Benita Yair, Oosting Ronald S, Lok Martin C, Wise Michael J, Humphery-Smith Ian
Department of Pharmaceutical Proteomics, Utrecht Institute of Pharmaceutical Sciences, Utrecht University, Sorbonnelaan 16, Utrecht, The Netherlands.
Nucleic Acids Res. 2003 Aug 15;31(16):e99. doi: 10.1093/nar/gng101.
A set of 1438 human exons was subjected to nested PCR. The initial success rate using a standard PCR protocol required for ligation-independent cloning was 83.4%. Logistic regression analysis was conducted on 27 primer- and template-related characteristics, of which most could be ignored apart from those related to the GC content of the template. Overall GC content of the template was a good predictor for PCR success; however, specificity and sensitivity values for predicted outcome were improved to 84.3 and 94.8%, respectively, when regionalized GC content was employed. This represented a significant improvement in predictability with respect to GC content alone (P < 0.001; chi(2)) and is expected to increase in relative sensitivity as template size increases. Regionalized GC was calculated with respect to a threshold of 61% GC content and a sliding window of 21 bp across the target sequence. Fine-tuning of PCR conditions is not practicable for all target sequences whenever a large number of genes of different lengths and GC content are to be amplified in parallel, particularly if total open reading frame or domain coverage is essential for recombinant protein synthesis. Thus, the present method is proposed as a means of grouping subsets of genes possessing potentially difficult target sequences so that PCR conditions can be optimized separately in order to obtain improved outcomes.
一组1438个人类外显子进行了巢式PCR。使用不依赖连接的克隆所需的标准PCR方案,初始成功率为83.4%。对27个引物和模板相关特征进行了逻辑回归分析,除了与模板GC含量相关的特征外,大多数特征都可以忽略。模板的总体GC含量是PCR成功的良好预测指标;然而,当采用区域化GC含量时,预测结果的特异性和敏感性值分别提高到84.3%和94.8%。这代表了仅就GC含量而言预测性的显著提高(P < 0.001;卡方检验),并且预计随着模板大小的增加,相对敏感性也会增加。区域化GC是根据GC含量61%的阈值和跨越目标序列的21 bp滑动窗口计算的。每当要并行扩增大量不同长度和GC含量的基因时,对所有目标序列进行PCR条件的微调是不实际的,特别是如果总开放阅读框或结构域覆盖对于重组蛋白合成至关重要。因此,提出本方法作为一种对具有潜在困难目标序列的基因子集进行分组的方法,以便可以分别优化PCR条件以获得更好的结果。