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Plant Molecular Breeding and Resistance: Phenomics, Genomics and Gene Editing

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A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Plant Sciences".

Deadline for manuscript submissions: closed (20 August 2024) | Viewed by 9256

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Special Issue Editor

Dr. Yong Suk Chung

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Guest Editor

Department of Plant Resouces and Environment, Jeju National University, Jeju 63243, Republic of Korea
Interests: phenomics; precision agriculture; plant breeding; smart farm; germplasm enhancement
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are pleased to announce a Special Issue in the International Journal of Molecular Sciences focusing on cutting-edge research and advancements in the field of plant breeding and resistance, specifically highlighting the revolutionary methodologies of phenomics, genomics, and gene editing.

This Special Issue aims to provide a comprehensive platform for researchers, scientists, and experts from around the world to share their groundbreaking research, innovative methodologies, and insightful findings. The Special Issue will encompass a wide range of topics related to phenomics, genomics, and gene editing as applied in plant breeding and resistance.

The scope of this Special Issue includes, but is not limited to, the following topics:

Phenomic approaches for high-throughput plant phenotyping;
Genomic tools and technologies for plant genome analysis and characterization;
Gene editing techniques (CRISPR/Cas9, TALENs, etc.) and their applications in plant improvement and disease resistance;
Molecular mechanisms underlying plant resistance to biotic and abiotic stresses;
Genetic variation and diversity studies in crop species for improved resilience;
Integrative omics approaches in elucidating plant-pathogen interactions;
Computational modeling and artificial intelligence in phenomics and genomics research.

Dr. Yong Suk Chung
Guest Editor

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Keywords

plant phenomics
high-throughput phenotyping
plant cells
plant genomics
plant genetics
gene editing
crop breeding
CRISPR/Cas9
abiotic stress
plant resistance
saline and alkali resistance
drought tolerance
genomics
resistance

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Published Papers (7 papers)

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10 pages, 256 KiB

Open AccessCommunication

Investigation of 2,4-Dihydroxylaryl-Substituted Heterocycles as Inhibitors of the Growth and Development of Biotrophic Fungal Pathogens Associated with the Most Common Cereal Diseases

by Klaudia Rząd, Aleksandra Nucia, Weronika Grzelak, Joanna Matysiak, Krzysztof Kowalczyk, Sylwia Okoń and Arkadiusz Matwijczuk

Int. J. Mol. Sci. 2024, 25(15), 8262; https://doi.org/10.3390/ijms25158262 - 29 Jul 2024

Viewed by 442

Abstract

Climate change forces agriculture to face the rapidly growing virulence of biotrophic fungal pathogens, which in turn drives researchers to seek new ways of combatting or limiting the spread of diseases caused by the same. While the use of agrochemicals may be the most efficient strategy in this context, it is important to ensure that such chemicals are safe for the natural environment. Heterocyclic compounds have enormous biological potential. A series of heterocyclic scaffolds (1,3,4-thiadiazole, 1,3-thiazole, 1,2,4-triazole, benzothiazine, benzothiadiazine, and quinazoline) containing 2,4-dihydroxylaryl substituents were investigated for their ability to inhibit the growth and development of biotrophic fungal pathogens associated with several important cereal diseases. Of the 33 analysed compounds, 3 were identified as having high inhibitory potential against Blumeria and Puccinia fungi. The conducted research indicated that the analysed compounds can be used to reduce the incidence of fungal diseases in cereals; however, further thorough research is required to investigate their effects on plant–pathogen systems, including molecular studies to determine the exact mechanism of their activity. Full article

(This article belongs to the Special Issue Plant Molecular Breeding and Resistance: Phenomics, Genomics and Gene Editing)

15 pages, 4763 KiB

Open AccessArticle

PpGATA21 Enhances the Expression of PpGA2ox7 to Regulate the Mechanism of Cerasus humilis Rootstock-Mediated Dwarf in Peach Trees

by Xiuzhen Li, Ruxin Wang, Yuman Wang, Xueqiang Li, Qiaofang Shi and Yihe Yu

Int. J. Mol. Sci. 2024, 25(13), 7402; https://doi.org/10.3390/ijms25137402 - 5 Jul 2024

