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Search Results (3,893)

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15 pages, 9050 KiB  
Article
Genome-Wide Identification of MKK Gene Family and Response to Hormone and Abiotic Stress in Rice
by Fan Zhang, Jingjing Wang, Yiwei Chen, Junjun Huang and Weihong Liang
Plants 2024, 13(20), 2922; https://doi.org/10.3390/plants13202922 - 18 Oct 2024
Viewed by 235
Abstract
Mitogen-activated protein kinase (MAPK/MPK) cascades are pivotal and highly conserved signaling modules widely distributed in eukaryotes; they play essential roles in plant growth and development, as well as biotic and abiotic stress responses. With the development of sequencing technology, the complete genome assembly [...] Read more.
Mitogen-activated protein kinase (MAPK/MPK) cascades are pivotal and highly conserved signaling modules widely distributed in eukaryotes; they play essential roles in plant growth and development, as well as biotic and abiotic stress responses. With the development of sequencing technology, the complete genome assembly of rice without gaps, T2T (Telomere-to-Telomere)—NIP (version AGIS-1.0), has recently been released. In this study, we used bioinformatic approaches to identify and analyze the rice MPK kinases (MKKs) based on the complete genome. A total of seven OsMKKs were identified, and their physical and chemical properties, chromosome localization, gene structure, subcellular localization, phylogeny, family evolution, and cis-acting elements were evaluated. OsMKKs can be divided into four subgroups based on phylogenetic relationships, and the family members located in the same evolutionary branch have relatively similar gene structures and conserved domains. Quantitative real-time PCR (qRT-PCR) revealed that all OsMKKs were highly expressed in rice seedling leaves. The expression levels of all OsMKKs were more or less altered under exogenous hormone and abiotic stress treatments, with OsMKK1, OsMKK6, and OsMKK3 being induced under almost all treatments, while the expression of OsMKK4 and OsMKK10-2 was repressed under salt and drought treatments and IAA treatment, respectively. In this study, we also summarized the recent progress in rice MPK cascades, highlighted their diverse functions, and outlined the potential MPK signaling network, facilitating further studies on OsMKK genes and rice MPK cascades. Full article
(This article belongs to the Section Plant Genetics, Genomics and Biotechnology)
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Figure 1

Figure 1
<p>Chromosomal distribution of <span class="html-italic">OsMKK</span> genes in rice. The duplicated <span class="html-italic">OsMKK</span> genes are shown in red dashed line. Shadows of the same color belong to the same group.</p>
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<p>Phylogenetic tree of the 7 OsMKK proteins and 33 known functional MKK proteins from other plants. Green stars represent OsMKKs, cyan triangles represent AtMKKs, and pink checkmarks are known function MKKs.</p>
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<p>Gene structure and conserved protein motifs analysis of <span class="html-italic">OsMKK</span> genes. (<b>A</b>) ML phylogenetic tree analysis of OsMKKs. (<b>B</b>) Exon–intron structure of <span class="html-italic">OsMKKs</span>, where golden yellow boxes represent coding sequences (CDS), the blue boxes represent upstream/downstream sequences, and the black lines represent the introns. (<b>C</b>) The conserved motifs in OsMKK proteins. The ten conversed motifs are displayed in various unique colors. The gene and protein length are indicated by the scale at bottom. (<b>D</b>) Sequence logos of ten conserved domains. The conserved sequences of the different motifs are highlighted in different colored rectangles. (<b>E</b>) Sequence alignment and motif analysis of OsMKKs. Identical amino acids are shaded black, and similar amino acids are shaded purple. The P, C, and T loops, CCD, and the NTF2 domain are highlighted in colored rectangles (P loop: red; C loop: green; T loop: blue; CDD: pink; NTF2: yellow). The red stars show the active site, and the green stars indicate the phosphorylation site of OsMKK proteins. Species information can be found in <a href="#app1-plants-13-02922" class="html-app">Figure S1</a>.</p>
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<p>Predicted 3D models of OsMKK proteins. Models have been generated by Alpha 2 and visualized by rainbow color from N (blue) to C terminus (red) using PyMOL v2.5.8 software.</p>
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<p>Expression profiling of 7 <span class="html-italic">OsMKK</span> genes in different organs and tissues. The red color represents high-level expression, while the blue color represents low-level expression. DAP, days after pollination.</p>
Full article ">Figure 6
<p>Expression patterns of 7 <span class="html-italic">OsMKK</span> genes in the roots, stems, and leaves of rice seedlings. Data are represented as the mean ± SD of three independent replicates. Asterisks indicate statistically significant differences compared with root (** <span class="html-italic">p</span> &lt; 0.01; Student’s <span class="html-italic">t</span>-test).</p>
Full article ">Figure 7
<p>Cis-acting elements in the promoter of <span class="html-italic">OsMKK</span> genes. (<b>A</b>) Numbers of predicted cis-acting elements in <span class="html-italic">OsMKK</span> promoters are shown. (<b>B</b>) The distribution of predicted cis-acting elements on different gene promoters. Different colors represent different cis-acting elements.</p>
Full article ">Figure 8
<p>Expression levels of <span class="html-italic">OsMKK</span> genes under ABA, GA, IAA, salt, and drought stress treatments. Data are represented as the mean ± SD of three independent replicates. Different letters above bars indicate significant differences (<span class="html-italic">p</span> &lt; 0.05; Tukey’s test).</p>
Full article ">Figure 9
<p>OsMKKs are involved in plant growth and development and diverse biotic and abiotic stresses. (<b>A</b>–<b>D</b>) represent the processes in which each subgroup participates [<a href="#B3-plants-13-02922" class="html-bibr">3</a>,<a href="#B35-plants-13-02922" class="html-bibr">35</a>,<a href="#B36-plants-13-02922" class="html-bibr">36</a>,<a href="#B39-plants-13-02922" class="html-bibr">39</a>,<a href="#B40-plants-13-02922" class="html-bibr">40</a>,<a href="#B41-plants-13-02922" class="html-bibr">41</a>,<a href="#B42-plants-13-02922" class="html-bibr">42</a>,<a href="#B45-plants-13-02922" class="html-bibr">45</a>,<a href="#B46-plants-13-02922" class="html-bibr">46</a>,<a href="#B47-plants-13-02922" class="html-bibr">47</a>,<a href="#B48-plants-13-02922" class="html-bibr">48</a>,<a href="#B49-plants-13-02922" class="html-bibr">49</a>,<a href="#B50-plants-13-02922" class="html-bibr">50</a>,<a href="#B51-plants-13-02922" class="html-bibr">51</a>,<a href="#B52-plants-13-02922" class="html-bibr">52</a>,<a href="#B53-plants-13-02922" class="html-bibr">53</a>,<a href="#B54-plants-13-02922" class="html-bibr">54</a>,<a href="#B55-plants-13-02922" class="html-bibr">55</a>].</p>
Full article ">
14 pages, 3511 KiB  
Article
The Impact of Short-Term Drought on the Photosynthetic Characteristics and Yield of Peanuts Grown in Saline Alkali Soil
by Kang He, Yang Xu, Hong Ding, Qing Guo, Dunwei Ci, Jialei Zhang, Feifei Qin, Manlin Xu and Guanchu Zhang
Plants 2024, 13(20), 2920; https://doi.org/10.3390/plants13202920 - 18 Oct 2024
Viewed by 176
Abstract
Peanuts grown in saline alkali soil are also subjected to drought stress caused by water scarcity. Therefore, we used HY25 (peanut variety) as an experimental material to investigate the effects of drought on the height of peanut main stems, length of the first [...] Read more.
Peanuts grown in saline alkali soil are also subjected to drought stress caused by water scarcity. Therefore, we used HY25 (peanut variety) as an experimental material to investigate the effects of drought on the height of peanut main stems, length of the first lateral branch, leaf area per plant, SPAD value, net photosynthetic rate, and accumulation and distribution of photosynthetic products in saline alkali soil. The results showed that the combined stress of short-term drought and salt significantly reduced the main stem height, first lateral branch length, single plant leaf area, SPAD value, net photosynthetic rate (Pn), intercellular carbon dioxide concentration (Ci), and dry matter accumulation of peanuts, including a decrease in single plant pod yield, 100-pod weight, 100-kernel weight, and peanut yield. And the impact of drought stress on peanut yield varies at different growth stages. For example, under drought stress alone, the sensitive period is the 40th day after planting (40D) > 60th day after planting (60D) > 30th day after planting (30D). Short-term drought has the greatest impact on peanut yield at 40D, while in contrast, resuming watering after drought at 30D results in a slight but not significant increase in peanut yield in comparison with the control. Under the combined stress of drought and salt, the sensitive period of peanuts was 40D > 30D > 60D, and the single pod weight of peanuts was significantly reduced by 15.26% to 57.60% from the flowering stage to the pod stage under drought treatment compared to salt treatment, indicating a significant interaction between drought and salt stress, reducing the single leaf area and net photosynthetic rate of peanut leaves, ultimately leading to a decrease in peanut yield. Therefore, when planting peanuts in saline alkali soil, drought should be avoided, especially early drought, in order to prevent the combined effects of drought and salt stress from harming peanut yield. Full article
(This article belongs to the Special Issue The Physiology of Abiotic Stress in Plants)
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Figure 1

Figure 1
<p>Effects of drought and salt stress on peanut stem length. CK means without treatment, Salt means salt treatment. Drought means drought. Drought + salt represents two types of stress treated together at different stages. The <span class="html-italic">X</span> axis represents the number of planting days. Different lowercase letters mean significant differences at the 0.05 level, and data are expressed as mean ± standard deviation (n = 3).</p>
Full article ">Figure 2
<p>Effects of drought and salt stress on peanut first lateral branch length. CK means without treatment, Salt means salt treatment. Drought means drought. Drought + salt represents two types of stress treated together at different stages. The <span class="html-italic">X</span> axis represents the number of planting days. Different lowercase letters mean significant differences at the 0.05 level; data are expressed as mean ± standard deviation (n = 3).</p>
Full article ">Figure 3
<p>Effects of drought and salt stress on peanut single plant leaf area. CK means without treatment, Salt means salt treatment. Drought means drought. Drought + salt represents two types of stress treated together at different stages. The leaf area was calculated using a punch with a diameter of one centimeter. The <span class="html-italic">X</span> axis represents the number of planting days. Different lowercase letters mean significant differences at the 0.05 level; data are expressed as mean ± standard deviation (n = 3).</p>
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<p>Pod dry weight per plant related to leaf dry weight per plant, stem dry weight per plant, root dry weight per plant, SPAD, Pn, Gs, Ci, Tr at harvest time. The net photosynthetic rate (Pn), intercellular carbon dioxide concentration (Ci), stomatal conductance (Gs), and transpiration rate (Tr) of leaves were measured using the CIRAS-3 portable photosynthesis system. * Indicates significant differences at <span class="html-italic">p</span> ≤ 0.05.</p>
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18 pages, 5160 KiB  
Article
A Soybean Pyrroline-5-Carboxylate Dehydrogenase GmP5CDH1 Modulates Plant Growth and Proline Sensitivity
by Shupeng Dong, Zhuozhuo Mao, Zhongyi Yang, Xiao Li, Dezhou Hu, Fei Wu, Deyue Yu and Fang Huang
Agronomy 2024, 14(10), 2411; https://doi.org/10.3390/agronomy14102411 - 18 Oct 2024
Viewed by 213
Abstract
Soybean [Glycine max (L.) Merr.], as a globally commercialized crop, is an important source of protein and oil for both humans and livestock. With more frequent extreme weather disasters, abiotic stress has become one of the critical factors restricting soybean production. Proline [...] Read more.
