We thank Ron Davis, Adam Deutschbauer, and the entire HIP HOP laboratory at the University of Toronto for discussions and advice. C.N. is supported by grants from the National Human Genome Research Institute (Grant Number HG000205), RO1 HG003317, CIHR MOP-84305, and Canadian Cancer Society (#020380). J.O. was supported by the Stanford Genome Training Program (Grant Number T32 HG00044 from the National Human Genome Research Institute) and the National Institutes of Health (Grant Number P01 GH000205). GG is supported by the NHGRI RO1 HG003317 and the Canadian Cancer Society, Grant # 020380, TD and the Donnelly Sequencing Centre is supported in part by grants from the Canadian Foundation for Innovation to Drs. Brenda Andrews and Jack Greenblatt. A.M.S. is supported by a University of Toronto Open Fellowship.

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H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Systematic+genetic+analysis+with+ordered+arrays+of+yeast+deletion+mutants.">Systematic genetic analysis with ordered arrays of yeast deletion mutants.</a> Science. 294, 2364-2368 (2001).</li><li>Pan, X. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+robust+toolkit+for+functional+profiling+of+the+yeast+genome.">A robust toolkit for functional profiling of the yeast genome.</a> Molecular cell. 16, 487-496 (2004).</li><li>Schuldiner, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Exploration+of+the+Function+and+Organization+of+the+Yeast+Early+Secretory+Pathway+through+an+Epistatic+Miniarray+Profile.">Exploration of the Function and Organization of the Yeast Early Secretory Pathway through an Epistatic Miniarray Profile.</a> Cell. 123, 507-519 (2005).</li><li>Deutschbauer, A. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mechanisms+of+haploinsufficiency+revealed+by+genome-wide+profiling+in+yeast.">Mechanisms of haploinsufficiency revealed by genome-wide profiling in yeast.</a> Genetics. 169, 1915-1925 (2005).</li><li>Giaever, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Chemogenomic+profiling:+identifying+the+functional+interactions+of+small+molecules+in+yeast.">Chemogenomic profiling: identifying the functional interactions of small molecules in yeast.</a> Proceedings of the National Academy of Sciences of the United States of America. 101, 793-798 (2004).</li><li>Lum, P. Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Discovering+modes+of+action+for+therapeutic+compounds+using+a+genome-wide+screen+of+yeast+heterozygotes.">Discovering modes of action for therapeutic compounds using a genome-wide screen of yeast heterozygotes.</a> Cell. 116, 121-137 (2004).</li><li>Hillenmeyer, M. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+chemical+genomic+portrait+of+yeast:+uncovering+a+phenotype+for+all+genes.">The chemical genomic portrait of yeast: uncovering a phenotype for all genes.</a> Science. 320, 362-365 (2008).</li><li>Oh, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+universal+TagModule+collection+for+parallel+genetic+analysis+of+microorganisms.">A universal TagModule collection for parallel genetic analysis of microorganisms.</a> Nucleic acids research. 38, e146-e146 (2010).</li><li>Oh, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Gene+annotation+and+drug+target+discovery+in+Candida+albicans+with+a+tagged+transposon+mutant+collection.">Gene annotation and drug target discovery in Candida albicans with a tagged transposon mutant collection.</a> PLoS pathogens. 6, (2010).</li><li>Nislow, C., Giaever, G., Stark, I., Stansfields, M. J. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Chapter+387.">Chapter 387.</a> Yeast Gene Analysis. , 387-414 (2007).</li><li>Pierce, S. E., Davis, R. W., Nislow, C., Giaever, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Genome-wide+analysis+of+barcoded+Saccharomyces+cerevisiae+gene-deletion+mutants+in+pooled+cultures.">Genome-wide analysis of barcoded Saccharomyces cerevisiae gene-deletion mutants in pooled cultures.</a> Nature protocols. 2, 2958-2974 (2007).</li><li>Sambrook, J., Russell, D. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Molecular cloning : a laboratory manual. , (2001).</li><li>Smith, A. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantitative+phenotyping+via+deep+barcode+sequencing.">Quantitative phenotyping via deep barcode sequencing.</a> Genome Res. , (2009).</li><li>Hamady, M., Walker, J. J., Harris, J. K., Gold, N. J., Knight, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Error-correcting+barcoded+primers+for+pyrosequencing+hundreds+of+samples+in+multiplex.">Error-correcting barcoded primers for pyrosequencing hundreds of samples in multiplex.</a> Nature. 5, 235-237 (2008).</li><li>Gresham, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=System-Level+Analysis+of+Genes+and+Functions+Affecting+Survival+During+Nutrient+Starvation+in+Saccharomyces+cerevisiae.">System-Level Analysis of Genes and Functions Affecting Survival During Nutrient Starvation in Saccharomyces cerevisiae.</a> Genetics. 187, 299-317 (2011).</li></ol>

No conflicts of interest declared.