Viewed by 599

Abstract

Dwarfing rootstocks enhance planting density, lower tree height, and reduce both labor in peach production. Cerasus humilis is distinguished by its dwarf stature, rapid growth, and robust fruiting capabilities, presenting substantial potential for further development. In this study, Ruipan 4 was used as the scion and grafted onto Amygdalus persica and Cerasus humilis, respectively. The results indicate that compared to grafting combination R/M (Ruipan 4/Amygdalus persica), grafting combination R/O (Ruipan 4/Cerasus humilis) plants show a significant reduction in height and a significant increase in flower buds. RNA-seq indicates that genes related to gibberellin (GA) and auxin metabolism are involved in the dwarfing process of scions mediated by C. humilis. The expression levels of the GA metabolism-related gene PpGA2ox7 significantly increased in R/O and are strongly correlated with plant height, branch length, and internode length. Furthermore, GA levels were significantly reduced in R/O. The transcription factor PpGATA21 was identified through yeast one-hybrid screening of the PpGA2ox7 promoter. Yeast one-hybrid (Y1H) and dual-luciferase reporter (DLR) demonstrate that PpGATA21 can bind to the promoter of PpGA2ox7 and activate its expression. Overall, PpGATA21 activates the expression of the GA-related gene PpGA2ox7, resulting in reduced GA levels and consequent dwarfing of plants mediated by C. humilis. This study provides new insights into the mechanisms of C. humilis and offers a scientific foundation for the dwarfing and high-density cultivation of peach trees. Full article

(This article belongs to the Special Issue Plant Molecular Breeding and Resistance: Phenomics, Genomics and Gene Editing)

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Figure 1

Figure 1
(A) Phenotypic comparison between R/M and R/O. (B) Branch phenotype of R/M and R/O. (C) Plant height, (D) branch length, (E) internode length, and (F) number of flower buds of R/M and R/O. The statistical significance of mean differences was evaluated using Student’s t-test, with significance levels denoted as ** p < 0.01. Full article ">Figure 2
(A) PCA of the transcriptomes of R/O and R/M. (B) Statistical analysis of the number of DEGs between R/O and R/M. (C) GO enrichment analysis. The p-values are represented on the x-axis, while the GO terms are shown on the y-axis, and the size of each circle indicates the number of genes. The top 16 enriched GO terms are displayed in descending order of significance based on their p-values. The size of each circle represents the number of genes associated with the GO term, while the color of the circle reflects the p-values. (D) KEGG enrichment analysis. The p-values are represented on the x-axis, while the KEGG pathways are shown on the y-axis, and the size of each circle indicates the number of genes. The enriched KEGG terms are shown in the order of p-values. Full article ">Figure 3
(A) WGCN heatmap showing correlations between traits and genes within modules. Each row represents a module, and each column corresponds to a specific trait. The correlation coefficients between modules and traits are denoted by the colors and text within the cells at the intersections (indicating p-values). Positive correlations are shown in red while negative correlations are shown in blue. (B) Venn diagram illustrating the overlap of 377 genes between the MEcyan module and DEGs. (C) Analysis of the expression patterns of 377 hormone-related differentially expressed genes in R/O and R/M. Full article ">Figure 4
(A) GA biosynthesis pathway. The third stage of GA biosynthesis follows a distinct metabolic pathway, starting with GA12 or its isomer GA53, which then diverges into two separate pathways. GA12 and GA53 are oxidized to produce inactive intermediates GA9 and GA20, as well as biologically active GAs such as GA1, GA3, GA4, and GA7. Ultimately, GA1 and GA4 are converted into the inactive forms GA8 and GA34, respectively. Red represents bioactive GAs and blue represents inactive GAs. Content of (B) GA7, (C) GA3, (D) GA4, (E) GA1, (F) GA34, and (G) GA8 in R/O and R/M. The statistical significance of mean differences was evaluated using Student’s t-test, with significance levels denoted as ** p < 0.01 and ns (no significance) p > 0.05. Full article ">Figure 5
(A) Analysis of PpGA2ox7 gene expression patterns in R/O and R/M. (B) GUS used as a negative control and 35S::GUS as a positive control to validate the activity of the PpGA2ox7 promoter. (C) PpGATA21 protein directly binds to the PpGA2ox7 promoter, cloned into the pABAi vector. An empty pGADT7 vector is used as a negative control, and the interaction is validated through the growth of transformed yeast on SD/-Leu/AbA100 medium. (D) Schematic of PpGATA21 effector vector and LUC reporter vector (top), and results of the dual-luciferase assay analyzed using the LUC/REN ratio (bottom), data presented as mean (±SE). The statistical significance of mean differences was evaluated using Student’s t-test, with significance levels denoted as ** p < 0.01. (E) Representative dual-luciferase images, control LUC/REN ratio normalized to 1 (n = 6). Full article ">Figure 6
(A) Analysis of PpGATA21 gene expression patterns in R/O and R/M. (B) Subcellular localization of PpGATA21 in N. benthamiana leaf cells, using pBI221-GFP as the empty vector control. mCherry served as the nuclei localization marker. The signals of bright field, GFP and mCherry were detected. Merged images show colocalization of GFP and mCherry signals. (C) Transcriptional activation of PpGATA21 in yeast cells demonstrated by growth on SD/-Trp-His + 3AT medium; pGBKT7/GAL4 used as the positive control and pGBKT7 empty vector as the negative control. (D) Schematic of the PpGATA21 effector vector and LUC reporter vector (top), with dual-luciferase assay results showing the transcriptional activation activity of the PpGATA21 transcription factor (bottom). Analysis based on the LUC/REN ratio. Data presented as mean (±SE). The statistical significance of mean differences was evaluated using Student’s t-test, with significance levels denoted as ** p < 0.01. Full article ">Figure 7
Functional model of the PpGATA21-PpGA2ox7 regulatory module in the dwarfing of peach trees mediated by C. humilis. On the left, when grafted onto A. persica rootstocks, the GA content in peach trees does not change, leading to increased plant height as the dwarfing pathway mediated by the PpGATA21-PpGA2ox7 module is not activated. On the right, grafting onto C. humilis rootstocks induces the expression of the PpGATA21 gene. The PpGATA21 transcription factor positively regulates the expression of PpGA2ox7 by binding to its promoter. The PpGA2ox7 gene acts as a negative regulator of GA biosynthesis. Arrows indicate positive regulatory effects between components. Solid arrows indicate activation, whereas blunt-ended arrows indicate inhibition. The dashed arrow remains to be further experimentally confirmed. Full article ">

