Overview
We design shRNA molecules with an algorithm. Our algorithm uses several criteria to rank potential 21mer targets within each human and mouse Refseq transcript. The algorithm applies a set of rules, including those derived from the siRNA literature, our cloning scheme, constraints on the synthesis of the oligonucleotides and others. In applying the algorithm, our aim is to achieve a balance of two competing goals: make hairpins that effectively knockdown the target transcript and, as best possible, design hairpins that knockdown only one gene and not other so-called 'off-target' genes. Each goal presents distinct challenges. The criteria for predicting effective knockdown with either siRNA or shRNA are not well understood. Our rules are primarily derived from the siRNA literature; how well these rules apply to shRNA design is unclear. Genome evolution constrains target specificity. Many genes are part of extensive gene families, which may make targeting any one gene difficult. Functionally distinct genes share many motifs. Our knowledge of transcript structure and variants is still very incomplete as well. For all these reasons and more, we construct 5 shRNAs for each transcript with the expectation of getting a range of knockdown efficiencies across the set and at least one or two which knockdown effectively.
Users of this database should be aware that in order to have consistent and reliable annotation, the TRC consortium decided early on to use NCBI's REFSEQ collection of transcripts as the definitive source of information for the primary target sequence for the design of shRNA molecules.
As a general rule in the construction of the library, we construct shRNA molecules targeting just the first Refseq transcript reported from each NCBI gene. In part due to our design process, see below, the majority of the shRNAs target all known transcript variants.
A brief narrative of the candidate selection process
Get the Candidate Sequences
For each human and mouse Refseq transcript, we generate all 21mers starting 25 bp after the beginning of the CDS up to those starting 150 bp from the end of the transcript. Each 21mer is called a 'candidate'.
Score the Candidate Sequences For Knockdown Efficiency
Each candidate is given an "original score" by applying a set of rules that either penalize or reward features predicting successful knockdown and clone-design considerations, and then calculating the product of all the penalties/rewards. The individual rules are listed below. The candidates are then sorted by score and all those above a minimum score are stored.
日前,國產期刊TheInnovation獲得首個影響因子(IF=32.1),成為科睿唯安JCR綜合性期刊分類下排名僅次于《自然》(IF=64.8)和《科學》(IF=56.9)的期刊,并且這本期刊在目前......
調控基因組元件的高階三維(3D)組織為基因調控提供了拓撲基礎,但尚不清楚哺乳動物基因組中的多個調控元件如何在單個細胞內相互作用。2023年8月28日,北京大學湯富酬團隊在NatureMethods(I......
近日,服務科學領域的全球領導者賽默飛世爾科技(以下簡稱賽默飛)宣布,在達成收購意向兩個月之后,賽默飛以28億美元、折合人民幣約190億元的價格,完成了對TheBindingSiteGroup的全現金收......
11月15日,施普林格·自然和TheLens平臺宣布結成重要的合作伙伴關系,以更深入地揭示學術研究和數據如何能通過經濟和社會成效,加速推動創新的問題解決方式。通過將科學、投資和企業領域的開放數據更好地......
多年來,出現了多種“大腦地圖”,每一種都關注不同的大腦過程,從新陳代謝到認知功能。雖然這些地圖很重要,但單獨使用它們會限制研究人員從中得出的發現。現在,來自蒙特利爾神經學研究所的一個團隊和其他研究人員......
分析測試百科網訊2019年10月10日,第三屆磁性相關測量講習班暨QuantumDesign中國子公司2019年華北區用戶會在北京中科院物理所舉辦,由中國電子學會應用磁學分會主辦,QuantumDes......
6月10日,QS教育集團正式發布了2021年世界大學排名,中國共有83所高校上榜,包括內地高校51所,港澳臺地區高校32所。中國大學的總體排名情況已經連續數年呈上升趨勢,今年再度刷新了榜單。大學排名,......
磷酸甘油酸突變酶1(PGAM1)通過其代謝活性以及與其他蛋白質(例如α平滑肌肌動蛋白(ACTA2))的相互作用,在癌癥代謝和腫瘤進展中起關鍵作用。變構調節被認為是發現針對PGAM1的高選擇性和有效抑制......
如果說宇宙蘊藏無數奧秘,那么大腦必定是其中最難解謎團之一。對人類大腦的研究不僅關乎我們對人體內這一最復雜器官發育與功能的理解,相關的病理學、藥物發現、再生醫學等研究更是與國計民生直接相關。基于干細胞、......
在國家自然科學基金項目(批準號:31127901,31730054,31661143041,31700743)等資助下,中國科學院生物物理研究所徐濤院士和紀偉教授級高級工程師在提高光學顯微鏡分辨率技術......