Here, we outlined a protocol that, with modest modification, can easily be adapted to a wide range of existing collections of barcoded mutant collections of different microorganisms to create tagged mutant collections. We emphasize that while we have reported a protocol on the tagged transposon mutagenesis for the pathogenic yeast C. albicans, a very similar protocol could be adapted to a wide variety of unicellular fungi. Modified, this protocol works well in bacteria 13, and currently collections for a number of additional fungal and bacterial genomes are under construction. At present, this assay provides the only comprehensive, genome-wide unbiased screen for gene-small molecule interactions. One particularly compelling feature of the assay is that no prior knowledge of the gene or small molecule is required. Despite the scope and power of these assays, their transferability to other labs has been hindered somewhat by the initial capital investment and informatics tools for the analysis of the results. With the adoption of a next generation sequence readout combined with robust tools for analysis, we expect their adoption to increase.

<table border="1">
	<tbody>
 <tr>
 <td>Antibiotics</td>
 <td>Vendor and catalogue numbers</td>
 </tr>
 <tr>
 <td>Carbenicillin</td>
 <td>Sigma, part# C1613</td>
 </tr>
 <tr>
 <td>Kanamycin</td>
 <td>Sigma, part# K1876</td>
 </tr>
 <tr>
 <td>spectinomycin </td>
 <td>Sigma, part# S0692</td>
 </tr>
 <tr>
 <td>Chloramphenicol </td>
 <td>Sigma, part# C0378</td>
 </tr>
 <tr>
 <td>DNA Clean-up and concentration kits</td>
 <td>&nbsp;</td>
 </tr>
 <tr>
 <td>QIAprep Spin Miniprep Kit</td>
 <td>Qiagen, part# 27106</td>
 </tr>
 <tr>
 <td>HiSpeed Plasmid Maxi Kit</td>
 <td>Qiagen, part# 12663</td>
 </tr>
 <tr>
 <td>QIAquick PCR Purification Kit</td>
 <td>Qiagen, part# 28106</td>
 </tr>
 <tr>
 <td>QIAquick Gel Extraction Kit</td>
 <td>Qiagen, part# 28704</td>
 </tr>
 <tr>
 <td>PCR and electrophoresis reagents</td>
 <td>&nbsp;</td>
 </tr>
 <tr>
 <td>Taq DNA Polymerase (Mg-free) Buffer</td>
 <td>New England Biolabs, part# M0320L</td>
 </tr>
 <tr>
 <td>Deoxynucleotide Solution Mix</td>
 <td>New England Biolabs, part# N0447L</td>
 </tr>
 <tr>
 <td>25 mM MgCl2</td>
 <td>Sigma, part# 63036</td>
 </tr>
 <tr>
 <td>Agarose, loading dye, and nucleic acid stain suitable for gel electrophoresis</td>
 <td>Various</td>
 </tr>
 <tr>
 <td>10X TAE buffer</td>
 <td>Sigma, part# T8280</td>
 </tr>
 <tr>
 <td>1 Kb Plus DNA Ladder</td>
 <td>Invitrogen, part# 10787026</td>
 </tr>
 <tr>
 <td>YPD broth</td>
 <td>&nbsp;</td>
 </tr>
 <tr>
 <td>10 g of yeast extract</td>
 <td>Sigma, part# Y1625</td>
 </tr>
 <tr>
 <td>20 g Bacto peptone </td>
 <td>BD Biosciences, part# 211677</td>
 </tr>
 <tr>
 <td>20 g of dextrose </td>
 <td>Sigma, part# D9434</td>
 </tr>
 <tr>
 <td>Labware</td>
 <td>&nbsp;</td>
 </tr>
 <tr>
 <td>Multichannel pipettes (1000, 200, and 20 &mu;L)</td>
 <td>Various</td>
 </tr>
 <tr>
 <td>Disposable pipetting reservoirs</td>
 <td>Various</td>
 </tr>
 <tr>
 <td>15 and 50 mL centrifuge tubes </td>
 <td>Various</td>
 </tr>
 <tr>
 <td>96- and 384-Well Deep Well Plates</td>
 <td>Axygen Scientific, part# P-2ML-SQ-C-S &amp; P-384240SQCS</td>
 </tr>
 <tr>
 <td>96-well and 384-well PCR plates and seal film</td>
 <td>Various</td>
 </tr>
 <tr>
 <td>Plate roller for sealing multi-well plates</td>
