networks, gene expression, genome-editing, and gene-silencing. Furthermore, significant progress has been made in the regeneration of plants from protoplasts, which has generated even more interest in the use of these systems for plant genomics. In this work, a protocol has been developed for automation of protoplast isolation and transformation from a &#39;Bright Yellow&#39; 2 (BY-2) tobacco suspension culture using a robotic platform. The transformation procedures were validated using an orange fluorescent protein (OFP) reporter gene (pporRFP) under the control of the Cauliflower mosaic virus 35S promoter (35S). OFP expression in protoplasts was confirmed by epifluorescence microscopy. Analyses also included protoplast production efficiency methods using propidium iodide. Finally, low-cost food-grade enzymes were used for the protoplast isolation procedure, circumventing the need for lab-grade enzymes that are cost-prohibitive in high-throughput automated protoplast isolation and analysis. Based on the protocol developed in this work, the complete procedure from protoplast isolation to transformation can be conducted in under 4 hr, without any input from the operator. While the protocol developed in this work was validated with the BY-2 cell culture, the procedures and methods should be translatable to any plant suspension culture/protoplast system, which should enable acceleration of crop genomics research.

A high-throughput, automated, tobacco protoplast production and transformation methodology is described. The robotic system enables massively parallel gene expression and discovery in the model BY-2 system that should be translatable to non-model crops.

Over the last decade there has been a resurgence in the use of plant protoplasts that range from model species to crop species, for analysis of signal ...

Using a Fluorescent PCR-capillary Gel Electrophoresis Technique to Genotype CRISPR/Cas9-mediated Knockout Mutants in a High-throughput Format

The development of programmable genome-editing tools has facilitated the use of reverse genetics to understand the roles specific genomic sequences play in the functioning of cells and whole organisms. This cause has been tremendously aided by the recent introduction of the CRISPR/Cas9 system-a versatile tool that allows researchers to manipulate the genome and transcriptome in order to, among other things, knock out, knock down, or knock in genes in a targeted manner. For the purpose of knocking out a gene, CRISPR/Cas9-mediated double-strand breaks recruit the non-homologous end-joining DNA repair pathway to introduce the frameshift-causing insertion or deletion of nucleotides at the break site. However, an individual guide RNA may cause undesirable off-target effects, and to rule these out, the use of multiple guide RNAs is necessary. This multiplicity of targets also means that a high-volume screening of clones is required, which in turn begs the use of an efficient high-throughput technique to genotype the knockout clones. Current genotyping techniques either suffer from inherent limitations or incur high cost, hence rendering them unsuitable for high-throughput purposes. Here, we detail the protocol for using fluorescent PCR, which uses genomic DNA from crude cell lysate as a template, and then resolving the PCR fragments via capillary gel electrophoresis. This technique is accurate enough to differentiate one base-pair difference between fragments and hence is adequate in indicating the presence or absence of a frameshift in the coding sequence of the targeted gene. This precise knowledge effectively precludes the need for a confirmatory sequencing step and allows users to save time and cost in the process. Moreover, this technique has proven to be versatile in genotyping various mammalian cells of various tissue origins targeted by guide RNAs against numerous genes, as shown here and elsewhere.

The genotyping technique described here, which couples fluorescent polymerase chain reaction (PCR) to capillary gel electrophoresis, allows for high-throughput genotyping of nuclease-mediated knockout clones. It circumvents limitations faced by other genotyping techniques and is more cost effective than sequencing methods.

The development of programmable genome-editing tools has facilitated the use of reverse genetics to understand the roles specific genomic sequences play ...

Retroviral Scanning: Mapping MLV Integration Sites to Define Cell-specific Regulatory Regions

Moloney murine leukemia (MLV) virus-based retroviral vectors integrate predominantly in acetylated enhancers and promoters. For this reason, mLV integration sites can be used as functional markers of active regulatory elements. Here, we present a retroviral scanning tool, which allows the genome-wide identification of cell-specific enhancers and promoters. Briefly, the target cell population is transduced with an mLV-derived vector and genomic DNA is digested with a frequently cutting restriction enzyme. After ligation of genomic fragments with a compatible DNA linker, linker-mediated polymerase chain reaction (LM-PCR) allows the amplification of the virus-host genome junctions. Massive sequencing of the amplicons is used to define the mLV integration profile genome-wide. Finally, clusters of recurrent integrations are defined to identify cell-specific regulatory regions, responsible for the activation of cell-type specific transcriptional programs.
The retroviral scanning tool allows the genome-wide identification of cell-specific promoters and enhancers in prospectively isolated target cell populations. Notably, retroviral scanning represents an instrumental technique for the retrospective identification of rare populations (e.g. somatic stem cells) that lack robust markers for prospective isolation.