Soybean [Glycine max (L.) Merr.], as a globally commercialized crop, is an important source of protein and oil for both humans and livestock. With more frequent extreme weather disasters, abiotic stress has become one of the critical factors restricting soybean production. Proline (Pro) is a well-known substance in plants that responds to abiotic stress. To identify potential effector genes involved in soybean resistance to abiotic stress, we focused on the pyrroline-5-carboxylate dehydrogenase (P5CDH) which is a key enzyme in the degradation process of Pro. Through homologous sequence alignment, phylogenetic tree, and predicted expression, we chose GmP5CDH1 (Glyma.05G029200) for further research. Tissue-specific expression assay showed that GmP5CDH1 had higher expression levels in soybean seed and cotyledon development. Subcellular localization assay revealed that GmP5CDH1 was a nuclear-membrane-localized protein. As the result of the predicted cis-acting regulatory element indicates, the expression level of GmP5CDH1 was induced by low temperature, drought, salt stress, and ABA in soybean. Next, we constructed transgenic Arabidopsis overexpressing GmP5CDH1. The results showed that GmP5CDH1 also strongly responded to exogenous Pro, and overcame the toxicity of abiotic stress on plants by regulating the endogenous concentration of Pro. The interaction between GmP5CDH1 and GmSAM1 was validated through yeast two-hybrid, LUC fluorescence complementary, and BIFC. In conclusion, overexpression of a soybean pyrroline-5-carboxylate dehydrogenase GmP5CDH1 regulates the development of Arabidopsis thaliana by altering proline content dynamically under salt stress, especially improving the growth of plants under exogenous Pro. Full article
(This article belongs to the Special Issue Functional Genomics and Molecular Breeding of Soybeans)
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Figure 1
<p>Bioinformatics analysis of P5CDH genes family in soybean. (<b>A</b>) Phylogenetic tree assay of seven species. (<b>B</b>) Gene structure assay of seven species. Different colored squares represent different protein motifs. (<b>C</b>) Predicted expression pattern for P5CDH genes family in soybean.</p>
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<p>Genomic sequence assay of <span class="html-italic">GmP5CDH1</span>. (<b>A</b>) The genome sequence structure diagram of <span class="html-italic">GmP5CDH1</span>. The black horizontal line represents the length of 100 bases. (<b>B</b>) Conserved structural domain of <span class="html-italic">GmP5CDH1</span>. (<b>C</b>) Protein sequence alignment of P5CDH gene family in three leguminous crops and <span class="html-italic">Arabidopsis</span>. The protein sequence of the Aldedh domain is shown in red underline. (<b>D</b>) Predicted cis-acting regulatory element structure of <span class="html-italic">GmP5CDH1</span>.</p>
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<p>The expression pattern of <span class="html-italic">GmP5CDH1</span>. (<b>A</b>) Tissue-specific analysis of <span class="html-italic">GmP5CDH1</span> in soybean. The Y-axis is divided into two parts, with the bottom value ranging from 1 to 3, accounting for 70% of the Y-axis, and the top value ranging from 3 to 18, accounting for 30%. (<b>B</b>) <span class="html-italic">GmP5CDH1</span> was induced by low temperature (<b>B1</b>), drought (<b>B2</b>), salt stress (<b>B3</b>), and ABA (<b>B4</b>). (<b>C</b>) Subcellular localization assay of GmP5CDH1 in <span class="html-italic">Nicotiana benthamiana</span> leaf. GFP, green fluorescent protein; BF, brightfield; Chlorophyll, chlorophyll autofluorescence (red); Scale bars, 20 µm. Significant differences according to two-sided Student’s <span class="html-italic">t</span>-test (0.01 &lt; * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01).</p>
Full article ">Figure 4
<p>Germination rate (<b>A</b>) and amino acid content (<b>B</b>) of transgenic <span class="html-italic">Arabidopsis</span> seeds. Significant differences according to two-sided Student’s <span class="html-italic">t</span>-test (0.01 &lt; * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01).</p>
Full article ">Figure 5
<p>The phenotype of transgenic <span class="html-italic">Arabidopsis</span> under salt stress. (<b>A</b>,<b>B</b>,<b>E</b>) Morphology (<b>A</b>), root length (<b>B</b>), and fresh weight (<b>E</b>) of transgenic <span class="html-italic">Arabidopsis</span> under salt stress. (<b>C</b>) Endogenous Pro content in plants under salt stress. (<b>D</b>) Expression level of <span class="html-italic">GmP5CDH1</span> in plants under salt stress. Significant differences according to two-sided Student’s <span class="html-italic">t</span>-test (** <span class="html-italic">p</span> &lt; 0.01).</p>
Full article ">Figure 6
<p>The phenotype of transgenic <span class="html-italic">Arabidopsis</span> under different exogenous Pro concentrations. (<b>A</b>) Germination rate of transgenic plants. (<b>B</b>–<b>D</b>) Phenotype (<b>C</b>), root length (<b>B</b>), and fresh weight (<b>D</b>) of transgenic plants. Endogenous Pro content (<b>E</b>) and expression level of <span class="html-italic">GmP5CDH1</span> (<b>F</b>) in plants treatment with 0 mM, 2 mM, and 150 mM concentrations of Pro. Significant differences according to two-sided Student’s <span class="html-italic">t</span>-test (** <span class="html-italic">p</span> &lt; 0.01).</p>
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<p>GmP5CDH1 interacts with GmSAM1. (<b>A</b>) Transformed yeast cells were grown on synthetic defined (SD) medium/—Trp–Leu/X-α-Gal and SD medium/—Trp–Leu–His–Ade/X-α-Gal. pGADT7-T+ pGBKT7-53 represents the positive control; pGADT7-T+ pGBKT7-lam represents the negative control. (<b>B</b>) LUC fluorescence complementary of GmP5CDH1 in <span class="html-italic">Nicotiana benthamiana</span> leaf. GmP5CDH1-C-LUC+N-LUC, C-LUC+GmSAM1-N-LUC, and C-LUC+ N-LUC constructs represent the negative control. (<b>C</b>) Bimolecular fluorescence complementation (BiFC) assay was conducted to confirm the interaction location. YFPc + GmP5CDH1-YFPn and GmSAM1-YFPc + YFPn constructs were used as controls. YFP, yellow fluorescent protein; BF, brightfield; Chlorophyll, chlorophyll autofluorescence (red). Scale bars, 50 μm.</p>
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13 pages, 4004 KiB  
Essay
Genome-Wide Identification and Expression Analysis of the PsTPS Gene Family in Pisum sativum
by Hao Yuan, Baoxia Liu, Guwen Zhang, Zhijuan Feng, Bin Wang, Yuanpeng Bu, Yu Xu, Zhihong Sun, Na Liu and Yaming Gong
Horticulturae 2024, 10(10), 1104; https://doi.org/10.3390/horticulturae10101104 - 18 Oct 2024
Viewed by 290
Abstract
This study aimed to explore the role of the trehalose-6-phosphate synthase (TPS) gene family in the adaptation of peas to environmental stress. A comprehensive analysis of the PsTPS gene family identified 20 genes with conserved domains and specific chromosomal locations. Phylogenetic [...] Read more.
This study aimed to explore the role of the trehalose-6-phosphate synthase (TPS) gene family in the adaptation of peas to environmental stress. A comprehensive analysis of the PsTPS gene family identified 20 genes with conserved domains and specific chromosomal locations. Phylogenetic analysis delineated evolutionary relationships, while gene structure analysis revealed compositional insights, and motif analysis provided functional insights. Cis-regulatory element identification predicted gene regulation patterns. Tissue-specific and stress-induced expression profiling highlighted eight genes with ubiquitous expression, with PsTPS15 and PsTPS18 displaying elevated expression levels in roots, nodules, and young stems, and PsTPS13 and PsTPS19 expression downregulated in seeds. Transcriptome analysis identified a differential expression of 20 PsTPS genes, highlighting the significance of 14 genes in response to drought and salinity stress. Notably, under drought conditions, the expression of PsTPS4 and PsTPS6 was initially upregulated and then downregulated, whereas that of PsTPS15 and PsTPS19 was downregulated. Salinity stress notably altered the expression of PsTPS4, PsTPS6, and PsTPS19. Taken together, these findings elucidate the regulatory mechanisms of the PsTPS gene family and their potential as genetic targets for enhancing crop stress tolerance. Full article
(This article belongs to the Section Genetics, Genomics, Breeding, and Biotechnology (G2B2))
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Figure 1
<p>Chromosomal locations of the <span class="html-italic">PsTPS</span> genes on the seven pea chromosomes. The distribution of <span class="html-italic">PsTPS</span> genes is relatively sparse, and they are not distributed on every chromosome. The highest distribution of <span class="html-italic">PsTPS</span> genes is observed on Chr5, which contains seven genes.</p>
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<p>Phylogenetic tree incorporating TPS proteins from <span class="html-italic">Pisum sativum</span> L, <span class="html-italic">Arabidopsis</span>, and <span class="html-italic">Glycine max</span>. The tree of the <span class="html-italic">TPS</span> gene family was constructed by the IQ-TREE 2 software (Version 2.2.0) using the maximum likelihood (ML) method with 1000 bootstrap replicates. The color of the outer ring and branches denote <span class="html-italic">TPS</span> subfamilies.</p>
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<p>The phylogenetic relationship, conserved motifs, and gene structure of <span class="html-italic">PsTPSs</span>. (<b>a</b>) The maximum likelihood (ML) phylogenetic tree of PsTPS proteins was constructed using a full-length sequence with 1000 bootstrap replicates; (<b>b</b>) Distribution of conserved motifs in PsTPS proteins. A total of 10 motifs were predicted, and the scale bar represents 100 aa; (<b>c</b>) Distribution of the TPS domain in PsTPSs; (<b>d</b>) The gene structures of <span class="html-italic">PsTPSs</span>, including introns (black lines) and exons (green rectangles). The scale bar indicates 1000 bp.</p>
Full article ">Figure 4
<p>CREs on the putative promoters of <span class="html-italic">PsTPSs</span>. (<b>a</b>) Distribution of CREs identified in the 2000 bp upstream promoter region of <span class="html-italic">PsTPSs</span>; (<b>b</b>) The number of CREs on the putative promoters of <span class="html-italic">PsTPSs</span>. Numbers in the heatmap represent the number of elements.</p>
Full article ">Figure 5
<p>Syntenic analyses of <span class="html-italic">TPS</span> genes in <span class="html-italic">Pisum sativum</span>, <span class="html-italic">Arabidopsis</span>, <span class="html-italic">G. max</span>. (<b>a</b>) Seven chromosomes from <span class="html-italic">Pisum sativum</span> (Ps1–Ps7) are mapped, with chromosome length expressed as Mb. Lines denote syntenic <span class="html-italic">TPS</span> gene pairs on the chromosomes. (<b>b</b>) The seven chromosomes of <span class="html-italic">Pisum sativum</span> (Ps1–7), five chromosomes of <span class="html-italic">A. thaliana</span> (At1–5), and twenty chromosomes of <span class="html-italic">G. max</span> (Gm1–20) are mapped. Lines represent syntenic <span class="html-italic">TPS</span> gene pairs.</p>
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<p>Predicted protein–protein interaction networks of PsTPS proteins with other proteins using the STRING tool. Interactions between proteins are represented by gray lines.</p>
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<p>Expression profiles of the eight <span class="html-italic">PsTPS</span> genes. The color scale from blue to red indicates increasing log2-transformed FPKM values.</p>
Full article ">Figure 8
<p>Transcriptome analysis depicting the expression levels of 14 <span class="html-italic">PsTPS</span> genes in <span class="html-italic">Pisum sativum</span> under drought stress conditions induced by 10%, 20%, and 30% PEG6000 and salt stress induced by 100 mM, 200 mM, and 300 mM NaCl. Each experiment was conducted independently with a minimum of three replicates. “CK_0h” denotes the control group.</p>
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20 pages, 4594 KiB  
Article
Potential of Ca-Complexed in Amino Acid in Attenuating Salt Stress in Sour Passion Fruit Seedlings
by Antônio Gustavo de Luna Souto, Angela Maria dos Santos Pessoa, Sarah Alencar de Sá, Nayana Rodrigues de Sousa, Emerson Serafim Barros, Francimar Maik da Silva Morais, Fagner Nogueira Ferreira, Wedson Aleff Oliveira da Silva, Rafael Oliveira Batista, Daniel Valadão Silva, Rita Magally Oliveira da Silva Marcelino, Hans Raj Gheyi, Geovani Soares de Lima, Rosa Maria dos Santos Pessoa and Mailson Monteiro do Rêgo
Plants 2024, 13(20), 2912; https://doi.org/10.3390/plants13202912 - 17 Oct 2024
Viewed by 360
Abstract
Salt stress results in physiological changes that inhibit plant growth and development. Ca-complex sources are used as a potential salt stress attenuator. This study was carried out with the aim of verifying the effects of Ca-complex sources in reducing the effects of saline [...] Read more.