 <td>Sigma, part# R1275</td>
 </tr>
 <tr>
 <td>30&deg;C and 37&deg;C shaking incubators for growing bacterial and yeast on plates and in tubes </td>
 <td>Various</td>
 </tr>
 <tr>
 <td>In vitro transposon mutagenesis</td>
 <td>&nbsp;</td>
 </tr>
 <tr>
 <td>EZ-Tn5 Transposase</td>
 <td>Epicentre Biotechnologies, part# TNP92110</td>
 </tr>
 <tr>
 <td>High-throughput transformation</td>
 <td>&nbsp;</td>
 </tr>
 <tr>
 <td>Seqprep 96 HT Plasmid Prep Kit</td>
 <td>Edge Biosystems, part# 84359</td>
 </tr>
 <tr>
 <td>polyethylene glycol, molecular weight 3350</td>
 <td>Various</td>
 </tr>
 <tr>
 <td>lithium acetate </td>
 <td>Sigma, part# 517992</td>
 </tr>
 <tr>
 <td>6-well plates, sterile </td>
 <td>Corning, part# 3335</td>
 </tr>
 <tr>
 <td>50 mg/mL uridine</td>
 <td>Sigma, part# U3750</td>
 </tr>
 <tr>
 <td>100X Tris-EDTA buffer solution </td>
 <td>Sigma, part# T9285</td>
 </tr>
 <tr>
 <td>1X TE/0.1M LiOAc</td>
 <td>Various</td>
 </tr>
 <tr>
 <td>salmon testis DNA </td>
 <td>Sigma, part# 1626</td>
 </tr>
 <tr>
 <td>Growth of barcoded collections</td>
 <td>&nbsp;</td>
 </tr>
 <tr>
 <td>48-well plates; if growing cultures in plates</td>
 <td>Greiner, part# M9437</td>
 </tr>
 <tr>
 <td>Adhesive plate seals</td>
 <td>ABgene, part# AB-0580</td>
 </tr>
 <tr>
 <td>200 mL culture flasks</td>
 <td>Various</td>
 </tr>
 <tr>
 <td>Spectrophotometer capable of absorbance </td>
 <td>Various</td>
 </tr>
 <tr>
 <td>Temperature-controlled shaker for 250 ml flasks or shaking spectrophotometer </td>
 <td>Various</td>
 </tr>
 <tr>
 <td>Safe-Lock Microcentrifuge Tube, 2 mL </td>
 <td>Eppendorf, part# 0030 120.094</td>
 </tr>
 <tr>
 <td>Hybridization equipment</td>
 <td>&nbsp;</td>
 </tr>
 <tr>
 <td>Hybridization Oven 640 </td>
 <td>Affymetrix, part# 800138</td>
 </tr>
 <tr>
 <td>GeneChip Fluidic Station 450 </td>
 <td>Affymetrix, part# 00-0079</td>
 </tr>
 <tr>
 <td>GeneArray Scanner 3000</td>
 <td>Affymetrix, part# 00-0212</td>
 </tr>
 <tr>
 <td>Boiling water bath with floating rack </td>
 <td>Various</td>
 </tr>
 <tr>
 <td>Hybridization consumables</td>
 <td>&nbsp;</td>
 </tr>
 <tr>
 <td>Genflex Tag 16K Array v2</td>
 <td>Affymetrix, part# 511331</td>
 </tr>
 <tr>
 <td>Denhardt's Solution, 50X concentrate</td>
 <td>Sigma, part# D2532</td>
 </tr>
 <tr>
 <td>Streptavidin, R-phycoerythrin conjugate (SAPE)</td>
 <td>Invitrogen, part# S866</td>
 </tr>
 <tr>
 <td>Safe-Lock Microcentrifuge Tube, 0.5 mL </td>
 <td>Eppendorf, part# 0030 123.301</td>
 </tr>
 <tr>
 <td>Teeny Tough-Spots</td>
 <td>Diversified Biotech, part# LTTM-1000</td>
 </tr>
 <tr>
 <td>0.5 M EDTA </td>
 <td>BioRad, part# 161-0729</td>
 </tr>
 <tr>
 <td>10% Tween</td>
 <td>Sigma, part# T2700</td>
 </tr>
 <tr>
 <td>MES free acid monohydrate</td>
 <td>Sigma, part# M5287</td>
 </tr>
 <tr>
 <td>MES sodium salt </td>
 <td>Sigma, part# M5057</td>
 </tr>
 <tr>
 <td>5 M NaCl</td>
 <td>Sigma, part# 71386</td>
 </tr>
 <tr>
 <td>20X SSPE</td>
 <td>Sigma, part# S2015</td>
 </tr>
 <tr>
 <td>Molecular biology grade water</td>
 <td>Sigma, part# W4502</td>
 </tr>
 <tr>
 <td>Hybridization Primers</td>
 <td>Various suppliers (standard desalting)</td>
 </tr>
 <tr>
 <td>Uptag </td>
 <td>5' GATGTCCACGAGGTCTCT 3'</td>
 </tr>
 <tr>
 <td>Buptagkanmx4</td>
 <td>5' biotin-GTCGACCTGCAGCGTACG 3'</td>
 </tr>
 <tr>
 <td>Dntag</td>
 <td>5' CGGTGTCGGTCTCGTAG 3'</td>