Here, we describe a protocol for genome-wide mapping of the integration sites of Moloney murine leukemia virus-based retroviral vectors in human cells.

Moloney murine leukemia (MLV) virus-based retroviral vectors integrate predominantly in acetylated enhancers and promoters. For this reason, mLV ...

Generation of Native Chromatin Immunoprecipitation Sequencing Libraries for Nucleosome Density Analysis

We present a modified native chromatin immunoprecipitation sequencing (ChIP-seq) experimental protocol compatible with a Gaussian mixture distribution based analysis methodology (nucleosome density ChIP-seq; ndChIP-seq) that enables the generation of combined measurements of micrococcal nuclease (MNase) accessibility with histone modification genome-wide. Nucleosome position and local density, and the posttranslational modification of their histone subunits, act in concert to regulate local transcription states. Combinatorial measurements of nucleosome accessibility with histone modification generated by ndChIP-seq allows for the simultaneous interrogation of these features. The ndChIP-seq methodology is applicable to small numbers of primary cells inaccessible to cross-linking based ChIP-seq protocols. Taken together, ndChIP-seq enables the measurement of histone modification in combination with local nucleosome density to obtain new insights into shared mechanisms that regulate RNA transcription within rare primary cell populations.

We present a modified native chromatin immunoprecipitation sequencing (ChIP-seq) methodology for the generation of sequence datasets suitable for a nucleosome density ChIP-seq analytical framework integrating micrococcal nuclease (MNase) accessibility with histone modification measurements.

We present a modified native chromatin immunoprecipitation sequencing (ChIP-seq) experimental protocol compatible with a Gaussian mixture distribution ...

Herbaria are an invaluable source of plant material that can be used in a variety of biological studies. The use of herbarium specimens is associated with a number of challenges including sample preservation quality, degraded DNA, and destructive sampling of rare specimens. In order to more effectively use herbarium material in large sequencing projects, a dependable and scalable method of DNA isolation and library preparation is needed. This paper demonstrates a robust, beginning-to-end protocol for DNA isolation and high-throughput library construction from herbarium specimens that does not require modification for individual samples. This protocol is tailored for low quality dried plant material and takes advantage of existing methods by optimizing tissue grinding, modifying library size selection, and introducing an optional reamplification step for low yield libraries. Reamplification of low yield DNA libraries can rescue samples derived from irreplaceable and potentially valuable herbarium specimens, negating the need for additional destructive sampling and without introducing discernible sequencing bias for common phylogenetic applications. The protocol has been tested on hundreds of grass species, but is expected to be adaptable for use in other plant lineages after verification. This protocol can be limited by extremely degraded DNA, where fragments do not exist in the desired size range, and by secondary metabolites present in some plant material that inhibit clean DNA isolation. Overall, this protocol introduces a fast and comprehensive method that allows for DNA isolation and library preparation of 24 samples in less than 13 h, with only 8 h of active hands-on time with minimal modifications.

This article demonstrates a detailed protocol for DNA isolation and high-throughput sequencing library construction from herbarium material including rescue of exceptionally poor-quality DNA.

Herbaria are an invaluable source of plant material that can be used in a variety of biological studies. The use of herbarium specimens is associated with ...

