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of TALEN and for Plant Genome Engineering
Abstract and Figures
Transcription activator-like effector (TALE) is a DNA-binding domain that can be paired with a nuclease to create DNA double-strand breaks, or with an effector protein to alter gene transcription. The ability to precisely alter plant genomes and transcriptomes has provided many insights into gene function and has recently been utilized for crop improvement. Easy design and construction of TALE make the tool more accessible to a variety of researchers. Here, we describe two TALE-based systems: transcription activator-like effector nucleases (TALEN), for creating targeted mutations in a gene of interest, and multiplex TALE activation (mTALE-Act), for activating one or a few genes of interest at the transcription level. Assembly of these tools is based on Golden Gate cloning and Gateway recombination, which are cost-effective and streamlined cloning methods.
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... TALEs are proteins secreted by the bacteria and help them to bind to sequences in the plant host genome (Richter, et al. 2020). The DNA binder domain has repeated 33-35 amino acid sequences, in which the 12th and 13th amino acids are called the Repeat Variable Diresidue (RVD), are highly variable, and able to recognize a nucleotide (Malzahn and Qi 2021). Unlike ZFN, this method is made easily and quickly for any DNA sequence, produces more specific targeting, and has much less cytotoxicity. ...
... In this method, transcription activator-like effectors (TALEs) are fused to a DNA scissor (Fok1) located in a spacer region, which facilitates genetic engineering. On TALEs, there are highly variable positions that act as guides to identify target nucleotides for binding [11]. The DNA-binding domain of TALEs comprises monomers capable of binding to nucleotides in the target sequence. ...
Efficient precision genome editing requires a quick, quantitative, and inexpensive assay of editing outcomes. Here we present ICE (Inference of C RISPR E dits), which enables robust analysis of CRISPR edits using Sanger data. ICE proposes potential outcomes for editing with guide RNAs (gRNAs) and then determines which are supported by the data via regression. Additionally, we develop a score called ICE-D (Discordance) that can provide information on large or unexpected edits. We empirically confirm through over 1,800 edits that the ICE algorithm is robust, reproducible, and can analyze CRISPR experiments within days after transfection. We also confirm that ICE strongly correlates with next-generation sequencing of amplicons (Amp-Seq). The ICE tool is free to use and offers several improvements over current analysis tools. For instance, ICE can analyze individual experiments as well as multiple experiments simultaneously (batch analysis). ICE can also detect a wider variety of outcomes, including multi-guide edits (multiple gRNAs per target) and edits resulting from homology-directed repair (HDR), such as knock-ins and base edits. ICE is a reliable analysis tool that can significantly expedite CRISPR editing workflows. It is available online at ice.synthego.com , and the source code is at github.com/synthego-open/ice
Genome editing via the homology-directed repair (HDR) pathway in somatic plant cells is very inefficient compared to error-prone repair by nonhomologous end joining (NHEJ). Here, we increased HDR-based genome editing efficiency approximately 3-fold compared to a Cas9-based single-replicon system via the use of de novo multi-replicon systems equipped with CRISPR/LbCpf1 in tomato and obtained replicon-free but stable HDR alleles. The efficiency of CRISPR/LbCpf1-based HDR was significantly modulated by physical culture conditions such as temperature and light. Ten days of incubation at 31°C under a light/dark cycle after Agrobacterium-mediated transformation resulted in the best performance among the tested conditions. Furthermore, we developed our single-replicon system into a multi-replicon system that effectively increased HDR efficiency. Although this approach is still challenging, we showed the feasibility of HDR-based genome editing of a salt-tolerant SlHKT1;2 allele without genomic integration of antibiotic markers or any phenotypic selection. Self-pollinated offspring plants carrying the HKT1;2 HDR allele showed stable inheritance and germination tolerance in the presence of 100 mM NaCl. Our work may pave the way for transgene-free editing of alleles of interest in asexually as well as sexually reproducing plants.