Salt stress results in physiological changes that inhibit plant growth and development. Ca-complex sources are used as a potential salt stress attenuator. This study was carried out with the aim of verifying the effects of Ca-complex sources in reducing the effects of saline water stress on the physiological aspects of sour passion fruit seedlings. The experiment was carried out in a randomized block design with a 2 × 2 × 3 factorial scheme, consisting of two cultivars of sour passion fruit (BRS GA1 and BRS SC1), two levels of water salinity (electrical conductivity of 0.5 and 4.0 dS m−1) and three sources of Ca-complex (without, organic acids and amino acids). The traits measured at 60 days after sowing were gas exchange, chlorophyll indices, chlorophyll fluorescence, electrolyte leakage, and relative water content in the leaf limb. Under moderate water salinity, the application of Ca-complex in amino acids promoted increases of 49.84% and 43.71%, respectively, in the efficiency of water use and carboxylation. The application of complex sources increased the stability of cell membranes, reducing electrolyte leakage, providing higher relative water content in seedlings irrigated with moderately saline water. From the results, we conclude that Ca-complex sources have potential as modulators of moderately saline water stress in sour passion fruit seedlings. Full article
(This article belongs to the Special Issue Mitigation Strategies and Tolerance of Plants to Abiotic Stresses)
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Figure 1
<p>Net assimilation rate—A (<b>A</b>), water use efficiency—WUE (<b>B</b>) and instantaneous carboxylation efficiency—iCE (<b>C</b>) of seedlings of sour passion fruit cultivars irrigated with low and moderate salinity water under application of Ca-complexed sources as attenuators. Means followed by same uppercase letters do not differ for cultivars within each irrigation water salinity and application of calcium sources, according to F test (<span class="html-italic">p</span> ≤ 0.05). Means followed by same lowercase letters do not differ for irrigation water salinity within each cultivar and calcium sources, by F test (<span class="html-italic">p</span> ≤ 0.05). Means followed by same Greek letters do not differ for calcium sources within each cultivar and irrigation water salinity, using Tukey test (<span class="html-italic">p</span> ≤ 0.05). Scatter above bar represents average standard deviation (<span class="html-italic">n</span> = 3).</p>
Full article ">Figure 2
<p>Leaf transpiration in seedlings of sour passion fruit cultivars irrigated with low and moderate salinity water (<b>A</b>), application of complex calcium sources (<b>B</b>) and internal CO<sub>2</sub> concentration of sour passion fruit seedlings irrigated with low and moderate salinity water and application of complex calcium sources (<b>C</b>). (<b>A</b>) Means followed by same uppercase letters do not differ for cultivars within each irrigation water salinity by F test (<span class="html-italic">p</span> ≤ 0.05) and means followed by same lowercase letters do not differ for irrigation water salinity within each cultivar by F test (<span class="html-italic">p</span> ≤ 0.05). (<b>B</b>) Means followed by same uppercase letters do not differ for cultivars within each calcium source by F test (<span class="html-italic">p</span> ≤ 0.05) and means followed by same lowercase letters do not differ for calcium sources within each passion fruit cultivar by Tukey test (<span class="html-italic">p</span> ≤ 0.05). (<b>C</b>) Means followed by same uppercase letters do not differ from each other for salinity of irrigation water within each calcium source by F test (<span class="html-italic">p</span> ≤ 0.05) and means followed by same lowercase letters do not differ from each other for calcium sources within each salinity of irrigation water by Tukey test (<span class="html-italic">p</span> ≤ 0.05). Scatter above bar represents average standard deviation (<span class="html-italic">n</span> = 3).</p>
Full article ">Figure 3
<p>Leaf transpiration in seedlings of sour passion fruit cultivars irrigated with low and moderate salinity water (<b>A</b>), application of complex calcium sources (<b>B</b>) and stomatal conductance of sour passion fruit seedlings irrigated with low and moderate salinity water and application of complex calcium sources (<b>C</b>). (<b>A</b>,<b>B</b>) Means followed by same lowercase letters do not differ for irrigation water salinity according to F test (<span class="html-italic">p</span> ≤ 0.05). (<b>C</b>) Means followed by same lowercase letters do not differ for calcium sources using Tukey test (<span class="html-italic">p</span> ≤ 0.05). Scatter above bar represents average standard deviation (<span class="html-italic">n</span> = 3).</p>
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<p>Chlorophyll <span class="html-italic">a</span> (<b>A</b>), chlorophyll <span class="html-italic">b</span> (<b>B</b>) and total chlorophyll (<b>C</b>) indices of seedlings of sour passion fruit cultivars irrigated with low and moderate salinity water under application of Ca-complex sources as attenuators. Means followed by same uppercase letters do not differ for cultivars within each irrigation water salinity and application of calcium sources, according to F test (<span class="html-italic">p</span> ≤ 0.05). Means followed by same lowercase letters do not differ for irrigation water salinity within each cultivar and calcium sources, by F test (<span class="html-italic">p</span> ≤ 0.05). Means followed by same Greek letters do not differ for calcium sources within each cultivar and irrigation water salinity, using Tukey test (<span class="html-italic">p</span> ≤ 0.05). Scatter above bar represents average standard deviation (<span class="html-italic">n</span> = 3).</p>
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<p>Electrolyte leakage (<b>A</b>) and relative water content (<b>B</b>) of seedlings of sour passion fruit cultivars irrigated with low and moderate salinity water under application of calcium complex sources as attenuators. Means followed by same uppercase letters do not differ for cultivars within each irrigation water salinity and application of calcium sources by F test (<span class="html-italic">p</span> ≤ 0.05). Means followed by same lowercase letters do not differ for irrigation water salinity within each cultivar and calcium sources by F test (<span class="html-italic">p</span> ≤ 0.05). Means followed by same Greek letters do not differ for calcium sources within each cultivar and irrigation water salinity by Tukey test (<span class="html-italic">p</span> ≤ 0.05). Scatter above bar represents mean standard deviation (<span class="html-italic">n</span> = 3).</p>
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<p>Principal component analysis (PCA) for the physiological traits of sour passion fruit seedlings cv. BRS GA1 irrigated with low and moderate salinity water under sources of complexed calcium as a mitigator (<span class="html-italic">n</span> = 3).</p>
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<p>Principal component analysis (PCA) for the physiological traits of sour passion fruit seedlings cv. BRS SC1 irrigated with low and moderate salinity water under sources of calcium complexed as an attenuator (<span class="html-italic">n</span> = 3).</p>
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<p>Temperature and relative humidity of air inside the protected environment during the experimental period (18 October to 18 December 2024).</p>
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19 pages, 15089 KiB  
Article
Genome-Scale Identification of Wild Soybean Serine/Arginine-Rich Protein Family Genes and Their Responses to Abiotic Stresses
by Yanping Wang, Xiaomei Wang, Rui Zhang, Tong Chen, Jialei Xiao, Qiang Li, Xiaodong Ding and Xiaohuan Sun
Int. J. Mol. Sci. 2024, 25(20), 11175; https://doi.org/10.3390/ijms252011175 - 17 Oct 2024
Viewed by 248
Abstract
Serine/arginine-rich (SR) proteins mostly function as splicing factors for pre-mRNA splicing in spliceosomes and play critical roles in plant development and adaptation to environments. However, detailed study about SR proteins in legume plants is still lacking. In this report, we performed a genome-wide [...] Read more.
Serine/arginine-rich (SR) proteins mostly function as splicing factors for pre-mRNA splicing in spliceosomes and play critical roles in plant development and adaptation to environments. However, detailed study about SR proteins in legume plants is still lacking. In this report, we performed a genome-wide investigation of SR protein genes in wild soybean (Glycine soja) and identified a total of 31 GsSR genes from the wild soybean genome. The analyses of chromosome location and synteny show that the GsSRs are unevenly distributed on 15 chromosomes and are mainly under the purifying selection. The GsSR proteins can be phylogenetically classified into six sub-families and are conserved in evolution. Prediction of protein phosphorylation sites indicates that GsSR proteins are highly phosphorylated proteins. The protein–protein interaction network implies that there exist numerous interactions between GsSR proteins. We experimentally confirmed their physical interactions with the representative SR proteins of spliceosome-associated components such as U1-70K or U2AF35 by yeast two-hybrid assays. In addition, we identified various stress-/hormone-responsive cis-acting elements in the promoter regions of these GsSR genes and verified their expression patterns by RT-qPCR analyses. The results show most GsSR genes are highly expressed in root and stem tissues and are responsive to salt and alkali stresses. Splicing analysis showed that the splicing patterns of GsSRs were in a tissue- and stress-dependent manner. Overall, these results will help us to further investigate the biological functions of leguminous plant SR proteins and shed new light on uncovering the regulatory mechanisms of plant SR proteins in growth, development, and stress responses. Full article
(This article belongs to the Special Issue Physiology and Molecular Biology of Plant Stress Tolerance)
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<p>Comparative phylogenetic tree of GsSR, AtSR, and OsSR proteins. The maximum likelihood (ML) tree was constructed based on the amino acid sequences of SR proteins from <span class="html-italic">Glycine soja</span>, <span class="html-italic">Arabidopsis thaliana,</span> and <span class="html-italic">Oryza sativa</span> using IQ-tree incorporated in TBtools with 5000 bootstrap replicates. The different colors indicate different sub-families.</p>
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<p>Chromosomal distribution and collinearity analysis of GsSR protein genes. (<b>A</b>) Chromosomal distribution of GsSR protein genes. The left scale determines the position of each <span class="html-italic">GsSR</span> on chromosome. Different shades of color reflect the distribution of gene density on chromosomes. (<b>B</b>) Inter-chromosomal relationships and segmental duplication of <span class="html-italic">GsSRs</span>. The green blocks indicate the part of wild soybean chromosomes (Chr01–Chr20). The duplicated GsSR protein gene pairs are highlighted in red lines. (<b>C</b>) Synteny analyses of SR protein genes between wild soybean and model plant species (Arabidopsis and rice). The gray lines indicate collinear blocks, and syntenic SR protein gene pairs are highlighted in blue lines.</p>
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<p>The gene structure and conserved protein motifs of 31 GsSR protein members. (<b>A</b>) The neighbor joining (NJ) tree was constructed using MEGA7 with 1000 bootstrap replicates. (<b>B</b>) Gene structure of GsSR protein genes. Grey boxes denote UTRs (untranslated regions); purple boxes denote exons; black lines denote introns. (<b>C</b>) Conserved motif analysis of GsSR proteins. A scale bar is provided at the bottom, and the length of each gene/protein is shown proportionally.</p>
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<p>Search of stress/hormone-associated <span class="html-italic">cis</span>-acting elements on <span class="html-italic">GsSR</span> gene promoters. (<b>A</b>) Putative stress/hormone-associated <span class="html-italic">cis</span>-acting elements in the promoter regions of <span class="html-italic">GsSR</span> genes. The putative <span class="html-italic">cis</span>-acting elements were searched from the 2000 bp promoter regions in the upstream of coding sequences of <span class="html-italic">GsSR</span> genes by using PlantCARE database. (<b>B</b>) Statistics of putative stress/hormone-associated <span class="html-italic">cis</span>-acting elements.</p>
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<p>Prediction of phosphorylation sites on GsSR proteins. (<b>A</b>) The distribution of phosphorylated serine (pSer), phosphorylated threonine (pThr), and phosphorylated tyrosine (pTyr) sites on GsSR proteins; (<b>B</b>) the sequence logos of the conserved motifs around the phosphosites (pSer or pTyr) extracted from GsSR proteins.</p>
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<p>Physical interactions between representative GsSR proteins and snRNPs revealed by Y2H assay. Yeast cells carrying the indicated constructs were diluted and grown on SD/-Trp-Leu or SD/-Trp-Leu-His medium for 6 days at 28 °C.</p>
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<p>Heatmap representation of expression profiles of the selected 20 <span class="html-italic">GsSR</span> genes in different tissues of wild soybean.</p>
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<p>Expression patterns of <span class="html-italic">GsSR</span> genes from wild soybean under salt and alkali stresses. (<b>A</b>) Expression patterns of selected 20 <span class="html-italic">GsSR</span> genes under salt treatment (150 mM NaCl) for 0, 3, 6 and 12 h respectively; (<b>B</b>) expression patterns of selected 10 <span class="html-italic">GsSR</span> genes under alkali treatment (150 mM NaHCO<sub>3</sub>) for 0, 3, 6, and 12 h, respectively. The error bars represent the standard error of the means of three replicates.</p>
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<p>Analyses of splicing patterns of selected eight <span class="html-italic">GsSR</span> genes based on RT-PCR. The diagrams on the left are schematic diagrams of predicted alternatively spliced transcripts of <span class="html-italic">GsSR6</span>, <span class="html-italic">GsSR11</span>, <span class="html-italic">Gs17</span>, and <span class="html-italic">GsSR29</span>. Green boxes represent exons, purple boxes represent untranslated regions (UTRs), and black lines represent introns. The red arrowheads indicate the position of primers used for RT-PCR. The numbers in the middle indicate the expected sizes of PCR products. The diagrams on the right are the representative gel images of RT-PCR results. The wild soybean seedlings were treated with salt (200 mM NaCl) or alkali (100 mM NaHCO<sub>3</sub>) for 6 h. R: root, L: leaf.</p>
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18 pages, 2773 KiB  
Article
Probiotic and Postbiotic Potentials of Enterococcus faecalis EF-2001: A Safety Assessment
by Kwon Il Han, Hyun-Dong Shin, Yura Lee, Sunhwa Baek, Eunjung Moon, Youn Bum Park, Junhui Cho, Jin-Ho Lee, Tack-Joong Kim and Ranjith Kumar Manoharan
Pharmaceuticals 2024, 17(10), 1383; https://doi.org/10.3390/ph17101383 - 17 Oct 2024
Viewed by 248
Abstract
Background: Probiotics, which are live microorganisms that, when given in sufficient quantities, promote the host’s health, have drawn a lot of interest for their ability to enhance gut health. Enterococcus faecalis, a member of the human gut microbiota, has shown promise as [...] Read more.
