Nuñez Pedrozo Cristian N, Peralta Tomás M, Olea Fernanda D, Locatelli Paola, Crottogini Alberto J, Belaich Mariano N, Cuniberti Luis A
Laboratorio de Regeneración Cardiovascular, IMETTYB - Universidad Favaloro - CONICET, Buenos Aires, CABA, C1078AAI, Argentina.
Departamento de Biología Comparada, Celular y Molecular, FICEN. Universidad Favaloro, Buenos Aires, CABA, C1078AAI, Argentina.
Comput Struct Biotechnol J. 2022 Jul 13;20:3779-3782. doi: 10.1016/j.csbj.2022.07.023. eCollection 2022.
Angiogenic gene overexpression has been the main strategy in numerous vascular regenerative gene therapy projects. However, most have failed in clinical trials. CRISPRa technology enhances gene overexpression levels based on the identification of sgRNAs with maximum efficiency and safety. CRISPick and CHOP CHOP are the most widely used web tools for the prediction of sgRNAs. The objective of our study was to analyze the performance of both platforms for the sgRNA design to angiogenic genes (VEGFA, KDR, EPO, HIF-1A, HGF, FGF, PGF, FGF1) involving different human reference genomes (GRCH 37 and GRCH 38). The top 20 ranked sgRNAs proposed by the two tools were analyzed in different aspects. No significant differences were found on the DNA curvature associated with the sgRNA binding sites but the sgRNA predicted on-target efficiency was significantly greater when CRISPick was used. Moreover, the mean ranking variation was greater for the same platform in EPO, EGF, HIF-1A, PGF and HGF, whereas it did not reach statistical significance in KDR, FGF-1 and VEGFA. The rearrangement analysis of the ranking positions was also different between platforms. CRISPick proved to be more accurate in establishing the best sgRNAs in relation to a more complete genome, whereas CHOP CHOP showed a narrower classification reordering.
血管生成基因过表达一直是众多血管再生基因治疗项目中的主要策略。然而，大多数项目在临床试验中都失败了。CRISPRa技术基于对具有最高效率和安全性的sgRNA的识别来提高基因过表达水平。CRISPick和CHOP CHOP是预测sgRNA最广泛使用的网络工具。我们研究的目的是分析这两个平台针对涉及不同人类参考基因组（GRCH 37和GRCH 38）的血管生成基因（VEGFA、KDR、EPO、HIF-1A、HGF、FGF、PGF、FGF1）进行sgRNA设计的性能。对这两个工具提出的排名前20的sgRNA进行了不同方面的分析。在与sgRNA结合位点相关的DNA曲率方面未发现显著差异，但使用CRISPick时预测的sgRNA靶向效率显著更高。此外，在EPO、EGF、HIF-1A、PGF和HGF中，同一平台的平均排名变化更大，而在KDR、FGF-1和VEGFA中未达到统计学显著差异。平台之间排名位置的重排分析也有所不同。CRISPick在针对更完整的基因组确定最佳sgRNA方面被证明更准确，而CHOP CHOP显示出更窄的分类重排。
