Chemical-genetic approaches offer the potential for unbiased functional annotation of chemical libraries. Mutations can alter the response of cells in the presence of a compound, revealing chemical-genetic interactions that can elucidate a compound's mode of action. We developed a highly parallel, unbiased yeast chemical-genetic screening system involving three key components. First, in a drug-sensitive genetic background, we constructed an optimized diagnostic mutant collection that is predictive for all major yeast biological processes. Second, we implemented a multiplexed (768-plex) barcode-sequencing protocol, enabling the assembly of thousands of chemical-genetic profiles. Finally, based on comparison of the chemical-genetic profiles with a compendium of genome-wide genetic interaction profiles, we predicted compound functionality. Applying this high-throughput approach, we screened seven different compound libraries and annotated their functional diversity. We further validated biological process predictions, prioritized a diverse set of compounds, and identified compounds that appear to have dual modes of action.

中文翻译：

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跨多种生物过程的化学文库的功能注释

化学遗传学方法为化学文库的无偏功能注释提供了潜力。突变可在化合物存在下改变细胞的反应，揭示化学-遗传相互作用，可阐明化合物的作用方式。我们开发了高度平行，无偏见的酵母化学遗传筛选系统，该系统涉及三个关键组件。首先，在药物敏感的遗传背景下，我们构建了可预测所有主要酵母生物过程的优化诊断突变体集合。其次，我们实现了一种多路复用（768多路）条形码排序协议，从而可以组装成千上万的化学遗传图谱。最后，基于化学基因图谱与全基因组遗传相互作用图谱纲要的比较，我们预测了化合物的功能。应用这种高通量方法，我们筛选了七个不同的化合物库并注释了它们的功能多样性。我们进一步验证了生物学过程的预测，确定了各种化合物的优先级，并确定了具有双重作用模式的化合物。