23 pages, 7427 KiB

Open AccessArticle

Physiological and Proteome Analysis of the Effects of Chitosan Oligosaccharides on Salt Tolerance of Rice Seedlings

by Xiangyu Qian, Yaqing He, Lu Zhang, Xianzhen Li and Wenzhu Tang

Int. J. Mol. Sci. 2024, 25(11), 5953; https://doi.org/10.3390/ijms25115953 - 29 May 2024

Cited by 1 | Viewed by 732

Abstract

Rice (Oryza sativa L.) is an important social-economic crop, and rice seedlings are easily affected by salt stress. Chitosan oligosaccharide (COS) plays a positive role in promoting plant growth and development. To gain a better understanding of the salt tolerance mechanism of rice under the action of COS, Nipponbare rice seedlings were selected as the experimental materials, and the physiological and biochemical indexes of rice seedlings in three stages (normal growth, salt stress and recovery) were measured. Unlabelled quantitative proteomics technology was used to study differential protein and signaling pathways of rice seedlings under salt stress, and the mechanism of COS to improve rice tolerance to salt stress was elucidated. Results showed that after treatment with COS, the chlorophyll content of rice seedlings was 1.26 times higher than that of the blank group (CK). The root activity during the recovery stage was 1.46 times that of the CK group. The soluble sugar in root, stem and leaf increased by 53.42%, 77.10% and 9.37%, respectively. The total amino acid content increased by 77% during the stem recovery stage. Furthermore, the malondialdehyde content in root, stem and leaf increased by 21.28%, 26.67% and 32.69%, respectively. The activity of oxide dismutase (SOD), peroxidase (POD) and oxygenase (CAT) were increased. There were more differentially expressed proteins in the three parts of the experimental group than in the CK group. Gene Ontology (GO) annotation of these differentially expressed proteins revealed that the experimental group was enriched for more entries. Then, through the Kyoto Encyclopedia of Genes and Genomes (KEGG), the top ten pathways enriched with differentially expressed proteins in the two groups (COS and CK groups) were utilized, and a detailed interpretation of the glycolysis and photosynthesis pathways was provided. Five key proteins, including phosphofructokinase, fructose bisphosphate aldolases, glycer-aldehyde-3-phosphate dehydrogenase, enolase and pyruvate kinase, were identified in the glycolysis pathway. In the photosynthesis pathway, oxygen evolution enhancement proteins, iron redox proteins and ferredoxin-NADPH reductase were the key proteins. The addition of COS led to an increase in the abundance of proteins, a response of rice seedlings to salt stress. COS helped rice seedlings resist salt stress. Furthermore, using COS as biopesticides and biofertilizers can effectively increase the utilization of saline-affected farmland, thereby contributing to the alleviating of the global food crisis. Full article