 </tr>
 <tr>
 <td>Bdntagkanmx4</td>
 <td>5' biotin-GAAAACGAGCTCGAATTCATCG 3'</td>
 </tr>
 <tr>
 <td>B213 </td>
 <td>5' biotin-CTGAACGGTAGCATCTTGAC 3'</td>
 </tr>
 <tr>
 <td>Uptagkanmx </td>
 <td>5' GTCGACCTGCAGCGTACG 3'</td>
 </tr>
 <tr>
 <td>Dntagkanmx</td>
 <td>5'GAAAACGAGCTCGAATTCATCG 3'</td>
 </tr>
 <tr>
 <td>Uptagcomp </td>
 <td>5'AGAGACCTCGTGGACATC 3'</td>
 </tr>
 <tr>
 <td>Dntagcomp</td>
 <td>5'CTACGAGACCGACACCG 3'</td>
 </tr>
 <tr>
 <td>Upkancomp </td>
 <td>5'CGTACGCTGCAGGTCGAC 3'</td>
 </tr>
 <tr>
 <td>Dnkancomp </td>
 <td>5'CGATGAATTCGAGCTCGTTTTC 3'</td>
 </tr>
 <tr>
 <td>Sequencing Primers: Illumina Platform</td>
 <td>Various suppliers</td>
 </tr>
 <tr>
 <td>UpTag Forward (100uM)</td>
 <td>5' CAA GCA GAA GAC GGC ATA CGA GCT CTT CCG ATC T GAT GTC CAC GAG GTC TCT 3' </td>
 </tr>
 <tr>
 <td>UpTag Reverse (100uM)</td>
 <td>5' AAT GAT ACG GCG ACC ACC GAC ACT CTT TCC CTA CAC GAC GCT CTT CCG ATC T NNNNN GTC GAC CTG CAG CGT ACG 3'</td>
 </tr>
 <tr>
 <td>DownTag Forward (100uM)</td>
 <td>5' CAA GCA GAA GAC GGC ATA CGA GCT CTT CCG ATC T GAA AAC GAG CTC GAA TTC ATC G 3'</td>
 </tr>
 <tr>
 <td>DownTag Reverse (100uM)</td>
 <td>5' AAT GAT ACG GCG ACC ACC GAC ACT CTT TCC CTA CAC GAC GCT CTT CCG ATC T NNNNN CGG TGT CGG TCT CGT AG 3`</td>
 </tr>
 <tr>
 <td>Read 1 UP-tag seq primer (100uM)</td>
 <td>5' GTC GAC CTG CAG CGT ACG 3'</td>
 </tr>
 <tr>
 <td>Read 1 DOWN-tag seq primer (100uM)</td>
 <td>5' CGG TGT CGG TCT CGT AG 3'</td>
 </tr>
 <tr>
 <td>Read 2 Index Sequencing primer (standard Illumina R1 primer) (100uM)</td>
 <td>5' AC ACT CTT TCC CTA CAC GAC GCT CTT CCG ATC T 3'</td>
 </tr>
 <tr>
 <td>Additional Sequencing Reagents/Equipment</td>
 <td>&nbsp;</td>
 </tr>
 <tr>
 <td>Qiagen MinElute 96 UF PCR purification Kit</td>
 <td>Qiagen, part# 29051</td>
 </tr>
 <tr>
 <td>Vaccum pump</td>
 <td>Any vendor</td>
 </tr>
 <tr>
 <td>Macherey-Nagel Vaccum Manifold</td>
 <td>Macherey-Nagel, part# 740 681</td>
 </tr>
 <tr>
 <td>Invitrogen Quant-iT dsDNA BR Assay Kit</td>
 <td>Invitrogen, part# Q32853</td>
 </tr>
 <tr>
 <td>Invitrogen Qubit assay tubes</td>
 <td>Invitrogen, part# Q32856</td>
 </tr>
 <tr>
 <td>40% acrylamide plus 1% N,N'-methylene-bis-acrylamide, 37.5:1</td>
 <td>Bio Rad, part# 161-0148</td>
 </tr>
 <tr>
 <td>Tris Base</td>
 <td>Sigma, part# T1503-1KG</td>
 </tr>
 <tr>
 <td>Boric Acid</td>
 <td>Sigma, part# B6768-500G</td>
 </tr>
 <tr>
 <td>0.5M EDTA, pH 8.0</td>
 <td>Teknova, part# E0306</td>
 </tr>
 <tr>
 <td>Ammonium Persulfate</td>
 <td>Sigma, part# A3678-25G</td>
 </tr>
 <tr>
 <td>TEMED </td>
 <td>Bioshop, part# TEM001.25</td>
 </tr>
 <tr>
 <td>Ethidium Bromide Solution</td>
 <td>Bioshop, part# ETB444.10</td>
 </tr>
 <tr>
 <td>0.5M Ammonium acetate</td>
 <td>Teknova, part# A2000</td>
 </tr>
 <tr>
 <td>10mM Magnesium acetate tetrahydrate</td>
 <td>Sigma, part# M0631-100G</td>
 </tr>
 <tr>
 <td>1mM EDTA, pH 8.0</td>
 <td>See 0.5M EDTA, pH 8.0</td>
 </tr>
 <tr>
 <td>Ethanol</td>
 <td>Various</td>
 </tr>
 <tr>
 <td>Sodium acetate, pH 5.2</td>
 <td>Teknova, part# S0297</td>
 </tr>
 <tr>
 <td>Speed vacuum</td>
 <td>Various </td>
 </tr>
 <tr>
 <td>Single-Read Cluster Generation Kit</td>
 <td>Illumina, part# GD-300-1001</td>
 </tr>
 <tr>
 <td>36c Sequencing Kit v4</td>
 <td>Illumina, part# FC-104-4002</td>
 </tr>
 <tr>
 <td>&nbsp;</td>
 <td>&nbsp;</td>
 </tr>
 </tbody>
 
