Hip-Hop Chemical Genomics Lab-Protocols

Competitive Genomic Screens of Barcoded Yeast Libraries

Follow link to video published in the Journal of Visual Experiments explaining the technology.
Summary: We have developed comprehensive, unbiased genome-wide screens to understand gene-drug and gene-environment interactions. Methods for screening these mutant collections are presented.

Robotics- Yeast Growing Robot

Growth assays have been automated for our genome-wide profiling prescreens, screens and follow-up confirmation assays. These robotic platforms comprise a central Packard Multiprobe II liquid handling instrument surrounded by 4 Tecan Genios Platereaders. The robotic system is coordinated by custom LabView software, which monitors growth, compound handling and sample storage. The software allows real-time growth analysis, and user-defined cell transfer and sample collection at specified generation times. All assay data from compound registration through analyzed data is stored in a central database. For more information, please contact mproctor at stanford.edu or ggiaever at utoronto.ca.

Watch Yeast Grower Movie

Quicktime movie, 3.2 MB

ACCESS Robotic Software and DB_interface

A web manual can be found at :

(this work is in progress, check back for updates)

HipHop Assay Protocol

Molecular barcode arrays allow the analysis of thousands of biological samples in parallel through the use of unique 20-base-pair (bp) DNA tags. Here we present a new barcode array, which is unique among microarrays in that it includes at least five replicates of every tag feature. The use of smaller dispersed replicate features dramatically improves performance versus a single larger feature and allows the correction of previously undetectable hybridization defects.

A full-text PDF of the publication can be found at :

Bar-seq Sequencing Protocol

Next-generation sequencing has proven an extremely effective technology for molecular counting applications where the number of sequence reads provides a digital readout for RNA-seq, ChIP-seq, Tn-seq and other applications. The extremely large number of sequence reads that can be obtained per run permits the analysis of increasingly complex samples. For lower complexity samples, however, a point of diminishing returns is reached when the number of counts per sequence results in oversampling with no increase in data quality. A solution to making next-generation sequencing as efficient and affordable as possible involves assaying multiple samples in a single run. Here, we report the successful 96-plexing of complex pools of DNA barcoded yeast mutants and show that such 'Bar-seq' assessment of these samples is comparable with data provided by barcode microarrays, the current benchmark for this application. The cost reduction and increased throughput permitted by highly multiplexed sequencing will greatly expand the scope of chemogenomics assays and, equally importantly, the approach is suitable for other sequence counting applications that could benefit from massive parallelization.

A full-text PDF of the publication can be found at :