Background: Probiotics, which are live microorganisms that, when given in sufficient quantities, promote the host’s health, have drawn a lot of interest for their ability to enhance gut health. Enterococcus faecalis, a member of the human gut microbiota, has shown promise as a probiotic candidate due to its functional attributes. However, safety concerns associated with certain strains warrant comprehensive evaluation before therapeutic application. Materials and Methods: In this study, E. faecalis EF-2001, originally isolated from fecal samples of a healthy human infant, was subjected to a multi-faceted assessment for its safety and probiotic potential. In silico analysis, CAZyme, biosynthetic, and stress-responsive proteins were identified. Results: The genome lacked biogenic amine genes but contained some essential amino acid and vitamin synthetic genes, and carbohydrate-related enzymes essential for probiotic properties. The negligible difference of 0.03% between the 1st and 25th generations indicates that the genetic information of the E. faecalis EF-2001 genome remained stable. The live E. faecalis EF-2001 (E. faecalis EF-2001L) demonstrated low or no virulence potential, minimal D-Lactate production, and susceptibility to most antibiotics except some aminoglycosides. No bile salt deconjugation or biogenic amine production was observed in an in vitro assay. Hemolytic activity assessment showed a β-hemolytic pattern, indicating no red blood cell lysis. Furthermore, the EF-2001L did not produce gelatinase and tolerated simulated gastric and intestinal fluids in an in vitro study. Similarly, heat-killed E. faecalis EF-2001 (E. faecalis EF-2001HK) exhibits tolerance in both acid and base conditions in vitro. Further, no cytotoxicity of postbiotic EF-2001HK was observed in human colorectal adenocarcinoma HT-29 cells. Conclusions: These potential properties suggest that probiotic and postbiotic E. faecalis EF-2001 could be considered safe and retain metabolic activity suitable for human consumption. Full article
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<p>Phenotypic safety assessment of EF-2001L. (<b>A</b>) Cell morphology by SEM analysis. (<b>B</b>) Hemolytic activity of <span class="html-italic">E. faecalis</span> EF-2001L and <span class="html-italic">S. aureus</span> ATCC 6538 (positive control). (<b>C</b>) Gelatinase activity of <span class="html-italic">E. faecalis</span> EF-2001L. (<b>D</b>) Acid tolerance. Control refers to neutral pH. (<b>E</b>) Survival of <span class="html-italic">E. faecalis</span> EF-2001L in simulated gastric fluid (SGF) and simulated intestinal fluid (SIF). (<b>F</b>,<b>G</b>) Co-aggregation and auto-aggregation abilities. * <span class="html-italic">p</span> &lt; 0.05 a significant difference between corresponding values at 0 h and treatment time intervals. Each experiment was performed using three independent cultures. (<b>H</b>). Bile salt deconjugation test. (<b>I</b>) D-lactate production assay. −ve and +ve denote negative and positive, respectively.</p>
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<p>Carbohydrate utilization of <span class="html-italic">E. faecalis</span> EF-2001L.</p>
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<p>Safety assessment of EF-2001HK <span class="html-italic">(</span><b>A</b>) Heat-killed probiotic powder (<span class="html-italic">E. faecalis</span> EF-2001 HK) (<b>B</b>) Cell morphology by SEM analysis. (<b>C</b>) Cytotoxicity of <span class="html-italic">E. faecalis</span> EF-2001HK using human colorectal adenocarcinoma HT-29 cells. * <span class="html-italic">p</span> &lt; 0.05 vs untreated control. (<b>D</b>,<b>E</b>) Auto-aggregation and co-aggregation abilities. (<b>E</b>,<b>F</b>) Log10 value of <span class="html-italic">E. faecalis</span> EF-2001HK cell numbers per gram exposed in pH 2 to 9 for respective days.</p>
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<p>Schematic diagram of probiotic and postbiotic properties of <span class="html-italic">E. faecalis</span> EF-2001.</p>
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12 pages, 2617 KiB  
Article
ZmLSD1 Enhances Salt Tolerance by Regulating the Expression of ZmWRKY29 in Maize
by Qiaolu Li, Rongrong Hu, Min Jiang, Wei Zhang, Xinyi Gao, Binglin Zhang, Weijuan Liu, Zhongyi Wu and Huawen Zou
Plants 2024, 13(20), 2904; https://doi.org/10.3390/plants13202904 - 17 Oct 2024
Viewed by 185
Abstract
Salt stress significantly impairs plant growth, presenting a challenge to agricultural productivity. Exploring the regulatory mechanisms underlying salt stress responses is critically important. Here, we identified a significant role for the maize LESION-SIMULATING DISEASE transcription factor, ZmLSD1, in enhancing salt stress response. Subcellular [...] Read more.
Salt stress significantly impairs plant growth, presenting a challenge to agricultural productivity. Exploring the regulatory mechanisms underlying salt stress responses is critically important. Here, we identified a significant role for the maize LESION-SIMULATING DISEASE transcription factor, ZmLSD1, in enhancing salt stress response. Subcellular localization analysis indicated that ZmLSD1-GFP was localized in the nucleus in the maize protoplast. Overexpressing ZmLSD1 in maize obviously enhanced the tolerance of plants to salt stress. Physiological analysis indicated that overexpressed ZmLSD1 in maize could mitigate the accumulation of H2O2 and MDA content exposed to salt stress. RNA-seq and qPCR-PCR analyses showed that ZmLSD1 positively regulated ZmWRKY29 expression. ChIP-qPCR and EMSA experiments demonstrated that ZmLSD1 could directly bind to the promoter of ZmWRKY29 through the GTAC motif both in vitro and in vivo. Overall, our findings suggest that ZmLSD1 plays a positive role in enhancing the tolerance of maize to salt by affecting ZmWRKY29 expression. Full article
(This article belongs to the Special Issue Stress-Resilient Maize for Climate-Vulnerable Environments)
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<p>Overexpressing <span class="html-italic">ZmLSD1</span> in maize improves plant survival rates under salt stress. (<b>A</b>) PCR detection of transgenic maize lines. (<b>B</b>) Protein level of ZmLSD1 in transgenic maize lines. (<b>C</b>) Phenotype of wild type and <span class="html-italic">ZmLSD1</span> overexpressors under salt stress. Ten-day-old seedlings were treated with 200 mmol/L NaCl for seven days and fourteen days. Scale bar: 5 cm. (<b>D</b>) Survival rate of wild type and <span class="html-italic">ZmLSD1</span> overexpressors after 14 days of treatment with 200 mmol/L NaCl in (<b>C</b>). The experiment shown in (<b>C</b>,<b>D</b>) was performed at least three times. Error bars in (<b>D</b>) indicate SD (<span class="html-italic">n</span> = 12). Different letters indicate a significant difference (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Effect of ZmLSD1 on lipid peroxidation and H<sub>2</sub>O<sub>2</sub> accumulation under salt stress. (<b>A</b>) MDA content. (<b>B</b>) Detection of H<sub>2</sub>O<sub>2</sub> accumulation using DAB staining. Scale bar: 1 cm. (<b>C</b>) H<sub>2</sub>O<sub>2</sub> content. The experiments were performed three times. Error bars in (<b>A</b>,<b>C</b>) indicate SD (<span class="html-italic">n</span> = 3). Different letters indicate a significant difference (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Subcellular localization of ZmLSD1. ZmLSD1-GFP constructs were introduced into maize protoplasts for transient expression. Nuclei (red arrow) were stained with DAPI (in blue). Scale bar: 5 μm.</p>
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<p>Transcriptome analysis identifies key genes regulated by ZmLSD1 under salt stress treatment. (<b>A</b>) Venn diagrams analyzing number of DEGs in wild type and <span class="html-italic">ZmLSD1</span> overexpressors treated with or without 200 mmol/L NaCl. (<b>B</b>) Heatmap analysis of 75 DEGs overlapping/shared in (<b>A</b>). (<b>C</b>) KEGG pathway analysis of genes in (<b>B</b>).</p>
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<p>The expression level of <span class="html-italic">ZmWRKY29</span> in the <span class="html-italic">ZmLSD1</span> overexpressor and WT under salt stress. Ten-day-old seedlings were subjected to a 48-h treatment with 200 mmol/L NaCl. Subsequently, the second leaves were collected from the seedlings for qRT-PCR analysis. Error bars indicate SD (<span class="html-italic">n</span> = 3). Different letters indicate a significant difference (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>ZmLSD1 directly binds to <span class="html-italic">ZmWRKY29</span> promoters. (A) ChIP-qPCR verified that ZmLSD1 directly bound to the <span class="html-italic">ZmWRKY29</span> promoter in <span class="html-italic">vivo</span>. P2 (−600 to −597 bp) and P3 (−232 to −229 bp) contained the GTAC motif, but P1 did not have the GTAC motif. Chromatin was extracted from the <span class="html-italic">ZmLSD1</span> overexpressor and subjected to immunoprecipitation using an anti-Flag antibody. qPCR was used to assess expression levels with a reference value of 1 assigned to the control (without antibody). (<b>B</b>) EMSA showed that ZmLSD1 bound to the <span class="html-italic">ZmWRKY29</span> promoter in <span class="html-italic">vitro</span>. The His-ZmLSD1 purified protein was incubated with a biotin-labeled probe (referred to as Biotin-Probe), while a 100-fold excess of an unlabeled probe (referred to as Cold-Probe) was used as a competitive control. Error bars in (<b>A</b>) indicate SD (<span class="html-italic">n</span> = 3). Different letters indicate a significant difference (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>A model of ZmLSD1 activity in maize salt response. ZmLSD1 plays a positive role in enhancing the salt tolerance of maize by binding to the <span class="html-italic">ZmWRKY29</span> promoter and affecting its expression.</p>
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12 pages, 2742 KiB  
Article
Effects of OsLPR2 Gene Knockout on Rice Growth, Development, and Salt Stress Tolerance
by Ying Gu, Chengfeng Fu, Miao Zhang, Changqiang Jin, Yuqi Li, Xingyu Chen, Ruining Li, Tingting Feng, Xianzhong Huang and Hao Ai
Agriculture 2024, 14(10), 1827; https://doi.org/10.3390/agriculture14101827 - 17 Oct 2024
Viewed by 321
Abstract
Rice (Oryza sativa L.), a globally staple food crop, frequently encounters growth, developmental, and yield limitations due to phosphate deficiency. LOW PHOSPHATE ROOT1/2 (LPR1/2) are essential genes in plants that regulate primary root growth and respond [...] Read more.