</table>
10X TBE recipe
<table border="1">
	<tbody>
 <tr>
 <td>Amounts</td>
 <td>Reagents</td>
 </tr>
 <tr>
 <td>108 grams</td>
 <td>Tris Base</td>
 </tr>
 <tr>
 <td>55 grams </td>
 <td>Boric Acid</td>
 </tr>
 <tr>
 <td>40mL</td>
 <td>0.5M EDTA (pH 8.0)</td>
 </tr>
 <tr>
 <td colspan="2">Add dH2O to 1L mark</td>
 </tr>
 </tbody>
</table>

12% Polyacrylamide gel recipe
<table border="1">
<tbody>
 <tr>
 <td>Volumes</td>
 <td>Reagents</td>
 </tr>
 <tr>
 <td>5.8 ml</td>
 <td>40% acrylamide plus 1% N,N'-methylene-bis-acrylamide, 37.5:1</td>
 </tr>
 <tr>
 <td>12 ml</td>
 <td>dH2O</td>
 </tr>
 <tr>
 <td>2 ml</td>
 <td>10X TBE</td>
 </tr>
 <tr>
 <td>140 &mu;l</td>
 <td>10% Ammonium Persulfate</td>
 </tr>
 <tr>
 <td>Total volume: 20ml</td>
 <td>&nbsp;</td>
 </tr>
 </tbody>
</table>

