The DOI matches its Crossref record; 22 of the 22 references it cites were found in a registry or an index.
Quantitative phenotyping via deep barcode sequencing
Open accessAbstract
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, Bar code analysis by Seq uencing, 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.
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Functional profiling of the Saccharomyces cerevisiae genome
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Self-citationAccurate whole human genome sequencing using reversible terminator chemistry
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Self-citationMapping short DNA sequencing reads and calling variants using mapping quality scores
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The Transcriptional Landscape of the Yeast Genome Defined by RNA Sequencing
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Chemogenomic profiling: Identifying the functional interactions of small molecules in yeast
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Anders, S., & Huber, W. (2010) · Genome Biology · doi:10.1186/gb-2010-11-10-r106 · Cited by 15,581
DNA-Damaging Agents in Cancer Chemotherapy: Serendipity and Chemical Biology
Cheung-Ong, K., Giaever, G., & Nislow, C. (2013) · Chemistry & Biology · doi:10.1016/j.chembiol.2013.04.007 · Cited by 591
Self-citationMutant phenotypes for thousands of bacterial genes of unknown function
Price, M. N., Wetmore, K. M., Waters, R. J., Callaghan, M., Ray, J., Liu, H., Kuehl, J. V., Melnyk, R. A., Lamson, J. S., Suh, Y., et al. (2018) · Nature · doi:10.1038/s41586-018-0124-0 · Cited by 576
The Yeast Deletion Collection: A Decade of Functional Genomics
Giaever, G., & Nislow, C. (2014) · Genetics · doi:10.1534/genetics.114.161620 · Cited by 481
Self-citationMolecular targets of oxidative stress
Avery, S. V. (2011) · Biochemical Journal · doi:10.1042/bj20101695 · Cited by 474
Metadata
- Authors
- Smith, A. M., Heisler, L. E., Mellor, J., Kaper, F., Thompson, M. J., Chee, M., Roth, F. P., Giaever, G., & Nislow, C.
- Venue
- Genome Research
- Publisher
- Cold Spring Harbor Laboratory
- Published
- 2009-07-21
- Volume
- 19
- Issue
- 10
- Pages
- 1836-1842
- ISSN
- 1088-9051 (ISSN-L)
- OpenAlex
- W1994624068
- Cited by
- 298
- References
- 22
- Type
- posted content
- Language
- en
- Open access
- bronze
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- Smith, A. M., Heisler, L. E., Mellor, J., Kaper, F., Thompson, M. J., Chee, M., Roth, F. P., Giaever, G., & Nislow, C. (2009). Quantitative phenotyping via deep barcode sequencing. Genome Research. https://doi.org/10.1101/gr.093955.109
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