美國賓州州立大學(xué)的Howard M. Salis研究團隊開發(fā)了自動化設(shè)計上千個非重復(fù)基因片段的技術(shù)，可用于建立穩(wěn)定的遺傳系統(tǒng)。 相關(guān)論文發(fā)表在2020年7月13日出版的《自然—生物技術(shù)》。

該課題組研究人員開發(fā)了“非重復(fù)片段計算器”，用于從特定設(shè)計約束位點（包括啟動子，核糖體結(jié)合位點和終止子）快速生成上千個高度不重復(fù)基因片段。作為演示，課題組研究人員設(shè)計并實驗表征了4350個非重復(fù)細(xì)菌啟動子，其轉(zhuǎn)錄率在820,000倍的范圍內(nèi)變化，以及1722個高度非重復(fù)性酵母啟動子，其轉(zhuǎn)錄率在25,000倍的范圍內(nèi)變化。

該課題組人員應(yīng)用機器學(xué)習(xí)來解釋特定的相互作用如何控制啟動子的轉(zhuǎn)錄率。研究人員還展示了使用非重復(fù)基因片段可以大幅減少同源重組，從而有更好的遺傳穩(wěn)定性。

據(jù)悉，當(dāng)基因部分包含重復(fù)序列時，改造基因系統(tǒng)容易失敗。設(shè)計具有所需功能的許多非重復(fù)基因片段有很高計算復(fù)雜度，仍然是一個困難的挑戰(zhàn)。

附：英文原文

: Automated design of thousands of nonrepetitive parts for engineering stable genetic systems

Author: Ayaan Hossain, Eriberto Lopez, Sean M. Halper, Daniel P. Cetnar, Alexander C. Reis, Devin Strickland, Eric Klavins, Howard M. Salis

Issue&Volume: 2020-07-13

Abstract: Engineered genetic systems are prone to failure when their genetic parts contain repetitive sequences. Designing many nonrepetitive genetic parts with desired functionalities remains a difficult challenge with high computational complexity. To overcome this challenge, we developed the Nonrepetitive Parts Calculator to rapidly generate thousands of highly nonrepetitive genetic parts from specified design constraints, including promoters, ribosome-binding sites and terminators. As a demonstration, we designed and experimentally characterized 4,350 nonrepetitive bacterial promoters with tran ion rates that varied across a 820,000-fold range, and 1,722 highly nonrepetitive yeast promoters with tran ion rates that varied across a 25,000-fold range. We applied machine learning to explain how specific interactions controlled the promoters’ tran ion rates. We also show that using nonrepetitive genetic parts substantially reduces homologous recombination, resulting in greater genetic stability.