Data normalization is vital to single-cell sequencing, addressing limitations presented by low input material and various forms of bias or noise present in the sequencing process. Several such normalization methods exist, some of which rely on spike-in genes, molecules added in known quantities to serve as a basis for a normalization model. Depending on available information and the type of data, some methods may express certain advantages over others. We compare the effectiveness of seven available normalization methods designed specifically for single-cell sequencing using two real data sets containing spike-in genes and one simulation study. Additionally, we test those methods not dependent on spike-in genes using a real data set with three distinct cell-cycle states and a real data set under the 10X Genomics GemCode platform with multiple cell types represented. We demonstrate the differences in effectiveness for the featured methods using visualization and classification assessment and conclude which methods are preferable for normalizing a certain type of data for further downstream analysis, such as classification or differential analysis. The comparison in computational time for all methods is addressed as well.
The evaluation of soil tillage quality parameters, such as cloddiness and surface roughness produced by tillage tools, is based on traditional methods ranging, respectively, from manual or mechanical sieving of ground samples to handheld rulers, non-contact devices or Precision Agriculture technics, such as laser profile meters. The aim of the study was to compare traditional methods of soil roughness and cloddiness assessment (laser profile meter and manual sieving), with light drone RGB 3D imaging techniques for the evaluation of different tillage methods (ploughed, harrowed and grassed). Light drone application was able to replicate the results obtained by the traditional methods, introducing advantages in terms of time, repeatability and analysed surface while reducing the human error during the data collection on the one hand and allowing a labour-intensive field monitoring solution for digital farming on the other. Indeed, the profilometer positioning introduces errors and may lead to false reading due to limited data collection. Future work could be done in order to streamline the data processing operation and so to produce a practical application ready to use and stimulate the adoption of new evaluation indices of soil cloddiness, such as Entropy and the Angular Second Moment (ASM), which seem more suitable than the classic ones to achieved data referred to more extended surfaces.
Background: Efficient organogenesis induction in eggplant (Solanum melongena L.) is required for multiple in vitro culture
applications. In this work, we aimed at developing a universal protocol for efficient in vitro regeneration of eggplant mainly
based on the use of zeatin riboside (ZR). We evaluated the effect of seven combinations of ZR with indoleacetic acid (IAA) for
organogenic regeneration in five genetically diverse S. melongena and one S. insanum L. accessions using two photoperiod
conditions. In addition, the effect of six different concentrations of indolebutyric acid (IBA) in order to promote rooting was
assessed to facilitate subsequent acclimatization of plants. The ploidy level of regenerated plants was studied.
Results: In a first experiment with accessions MEL1 and MEL3, significant (p < 0.05) differences were observed for the
four factors evaluated for organogenesis from cotyledon, hypocotyl and leaf explants, with the best results obtained (9
and 11 shoots for MEL1 and MEL3, respectively) using cotyledon tissue, 16 h light / 8 h dark photoperiod conditions,
and medium E6 (2 mg/L of ZR and 0 mg/L of IAA). The best combination of conditions was tested in the other four
accessions and confirmed its high regeneration efficiency per explant when using both cotyledon and hypocotyl
tissues. The best rooting media was R2 (1 mg/L IBA). The analysis of ploidy level revealed that between 25 and 50% of
the regenerated plantlets were tetraploid.
Conclusions: An efficient protocol for organogenesis of both cultivated and wild accessions of eggplant, based on the
use of ZR, is proposed. The universal protocol developed may be useful for fostering in vitro culture applications in
eggplant requiring regeneration of plants and, in addition, allows developing tetraploid plants without the need of
antimitotic chemicals.
Plant function is the result of the concerted action of single cells in different tissues. Advances in RNA-seq technologies and tissue processing allow us now to capture transcriptional changes at single-cell resolution. The incredible potential of single-cell RNA-seq lies in the novel ability to study and exploit regulatory processes in complex tissues based on the behaviour of single cells. Importantly, the independence from reporter lines allows the analysis of any given tissue in any plant. While there are challenges associated with the handling and analysis of complex datasets, the opportunities are unique to generate knowledge of tissue functions in unprecedented detail and to facilitate the application of such information by mapping cellular functions and interactions in a plant cell atlas.
