Generation of a more efficient prime editor 2 by addition of the Rad51 DNA-binding domain

Although prime editing is a promising genome editing method, the efficiency of prime editor 2 (PE2) is often insufficient. Here we generate a more efficient variant of PE2, named hyPE2, by adding the Rad51 DNA-binding domain. When tested at endogenous sites, hyPE2 shows a median of 1.5- or 1.4- fold (range, 0.99- to 2.6-fold) higher efficiencies than PE2; furthermore, at sites where PE2-induced prime editing is very inefficient (efficiency < 1%), hyPE2 enables prime editing with efficiencies ranging from 1.1% to 2.9% at up to 34% of target sequences, potentially facilitating prime editing applications.ope

Study on Effects of Sloshing Loads on Fatigue Strength of Independent B-Type LNG Tank

The main objective of this thesis is to investigate the load effects due to sloshing on the fatigue assessment of an IMO independent type B LNG tank. The selection of the cargo containment system type and the number of cargo tanks of large LNG carrier or LNG FPSO (FLNG) is mainly related to the sloshing problem. In contrast to earlier design concept, nowadays the LNG carriers and FLNG are considered to be operating at intermediate loading condition in harsh environmental conditions. The most popular LNG containment system for the FLNG is an independent prismatic tank categorized as IMO (International Maritime Organization) type B tank, in which the ship hull supporting the LNG tanks. It is recognized that the independent prismatic tank type B is free from possible liquid sloshing inside the tank in the view point of the strength. However in the view point of fatigue assessment of the cargo tank, it needs careful verification in accordance with IMO type B independent tank requirements. The sloshing pressures at the internal structures of DSME ACTIB (Aluminum Cargo Tank Independent type B) LNG cargo tank are predicted based on scaled sloshing model tests to calculate fatigue damage for the internal structures of the tank. The chaotic nature of the sloshing causes difficulties in the conventional spectral fatigue analysis method for the fatigue analysis of internal structures of the LNG tanks. In this thesis, an experimental investigation of the load effects due to sloshing impact on the fatigue analysis of an independent type B LNG tank, DSME ACTIB, is carried out. A scaled model tests with 2D tank including internal structured are performed to predict the long-term responses of sloshing pressures near the internal structure at each cell of designated wave scatter diagram, IACS 34 North Atlantic wave scatter diagram. A schematic procedure for fatigue assessment of independent type B LNG tank based on sloshing model test is proposed, and applied to fatigue assessment of LNG tank of a 210k FLNG. Finally, integrity of the internal structure member of an independent type B LNG tank against fatigue due to sloshing impact is to be verified.최근의 천연가스에 대한 수요 증가는 해저 천연가스 개발을 촉진하는 계기가 되고 있다. 하지만 많은 수의 해저유전은 육상 플랜트 등의 기반시설이나 해저 파이프라인로부터 멀리 떨어진 해역에 위치하고 있다. 이로 인해 해상에서 천연가스의 생산, 저장 및 하역을 위한 새로운 형태의 해양구조물인 FLNG가 제안되었다. FLNG의 개발을 위한 많은 연구가 이루어 지고 있으며, 이 결과로 FLNG는 해저천연가스 개발을 위한 적절한 방안으로 평가되고 있다. FLNG와 관련된 주요 유체역학적 기술은 1) 하역작업을 위한 FLNG와 LNG운반선으로 구성되는 다물체 시스템의 거동, 2) FLNG 화물창내의 슬로싱 및 관련 응답 및 3) FLNG와 계류시스템간의 연성운동 등으로 구분할 수 있다. 슬로싱문제는 FLNG에서 생산된 천연가스를 액화천연가스의 형태로 보관하는 화물창의 형태 및 구조를 결정하기 위한 중요한 인자이다. FLNG는 해상에 설치된 상태로 천연가스를 생산하여 액화천연가스 상태로 화물창에 저장하고, 저장된 액화천연가스를 파이프라인 또는 LNG 운반선을 통하여 하역하는 작업을 반복하게 된다. 이로 인해 FLNG의 화물창에는 액화천연가스가 부분적으로 적재 되는 상태가 반복으로 발생하며, 이때 화물창의 벽면에는 슬로싱에 따른 충격하중이 발생할 수 있다. FLNG의 부분적재 특징에 의해 FLNG에 적용되는 LNG 화물창의 형태는 IMO B형 형태의 독립형 탱크가 선호되고 있다. 일반적으로 B형 독립형 탱크는 슬로싱 하중에 따른 구조강도 측면의 문제는 없다고 인식되고 있다. 그러나 FLNG에 설치되는 탱크의 크기가 대형임에 따라 슬로싱 하중에 의한 피로강도는 의문으로 제기되고 있다. 본 논문에서는 FLNG에 적용되는 IMO B형 독립형 탱크의 피로강도에 대한 슬로싱 하중의 영향을 실험적으로 규명하는 것을 목표로 한다. 슬로싱 현상은 외력의 크기에 선형적으로 비례하지 않는 비선형 특징을 가지고 있으며, 이로 인해 종래의 스펙트럴 피로해석 방법을 직접 적용하기가 용이하지 않다. 본 연구에서는 슬로싱 하중에 의한 국부구조의 누적피로손상을 실험적으로 평가하고, 이로부터 응력분포함수를 직접 구하여 화물창 내부 구조부재의 피로강도를 평가하는 방법을 제안한다. 제안된 방법에 따라 IMO B형 독립탱크를 적용한 210k FLNG의 화물창 내부 구조부재에 대한 피로강도 평가를 수행하였다.Docto

