| Literature DB >> 19622793 |
Andrew M Smith1, Lawrence E Heisler, Joseph Mellor, Fiona Kaper, Michael J Thompson, Mark Chee, Frederick P Roth, Guri Giaever, Corey Nislow.
Abstract
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 approximately 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.Entities:
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Year: 2009 PMID: 19622793 PMCID: PMC2765281 DOI: 10.1101/gr.093955.109
Source DB: PubMed Journal: Genome Res ISSN: 1088-9051 Impact factor: 9.043