Rice (Oryza sativa L.), a globally staple food crop, frequently encounters growth, developmental, and yield limitations due to phosphate deficiency. LOW PHOSPHATE ROOT1/2 (LPR1/2) are essential genes in plants that regulate primary root growth and respond to local phosphate deficiency signals under low phosphate stress. In rice, five LPR genes, designated OsLPR1OsLPR5 based on their sequence identity with AtLPR1, have been identified. OsLPR3 and OsLPR5 are specifically expressed in roots and induced by phosphate deficiency, contributing to rice growth, development, and the maintenance of phosphorus homeostasis under low phosphate stress. In contrast, OsLPR2 is uniquely expressed in shoots, suggesting it may have distinct functions compared with other family members. This study employed Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-associated protein 9 (CRISPR/Cas9) gene editing technology to generate oslpr2 mutant transgenic lines and subsequently investigated the effect of OsLPR2 gene knockout on rice growth, phosphate utilization, and salt stress tolerance in the seedling stage, as well as the effect of OsLPR2 gene knockout on rice development and agronomic traits in the maturation stage. The results indicated that the knockout of OsLPR2 did not significantly impact rice seedling growth or phosphate utilization, which contrasts significantly with its homologous genes, OsLPR3 and OsLPR5. However, the mutation influenced various agronomic traits at maturity, including plant height, tiller number, and seed setting rate. Moreover, the OsLPR2 mutation conferred enhanced salt stress tolerance in rice. These findings underscore the distinct roles of OsLPR2 compared with other homologous genes, establishing a foundation for further investigation into the function of the OsLPR family and the functional differentiation among its members. Full article
(This article belongs to the Section Crop Genetics, Genomics and Breeding)
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<p>Transcript level of <span class="html-italic">OsLPR2</span> under different nutrient deficiencies. Wild type rice seedlings of Nipponbare were cultivated for 7 days in complete nutrient solution (CK) or in nutrient-deficiency solution, which excluded nitrogen (−N), phosphorus (−P), potassium (−K), magnesium (−Mg), or iron (−Fe). Relative expression levels of OsLPR2 in shoot (<b>A</b>) and root (<b>B</b>) were determined via qRT-PCR. Values are presented as means ± SE (<span class="html-italic">n</span> = 3). Different letters above the bars indicate significant differences in the relative expression levels of OsLPR2 (<span class="html-italic">p</span> &lt; 0.05, one-way ANOVA).</p>
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<p>Construction and identification of <span class="html-italic">OsLPR2</span> mutant material. (<b>A</b>) Schematic diagram of the <span class="html-italic">oslpr2</span> target sites. (<b>B</b>) Identification of positive <span class="html-italic">oslpr2</span> seedlings. (<b>C</b>) Sequencing sequences and chromatograms of homozygous <span class="html-italic">oslpr2</span> mutant lines. (<b>D</b>) Cas9 segregation identification of mutant lines.</p>
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<p>The effect of <span class="html-italic">OsLPR2</span> mutation on the plant height and tillers per plant at maturity. (<b>A</b>) Plant types. (<b>B</b>) Plant height. (<b>C</b>) Number of tillers per plant. Scale bar: 20 cm. Values are means ± SE (<span class="html-italic">n</span> = 15). Different letters above the bars indicate significant differences (<span class="html-italic">p</span> &lt; 0.05, one-way ANOVA).</p>
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<p>The effect of <span class="html-italic">OsLPR2</span> mutation on panicle type of rice. (<b>A</b>) Panicle types. (<b>B</b>) Panicle length. (<b>C</b>) Number of primary branches. (<b>D</b>) Number of secondary branches. (<b>E</b>) Number of grains per panicle. (<b>F</b>) Seed setting rate. Scale bar: 5 cm. Values are means ± SE (<span class="html-italic">n</span> = 15). Different letters above the bars indicate significant differences (<span class="html-italic">p</span> &lt; 0.05, one-way ANOVA).</p>
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<p>The effect of <span class="html-italic">OsLPR2</span> mutation on the lengths of shoots and roots. (<b>A</b>,<b>B</b>) Images showing the relative growth performances of WT and <span class="html-italic">oslpr2</span> mutant lines under +P and −P conditions (bar = 10 cm). (<b>C</b>,<b>E</b>) Lengths and biomass of shoots or roots under phosphate sufficiency. (<b>D</b>,<b>F</b>) Lengths and biomass of shoots and roots under phosphate deficiency. Values are presented as means ± SE (<span class="html-italic">n</span> = 6). Same letters above the bars indicate no significant differences (<span class="html-italic">p</span> &lt; 0.05, one-way ANOVA).</p>
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<p>The effect of <span class="html-italic">OsLPR2</span> mutation on soluble Pi concentration of rice. (<b>A</b>) <span class="html-italic">OsLPR2</span> transgenic materials and wild type plants with consistent growth under normal phosphate supply. (<b>B</b>) After 21 days of phosphate deficiency treatment, sampling of different plant parts (leaves, leaf sheaths, roots) for extractable phosphate content measurement. Values are means ± SE (<span class="html-italic">n</span> = 3). Different letters above the bars indicate significant differences (<span class="html-italic">p</span> &lt; 0.05, one-way ANOVA).</p>
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<p>Assessment of <span class="html-italic">oslpr2</span> mutant survival and physiological responses under saline conditions. (<b>A</b>) Phenotypes of WT and <span class="html-italic">oslpr2</span> mutants after 200 mM NaCl treatment. (<b>B</b>) Survival rate statistics. (<b>C</b>) POD activity after 150 mM NaCl treatment. (<b>D</b>) MDA content after 150 mM NaCl treatment. Values are means ± SE (<span class="html-italic">n</span> = 3). Different letters above the bars indicate significant differences (<span class="html-italic">p</span> &lt; 0.05, one-way ANOVA).</p>
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16 pages, 3185 KiB  
Article
The Effect of Szigetvár Medicinal Water on HaCaT Cells Exposed to Dithranol
by István Szabó, Ágnes Szenczi, Afshin Zand, Tímea Varjas and Csaba Varga
Life 2024, 14(10), 1318; https://doi.org/10.3390/life14101318 - 17 Oct 2024
Viewed by 308
Abstract
(1) Introduction: Topical dithranol is still commonly used today as an effective treatment for psoriasis. Dithranol treatment is often supplemented with balneotherapy, which has been shown to increase effectiveness and reduce side effects. The inorganic salts (sulfhide, selenium, zinc) are usually thought to [...] Read more.
(1) Introduction: Topical dithranol is still commonly used today as an effective treatment for psoriasis. Dithranol treatment is often supplemented with balneotherapy, which has been shown to increase effectiveness and reduce side effects. The inorganic salts (sulfhide, selenium, zinc) are usually thought to be responsible for the effect. The antioxidant effect of the waters is thought to be behind the therapeutic effect, for which inorganic substances (sulfides, selenium, zinc) are thought to be responsible. The organic matter content of medicinal waters is also particularly important, as humic acids, which are often found in medicinal waters, have antioxidant effects. (2) Methods: In this short-term experiment, we aimed to test the possible protective effect of Szigetvár medicinal water and its organic matter isolate on HaCaT cells exposed to dithranol. Malondialdehyde levels were measured, and RT-qPCR was used to investigate the gene expression of selected cytokines relevant in the oxidative stress response (IL-6, IL-8, TNF-α, GM-CSF) and the expression of microRNA-21. (3) Results: Szigetvár medicinal water and the organic isolate prevented the increase in malondialdehyde levels caused by dithranol treatment. The cytokine gene expressions elevated by dithranol exposure were reduced by the treatment. (4) Conclusions: Szigetvár medicinal water and organic substances alone may have a protective effect on patients’ healthy skin surfaces against dithranol damage. We also demonstrated that the organic compounds are also responsible for the protective effect. Full article
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<p>The sequence of the primers used in the experiment.</p>
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<p>(<b>a</b>) Survival of HaCaT cells in different dilutions of Szigetvár organic matter isolate in 3 h. (<b>b</b>) Survival of HaCaT cell in different concentrations of Szigetvár medicinal water containing cell culture medium (SVNM). 6×–3000×–dilution of the isolate (Composition shown in <a href="#life-14-01318-t001" class="html-table">Table 1</a>) in 10–90% Szigetvár medicinal water content of different studied SVNMs.</p>
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<p>Amount of MDA (nmol/sample) in HaCaT cells in different experimental settings (See <a href="#life-14-01318-t002" class="html-table">Table 2</a>). (* = <span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Relative gene expression level of TNF-α in HaCaT cells treated according to the experimental protocol. (* = <span class="html-italic">p</span> &lt; 0.05). DTH—dithranol; 120×, 600×, 1200×-dilution of the tested organic matter isolate (Composition shown in <a href="#life-14-01318-t001" class="html-table">Table 1</a>); SVNM—Cell culture medium with 90% Szigetvár medicinal water content.</p>
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<p>Relative gene expression level of GM-CSF in HaCaT cells treated according to the experimental protocol. (* = <span class="html-italic">p</span> &lt; 0.05). DTH—dithranol; 120×, 600×, 1200×-dilution of the tested organic matter isolate (Composition shown in <a href="#life-14-01318-t001" class="html-table">Table 1</a>); SVNM—Cell culture medium with 90% Szigetvár medicinal water content.</p>
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<p>Relative gene expression level of IL-6 in HaCaT cells treated according to the experimental protocol. (* = <span class="html-italic">p</span> &lt; 0.05). DTH—dithranol; 120×, 600×, 1200×—dilution of the tested organic matter isolate (Composition shown in <a href="#life-14-01318-t001" class="html-table">Table 1</a>.); SVNM—Cell culture medium with 90% Szigetvár medicinal water content.</p>
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<p>Relative gene expression level of IL-8 in HaCaT cells treated according to the experimental protocol. (* = <span class="html-italic">p</span> &lt; 0.05). DTH—dithranol; 120×, 600×, 1200×-dilution of the tested organic matter isolate (Composition shown in <a href="#life-14-01318-t001" class="html-table">Table 1</a>); SVNM—Cell culture medium with 90% Szigetvár medicinal water content.</p>
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<p>Relative gene expression level of miR-21 in HaCaT cells treated according to the experimental protocol. (* = <span class="html-italic">p</span> &lt; 0.05). DTH—dithranol; 120×, 600×, 1200×-dilution of the tested organic matter isolate (Composition shown in <a href="#life-14-01318-t001" class="html-table">Table 1</a>); SVNM—Cell culture medium with 90% Szigetvár medicinal water content.</p>
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22 pages, 14941 KiB  
Article
Profiling of Key Hub Genes Using a Two-State Weighted Gene Co-Expression Network of ‘Jao Khao’ Rice under Soil Salinity Stress Based on Time-Series Transcriptome Data
by Prasit Khunsanit, Kitiporn Plaimas, Supachitra Chadchawan and Teerapong Buaboocha
Int. J. Mol. Sci. 2024, 25(20), 11086; https://doi.org/10.3390/ijms252011086 - 16 Oct 2024
Viewed by 317
Abstract
RNA-sequencing enables the comprehensive detection of gene expression levels at specific time points and facilitates the identification of stress-related genes through co-expression network analysis. Understanding the molecular mechanisms and identifying key genes associated with salt tolerance is crucial for developing rice varieties that [...] Read more.