Deep learning models to predict the editing efficiencies and outcomes of diverse base editors

Applications of base editing are frequently restricted by the requirement for a protospacer adjacent motif (PAM), and selecting the optimal base editor (BE) and single-guide RNA pair (sgRNA) for a given target can be difficult. To select for BEs and sgRNAs without extensive experimental work, we systematically compared the editing windows, outcomes and preferred motifs for seven BEs, including two cytosine BEs, two adenine BEs and three C•G to G•C BEs at thousands of target sequences. We also evaluated nine Cas9 variants that recognize different PAM sequences and developed a deep learning model, DeepCas9variants, for predicting which variants function most efficiently at sites with a given target sequence. We then develop a computational model, DeepBE, that predicts editing efficiencies and outcomes of 63 BEs that were generated by incorporating nine Cas9 variants as nickase domains into the seven BE variants. The predicted median efficiencies of BEs with DeepBE-based design were 2.9- to 20-fold higher than those of rationally designed SpCas9-containing BEs.restrictio

Deep learning improves prediction of CRISPR-Cpf1 guide RNA activity

We present two algorithms to predict the activity of AsCpf1 guide RNAs. Indel frequencies for 15,000 target sequences were used in a deep-learning framework based on a convolutional neural network to train Seq-deepCpf1. We then incorporated chromatin accessibility information to create the better-performing DeepCpf1 algorithm for cell lines for which such information is available and show that both algorithms outperform previous machine learning algorithms on our own and published data sets.restrictio

Sequence-specific prediction of the efficiencies of adenine and cytosine base editors

Base editors, including adenine base editors (ABEs)1 and cytosine base editors (CBEs)2,3, are widely used to induce point mutations. However, determining whether a specific nucleotide in its genomic context can be edited requires time-consuming experiments. Furthermore, when the editable window contains multiple target nucleotides, various genotypic products can be generated. To develop computational tools to predict base-editing efficiency and outcome product frequencies, we first evaluated the efficiencies of an ABE and a CBE and the outcome product frequencies at 13,504 and 14,157 target sequences, respectively, in human cells. We found that there were only modest asymmetric correlations between the activities of the base editors and Cas9 at the same targets. Using deep-learning-based computational modeling, we built tools to predict the efficiencies and outcome frequencies of ABE- and CBE-directed editing at any target sequence, with Pearson correlations ranging from 0.50 to 0.95. These tools and results will facilitate modeling and therapeutic correction of genetic diseases by base editing.restrictio