Lee Minho, Choi Shin-Jung, Han Sangjo, Nam Miyoung, Kim Dongsup, Kim Dong-Uk, Hoe Kwang-Lae
Catholic Precision Medicine Research Center, College of Medicine, The Catholic University of Korea, Seoul 06591, Korea.
Aging Research Center, Korea Research Institute of Bioscience & Biotechnology (KRIBB), Daejeon 34141, Korea.
Genomics Inform. 2018 Jun;16(2):22-29. doi: 10.5808/GI.2018.16.2.22. Epub 2018 Jun 30.
Incorporation of unique barcodes into fission yeast gene deletion collections has enabled the identification of gene functions by growth fitness analysis. For fine tuning, it is important to examine barcode sequences, because mutations arise during strain construction. Out of 8,708 barcodes (4,354 strains) covering 88.5% of all 4,919 open reading frames, 7,734 barcodes (88.8%) were validated as high-fidelity to be inserted at the correct positions by Sanger sequencing. Sequence examination of the 7,734 high-fidelity barcodes revealed that 1,039 barcodes (13.4%) deviated from the original design. In total, 1,284 mutations (mutation rate of 16.6%) exist within the 1,039 mutated barcodes, which is comparable to budding yeast (18%). When the type of mutation was considered, substitutions accounted for 845 mutations (10.9%), deletions accounted for 319 mutations (4.1%), and insertions accounted for 121 mutations (1.6%). Peculiarly, the frequency of substitutions (67.6%) was unexpectedly higher than in budding yeast (∼28%) and well above the predicted error of Sanger sequencing (∼2%), which might have arisen during the solid-phase oligonucleotide synthesis and PCR amplification of the barcodes during strain construction. When the mutation rate was analyzed by position within 20-mer barcodes using the 1,284 mutations from the 7,734 sequenced barcodes, there was no significant difference between up-tags and down-tags at a given position. The mutation frequency at a given position was similar at most positions, ranging from 0.4% (32/7,734) to 1.1% (82/7,734), except at position 1, which was highest (3.1%), as in budding yeast. Together, well-defined barcode sequences, combined with the next-generation sequencing platform, promise to make the fission yeast gene deletion library a powerful tool for understanding gene function.
将独特的条形码整合到裂殖酵母基因缺失文库中,使得通过生长适应性分析来鉴定基因功能成为可能。为了进行微调,检查条形码序列很重要,因为在菌株构建过程中会出现突变。在覆盖所有4919个开放阅读框中88.5%的8708个条形码(4354个菌株)中,7734个条形码(88.8%)经桑格测序验证为高保真,可插入到正确位置。对这7734个高保真条形码的序列检查发现,1039个条形码(13.4%)与原始设计存在偏差。在这1039个突变条形码中总共存在1284个突变(突变率为16.6%),这与芽殖酵母(18%)相当。考虑突变类型时,替换占845个突变(10.9%),缺失占319个突变(4.1%),插入占121个突变(1.6%)。特别的是,替换的频率(67.6%)意外高于芽殖酵母(约28%),且远高于桑格测序的预测误差(约2%),这可能是在菌株构建过程中条形码的固相寡核苷酸合成和PCR扩增期间出现的。当使用来自7734个测序条形码的1284个突变,按20聚体条形码内的位置分析突变率时,给定位置的上游标签和下游标签之间没有显著差异。除了位置1的突变频率最高(3.1%)(与芽殖酵母情况相同)外,大多数位置的给定位置突变频率相似,范围从0.4%(32/7734)到1.1%(82/7734)。总之,明确的条形码序列与新一代测序平台相结合,有望使裂殖酵母基因缺失文库成为理解基因功能的强大工具。