RNA-sequencing enables the comprehensive detection of gene expression levels at specific time points and facilitates the identification of stress-related genes through co-expression network analysis. Understanding the molecular mechanisms and identifying key genes associated with salt tolerance is crucial for developing rice varieties that can thrive in saline environments, particularly in regions affected by soil salinization. In this study, we conducted an RNA-sequencing-based time-course transcriptome analysis of ‘Jao Khao’, a salt-tolerant Thai rice variety, grown under normal or saline (160 mM NaCl) soil conditions. Leaf samples were collected at 0, 3, 6, 12, 24, and 48 h. In total, 36 RNA libraries were sequenced. ‘Jao Khao’ was found to be highly salt-tolerant, as indicated by the non-significant differences in relative water content, cell membrane stability, leaf greenness, and chlorophyll fluorescence over a 9-day period under saline conditions. Plant growth was slightly retarded during days 3–6 but recovered by day 9. Based on time-series transcriptome data, we conducted differential gene expression and weighted gene co-expression network analyses. Through centrality change from normal to salinity network, 111 key hub genes were identified among 1,950 highly variable genes. Enriched genes were involved in ATP-driven transport, light reactions and response to light, ATP synthesis and carbon fixation, disease resistance and proteinase inhibitor activity. These genes were upregulated early during salt stress and RT-qPCR showed that ‘Jao Khao’ exhibited an early upregulation trend of two important genes in energy metabolism: RuBisCo (LOC_Os10g21268) and ATP synthase (LOC_Os10g21264). Our findings highlight the importance of managing energy requirements in the initial phase of the plant salt-stress response. Therefore, manipulation of the energy metabolism should be the focus in plant resistance breeding and the genes identified in this work can serve as potentially effective candidates. Full article
(This article belongs to the Special Issue Abiotic Stress Tolerance and Genetic Diversity in Plants, 2nd Edition)
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<p>Comparison of phenotypic traits between normal and saline conditions of ‘Jao Khao’. (<b>A</b>) tiller number, (<b>B</b>) SES, (<b>C</b>) shoot fresh weight, (<b>D</b>) root fresh weight, (<b>E</b>) shoot dry weight, (<b>F</b>) root dry weight, (<b>G</b>) shoot dry-to-fresh weight ratio, (<b>H</b>) root dry-to-fresh weight ratio, (<b>I</b>) CMS, and (<b>J</b>) RWC. Data are presented as means ± SD (n = 3). Statistical significance was determined using the Duncan multiple range test. Significant differences (<span class="html-italic">p</span> ≤ 0.05) are indicated by different letters. ns: not significant.</p>
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<p>Leaf greenness and chlorophyll fluorescence of ‘Jao Khao’ compared between that of control and salt conditions. (<b>A</b>) SPAD index, (<b>B</b>) Maximum PSII efficiency (Fv/Fm), and (<b>C</b>) Performance index (Pi). Data are presented as means ± SD (n = 3). Statistical significance was determined using the Duncan multiple range test. Significant differences (<span class="html-italic">p</span> ≤ 0.05) are indicated by different letters. ns: not significant.</p>
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<p>Normalized read counts of 36 RNA-sequencing library (<b>A</b>), scale-free topology and mean connectivity (the horizontal red line was at <span class="html-italic">R</span><sup>2</sup> = 0.9) (<b>B</b>), the heatmap of topological overlapping matrix (TOM) plot visualizing the strength of the connections (similarity) between genes with the bright yellow color indicating genes with more connections or shared neighbors in the network and the colors representing modules displayed on both axes (<b>C</b>), and module–trait relationships (MTR) (<b>D</b>). The colors of modules include blue, red, turquoise, green, brown, yellow and grey. The letters ct and ss indicate control conditions and salt stress conditions, respectively. ME: Module Eigengene, a representative of gene expression levels in a cluster of co-expressed genes. Significant differences (<span class="html-italic">p</span> ≤ 0.05) are indicated by *.</p>
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<p>Comparison of the distribution of centrality between the normal-state and saline-state networks for (<b>A</b>) degree, (<b>B</b>) closeness, (<b>C</b>) betweenness, and (<b>D</b>) the clustering coefficient.</p>
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<p>Gene Ontology (GO) enrichment analysis results for each module. <span class="html-italic">p</span>-values were adjusted using the Benjamini–Hochberg correction. (<b>A</b>) Brown module, (<b>B</b>) turquoise module, (<b>C</b>) yellow module, (<b>D</b>) blue module, (<b>E</b>) red module, and (<b>F</b>) green module. GO terms include biological process (BP), cellular component (CC), and molecular function (MF).</p>
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<p>Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment results for each module. <span class="html-italic">p</span>-values were adjusted using the Benjamini–Hochberg correction.</p>
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<p>Gene networks and key genes were identified based on the centrality change between the two states (normal and saline) and mapped to the global state network. (<b>A</b>) Brown module, (<b>B</b>) turquoise module, (<b>C</b>) yellow module, (<b>D</b>) blue module, (<b>E</b>) red module, (<b>F</b>) green module, and (<b>G</b>) grey module. Small nodes and edges are colored according to the module they belong to. Large nodes represent key genes detected based on DG, BW, CN, and CC centrality, with combinations of 1, 2, 3, and 4 centrality measures, which are indicated in bright colors: green, blue, orange, and red, respectively.</p>
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<p>Relative expression levels (fold change) of two genes involved in energy metabolism: <span class="html-italic">LOC_Os10g21268</span> and <span class="html-italic">LOC_Os10g21264</span> in three varieties: ‘Jao Khao’ (<b>A</b>,<b>D</b>), ‘Pokkali’ (<b>B</b>,<b>E</b>), and ‘IR29’ (<b>C</b>,<b>F</b>) grown under salt stress conditions relative to those under control conditions by RT-qPCR. Data are presented as means ± SD (<span class="html-italic">n</span> = 3). Statistical significance was determined using the Duncan multiple range test. Significant differences (<span class="html-italic">p</span> ≤ 0.05) are indicated by different letters.</p>
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<p>Proposed mechanism of salt stress responses in ‘Jao Khao’ rice as inferred from a comprehensive analysis of time-course transcriptome data. Names bordered by colored lines are key genes. Transcription factors are shown in red letters. GO enrichment analysis revealed several GO terms related to key plant energy metabolism processes, such as light reactions, carbon fixation, and ATP synthesis. Many genes associated with these GO terms exhibited increased expression under salt stress. These enriched processes indicate the importance of maintaining energy production early during salt stress to regulate ion and water uptake and transport. Other enriched GO terms suggested the involvement of ATP-driven transport and the ubiquitination-proteasome pathway in responses to salt stress. Several candidate transcription factors, including <span class="html-italic">bZIP46</span>, <span class="html-italic">SPL4</span>, <span class="html-italic">ASR5</span>, and the transcriptional corepressor LEUNIG, may coordinate these processes. Dash-arrows and question marks suggest potential regulatory relationships.</p>
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<p>Diagram illustrating the co-expression network analysis pipeline used in the present study.</p>
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12 pages, 2085 KiB  
Article
Rapidly Evolved Genes in Three Reaumuria Transcriptomes and Potential Roles of Pentatricopeptide Repeat Superfamily Proteins in Endangerment of R. trigyna
by Ruizhen Zhang, Xiaoyun Cui and Pengshan Zhao
Int. J. Mol. Sci. 2024, 25(20), 11065; https://doi.org/10.3390/ijms252011065 - 15 Oct 2024
Viewed by 292
Abstract
Reaumuria genus (Tamaricaceae) is widely distributed across the desert and semi-desert regions of Northern China, playing a crucial role in the restoration and protection of desert ecosystems. Previous studies mainly focused on the physiological responses to environmental stresses; however, due to the limited [...] Read more.
Reaumuria genus (Tamaricaceae) is widely distributed across the desert and semi-desert regions of Northern China, playing a crucial role in the restoration and protection of desert ecosystems. Previous studies mainly focused on the physiological responses to environmental stresses; however, due to the limited availability of genomic information, the underlying mechanism of morphological and ecological differences among the Reaumuria species remains poorly understood. In this study, we presented the first catalog of expressed transcripts for R. kaschgarica, a sympatric species of xerophyte R. soongorica. We further performed the pair-wise transcriptome comparison to determine the conserved and divergent genes among R. soongorica, R. kaschgarica, and the relict recretohalophyte R. trigyna. Annotation of the 600 relatively conserved genes revealed that some common genetic modules are employed by the Reaumuria species to confront with salt and drought stresses in arid environment. Among the 250 genes showing strong signs of positive selection, eight pentatricopeptide repeat (PPR) superfamily protein genes were specifically identified, including seven PPR genes in the R. soongorica vs. R. trigyna comparison and one PPR gene in the R. kaschgarica vs. R. trigyna comparison, while the cyclin D3 gene was found in the R. soongorica vs. R. trigyna comparison. These findings suggest that genetic variations in PPR genes may affect the fertility system or compromise the extent of organelle RNA editing in R. trigyna. The present study provides valuable genomic information for R. kaschgarica and preliminarily reveals the conserved genetic bases for the abiotic stress adaptation and interspecific divergent selection in the Reaumuria species. The rapidly evolved PPR and cyclin D3 genes provide new insights on the endangerment of R. trigyna and the leaf length difference among the Reaumuria species. Full article
(This article belongs to the Section Molecular Biology)
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<p>Distribution and morphology of three <span class="html-italic">Reaumuria</span> species. (<b>A</b>) Distribution of three <span class="html-italic">Reaumuria</span> species. The background imagery is from GEBCO_2014 Grid, version 20150318 (<a href="http://www.gebco.net" target="_blank">http://www.gebco.net</a>), and the desert dataset (in orange) is provided by National Cryosphere Desert Data Center (NCDC, <a href="http://www.ncdc.ac.cn/" target="_blank">http://www.ncdc.ac.cn/</a>). The map was generated based on the latitude and longitude of the location sites of each species. The information for each red dot of <span class="html-italic">R. soongorica</span> was from the natural field survey and previous report [<a href="#B2-ijms-25-11065" class="html-bibr">2</a>]. The distribution information of <span class="html-italic">R. kaschgarica</span> (green dots) was modified according to the description by Hao et al. [<a href="#B7-ijms-25-11065" class="html-bibr">7</a>]. Dark gray dots represent the location of <span class="html-italic">R. trigyna</span>, and the information was based on the natural field survey and previous publications [<a href="#B7-ijms-25-11065" class="html-bibr">7</a>,<a href="#B8-ijms-25-11065" class="html-bibr">8</a>,<a href="#B9-ijms-25-11065" class="html-bibr">9</a>]. (<b>B</b>) Morphology of <span class="html-italic">R. soongorica</span>, <span class="html-italic">R. trigyna</span>, and <span class="html-italic">R. kaschgarica</span> in their habitat. (<b>C</b>) Dry leaves and leaf length of <span class="html-italic">R. soongorica</span>, <span class="html-italic">R. trigyna</span>, and <span class="html-italic">R. kaschgarica</span> (<span class="html-italic">n</span> = 20).</p>
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<p>Analysis of the <span class="html-italic">R. kaschgarica</span> transcriptome. (<b>A</b>) Length distribution of assembled unigenes. (<b>B</b>) Taxonomic distribution of the top Blast hits in Nr database for each unigene.</p>
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<p>Characteristics of three <span class="html-italic">Reaumuria</span> transcriptomes. (<b>A</b>,<b>B</b>) Boxplots of unigene length and GC content of assembled unigenes. (<b>C</b>,<b>D</b>) Boxplots of percentage identity and percentage coverage of each <span class="html-italic">Reaumuria</span> unigene versus an <span class="html-italic">Arabidopsis</span> peptide. The percentage coverage is the longest positive hit/protein length ratio [<a href="#B23-ijms-25-11065" class="html-bibr">23</a>]. Rk, <span class="html-italic">R. kaschgarica</span>; Rt, <span class="html-italic">R. trigyna</span>; Rs, <span class="html-italic">R. soongorica</span>.</p>
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<p>Venn diagram of orthologous genes and scatter diagram of Ka and Ks values for three <span class="html-italic">Reaumuria</span> species. (<b>A</b>) Orthologous genes of three <span class="html-italic">Reaumuria</span> species. There are 5182 orthologous groups, each containing three genes from <span class="html-italic">R. kaschgarica</span>, <span class="html-italic">R. trigyna</span>, and <span class="html-italic">R. soongorica</span>. (<b>B</b>) The number of genes under purifying selection in each pair-wise transcriptome comparison. Six hundred relatively conserved genes are identified in three <span class="html-italic">Reaumuria</span> species. (<b>C</b>) Positively selected genes in three pair-wise comparisons. Only one highly divergent gene is found among three <span class="html-italic">Reaumuria</span> species. (<b>D</b>) Rapidly evolved PPR genes in <span class="html-italic">Reaumuria</span>. (<b>E</b>–<b>G</b>) Ka and Ks values of three comparisons were estimated. Orthologous genes with Ka &gt; 1 are excluded. Green dots represent divergent ortholog genes with Ka/Ks &gt; 1, red dots indicate conserved ortholog genes with Ka/Ks &lt; 0.1, and blue dots represent no positive or negative selections were detected.</p>
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17 pages, 3926 KiB  
Article
Minimizing the Adverse Impacts of Soil Salinity on Maize and Tomato Growth and Productivity through the Application of Plant Growth-Promoting Rhizobacteria
by Hiba Yahyaoui, Nadia El Allaoui, Aziz Aziz, Majida Hafidi and Khaoula Habbadi
Crops 2024, 4(4), 463-479; https://doi.org/10.3390/crops4040033 - 12 Oct 2024
Viewed by 398
Abstract
Soil salinity significantly impacts crop productivity. In response, plant growth-promoting rhizobacteria (PGPR) offer an innovative and eco-friendly solution to mitigate salinity stress. However, research on PGPR’s effects on crop physiology under varying salinity levels is still emerging. This study evaluates the impact of [...] Read more.