(This article belongs to the Special Issue Plant Molecular Breeding and Resistance: Phenomics, Genomics and Gene Editing)

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Figure 1

Figure 1
Growth of Nipponbare rice seedlings. (A–C) The growth of Nipponbare rice seedlings in the CK group. (D–F) The growth of Nipponbare rice seedlings in the COS group. (A,D) Normal growth. (B,E) 150 mM NaCl stress. (C,F) Recovery. Full article ">Figure 2
Biochemical indicators of the three stages of the Nipponbare rice seedlings. (A) Chlorophyll content, (B) root activity, (C–E) soluble sugar content, (F–H) malondialdehyde content, (I–K) total amino acid content, (L–N) SOD activity, (O–Q) POD activity, (R–T) CAT active. (C–T) A group of three biochemical indicators, including the three parts of the roots, stems and leaves, respectively. * p < 0.05; ** p < 0.01. Full article ">Figure 3
Venn diagram of DEPs between CK group and COS group in the rice seedlings of Nipponbare. (A–C) Venn diagrams of roots, stems and leaves of the CK group. (D–F) Venn diagrams of roots, stems and leaves of the COS group. S/N: salt stress/normal growth, R/N: recover/normal growth, R/S: recover/salt stress. Full article ">Figure 4
GO annotation of DEPs in the rice leaves of Nipponbare. (A–C) CK groups. (A) S/N salt stress/normal growth; (B) R/N recover/normal growth; (C) R/S recover/salt stress. (D–F) COS groups. (D) S/N salt stress/normal growth; (E) R/N recover/normal growth; (F) R/S recover/salt stress. BP: biological process, CC: cellular component, MF: molecular function. Full article ">Figure 5
GO annotation of DEPs in the rice stems of Nipponbare. (A–C) CK groups. (A) S/N salt stress/normal growth; (B) R/N recover/normal growth; (C) R/S recover/salt stress. (D–F) COS groups. (D) S/N salt stress/normal growth; (E) R/N recover/normal growth; (F) R/S recover/salt stress. BP: biological process, CC: cellular component, MF: molecular function. Full article ">Figure 6
GO annotation of DEPs in the rice roots of Nipponbare. GO annotation of DEPs in the rice leaves of Nipponbare. (A–C) CK groups. (A) S/N salt stress/normal growth; (B) R/N recover/normal growth; (C) R/S recover/salt stress. (D–F) COS groups. (D) S/N salt stress/normal growth; (E) R/N recover/normal growth; (F) R/S recover/salt stress. BP: biological process, CC: cellular component, MF: molecular function. Full article ">Figure 7
Top 10 key pathways for DEP enrichment in the rice seedlings of Nipponbare. (A–I) The enrichment of leaves ((A) S/N (B) R/N (C) R/S), stems ((D), S/N (E) R/N (F) R/S) and roots ((G) S/N (H) R/N (I) R/S) under salt stress/normal, recover/normal, and recover/salt stress stage. 00500: starch and sucrose metabolism, 00020: citrate cycle, 03050: proteasome, 00620: pyruvate metabolism, 00195: photosynthesis, 00010: glycolysis/gluconeogenesis, 04141: protein processing in endoplasmic reticulum, 00190: oxidative phosphorylation, 03040: splice body, 03010: ribosome, 00520: amino sugar and nucleotide sugar metabolism, 00970: aminoacyl-tRNA biosynthesis, 03013: nuclear and cytoplasmic transport, 00270: cysteine and methionine metabolism, 00710: carbon sequestration in photosynthetic organisms, 00260: metabolism of glycine, serine and threonine, 00630: glyoxylic acid and dicarboxylic acid metabolism, 04142: lysosome. Full article ">

22 pages, 5854 KiB

Open AccessArticle

Revealing the Complete Bispecific Phosphatase Genes (DUSPs) across the Genome and Investigating the Expression Patterns of GH_A11G3500 Resistance against Verticillium wilt

by Yahui Deng, Xiaojuan Deng, Jieyin Zhao, Shuo Ning, Aixing Gu, Quanjia Chen and Yanying Qu