Uptag primer mix:
Resuspend Uptag and Buptagkanmx4 each in ddH2O at 100 &mu;M, then mix in a 1:1 ratio for a final concentration of 50 &mu;M each. Store at -20&deg;C.
Downtag primer mix:
Resuspend Dntag and Bdntagkanmx4 each in ddH2O at 100 &mu;M, then mix in a 1:1 ratio for a final concentration of 50 &mu;M each. Store at -20&deg;C.
Mixed oligonucleotides:
Resuspend each of the following eight oligos (standard desalted) in ddH2O at 100 &mu;M: 
Uptag, Dntag, Uptagkanmx, Dntagkanmx, Uptagcomp, Dntagcomp, Upkancomp, Dnkancomp. 
Mix an equal volume of the eight oligonucleotides for a final concentration of 12.5 &mu;M each.
12X MES stock:
For 10 ml, dissolve 0.7 g MES free acid monohydrate and 1.93 g MES sodium salt in 8 ml molecular biology grade water. After mixing well, check pH and adjust if needed to a pH 6.5-6.7. Add water to a total volume of 10 ml. Filter sterilize and store at 4&deg;C protected from light (e.g., wrap the tube in foil). Replace if solution becomes visibly yellow or after 6 months.
2X Hybridization buffer:
For 50 ml, mix 8.3 ml of 12X MES stock (from 2.9.14), 17.7 ml of 5 M NaCl, 4.0 ml of 0.5 M EDTA, 0.1 ml of 10% Tween 20 (vol/vol), and 19.9 ml filtered ddH2O. Filter sterilize.
Wash A: Mix 300 ml 20X SSPE, 1 mL 10% Tween (vol/vol), 699 ml ddH2O. Filter sterilize. 
Wash B: Mix 150 ml 20X SSPE, 1 mL 10% Tween (vol/vol), 849 ml ddH2O. Filter sterilize.
Barcode sequencing primers 
In UP-tag primer sequences the 5' tail (bold) are Illumina specific adaptor sequences incorporated into the F and R primer. The variable sequence (italics) represents the 5-mer indexing tag used in multiplexing/ index read-out. The 3' tail (underlined) represents the common primer flanking the uptag barcode and is required to amplify the yeast barcodes.
In DOWN-tag primer sequences the 5' tail is identical to 5' tail of UP-tag primers (Illumina specific sequence), however, the 3' tail (underlined) is replaced with the common primers that are used to amplify the DOWN-tag barcodes.

competitive genomic screens of barcoded yeast libraries

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

Watch this Scientific Journal Video about Competitive Genomic Screens of Barcoded Yeast Libraries at JoVE.com

Competitive Genomic Screens of Barcoded Yeast Libraries

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

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

competitive-genomic-screens-of-barcoded-yeast-libraries

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Biology

18.0K ビュー.  University of Toronto. 我々は包括的、公平なゲノムワイドな遺伝子薬剤と遺伝子 - 環境相互作用を理解するために画面を開発しました。これらの変異体のコレクションをスクリーニングするための方法が提示されます。

ビデオ: Competitive Genomic Screens of Barcoded Yeast Libraries

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

rapid identification of chemical genetic interactions in saccharomyces cerevisiae

Rapid Identification of Chemical Genetic Interactions in Saccharomyces cerevisiae

Here we present a cost-effective method for defining chemical-genetic interactions in budding yeast. The approach is built on fundamental techniques in yeast molecular biology and is well suited for the mechanistic interrogation of small to medium collections of chemicals and other media...

Rapid Identification of Chemical Genetic Interactions in Saccharomyces cerevisiae

a quantitative fitness analysis workflow

A Quantitative Fitness Analysis Workflow

Quantitative Fitness Analysis (QFA) is a complementary series of experimental and computational methods for estimating microbial culture fitnesses.  QFA estimates the effect of genetic mutations, drugs or other applied treatments on microbe growth.  Experiments scaling from focussed analysis of single cultures to thousands of parallel cultures can be...

large-scale screens of metagenomic libraries

Large-Scale Screens of Metagenomic Libraries

Metagenomic libraries archive large fragments of contiguous genomic sequences from microorganisms without requiring prior cultivation.  Generating a ...

informatic analysis of sequence data from batch yeast 2-hybrid screens

Informatic Analysis of Sequence Data from Batch Yeast 2-Hybrid Screens

Deep sequencing of yeast populations selected for positive yeast 2-hybrid interactions potentially yields a wealth of information about interacting partner proteins. Here, we describe the operation of specific bioinformatics tools and customized updated software to analyze sequence data from such...

enhanced yeast one-hybrid screens to identify transcription factor binding to human dna sequences

Enhanced Yeast One-hybrid Screens To Identify Transcription Factor Binding To Human DNA Sequences

Here, we present an enhanced yeast one-hybrid screening protocol to identify the transcription factors (TFs) that can bind to a human DNA region of interest. This method uses a high-throughput screening pipeline that can interrogate the binding of &#62;1,000 TFs in a single...

lentiviral infection of mpnst cells and genomic dna isolation for genome-scale shrna screens

Lentiviral Infection of MPNST Cells and Genomic DNA Isolation for Genome-Scale shRNA Screens  

identification of host pathways targeted by bacterial effector proteins using yeast toxicity and suppressor screens

Identification of Host Pathways Targeted by Bacterial Effector Proteins using Yeast Toxicity and Suppressor Screens

Bacterial pathogens secrete proteins into the host that target crucial biological processes. Identifying the host pathways targeted by bacterial effector proteins is key to addressing molecular pathogenesis. Here, a method using a modified yeast suppressor and toxicity screen to elucidate host pathways targeted by toxic bacterial effector proteins is...

fission yeast as a platform for antibacterial drug screens targeting bacterial cytoskeleton proteins

Author Spotlight: Exploring Cytoskeletal Dynamics to Unveil Novel Antibiotics Through Innovative Cell-Based Assays

Fission yeast is used here as a heterologous host to express bacterial cytoskeletal proteins such as FtsZ and MreB as translational fusion proteins with GFP to visualize their polymerization. Also, compounds that affect polymerization are identified by imaging using a fluorescence...