Soil salinity significantly impacts crop productivity. In response, plant growth-promoting rhizobacteria (PGPR) offer an innovative and eco-friendly solution to mitigate salinity stress. However, research on PGPR’s effects on crop physiology under varying salinity levels is still emerging. This study evaluates the impact of five bacterial strains, isolated from compost, on the growth of maize (Zea mays) and tomato (Solanum lycopersicum) plants under different levels of salt stress. This study involved treating maize and tomato seeds with five bacterial strains, and then planting them in a greenhouse under varying salt stress conditions (43 mM, 86 mM, 172 mM, 207 mM NaCl) using a Randomized Complete Block Design. Results showed that bacterial inoculation improved plant growth under saline conditions. S2015-1, S2026-2, and S2027-2 (Bacillus cereus, Acinetobacter calcoaceticus, Bacillus subtilis) were particularly effective in promoting plant growth under salt stress, especially at ionic concentrations of 43 mM and 86 mM, leading to a substantial increase in fresh and dry weight, with strain S2015-1 boosting chlorophyll by 29% at 86 mM in both crops. These results highlight the potential of PGPR to enhance crop resilience and productivity under salinity stress, promoting climate-smart agricultural practices. Full article
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<p>Effects of bacterial strains irrigated with saline solution on (<b>A</b>) fresh weight (FW, g), (<b>B</b>) dry weight (DW, g), (<b>C</b>) shoot length (cm), and (<b>D</b>) relative water content (RWC) of tomato plants. Means sharing the same letter are considered relatively similar. The order of the letters (a &gt; b &gt; c &gt; d &gt; e &gt; f) indicates a decreasing value of the means. Some means may belong to multiple groups (for example, ‘cd’ indicates that this mean is relatively similar to the means of groups c and d).</p>
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<p>Effect of bacterial strains on fresh weight (FW, g) and dry weight (DW, g) of tomato plants under saline irrigation.</p>
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<p>Fresh weight (FW, g) variation in maize plants with increasing salinity levels.</p>
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<p>Photographs of tomato plants irrigated with varying salt concentrations. (<b>A</b>): not inoculated with bacterial suspension 2015-1. (<b>B</b>): inoculated with bacterial suspension 2015-1.</p>
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<p>Maize growth progression under varying salt concentrations (43 mM, 86 mM, 172 mM, 207 mM) and inoculation with bacterial suspensions.</p>
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<p>Photographs0 depicting (<b>A</b>,<b>B</b>) size regression, (<b>C</b>) leaf yellowing, and (<b>D</b>) leaf wilting as a function of increasing salt concentration of maize plants.</p>
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<p>Effect of rhizobacteria on (<b>A</b>) root length (cm) and (<b>B</b>) stem diameter (mm) during irrigation of maize plants with five NaCl concentrations.</p>
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<p>The effect of rhizobacteria on (<b>A</b>) chlorophyll content (CCl), (<b>B</b>) leaf area (mm<sup>2</sup>), and (<b>C</b>) the number of leaves per plant during irrigation with a range of saline concentrations. Means sharing the same letter are considered relatively similar. The order of the letters indicates a decreasing value of the means. Means may that belong to multiple groups, example, ‘cd’ indicates that this mean is relatively similar to the means of groups c and d.</p>
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<p>PCR amplification of 16S rDNA from five bacterial strains tested.</p>
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18 pages, 6737 KiB  
Article
Genome-Wide Identification and Functional Validation of Actin Depolymerizing Factor (ADF) Gene Family in Gossypium hirsutum L.
by Jingxuan Guo, Qingtao Zeng, Ying Liu, Zhaoyuan Ba and Xiongfeng Ma
Agronomy 2024, 14(10), 2349; https://doi.org/10.3390/agronomy14102349 - 11 Oct 2024
Viewed by 416
Abstract
The Actin Depolymerizing Factor (ADF) protein, highly conserved among eukaryotes, is essential for plant growth, development, and stress responses. Cotton, a vital economic crop with applications spanning oilseed, textiles, and military sectors, has seen a limited exploration of its ADF gene family. This [...] Read more.
The Actin Depolymerizing Factor (ADF) protein, highly conserved among eukaryotes, is essential for plant growth, development, and stress responses. Cotton, a vital economic crop with applications spanning oilseed, textiles, and military sectors, has seen a limited exploration of its ADF gene family. This research has identified 118 unique ADF sequences across four principal cotton species: Gossypium hirsutum L., Gossypium barbadense Linn, Gossypium raimondii, and Asiatic cotton. The study found that the structural domains and physicochemical properties of these proteins are largely uniform across species. The ADF genes were classified into four subfamilies with a notable expansion in groups III and IV due to tandem and chromosomal duplication events. A thorough analysis revealed a high degree of conservation in gene structure, including exon counts and the lengths of introns and exons, with the majority of genes containing three exons, aligning with the characteristics of the ADF family. RNA-seq analysis uncovered a spectrum of responses by GhADFs to various abiotic stresses with GhADF19 showing the most significant reaction. Virus-induced gene silencing (VIGS) experiments were conducted to assess the role of GhADF19 in plant growth under abiotic stress. The results demonstrated that plants with silenced GhADF19 exhibited significantly slower growth rates and lower dry weights when subjected to cold, salt, and drought stress compared to the control group. This marked reduction in growth and dry weight under stress conditions highlights the potential importance of GhADF19 in stress tolerance mechanisms. Full article
(This article belongs to the Section Plant-Crop Biology and Biochemistry)
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<p>Phylogenetic tree of ADF proteins from four cotton species and other species. Using MEGA 7.0 software, the phylogenetic tree was constructed with 1000 bootstrap replicates using the neighbor-joining method, where only bootstrap values &gt; 50% are shown. Different colored lines and regions indicate ADF protein scores in different subgroups. Red stars represent ADF proteins of <span class="html-italic">Gossypium hirsutum</span> L. All ADFs were classified into four groups (I, II, III, IV).</p>
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<p>Distribution of ADF gene on cotton chromosome. The vertical bar on the far left indicates chromosome size in megabases (Mbs) with chromosome numbering to the left of each chromosome.</p>
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<p>Collinearity analysis. (<b>a</b>) Intraspecies collinearity analysis, where red lines indicate segmentally duplicated pairs of ADF genes. (<b>b</b>) Interspecies collinearity analysis.</p>
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<p>The exon–intron structures and conserved motifs of ADF. Structural triplets of cotton ADF proteins. Protein and DNA sequence lengths are estimated using the scale at the bottom with black lines indicating non-conserved amino acids or introns. The (<b>left</b>) panel shows the phylogenetic relationship of cotton ADF proteins; the (<b>right</b>) panel shows the conserved motifs and gene structure of the ADF gene family.</p>
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<p>Cis-acting element analysis of the ADF gene. The promoter region (2000 bp upstream of ATG) of each cotton ADF family member was analyzed by PlantCARE.</p>
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<p>Expression profiles of ADF genes under different stresses. Cold treatment (<b>a</b>), heat treatment (<b>b</b>), salt treatment (<b>c</b>), drought treatment (<b>d</b>). The red color represents a high expression and the green color represents a low expression. (The detailed FPKM values are present in <a href="#app1-agronomy-14-02349" class="html-app">Supplementary Additional File S1</a>).</p>
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<p>The expression of GhADFs under different stress treatments. (<b>a</b>) NaCl represents salt stress; (<b>b</b>) COLD represents low-temperature stress; (<b>c</b>) PEG represents drought stress. (The error line in the graph represents the standard deviation (SD) with a sample size of <span class="html-italic">n</span> = 3. The data presented here represent the mean of three biological experiments with the standard error of the mean indicated. The root relative expression values were standardized to a value of 1. A one-way ANOVA test was employed to perform the significance analyses, with a significance level of <span class="html-italic">p</span> &lt; 0.05). In the context of reference controls, the selected control was actin.</p>
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<p>Abiotic stress phenotypic characteristics, silencing efficiency and expression of <span class="html-italic">GhADF19</span> after gene silencing. (<b>a</b>) Plant growth after four genes were silenced under three abiotic stresses. (<b>b</b>) Dry weight of single plant after four genes were silenced under three abiotic stresses. (The error line in the graph represents the standard deviation (SD) with a sample size of <span class="html-italic">n</span> = 3. The data presented here represent the mean of three biological experiments with the standard error of the mean indicated. The root relative expression values were standardized to a value of 1. A one-way ANOVA test was employed to perform the significance analyses with a significance level of <span class="html-italic">p</span> &lt; 0.05. As indicated by Duncan’s multiple range test, the presence of different lowercase letters signifies a statistically significant distinction between groups at the <span class="html-italic">p</span> &lt; 0.05 level of significance.) (<b>c</b>) Silence efficiency of <span class="html-italic">GhADF19</span>.</p>
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<p>Abiotic stress phenotypic characteristics, silencing efficiency and expression of <span class="html-italic">GhADF19</span> after gene silencing. (<b>a</b>) Plant growth after four genes were silenced under three abiotic stresses. (<b>b</b>) Dry weight of single plant after four genes were silenced under three abiotic stresses. (The error line in the graph represents the standard deviation (SD) with a sample size of <span class="html-italic">n</span> = 3. The data presented here represent the mean of three biological experiments with the standard error of the mean indicated. The root relative expression values were standardized to a value of 1. A one-way ANOVA test was employed to perform the significance analyses with a significance level of <span class="html-italic">p</span> &lt; 0.05. As indicated by Duncan’s multiple range test, the presence of different lowercase letters signifies a statistically significant distinction between groups at the <span class="html-italic">p</span> &lt; 0.05 level of significance.) (<b>c</b>) Silence efficiency of <span class="html-italic">GhADF19</span>.</p>
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32 pages, 8280 KiB  
Review
Understanding of Plant Salt Tolerance Mechanisms and Application to Molecular Breeding
by Yuxia Zhou, Chen Feng, Yuning Wang, Chunxia Yun, Xinqing Zou, Nuo Cheng, Wenping Zhang, Yan Jing and Haiyan Li
Int. J. Mol. Sci. 2024, 25(20), 10940; https://doi.org/10.3390/ijms252010940 - 11 Oct 2024
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Abstract
Soil salinization is a widespread hindrance that endangers agricultural production and ecological security. High salt concentrations in saline soils are primarily caused by osmotic stress, ionic toxicity and oxidative stress, which have a negative impact on plant growth and development. In order to [...] Read more.