Int. J. Mol. Sci. 2024, 25(8), 4500; https://doi.org/10.3390/ijms25084500 - 19 Apr 2024

Viewed by 791

Abstract

DUSPs, a diverse group of protein phosphatases, play a pivotal role in orchestrating cellular growth and development through intricate signaling pathways. Notably, they actively participate in the MAPK pathway, which governs crucial aspects of plant physiology, including growth regulation, disease resistance, pest resistance, and stress response. DUSP is a key enzyme, and it is the enzyme that limits the rate of cell metabolism. At present, complete understanding of the DUSP gene family in cotton and its specific roles in resistance to Verticillium wilt (VW) remains elusive. To address this knowledge gap, we conducted a comprehensive identification and analysis of four key cotton species: Gossypium arboreum, Gossypium barbadense, Gossypium hirsutum, and Gossypium raimondii. The results revealed the identification of a total of 120 DUSP genes in the four cotton varieties, which were categorized into six subgroups and randomly distributed at both ends of 26 chromosomes, predominantly localized within the nucleus. Our analysis demonstrated that closely related DUSP genes exhibited similarities in terms of the conserved motif composition and gene structure. A promoter analysis performed on the GhDUSP gene promoter revealed the presence of several cis-acting elements, which are associated with abiotic and biotic stress responses, as well as hormone signaling. A tissue expression pattern analysis demonstrated significant variations in GhDUSP gene expression under different stress conditions, with roots exhibiting the highest levels, followed by stems and leaves. In terms of tissue-specific detection, petals, leaves, stems, stamens, and receptacles exhibited higher expression levels of the GhDUSP gene. The gene expression analysis results for GhDUSPs under stress suggest that DUSP genes may have a crucial role in the cotton response to stress in cotton. Through Virus-Induced Gene Silencing (VIGS) experiments, the silencing of the target gene significantly reduced the resistance efficiency of disease-resistant varieties against Verticillium wilt (VW). Consequently, we conclude that GH_A11G3500-mediated bispecific phosphorylated genes may serve as key regulators in the resistance of G. hirsutum to Verticillium wilt (VW). This study presents a comprehensive structure designed to provide an in-depth understanding of the potential biological functions of cotton, providing a strong foundation for further research into molecular breeding and resistance to plant pathogens. Full article

(This article belongs to the Special Issue Plant Molecular Breeding and Resistance: Phenomics, Genomics and Gene Editing)

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13 pages, 1965 KiB

Open AccessArticle

Patch Track Software for Measuring Kinematic Phenotypes of Arabidopsis Roots Demonstrated on Auxin Transport Mutants

by Ashley R. Henry, Nathan D. Miller and Edgar P. Spalding

Int. J. Mol. Sci. 2023, 24(22), 16475; https://doi.org/10.3390/ijms242216475 - 18 Nov 2023

Cited by 1 | Viewed by 1110

Abstract

Plant roots elongate when cells produced in the apical meristem enter a transient period of rapid expansion. To measure the dynamic process of root cell expansion in the elongation zone, we captured digital images of growing Arabidopsis roots with horizontal microscopes and analyzed them with a custom image analysis program (PatchTrack) designed to track the growth-driven displacement of many closely spaced image patches. Fitting a flexible logistics equation to patch velocities plotted versus position along the root axis produced the length of the elongation zone (mm), peak relative elemental growth rate (% h⁻¹), the axial position of the peak (mm from the tip), and average root elongation rate (mm h⁻¹). For a wild-type root, the average values of these kinematic traits were 0.52 mm, 23.7% h⁻¹, 0.35 mm, and 0.1 mm h⁻¹, respectively. We used the platform to determine the kinematic phenotypes of auxin transport mutants. The results support a model in which the PIN2 auxin transporter creates an area of expansion-suppressing, supraoptimal auxin concentration that ends 0.1 mm from the quiescent center (QC), and that ABCB4 and ABCB19 auxin transporters maintain expansion-limiting suboptimal auxin levels beginning approximately 0.5 mm from the QC. This study shows that PatchTrack can quantify dynamic root phenotypes in kinematic terms. Full article

(This article belongs to the Special Issue Plant Molecular Breeding and Resistance: Phenomics, Genomics and Gene Editing)