Fission Yeast as a Platform for Antibacterial Drug Screens Targeting Bacterial Cytoskeleton Proteins

genetic profiling and genome-scale dropout screening to identify therapeutic targets in mouse models of malignant peripheral nerve sheath tumor

Author Spotlight: Finding New Therapeutic Targets for Malignant Peripheral Nerve Sheath Tumor Through Genome-Scale shRNA Screens 

We have developed a cross-species comparative oncogenomics approach utilizing genomic analyses and functional genomic screens to identify and compare therapeutic targets in tumors arising in genetically engineered mouse models and the corresponding human tumor...

Genome-Scale Screening to Identify and Compare Therapeutic Targets in Tumors

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digital pcr-based competitive index for high-throughput analysis of fitness in salmonella

Digital PCR-based Competitive Index for High-throughput Analysis of Fitness in Salmonella

This molecular-based approach for determining bacterial fitness facilitates precise and accurate detection of microorganisms using unique genomic DNA barcodes that are quantified via digital PCR. The protocol describes calculating the competitive index for Salmonella strains; however, the technology is readily adaptable to protocols requiring absolute quantification of any genetically-malleable...

Digital PCR-based Competitive Index for High-throughput Analysis of Fitness in Salmonella

pooled crispr-based genetic screens in mammalian cells

Pooled CRISPR-Based Genetic Screens in Mammalian Cells

CRISPR-Cas9 technology provides an efficient method to precisely edit the mammalian genome in any cell type and represents a novel means to perform genome-wide genetic screens. A detailed protocol discussing the steps required for the successful performance of pooled genome-wide CRISPR-Cas9 screens is provided...

cell surface receptor identification using genome-scale crispr/cas9 genetic screens

Cell Surface Receptor Identification Using Genome-Scale CRISPR/Cas9 Genetic Screens

This manuscript describes a genome-scale cell-based screening approach to identify extracellular receptor-ligand...

genomic mri - a public resource for studying sequence patterns within genomic dna

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

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

quantitative and automated high-throughput genome-wide rnai screens in c. elegans

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.

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

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

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

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

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

competitive transplants to evaluate hematopoietic stem cell fitness

Competitive Transplants to Evaluate Hematopoietic Stem Cell Fitness

This protocol provides step-by-step guidelines for setting up competitive mouse bone marrow transplant experiments to study hematopoietic stem/progenitor cell function without prior purification of stem cells by cell sorting.

assessing differences in sperm competitive ability in drosophila

Assessing Differences in Sperm Competitive Ability in Drosophila

Differential sperm competitive ability among Drosophila males with distinct genotypes can be ascertained through double-mating experiments. Each of these experiments involves one of the males of interest and a reference male. Readily identifiable markers in the progeny allow inference of the fraction of individuals fathered by each...

Assessing Differences in Sperm Competitive Ability in Drosophila

generating transposon insertion libraries in gram-negative bacteria for high-throughput sequencing

Generating Transposon Insertion Libraries in Gram-Negative Bacteria for High-Throughput Sequencing

We describe a method to generate saturating transposon mutant libraries in Gram-negative bacteria and subsequent preparation of DNA amplicon libraries for high-throughput sequencing. As an example, we focus on the ESKAPE pathogen, Acinetobacter baumannii, but this protocol is amenable to a wide range of Gram-negative...

large insert environmental genomic library production

Large Insert Environmental Genomic Library Production

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

Metagenomic libraries archive large fragments of contiguous genomic sequences from microorganisms without requiring prior cultivation. Generating a streamlined procedure for creating and screening metagenomic libraries is therefore useful for efficient high-throughput investigations into the genetic and metabolic properties of uncultured microbial assemblages. Here, key protocols are presented on video, which we propose is the most useful format for accurately describing a long process that alternately depends on robotic instrumentation and (human) manual interventions. First, we employed robotics to spot library clones onto high-density macroarray membranes, each of which can contain duplicate colonies from twenty-four 384-well library plates. Automation is essential for this procedure not only for accuracy and speed, but also due to the miniaturization of scale required to fit the large number of library clones into highly dense spatial arrangements. Once generated, we next demonstrated how the macroarray membranes can be screened for genes of interest using modified versions of standard protocols for probe labeling, membrane hybridization, and signal detection. We complemented the visual demonstration of these procedures with detailed written descriptions of the steps involved and the materials required, all of which are available online alongside the video.