Soil salinization is a widespread hindrance that endangers agricultural production and ecological security. High salt concentrations in saline soils are primarily caused by osmotic stress, ionic toxicity and oxidative stress, which have a negative impact on plant growth and development. In order to withstand salt stress, plants have developed a series of complicated physiological and molecular mechanisms, encompassing adaptive changes in the structure and function of various plant organs, as well as the intricate signal transduction networks enabling plants to survive in high-salinity environments. This review summarizes the recent advances in salt perception under different tissues, physiological responses and signaling regulations of plant tolerance to salt stress. We also examine the current knowledge of strategies for breeding salt-tolerant plants, including the applications of omics technologies and transgenic approaches, aiming to provide the basis for the cultivation of salt-tolerant crops through molecular breeding. Finally, future research on the application of wild germplasm resources and muti-omics technologies to discover new tolerant genes as well as investigation of crosstalk among plant hormone signaling pathways to uncover plant salt tolerance mechanisms are also discussed in this review. Full article
(This article belongs to the Section Molecular Plant Sciences)
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<p>A series of adverse effects in plants induced by salt stress.</p>
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<p>Salt responses in different tissues and organs of the plant.</p>
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<p>A schematic diagram of plants suffering from osmotic stress, ionic stress and oxidative stress under salt stress. When plants experience osmotic stress due to salt, the soluble sugar content in their cells increases, while RWC and MDA levels decrease. In response to ionic stress caused by salt stress, the concentration of Na<sup>+</sup> within their cells increases, resulting in a higher Na<sup>+</sup>/K<sup>+</sup> ratio in the cytoplasm. At this stage, ion transporters play a crucial role in maintaining the Na<sup>+</sup>-K<sup>+</sup> balance within the cells. Additionally, when plants encounter oxidative stress caused by salt, the levels of ROS in plant cells increase, resulting in membrane lipid peroxidation. Plant cells mitigate ROS through the action of antioxidant enzymes. RWC, relative water content; MDA, malonaldehyde; ROS, reactive oxygen species.</p>
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<p>A schematic representation of the Ca<sup>2+</sup> signaling pathway induced by salt stress. The Na<sup>+</sup> receptor, GIPC, located on the plasma membrane, activates the Ca<sup>2+</sup> channel CNGC. This leads to the generation of Ca<sup>2+</sup> signals within the cell and subsequently triggers a series of signaling pathways. Ca<sup>2+</sup> in the cytoplasm are recognized by SOS3/SCaBP8, which recruits SOS2 to the plasma membrane to phosphorylate SOS1, facilitating the efflux of Na<sup>+</sup>. Additionally, the CBL-CIPK module plays a crucial role in the SOS pathway. SOS3 interacts with SOS2 upon sensing Ca<sup>2+</sup>, forming the SOS2/SOS3 complex to phosphorylate SOS1 and promote Na<sup>+</sup> efflux. The activity of SOS2 is negatively regulated by 14-3-3 proteins; however, this inhibitory effect is alleviated by Ca<sup>2+</sup>-mediated binding of PKS5 to the 14-3-3 proteins. TPC1, located on the vacuolar membrane, helps maintain the appropriate balance of Na<sup>+</sup>/Ca<sup>2+</sup>, thereby promoting the proton gradient. Ca<sup>2+</sup> binding to CPK3 can phosphorylate TPK1 on the vacuolar membrane, ensuring the stable Na<sup>+</sup>/K<sup>+</sup> in the cytoplasm. Collectively, these ion transporters contribute to the plant tolerance to salt stress. GIPC, glycosyl inositol phosphoryl ceramides; CNGC, cyclic nucleotide gated Ca<sup>2+</sup> channel; SOS, salt overly sensitive; SCaBP8, SOS3/SOS3-like calcium-binding protein 8; CBL, calcineurin B-like protein; CIPK, CBL-interacting protein kinase; PKS5, SOS2-like protein kinase 5; TPC1, two-pore channel 1; CPK3, calcium-dependent protein kinase 3; TPK1, two-pore K<sup>+</sup> channel 1.</p>
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<p>A model of the plant salt tolerance mechanism regulated by hormones under salt stress. (<b>A</b>) Salt stress induces an increase in ABA levels. The enhanced binding of ABA to PYR/PYL/RCAR alters its conformation and promotes its interaction with PP2C, thereby inhibiting the activity of PP2C and stimulating the activity of SnRK2. The formation of the PYR/PYL/RCAR-PP2C-SnRK2 complex is a crucial component of the ABA signaling pathway. This complex phosphorylates bZIPs, enhancing its activity. Subsequently, bZIPs translocate to the nucleus to regulate the expression of ABA-responsive genes. Additionally, the complex can phosphorylate SLAC1 and KAT1 on the plasma membrane, facilitating stomatal closure. ABA can also induce stomatal closure through NADPH oxidase-mediated hydrogen peroxide production. (<b>B</b>) Under normal conditions, the interaction between IAA and TIR1 leads to the ubiquitination and degradation of Aux/IAA, thereby alleviating the inhibition of Aux/IAA on the activity of the ARF transcription factor. However, under salt stress, the reduced expression of TIR1 prevents the degradation of Aux/IAA, resulting in the continued inhibition of ARF transcription factor activity. (<b>C</b>) DELLA acts as a negative regulator in the GA signal transduction pathway. GA forms a complex with GID1 and DELLA, leading to the degradation of DELLA and thereby alleviating its inhibitory effect on GA-responsive genes. Under salt stress, the GA/GID1 complex binds to the N-terminus of DELLA, inducing a conformational change in DELLA that prevents GID2 from binding to it. As a result, DELLA is not degraded, which allows it to maintain its inhibitory effect on gene transcription. The cross means that this process is inhibited. (<b>D</b>) JA, induced by salt stress, is recognized by COI1, forming the COI1-JA complex. This complex releases JAZ from its association with co-repressors (NINJA, TPL), which normally inhibit the transcription of JA-responsive genes. Subsequently, JAZ undergoes ubiquitination and is degraded by the 26S proteasome, thereby removing the inhibition on the transcription of JA-responsive genes. ABA, abscisic acid; PP2C, protein phosphatase 2C; SnRK2, sucrose nonfermenting1-related protein kinase 2; SLAC1, slow anion channel 1; KAT1, potassium channel 1; TIR1, transport inhibitor response 1; Aux/IAA, auxin/indole 3-acetic acid; GA, gibberellin; GID, gibberellin insensitive dwarf; JA, jasmonic acid; COI1, coronatine-insensitive 1; JAZ, jasmonate ZIM domain.</p>
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<p>A model of PA signaling in plant cells induced by salt stress. Salt stress is detected at the cell membrane, activating the PLC and PLD signaling pathways. In the PLC pathway, PI is sequentially phosphorylated to form PIP and PIP<sub>2</sub>. Upon cleavage by PI-PLC, PIP<sub>2</sub> is converted into DAG and IP<sub>3</sub>. DAG can then be transformed into PA in the presence of DGK, while IP<sub>3</sub> diffuses into the cytoplasm and is further converted into IP<sub>6</sub>. IP<sub>6</sub> plays a crucial role in the ABA signaling pathway, influencing the release of Ca<sup>2+</sup> and subsequently modulating the expression of salt stress-responsive genes. In the PLD pathway, PA can be generated from the hydrolysis of PC by PLD or from the hydrolysis of both PC and PE by PLDα. Through the action of PAK, the resulting PA can induce the formation of DGPP, a signaling molecule in plant cells. Alternatively, MPK6 can bind to PA to activate SOS1 on the plasma membrane, facilitating the expulsion of Na<sup>+</sup>. MPK6 can also phosphorylate MAP65-1 bound to PA, enhancing microtubule polymerization in response to salt stress. Additionally, SnRK2.4 can promote salt tolerance in plants by binding to PA. PA, phosphatidic acid; PLC, phospholipase C; PLD, phospholipase D; PI, phosphoinositides; PIP, phosphatidylinositol 4-phosphate; PIP<sub>2</sub>, phosphatidylinositol 4,5-bisphosphate; DAG, diacylglycerol; IP<sub>3,</sub> inositol 1,4,5-triphosphate; DGK, diacylglycerol kinase; IP<sub>6,</sub> hexakisphosphate; PC, phosphatidylcholine; PE, phosphatidylcholine; PAK, PA kinase; DGPP, diacylglycerol pyrophosphate; MPK6, mitogen protein kinase 6; MAP65-1, microtubule-associated protein 65-1.</p>
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<p>A schematic diagram of ROS signal transduction induced by salt stress. When plant cells are exposed to salt stress, they generate a significant amount of ROS, which can lead to oxidative damage. To mitigate this damage, plant cells maintain ROS homeostasis through various signal transduction pathways activated by salt stress. Under normal conditions, ROS, such as H<sub>2</sub>O<sub>2</sub>, are typically produced by chloroplasts, mitochondria and peroxisomes. Additionally, H<sub>2</sub>O<sub>2</sub> can be generated from extracellular oxygen through the action of RBOH and SOD under salt stress conditions. The produced H<sub>2</sub>O<sub>2</sub> is subsequently transported into the cell or detected by ROS receptors on the cell membrane, which activates the MAPK signaling pathway to help maintain intracellular ROS homeostasis. Excessive H<sub>2</sub>O<sub>2</sub> in the cytoplasm is recognized by ROS sensors, triggering downstream signal transduction pathways. For instance, H<sub>2</sub>O<sub>2</sub> interacts with the ROS sensor Hsf to form a homotrimer that translocates to the nucleus, where it activates the expression of genes associated with oxidative stress. Furthermore, ROS can also be detected by other ROS sensors, such as p46-MAPK, to facilitate the plant response to salt stress. Additionally, ROS signaling can interact with other signaling pathways, highlighting the complexity of stress responses in plants. For example, ROS generated by RBOHD stimulate the opening of Ca<sup>2+</sup> channels in the plasma membrane, leading to an influx of calcium ions, which generates Ca<sup>2+</sup> signals. Subsequently, this influx activates TPC1 on the vacuolar membrane, allowing Ca<sup>2+</sup> from the vacuole to enter the cytoplasm, which further activates RBOHD. This cycle can create a ROS/Ca²⁺ wave, thereby enhancing the salt tolerance of plants. RBOH, respiratory burst oxidase homolog; SOD, superoxide dismutase; MAPK, mitogen-activated protein kinase; Hsf, heat shock factor; RBOHD, respiratory burst oxidase homolog D.</p>
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<p>A schematic diagram of the strategies using molecular technologies for breeding salt-tolerant crops. Salt-tolerant genes are identified through (<b>A</b>) QTL mapping population, (<b>B</b>) GWAS population and (<b>C</b>) metabolomics and transcriptomics analysis. (<b>D</b>) Plants with salt tolerance can be acquired via transgenic breeding, including gene overexpression and knockout techniques. Furthermore, the superior alleles of genes can be developed into a functional molecular marker, aiding in the breeding of salt-tolerant plants through MAS. QTL, quantitative trait locus; GWAS, genome-wide association study; MAS, marker assisted selection. The red dotted box represents the selected salt-tolerant plants. A cross with a black circle indicates self-intersection. The cross without a black circle indicates hybridization.</p>
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