Quantifying plant water content and nitrogen levels and determining water and nitrogen phenotypes is important for crop management and achieving optimal yield and quality. Hyperspectral methods have the potential to advance high throughput phenotyping efforts by providing a rapid, accurate, and nondestructive alternative for estimating biochemical and physiological plant traits. Our study (i) acquired hyperspectral images of wheat plants using a high throughput phenotyping system, (ii) developed regression models capable of predicting water and nitrogen levels of wheat plants, and (iii) applied the regression coefficients from the best-performing models to hyperspectral images in order to develop prediction maps to visualize nitrogen and water distribution within plants. Hyperspectral images were collected of four wheat (Triticum aestivum) genotypes grown in nine soil nutrient conditions and under two water treatments. Five multivariate regression methods in combination with 10 spectral preprocessing techniques were employed to find a model with strong predictive performance. Visible and near infrared wavelengths (VNIR: 400–1,000nm) alone were not sufficient to accurately predict water and nitrogen content (validation R² = 0.56 and R² = 0.59, respectively) but model accuracy was improved when shortwave-infrared wavelengths (SWIR: 1,000–2,500nm) were incorporated (validation R² = 0.63 and R² = 0.66, respectively). Wavelength reduction produced equivalent model accuracies while reducing model size and complexity (validation R² = 0.69 and R² = 0.66 for water and nitrogen, respectively). Developed distribution maps provided a visual representation of the concentration and distribution of water within plants while nitrogen maps seemed to suffer from noise. The findings and methods from this study demonstrate the high potential of high-throughput hyperspectral imagery for estimating and visualizing the distribution of plant chemical properties.
RNA-seq and single-cell genomic research emerge as an important research area in the recent years due to its ability to examine genetic information of any number of single cells in all living organisms. The knowledge gained from RNA-seq and single-cell genomic research will have a great impact in many aspects of plant biology. In this review, we summary and discuss the biological significance of RNA-seq and single-cell genomic research in plants including the single-cell DNA-sequencing, RNA-seq and single-cell RNA sequencing in woody plants, methods of RNA-seq and single-cell RNA-sequencing, single-cell RNA-sequencing for studying plant development, and single-cell RNA-sequencing for elucidating cell type composition. We will focus on RNA-seq and single-cell RNA sequencing in woody plants, understanding of plant development through single-cell RNA-sequencing, and elucidation of cell type composition via single-cell RNA-sequencing. Information presented in this review will be helpful to increase our understanding of plant genomic research in a way with the power of plant single-cell RNA-sequencing analysis.
Herbal products, such as dietary supplements, have become a subject of increasing global importance for their health benefits and economic considerations. However, they have also been targets of adulteration practices, being the accurate identification of botanicals in herbal products of utmost importance to protect the health and expectations of consumers. Particularly, in the case of dietary supplements, which can have different types of formulations, the identification of plant material used in their production is often a research challenge. DNA‐based techniques have played a crucial role on the development of a wide range of tools for the authentication of herbal products. Therefore, this review intends to describe their main progresses, critically discussing their advantages and drawbacks when applied to authenticate herbal products, focusing on dietary supplements. DNA barcoding is particularly emphasized because it has provided the highest number of applications, followed by the advances on high‐resolution melting analysis combined with DNA barcodes. A special emphasis is also given to the promising approaches relying on DNA metabarcoding and isothermal amplification.
Nowadays precision agriculture is undertaking a steep growth in terms of both, commercial products and research and development applications. This is rapidly changing the crop management system taking into grater consideration data acquisition and their elaboration, real-time or offline, to correctly consider the spatial and temporal variability of crop and soil factors. This step is due to reduce the energy inputs and the applications of chemicals and fertilizers, as well as Greenhouse gas (GHGs), while increasing the production. Sustainability is a must while trying to fulfil the food and fiber needs of the rapidly growing human population. In this light, the present review, more than reporting an exhaustive picture, aims attempt to show a clear panorama of such a context underlining the principal scientific researches and applications inherent optoelectronic proximal sensing vehicle-mounted technologies in precision agriculture. The review has been structured following the main sensors types and their core applications: grayscale/RGB imaging, Visible-Near infrared (Vis-NIR) and NIR, sensors dedicated to Normalized Difference Vegetation Index (NDVI) and Normalized Difference Red Edge index (NDRE), stereovision, thermography, combined sensors, sensors dedicated to phenotyping and others. Moreover, were considered two separate chapters regarding dedicated analytical approaches use and development and a term map analysis to graphically highlight the main clusters owing each to a specific subject area.