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Figure 1

Figure 1
Diagram of the growing and imaging process of the Arabidopsis seedling roots for kinematic analysis. (A) Coverslip with seedlings sown into an agar-based medium. (B) The coverslip mounted in a 3D-printed cartridge and placed on the stage of a horizontal microscope. (C) Four frames from a one-hour time series, where images are taken every 30 s at a resolution of 1500 px mm−1. Full article ">Figure 2
The process of our kinematic analysis pipeline, from root images to extracted features of each root’s growth zone. (A–D) Image patch tracking as a root elongates. (A) Root at 0 min with a disk capturing an image patch at the beginning of the elongation zone. (B) Possible disk transformations to match the image patch in A to the sequential image patch in (C). (C) Root at 5 min with a translated, stretched, and rotated disk capturing the same image patch as the disk in (A). (D) Several disks along the root midline, each capturing and tracking their respective image patches as the root elongates. (E) Velocity points along the root midline from all disks tracking image patches from one frame to the next. (F) Velocity points along the root midline for all frames and all disks. The red line is the fitted velocity profile for that root. (G) The red line is the derivative of the velocity curve in F and is the relative elemental growth rate (REGR) curve. The arrows and text denote the four kinematic traits that are extracted from the REGR curve of each root. Full article ">Figure 3
REGR profiles of the auxin transport mutants. (A–D) REGR profiles of abcb4, abcb19, abcb4 abcb19, pin2, and pin2 abcb4 mutants with their Col-0 wild types, respectively. (A) Two alleles of the abcb4 mutation. In each experiment, 13 to 18 primary roots were analyzed. Full article ">Figure 4
Distribution of growth zone traits by genotype. (A–D) Final growth rate, length of growth zone, max REGR, and position of max. REGR differences between the WT and auxin transport mutants, respectively. In each experiment, 13 to 18 primary roots were analyzed. ** denotes p-value < 0.001 and * denotes p-value < 0.01. Full article ">

16 pages, 3255 KiB

Open AccessArticle

Resistant and Susceptible Pinus thunbergii ParL. Show Highly Divergent Patterns of Differentially Expressed Genes during the Process of Infection by Bursaphelenchus xylophilus

by Tingyu Sun, Mati Ur Rahman, Xiaoqin Wu and Jianren Ye

Int. J. Mol. Sci. 2023, 24(18), 14376; https://doi.org/10.3390/ijms241814376 - 21 Sep 2023

Cited by 2 | Viewed by 1208

Abstract

Pine wilt disease (PWD) is a devastating disease that threatens pine forests worldwide, and breeding resistant pines is an important management strategy used to reduce its impact. A batch of resistant seeds of P. thunbergii was introduced from Japan. Based on the resistant materials, we obtained somatic plants through somatic embryogenesis. In this study, we performed transcriptome analysis to further understand the defense response of resistant somatic plants of P. thunbergii to PWD. The results showed that, after pine wood nematode (PWN) infection, resistant P. thunbergii stimulated more differential expression genes (DEGs) and involved more regulatory pathways than did susceptible P. thunbergii. For the first time, the alpha-linolenic acid metabolism and linoleic acid metabolism were intensively observed in pines resisting PWN infection. The related genes disease resistance protein RPS2 (SUMM2) and pathogenesis-related genes (PR1), as well as reactive oxygen species (ROS)-related genes were significantly up-expressed in order to contribute to protection against PWN inoculation in P. thunbergii. In addition, the diterpenoid biosynthesis pathway was significantly enriched only in resistant P. thunbergii. These findings provided valuable genetic information for future breeding of resistant conifers, and could contribute to the development of new diagnostic tools for early screening of resistant pine seedlings based on specific PWN-tolerance-related markers. Full article

(This article belongs to the Special Issue Plant Molecular Breeding and Resistance: Phenomics, Genomics and Gene Editing)

