The CRISPR/Cas9 revolution continues: from base editing to prime editing in plant science

Author(s):  
Yan Li ◽  
Wenjing Li ◽  
Jun Li
Keyword(s):  
HortScience ◽  
1998 ◽  
Vol 33 (3) ◽  
pp. 504e-504
Author(s):  
Erika Szendrak ◽  
Paul E. Read ◽  
Jon S. Miller

Modern aspects of many subjects (e.g., computer science and some aspects of medical science) are now taught in many high schools, but the plant sciences are often given short shrift. A collaboration was therefore established with a high school biology program in which pilot workshops could be developed to enable advanced students to gain insights into modern plant science techniques. A successful example is the workshop on plant biotechnology presented in this report. This workshop is simple and flexible, taking into account that most high school biology laboratories and classrooms are not set up for sophisticated plant science/biotechnology projects. It is suitable for from 10 to 30 students, depending upon space and facilities available. Students work in pairs or trios, and learn simple disinfestation and transfer techniques for micropropagation and potential subsequent transformation treatments. Students gain insights into: sterile technique and hygiene; plant hormones and their physiological effects; plant cell, tissue and organ culture; the influence of environmental factors on response of cells and tissues cultured in vitro; and an understanding of the phenomenon of organogenesis and resulting plant growth and development. This workshop has been tested on several classes of students and following analysis, several refinements were included in subsequent iterations. Results of the students' experiments have been positive and instructive, with student learning outcomes above expectations. Further details of the workshop techniques and approach will be presented.


Genes ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 283
Author(s):  
Eyal Seroussi

Determination of the relative copy numbers of mixed molecular species in nucleic acid samples is often the objective of biological experiments, including Single-Nucleotide Polymorphism (SNP), indel and gene copy-number characterization, and quantification of CRISPR-Cas9 base editing, cytosine methylation, and RNA editing. Standard dye-terminator chromatograms are a widely accessible, cost-effective information source from which copy-number proportions can be inferred. However, the rate of incorporation of dye terminators is dependent on the dye type, the adjacent sequence string, and the secondary structure of the sequenced strand. These variable rates complicate inferences and have driven scientists to resort to complex and costly quantification methods. Because these complex methods introduce their own biases, researchers are rethinking whether rectifying distortions in sequencing trace files and using direct sequencing for quantification will enable comparable accurate assessment. Indeed, recent developments in software tools (e.g., TIDE, ICE, EditR, BEEP and BEAT) indicate that quantification based on direct Sanger sequencing is gaining in scientific acceptance. This commentary reviews the common obstacles in quantification and the latest insights and developments relevant to estimating copy-number proportions based on direct Sanger sequencing, concluding that bidirectional sequencing and sophisticated base calling are the keys to identifying and avoiding sequence distortions.


Author(s):  
Salah Adlat ◽  
Farooq Hayel ◽  
Ping Yang ◽  
Yang Chen ◽  
Zin Mar Oo ◽  
...  

Viruses ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 1288
Author(s):  
Wendy Dong ◽  
Boris Kantor

CRISPR/Cas technology has revolutionized the fields of the genome- and epigenome-editing by supplying unparalleled control over genomic sequences and expression. Lentiviral vector (LV) systems are one of the main delivery vehicles for the CRISPR/Cas systems due to (i) its ability to carry bulky and complex transgenes and (ii) sustain robust and long-term expression in a broad range of dividing and non-dividing cells in vitro and in vivo. It is thus reasonable that substantial effort has been allocated towards the development of the improved and optimized LV systems for effective and accurate gene-to-cell transfer of CRISPR/Cas tools. The main effort on that end has been put towards the improvement and optimization of the vector’s expression, development of integrase-deficient lentiviral vector (IDLV), aiming to minimize the risk of oncogenicity, toxicity, and pathogenicity, and enhancing manufacturing protocols for clinical applications required large-scale production. In this review, we will devote attention to (i) the basic biology of lentiviruses, and (ii) recent advances in the development of safer and more efficient CRISPR/Cas vector systems towards their use in preclinical and clinical applications. In addition, we will discuss in detail the recent progress in the repurposing of CRISPR/Cas systems related to base-editing and prime-editing applications.


Plant Methods ◽  
2021 ◽  
Vol 17 (1) ◽  
Author(s):  
Shuo Zhou ◽  
Xiujuan Chai ◽  
Zixuan Yang ◽  
Hongwu Wang ◽  
Chenxue Yang ◽  
...  

Abstract Background Maize (Zea mays L.) is one of the most important food sources in the world and has been one of the main targets of plant genetics and phenotypic research for centuries. Observation and analysis of various morphological phenotypic traits during maize growth are essential for genetic and breeding study. The generally huge number of samples produce an enormous amount of high-resolution image data. While high throughput plant phenotyping platforms are increasingly used in maize breeding trials, there is a reasonable need for software tools that can automatically identify visual phenotypic features of maize plants and implement batch processing on image datasets. Results On the boundary between computer vision and plant science, we utilize advanced deep learning methods based on convolutional neural networks to empower the workflow of maize phenotyping analysis. This paper presents Maize-IAS (Maize Image Analysis Software), an integrated application supporting one-click analysis of maize phenotype, embedding multiple functions: (I) Projection, (II) Color Analysis, (III) Internode length, (IV) Height, (V) Stem Diameter and (VI) Leaves Counting. Taking the RGB image of maize as input, the software provides a user-friendly graphical interaction interface and rapid calculation of multiple important phenotypic characteristics, including leaf sheath points detection and leaves segmentation. In function Leaves Counting, the mean and standard deviation of difference between prediction and ground truth are 1.60 and 1.625. Conclusion The Maize-IAS is easy-to-use and demands neither professional knowledge of computer vision nor deep learning. All functions for batch processing are incorporated, enabling automated and labor-reduced tasks of recording, measurement and quantitative analysis of maize growth traits on a large dataset. We prove the efficiency and potential capability of our techniques and software to image-based plant research, which also demonstrates the feasibility and capability of AI technology implemented in agriculture and plant science.


Methods ◽  
2021 ◽  
Author(s):  
Jiajie Kuang ◽  
Qinghua Lyu ◽  
Jiao Wang ◽  
Yubo Cui ◽  
Jun Zhao
Keyword(s):  

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