Embryo Microinjection and Transplantation Technique for Nasonia vitripennis Genome Manipulation

The jewel wasp Nasonia vitripennis has emerged as an effective model system for the study of processes including sex determination, haplo-diploid sex determination, venom synthesis, and host-symbiont interactions, among others. A major limitation of working with this organism is the lack of effective protocols to perform directed genome modifications. An important part of genome modification is delivery of editing reagents, including CRISPR/Cas9 molecules, into embryos through microinjection. While microinjection is well established in many model organisms, this technique is particularly challenging to perform in N. vitripennis primarily due to its small embryo size, and the fact that embryonic development occurs entirely within a parasitized blowfly pupa. The following procedure overcomes these significant challenges while demonstrating a streamlined, visual procedure for effectively removing wasp embryos from parasitized host pupae, microinjecting them, and carefully transplanting them back into the host for continuation and completion of development. This protocol will strongly enhance the capability of research groups to perform advanced genome modifications in this organism.

Embryo Microinjection and Transplantation Technique for Nasonia vitripennis Genome Manipulation

Microinjection of Nasonia vitripennis embryos is an essential method for generating heritable genome modifications. Described here is a detailed procedure for microinjection and transplantation of Nasonia vitripennis embryos, which will greatly facilitate future genome manipulation in this organism.

The jewel wasp Nasonia vitripennis has emerged as an effective model system for the study of processes including sex determination, haplo-diploid sex ...

High-throughput Identification of Synergistic Drug Combinations by the Overlap2 Method

Although antimicrobial drugs have dramatically increased the lifespan and quality of life in the 20th century, antimicrobial resistance threatens our entire society's ability to treat systemic infections. In the United States alone, antibiotic-resistant infections kill approximately 23,000 people a year and cost around 20 billion USD in additional healthcare. One approach to combat antimicrobial resistance is combination therapy, which is particularly useful in the critical early stage of infection, before the infecting organism and its drug resistance profile have been identified. Many antimicrobial treatments use combination therapies. However, most of these combinations are additive, meaning that the combined efficacy is the same as the sum of the individual antibiotic efficacy. Some combination therapies are synergistic: the combined efficacy is much greater than additive. Synergistic combinations are particularly useful because they can inhibit the growth of antimicrobial drug resistant strains. However, these combinations are rare and difficult to identify. This is due to the sheer number of molecules needed to be tested in a pairwise manner: a library of 1,000 molecules has 1 million potential combinations. Thus, efforts have been made to predict molecules for synergy. This article describes our high-throughput method for predicting synergistic small molecule pairs known as the Overlap2 Method (O2M). O2M uses patterns from chemical-genetic datasets to identify mutants that are hypersensitive to each molecule in a synergistic pair but not to other molecules. The Brown lab exploits this growth difference by performing a high-throughput screen for molecules that inhibit the growth of mutant but not wild-type cells. The lab's work previously identified molecules that synergize with the antibiotic trimethoprim and the antifungal drug fluconazole using this strategy. Here, the authors present a method to screen for novel synergistic combinations, which can be altered for multiple microorganisms.

High-throughput Identification of Synergistic Drug Combinations by the Overlap2 Method

Synergistic drug combinations are difficult and time-consuming to identify empirically. Here, we describe a method for identifying and validating synergistic small molecules.

Although antimicrobial drugs have dramatically increased the lifespan and quality of life in the 20th century, antimicrobial resistance threatens our ...

Promoter Capture Hi-C: High-resolution, Genome-wide Profiling of Promoter Interactions

The three-dimensional organization of the genome is linked to its function. For example, regulatory elements such as transcriptional enhancers control the spatio-temporal expression of their target genes through physical contact, often bridging considerable (in some cases hundreds of kilobases) genomic distances and bypassing nearby genes. The human genome harbors an estimated one million enhancers, the vast majority of which have unknown gene targets. Assigning distal regulatory regions to their target genes is thus crucial to understand gene expression control. We developed Promoter Capture Hi-C (PCHi-C) to enable the genome-wide detection of distal promoter-interacting regions (PIRs), for all promoters in a single experiment. In PCHi-C, highly complex Hi-C libraries are specifically enriched for promoter sequences through in-solution hybrid selection with thousands of biotinylated RNA baits complementary to the ends of all promoter-containing restriction fragments. The aim is to then pull-down promoter sequences and their frequent interaction partners such as enhancers and other potential regulatory elements. After high-throughput paired-end sequencing, a statistical test is applied to each promoter-ligated restriction fragment to identify significant PIRs at the restriction fragment level. We have used PCHi-C to generate an atlas of long-range promoter interactions in dozens of human and mouse cell types. These promoter interactome maps have contributed to a greater understanding of mammalian gene expression control by assigning putative regulatory regions to their target genes and revealing preferential spatial promoter-promoter interaction networks. This information also has high relevance to understanding human genetic disease and the identification of potential disease genes, by linking non-coding disease-associated sequence variants in or near control sequences to their target genes.