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Figure 1

Figure 1
Comparison of DEGs between susceptible and resistant P. thunbergii at different disease stages. (A,B) indicated the number of DEGs obtained in susceptible and resistant P. thunbergii at infection stages, respectively. (C,D) indicated the number and overlapping relationships of DEGs in venn diagram between susceptible and resistant P. thunbergii at different infection stages, respectively. Full article ">Figure 2
Enriched biological processes in DEGs by GO annotation for susceptible and resistant P. thunbergii at different infection stages. (A) indicated GO annotation of susceptible and resistant P. thunbergii at first infection stage (1d vs 3d). (B) indicated GO annotation of susceptible and resistant P. thunbergii at second infection stage (3d vs 7d). Full article ">Figure 3
qRT-PCR validation of selected transcripts for validation. Relative expression levels of qRT-PCR are calculated using elongation factor 1-alpha as the internal control. The data are expressed as the mean (±SE). Error bars represent the SE. Full article ">Figure 4
DEGs involved in alpha-linolenic acid metabolism and linoleic acid metabolism in P. thunbergii. (A) indicated linoleic acid metabolism pathway. (B) indicated alpha-linolenic acid metabolism pathway. Enzymes involved in each step are shown in purple, and the green boxes represent DEGs encoding enzyme activity. R represents resistant P. thunbergii. S represents susceptible P. thunbergii. R1 represents the first stage of the resistant P. thunbergii inoculated with PWN (1 d vs. 3 d). S2 represents the second stage of susceptible P. thunbergii inoculated with PWN (3 d vs. 7 d). LOX1-5 (E5.5.1.13) represents lindoleate 9S-lipoxygenase. LOX2S (E1.14.11.13) represents lipoxygenase. AOS represents hydroperoxide dehydratase. OPR represents 12-oxophytodienoic acid reductase. ADH1 represents alcohol dehydrogenase class-P, E2.2.1.141 represents jasmonate O-methyltransferase. Full article ">Figure 5
The expression of partial DEGs in “MAPK signaling pathway—plant” and “biosynthesis of various secondary metabolites—part 2” pathways. (A,B) The expression of DEGs in the “MAPK signaling pathway—plant” in susceptible and PWN-resistant P. thunbergii, respectively. (C,D) Expression of DEGs in “biosynthesis of various secondary metabolites—part 2” in susceptible and PWN-resistant P. thunbergii, respectively. S1 represents the 1st stage (1 d vs. 3 d) of PWN infection in susceptible P. thunbergii. S2 represents the 2nd stage (3 d vs. 7 d) of PWN infection in susceptible P. thunbergii. R1 represents the 1st stage (1d vs. 3d) of PWN infection in resistant P. thunbergii. R2 represents the 2nd stage (3 d vs. 7 d) of PWN infection in resistant P. thunbergii. * and ** indicate significant differences at p < 0.05 and p < 0.01, respectively. *** indicate significant differences at p < 0.001. Full article ">Figure 6
DEGs involved in diterpenoid biosynthesis in the stem of P. thunbergii. (A) indicates the number of DEG terpenoid types. (B) indicated diterpenoid biosynthesis pathway. Enzymes involved in each step are shown in purple, and the green boxes represent DEGs encoding enzyme activity. R represents resistant P. thunbergii. S represents susceptible P. thunbergii. R1 represents the first stage of the resistant P. thunbergii inoculated with PWN (1 d vs. 3 d). S1 represents the first stage of the susceptible P. thunbergii inoculation with PWN (1 d vs. 3 d). S2 represents the second stage of susceptible P. thunbergii inoculated with PWN (3 d vs. 7 d). E5.5.1.13 represents ent-copalyl diphosphate synthase. E3.1.7.10 represents (13E)-labda-7,13-dien-15-ol synthase. E1.14.11.13 represents gibberellin 2beta-dioxygenase. Full article ">

Review

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13 pages, 1147 KiB

Open AccessReview

CRISPR Variants for Gene Editing in Plants: Biosafety Risks and Future Directions

by Ali Movahedi, Soheila Aghaei-Dargiri, Hongyan Li, Qiang Zhuge and Weibo Sun

Int. J. Mol. Sci. 2023, 24(22), 16241; https://doi.org/10.3390/ijms242216241 - 13 Nov 2023

Cited by 2 | Viewed by 3451

Abstract

The CRISPR genome editing technology is a crucial tool for enabling revolutionary advancements in plant genetic improvement. This review shows the latest developments in CRISPR/Cas9 genome editing system variants, discussing their benefits and limitations for plant improvement. While this technology presents immense opportunities for plant breeding, it also raises serious biosafety concerns that require careful consideration, including potential off-target effects and the unintended transfer of modified genes to other organisms. This paper highlights strategies to mitigate biosafety risks and explores innovative plant gene editing detection methods. Our review investigates the international biosafety guidelines for gene-edited crops, analyzing their broad implications for agricultural and biotechnology research and advancement. We hope to provide illuminating and refined perspectives for industry practitioners and policymakers by evaluating CRISPR genome enhancement in plants. Full article

(This article belongs to the Special Issue Plant Molecular Breeding and Resistance: Phenomics, Genomics and Gene Editing)

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