| Literature DB >> 36235491 |
Mohd Fadhli Hamdan1, Chou Khai Soong Karlson1, Ee Yang Teoh1, Su-Ee Lau1,2, Boon Chin Tan1.
Abstract
Climate change poses a serious threat to global agricultural activity and food production. Plant genome editing technologies have been widely used to develop crop varieties with superior qualities or can tolerate adverse environmental conditions. Unlike conventional breeding techniques (e.g., selective breeding and mutation breeding), modern genome editing tools offer more targeted and specific alterations of the plant genome and could significantly speed up the progress of developing crops with desired traits, such as higher yield and/or stronger resilience to the changing environment. In this review, we discuss the current development and future applications of genome editing technologies in mitigating the impacts of biotic and abiotic stresses on agriculture. We focus specifically on the CRISPR/Cas system, which has been the center of attention in the last few years as a revolutionary genome-editing tool in various species. We also conducted a bibliographic analysis on CRISPR-related papers published from 2012 to 2021 (10 years) to identify trends and potential in the CRISPR/Cas-related plant research. In addition, this review article outlines the current shortcomings and challenges of employing genome editing technologies in agriculture with notes on future prospective. We believe combining conventional and more innovative technologies in agriculture would be the key to optimizing crop improvement beyond the limitations of traditional agricultural practices.Entities:
Keywords: CRISPR; biotechnology; climate change; crop improvement; genome editing
Year: 2022 PMID: 36235491 PMCID: PMC9573444 DOI: 10.3390/plants11192625
Source DB: PubMed Journal: Plants (Basel) ISSN: 2223-7747
Figure 1Different types of sequence-specific nucleases and types of editing. (A) Meganucleases, zinc finger nuclease (ZFN), transcription activator-like effector nuclease (TALEN), and CRISPR/Cas9 induces double-stranded breaks, which were corrected by non-homologous end-joining (NHEJ) and homologous recombination (HR). (B) Schematic diagram of target insertion, target deletion, and chromosomal arrangement through genome editing technologies. InDel, insertion-deletion.
Figure 2General procedures in plant transformation, delivery methods of CRISPR cargo, and transgene-free mutant development. (A) Major steps in plant genome editing. Once transformation vectors are designed and constructed, their activity may be validated with protoplasts before being delivered into the host plant. Protoplast transformation can also be used directly to produce transformed cells and eventually plants as described in panel D. The general procedure of transformation also usually followed by a selection process to select resistant cells and seedlings, and finally a sequencing process to confirm presence of transformed mutants. (B) Plant genome editing via Agrobacterium-mediated delivery of CRISPR DNA. Agrobacterium containing the vectors are transfected into plant cells in the form of calli, embryos, or leaf explants, followed by the selection process to produce genome-edited plants (C) Conventional and transient expression approaches for particle bombardment-mediated genome editing via CRISPR DNA, RNA, or RNP delivery. Transformation vectors-coated gold particles are bombarded into plant cells followed by the selection process (D) Protoplast transformation with CRISPR DNA, RNA, or RNP. Transformation vectors, protoplasts, PEG, and Ca2+ ions are mixed before further selection processes to isolate transformed calli, seedlings, and finally genome-edited plants. (E) Two ways to obtain transgene-free mutants. Using the conventional method, a selection agent is used to select resistant calli and transgenic plants. Transformation vectors can be segregated out from the mutant genomes via selfing or crossing. Using the transient method, no selection agent is needed to segregate out the transformation vectors to produce transgene-free mutants. [RNP, ribonucleotide protein].
Examples of CRISPR/Cas9 applications for crop improvement.
