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Agronomy
Special Issues
Rice Germplasm Innovation and Tolerance to Abiotic Stress
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Rice Germplasm Innovation and Tolerance to Abiotic Stress

A special issue of Agronomy (ISSN 2073-4395). This special issue belongs to the section "Crop Breeding and Genetics".

Deadline for manuscript submissions: closed (30 September 2024) | Viewed by 1321

Special Issue Editor

Dr. Weihua Qiao

E-Mail Website
Guest Editor
National Key Facility for Crop Gene Resources and Genetic Improvement, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
Interests: rice genomics; rice germplasm resource innovation; salt tolerance; gene function analysis
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

As the staple food source for around 4 billion people, rice is one of the most important food crops in the world. Currently, with changes to the global climate, rice is facing a great deal of abiotic stresses such as soil salinity, drought, and cold and heat stress. The devolpment of innovative rice germplasm, with strong stress tolerance, is a key step to coping with this challenge. The identification of stress tolerance genes from wild relatives would, in particular, greatly expand the gene pool for rice breeding for stress tolerance. In this respect, innovated rice germplasm provides novel resources for rice breeding, and new insights for the stress tolerance mechanisms of rice.

In this Special Issue, we aim to exchange knowledge on any aspect related to innovations in rice germplasm for abiotic stress tolerance. Including indentificaiton of how new genes respond to abiotic stress, novel gene function analysis, and genetic or physiological mechanisms.

Dr. Weihua Qiao
Guest Editor

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Agronomy is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • rice
  • abiotic salt tolerance
  • germplasm innovation
  • gene identification
  • regulation network
  • QTL mapping
  • genomics
  • transcriptomic
  • gene expression
  • natural variation

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Published Papers (2 papers)

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Research

19 pages, 5151 KiB  
Article
Physiological and Transcriptomic Characterization of Rice Genotypes under Drought Stress
by Qian Zhu, Muhammad Ahmad Hassan, Yiru Li, Wuyun Fang, Jingde Wu and Shimei Wang
Agronomy 2024, 14(10), 2247; https://doi.org/10.3390/agronomy14102247 - 29 Sep 2024
Viewed by 390
Abstract
Drought is a primary abiotic stress that inhibits rice (Oryza sativa L.) growth and development, and during the reproductive stage it has a negative impact on the rice seed-setting rate. This research study examined two rice lines, La-96 (drought sensitive) and La-163 [...] Read more.
Drought is a primary abiotic stress that inhibits rice (Oryza sativa L.) growth and development, and during the reproductive stage it has a negative impact on the rice seed-setting rate. This research study examined two rice lines, La-96 (drought sensitive) and La-163 (drought resistant), for drought stress treatment (with soil moisture at 20% for 7 days) and control (normal irrigation and kept soil moisture ≥40%). To elucidate the photosynthesis and molecular mechanisms underlying drought tolerance in rice, leaf photosynthetic traits and transcriptome sequencing were used to compare differences between two contrasting recombinant inbred lines (RIL) during drought and subsequent recovery at the booting stage. The rice line La-96 showed a significant decrease in seed-setting rate after being treated for seven days’ drought stress (from 86.64% to 22.75%), while La-163 was slightly affected (from 89.04% to 79.33%). The photosynthetic activities of both lines significantly decreased under the drought treatment, and these traits of La-163 recovered to a comparable level with the control after three days of rewatering. The transcriptome of both lines in three treatments (the control, drought stress, and subsequent recovery) were tested, and a total of 16,051 genes were identified, among which 10,566 genes were differentially expressed in various treatments and rice lines. Comprehensive gene expression profiles revealed that the specifically identified DEGs were involved in the ribosome synthesis and the metabolic pathway of photosynthesis, starch, and sucrose metabolism. The DEGs that are activated and respond quickly, as seen during recovery in the tolerant rice line, may play essential roles in regulating subsequent growth and development. This study uncovered the molecular genetic pathways of drought tolerance and extended our understanding of the drought tolerance mechanisms and subsequent recovery regulation in rice. Full article
(This article belongs to the Special Issue Rice Germplasm Innovation and Tolerance to Abiotic Stress)
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Figure 1

