RT Journal
A1 Smith, Andrew M.
A1 Heisler, Lawrence E.
A1 Mellor, Joseph
A1 Kaper, Fiona
A1 Thompson, Michael J.
A1 Chee, Mark
A1 Roth, Frederick P.
A1 Giaever, Guri
A1 Nislow, Corey
T1 Quantitative phenotyping via deep barcode sequencing
JF Genome Research 
JO Genome Research 
YR 2009 
FD October 01 
VO 19 
IS 10 
SP 1836 
OP 1842 
DO 10.1101/gr.093955.109 
UL http://genome.cshlp.org/content/19/10/1836.abstract 
AB Next-generation DNA sequencing technologies have revolutionized diverse genomics applications, including de novo genome sequencing, SNP detection, chromatin immunoprecipitation, and transcriptome analysis. Here we apply deep sequencing to genome-scale fitness profiling to evaluate yeast strain collections in parallel. This method, Barcode analysis by Sequencing, or “Bar-seq,” outperforms the current benchmark barcode microarray assay in terms of both dynamic range and throughput. When applied to a complex chemogenomic assay, Bar-seq quantitatively identifies drug targets, with performance superior to the benchmark microarray assay. We also show that Bar-seq is well-suited for a multiplex format. We completely re-sequenced and re-annotated the yeast deletion collection using deep sequencing, found that ∼20% of the barcodes and common priming sequences varied from expectation, and used this revised list of barcode sequences to improve data quality. Together, this new assay and analysis routine provide a deep-sequencing-based toolkit for identifying gene–environment interactions on a genome-wide scale.