| Improvement | Trait | Crop | sgRNA Target Area | Type of Editing | Target Area | Result | References |
|---|---|---|---|---|---|---|---|
| Abiotic stress resistance | Drought | Chickpea | cDNA | Frameshift deletion | Enhanced tolerance | [ | |
| Cold | Rice | cDNA | InDel mutation |
| Improved tolerance | [ | |
| Herbicide | Maize | cDNA | Base editing |
| Plants with Sulfonylurea herbicide-resistant | [ | |
| Salinity | Tomato | DBD domain of cDNA | 49-bp deletion |
| Enhanced salinity tolerance | [ | |
| Heavy metals | Rice | cDNA | Downregulation |
| Decreased cadmium accumulation | [ | |
| Heat | Tomato | cDNA | 1-bp insertion |
| Enhanced heat tolerance | [ | |
| Biotic stress resistance | Viral disease | Barley | Coding sequence | Base editing | MP, CP, Rep/Rep, IR/Virus genome | Resistant plants | [ |
| Fungal disease | Rice | Genome | 80-bp insert | ALB1, RSY1/ Fungal gene | Improved resistance to rice blast | [ | |
| Bacterial disease | Tomato | JAS domain C-terminal | Deletion | Resistant plants | [ | ||
| Insect pest | Soybean | Coding region | 1-bp and 33-bp deletion |
| Enhanced resistance to | [ | |
| Plant/crop quality | Crop growth | Rice | cDNA | Frameshift | Improved plant growth and grain productivity | [ | |
| Crop yield | Wheat | cDNA | 10-bp deletion | Improved grain yield | [ | ||
| Crop nutrition | Rice | Genomic Safe Harbor | 5.2kb insertion | 5.2 kb carotenoid cassette insertion | Increased β-carotene content | [ | |
| Grain size | Rice | cDNA | InDel mutation |
| Increased grain size | [ | |
| Grain number | Rice | cDNA | InDel mutation |
| Increased grain number | [ | |
| Fruit size | Tomato | Promoter | 85-bp deletion |
| Enhanced fruit size | [ |
Figure 3Co-occurrence network of 50 most used keywords in CRISPR-related plant research from 2012 to 2021. (A) Network visualization of the keywords based on total link strength. Green, yellow, red, and blue nodes represent four different clusters of keywords identified. A minimum strength of 40 was set for the lines to appear between the nodes. The relatedness of the keywords depends on the number of articles in which they occur together, which is indicated by the size of the nodes/keywords, and the length/thickness of the lines between the nodes. The bigger the nodes/keywords, the larger the weight of the nodes/keywords. The shorter and thicker the lines between the nodes, the more frequently they appear together in the publications. (B) Density visualization of the keywords based on occurrences. The density of a keyword depends on the number of keywords around the node. Keywords in the yellow areas indicate a more frequent occurrence in the publications while green areas indicate a less frequent appearance.
A list of 50 most frequently occurring keywords in CRISPR-related plant research publications from 2012 to 2021. The ranking is based on the number of occurrences in the publications. Total link strength indicates the number of publications in which two keywords occur together.
| Rank | Keyword | Occurrences | Total Link Strength | Rank | Keyword | Occurrences | Total Link Strength |
|---|---|---|---|---|---|---|---|
| 1 | crispr | 2386 | 6260 | 26 | chloroplast | 146 | 384 |
| 2 | CRISPR/Cas9 | 821 | 1873 | 27 | plasmid | 146 | 499 |
| 3 | plant protein | 769 | 2385 | 28 | crispr/cas | 144 | 267 |
| 4 | arabidopsis | 673 | 2111 | 29 | transgene | 141 | 542 |
| 5 | human | 535 | 1629 | 30 | protoplast | 140 | 494 |
| 6 | crop | 531 | 1450 | 31 | soybean | 134 | 453 |
| 7 | rice | 525 | 1462 | 32 | enzyme | 128 | 437 |
| 8 | gene | 514 | 1677 | 33 | flower | 124 | 427 |
| 9 | plant | 512 | 1597 | 34 | quantitative trait locus | 123 | 405 |
| 10 | animal | 409 | 1287 | 35 | transcription activator like effector nuclease | 117 | 494 |
| 11 | plant disease | 335 | 991 | 36 | chromosome | 110 | 376 |
| 12 | transcription factor | 292 | 1008 | 37 | microrna | 110 | 387 |
| 13 | agrobacterium | 282 | 1026 | 38 | mitochondrion | 108 | 285 |
| 14 | protein | 262 | 938 | 39 | double stranded dna break | 105 | 440 |
| 15 | tomato | 239 | 772 | 40 | plant cell | 105 | 375 |
| 16 | wheat | 224 | 690 | 41 | bacterial protein | 99 | 414 |
| 17 | plant leaf | 220 | 814 | 42 | plant virus | 96 | 310 |
| 18 | maize | 213 | 742 | 43 | fungus | 91 | 314 |
| 19 | allele | 195 | 708 | 44 | drought | 76 | 211 |
| 20 | esterase | 193 | 398 | 45 | intron | 75 | 156 |
| 21 | tobacco | 192 | 699 | 46 | host pathogen interaction | 72 | 267 |
| 22 | bacterium | 181 | 625 | 47 | cas | 70 | 292 |
| 23 | site-directed mutagenesis | 170 | 630 | 48 | mouse | 60 | 215 |
| 24 | endonuclease | 155 | 687 | 49 | fatty acid | 54 | 159 |
| 25 | plant root | 152 | 498 | 50 | recombinant protein | 53 | 192 |