Isolation of Genomic DNA from Mouse Tails

Technical Demonstration of Whole Genome Array Comparative Genomic Hybridization

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

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

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

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

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

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

Development of automated imaging and analysis for zebrafish chemical screens.

We demonstrate the application of image-based high-content screening (HCS) methodology to identify small molecules that can modulate the FGF/RAS/MAPK pathway in zebrafish embryos. The zebrafish embryo is an ideal system for in vivo high-content chemical screens. The 1-day old embryo is approximately 1mm in diameter and can be easily arrayed into 96-well plates, a standard format for high throughput screening. During the first day of development, embryos are transparent with most of the major organs present, thus enabling visualization of tissue formation during embryogenesis. The complete automation of zebrafish chemical screens is still a challenge, however, particularly in the development of automated image acquisition and analysis. We previously generated a transgenic reporter line that expresses green fluorescent protein (GFP) under the control of FGF activity and demonstrated their utility in chemical screens 1. To establish methodology for high throughput whole organism screens, we developed a system for automated imaging and analysis of zebrafish embryos at 24-48 hours post fertilization (hpf) in 96-well plates 2. In this video we highlight the procedures for arraying transgenic embryos into multiwell plates at 24hpf and the addition of a small molecule (BCI) that hyperactivates FGF signaling 3. The plates are incubated for 6 hours followed by the addition of tricaine to anesthetize larvae prior to automated imaging on a Molecular Devices ImageXpress Ultra laser scanning confocal HCS reader. Images are processed by Definiens Developer software using a Cognition Network Technology algorithm that we developed to detect and quantify expression of GFP in the heads of transgenic embryos. In this example we highlight the ability of the algorithm to measure dose-dependent effects of BCI on GFP reporter gene expression in treated embryos.

We report the development of a system for automated imaging and analysis of zebrafish transgenic embryos in multiwell plates. This demonstrates the ability to measure dose dependent effects of a small molecule, BCI, on Fibroblast Growth Factor reporter gene expression and provide technology for establishing high-throughput zebrafish chemical screens.

We demonstrate the application of image-based high-content screening (HCS) methodology to identify small molecules that can modulate the FGF/RAS/MAPK ...

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

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

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

Genomic Transformation of the Picoeukaryote Ostreococcus tauri

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

Genomic Transformation of the Picoeukaryote Ostreococcus tauri

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

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

Selective Capture of 5-hydroxymethylcytosine from Genomic DNA

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

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

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

Competition among conspecific males for fertilizing the ova is one of the mechanisms of sexual selection, i.e. selection that operates on maximizing the number of successful mating events rather than on maximizing survival and viability 1. Sperm competition represents the competition between males after copulating with the same female 2, in which their sperm are coincidental in time and space. This phenomenon has been reported in multiple species of plants and animals 3. For example, wild-caught D. melanogaster females usually contain sperm from 2-3 males 4. The sperm are stored in specialized organs with limited storage capacity, which might lead to the direct competition of the sperm from different males 2,5.
Comparing sperm competitive ability of different males of interest (experimental male types) has been performed through controlled double-mating experiments in the laboratory 6,7. Briefly, a single female is exposed to two different males consecutively, one experimental male and one cross-mating reference male. The same mating scheme is then followed using other experimental male types thus facilitating the indirect comparison of the competitive ability of their sperm through a common reference. The fraction of individuals fathered by the experimental and reference males is identified using markers, which allows one to estimate sperm competitive ability using simple mathematical expressions 7,8. In addition, sperm competitive ability can be estimated in two different scenarios depending on whether the experimental male is second or first to mate (offense and defense assay, respectively) 9, which is assumed to be reflective of different competence attributes.
Here, we describe an approach that helps to interrogate the role of different genetic factors that putatively underlie the phenomenon of sperm competitive ability in D. melanogaster.

Differential sperm competitive ability among Drosophila males with distinct genotypes can be ascertained through double-mating experiments. Each of these experiments involves one of the males of interest and a reference male. Readily identifiable markers in the progeny allow inference of the fraction of individuals fathered by each male.

Competition among conspecific males for fertilizing the ova is one of the mechanisms of sexual selection, i.e. selection that operates on maximizing the ...

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

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