DNA regulatory elements, such as enhancers, control gene expression by physically contacting target gene promoters, often through long-range chromosomal interactions spanning large genomic distances. Promoter Capture Hi-C (PCHi-C) identifies significant interactions between promoters and distal regions, enabling the assignment of potential regulatory sequences to their target genes.

The three-dimensional organization of the genome is linked to its function. For example, regulatory elements such as transcriptional enhancers control the ...

The identification of regulatory elements for a given target gene poses a significant technical challenge owing to the variability in the positioning and effect sizes of regulatory elements to a target gene. Some progress has been made with the bioinformatic prediction of the existence and function of proximal epigenetic modifications associated with activated gene expression using conserved transcription factor binding sites. Chromatin conformation capture studies have revolutionized our ability to discover physical chromatin contacts between sequences and even within an entire genome. Circular chromatin conformation capture coupled with next-generation sequencing (4C-seq), in particular, is designed to discover all possible physical chromatin interactions for a given sequence of interest (viewpoint), such as a target gene or a regulatory enhancer. Current 4C-seq strategies directly sequence from within the viewpoint but require numerous and diverse viewpoints to be simultaneously sequenced to avoid the technical challenges of uniform base calling (imaging) with next generation sequencing platforms. This volume of experiments may not be practical for many laboratories. Here, we report a modified approach to the 4C-seq protocol that incorporates both an additional restriction enzyme digest and qPCR-based amplification steps that are designed to facilitate a greater capture of diverse sequence reads and mitigate the potential for PCR bias, respectively. Our modified 4C method is amenable to the standard molecular biology lab for assessing chromatin architecture.

The identification of physical interactions between genes and regulatory elements is challenging but has been facilitated by chromosome conformation capture methods. This modification to the 4C-seq protocol mitigates PCR bias by minimizing over-amplification of PCR templates and maximizes the mappability of reads by incorporating an addition restriction enzyme digest step.

The identification of regulatory elements for a given target gene poses a significant technical challenge owing to the variability in the positioning and ...

CRISPR-mediated Genome Editing of the Human Fungal Pathogen Candida albicans

This method describes the efficient CRISPR mediated genome editing of the diploid human fungal pathogen Candida albicans. CRISPR-mediated genome editing in C. albicans requires Cas9, guide RNA, and repair template. A plasmid expressing a yeast codon optimized Cas9 (CaCas9) has been generated. Guide sequences directly upstream from a PAM site (NGG) are cloned into the Cas9 expression vector. A repair template is then made by primer extension in vitro. Cotransformation of the repair template and vector into C. albicans leads to genome editing. Depending on the repair template used, the investigator can introduce nucleotide changes, insertions, or deletions. As C. albicans is a diploid, mutations are made in both alleles of a gene, provided that the A and B alleles do not harbor SNPs that interfere with guide targeting or repair template incorporation. Multimember gene families can be edited in parallel if suitable conserved sequences exist in all family members. The C. albicans CRISPR system described is flanked by FRT sites and encodes flippase. Upon induction of flippase, the antibiotic marker (CaCas9) and guide RNA are removed from the genome. This allows the investigator to perform subsequent edits to the genome. C. albicans CRISPR is a powerful fungal genetic engineering tool, and minor alterations to the described protocols permit the modification of other fungal species including C. glabrata, N. castellii, and S. cerevisiae.

CRISPR-mediated Genome Editing of the Human Fungal Pathogen Candida albicans

Efficient genome engineering of Candida albicans is critical to understanding the pathogenesis and development of therapeutics. Here, we described a protocol to quickly and accurately edit the C. albicans genome using CRISPR. The protocol allows investigators to introduce a wide variety of genetic modifications including point mutations, insertions, and deletions.

This method describes the efficient CRISPR mediated genome editing of the diploid human fungal pathogen Candida albicans. CRISPR-mediated genome editing ...