Figure 1
<p>The phenotype of the main panicle of two contrasting rice lines under drought treatment and control. Main panicle of La-96 (<b>A</b>), main panicle of La-163 (<b>B</b>), statistical analysis of seed setting rate in La-96 (<b>C</b>) and La-163 (<b>D</b>). Here, TS is the total seed number, FS is the filled seed number, and SR is the seed-setting rate.</p> Full article ">Figure 2
<p>Leaf chlorophyll value (Chl) and relative water content (RWC) of two contrasting rice lines under drought treatment (D), recovery (R), and control (C). Different letters indicate a significant difference (<span class="html-italic">p</span> &lt; 0.05). The standard error (SE) of three biological replications is shown by error bars.</p> Full article ">Figure 3
<p>Photosynthetic traits of flag leaves of two contrasting rice lines under drought (D), recovery (R), and control (C) treatments. Different letters indicate a significant difference (<span class="html-italic">p</span> &lt; 0.05). The standard error (SE) of three biological replications is shown by error bars. Here, Pn: net photosynthesis rate (<b>A</b>), Ci: intercellular CO<sub>2</sub> concentration (<b>B</b>), Tr: transpiration rate (<b>C</b>), Gs: stomatal conductance (<b>D</b>).</p> Full article ">Figure 4
<p>(<b>A</b>) The principal component analysis (PCA) between different treatments and rice lines. The samples have relative coordination points on the principal components following dimensionality reduction analysis. Each sample point’s distance indicates the sample distance; the higher the similarities between samples, the closer the distance is. In the two-dimensional graph of the distinct samples, the contribution degree of principal component 1 (PC1) is illustrated by the horizontal axis, and the vertical axis depicts the contribution degree of principal component 2 (PC2). C96, D96, and R96 represent La-96 under control, drought treatment, and recovery, respectively, and C163, D163, and R163 represent La-163 under control, drought treatment, and recovery, respectively. (<b>B</b>) The Venn diagram between different treatments of two rice lines. Different colored circles represent different gene sets, and numerical values exhibit the number of shared and unique genes between different gene sets. (<b>C</b>) Histogram of DEGs among different treatments. The horizontal axis illustrates the individual comparison groups; the vertical axis displays the number of differential genes in each comparison group, denoting the number of genes upregulated for significant differences and the number of genes downregulated for significant differences. The horizontal axis displays the individual comparison groups. (<b>D</b>) The Venn diagram among comparisons of different treatments. (<b>E</b>) Histogram of differentially expressed genes between rice lines. (<b>F</b>) The Venn diagram among comparisons of different rice lines.</p> Full article ">Figure 5
<p>KEGG annotation analysis of D96_vs_C96 (<b>A</b>), D163_vs_C163 (<b>B</b>), R96_vs_D96 (<b>C</b>), R163_vs_D163 (<b>D</b>), R96_vs_C96 (<b>E</b>), R163_vs_C163 (<b>F</b>). The horizontal axis exhibits the KEGG metabolism pathway, and the vertical axis illustrates the number of annotated genes in the different pathways. Five categories of KEGG metabolic pathways were included: Metabolism, Environmental Information Processing, Genetic Information Processing, Organismal Systems, and Cellular Processes. C96, D96, and R96 represent La-96 under control, drought treatment, and recovery, respectively, and C163, D163, and R163 represent La-163 under control, drought treatment, and recovery, respectively.</p> Full article ">Figure 6
<p>KEGG enrichment analysis of D96_vs_C96 (<b>A</b>), D163_vs_C163 (<b>B</b>), R96_vs_D96 (<b>C</b>), R163_vs_D163 (<b>D</b>), R96_vs_C96 (<b>E</b>), R163_vs_C163 (<b>F</b>). The pathway name is displayed vertically, and the Rich factor (the ratio of the sample number of genes enriched in this pathway to the background number of annotated genes) is displayed horizontally—the greater the Rich factor, the greater the degree of enrichment. The size of the dots indicates the number of genes in this pathway, and the color of the dots corresponds to different Padjust ranges. C96, D96, and R96 represent La-96 under control, drought treatment, and recovery, respectively, and C163, D163, and R163 represent La-163 under control, drought treatment, and recovery, respectively.</p> Full article ">Figure 7
<p>(<b>A</b>) Characterization of the functionality of drought- and recovery-responsive genes under drought and successive recovery. D96/C96, La-96 from normal water to drought, D163/C163, La-163 from normal water to drought, R96/D96, La-96 from drought recovery to normal water treatment, R163/D163, La-163 from drought recovery to normal water treatment. (<b>B</b>) Common and specific DEGs were identified in different treatments and rice lines. + represents upregulated, - represents downregulated.</p> Full article ">Figure 8
<p>The analysis using qRT-PCR exhibits gene expression under drought (D), recovery (R), and control (C) treatments. Different letters indicate a significant difference (<span class="html-italic">p</span> &lt; 0.05). The standard error (SE) of three biological replications is shown by error bars.</p> Full article ">
12 pages, 5395 KiB  
Article
Submergence Stress Reduces the Ability of Rice to Regulate Recovery after Disaster
by Yanmei Yu, Yan Meng, Peng Chen and Kaihua Cao
Agronomy 2024, 14(6), 1319; https://doi.org/10.3390/agronomy14061319 - 18 Jun 2024
Viewed by 590
Abstract
Flood submergence has devastating effects on agricultural production in China, with rice being particularly vulnerable to its impacts. Previous studies on rice submergence stress have primarily focused on immediate yield reduction and short-term growth. In this study, a submergence stress experiment was carried [...] Read more.
Flood submergence has devastating effects on agricultural production in China, with rice being particularly vulnerable to its impacts. Previous studies on rice submergence stress have primarily focused on immediate yield reduction and short-term growth. In this study, a submergence stress experiment was carried out by using the method of potted rice flooding. The growth recovery characteristics of rice under different submergence stress were analyzed through the continuous observation of rice growth after the disaster. The results showed that submergence stress had a persistent effect on rice growth, which persisted until the recovery period after the disaster. The recovery ability of rice plants decreased with the aggravation of stress, leading to increased damage to the plant. The average yield decreased by 17.07% and 15.56% due to submergence stress during the jointing and booting stage, respectively. The current study pointed out that the growth traits of and, furthermore, the mechanism of physiological changes in rice during the recovery period need to be explored in order to understand the effects of flooding stress on rice. Full article
(This article belongs to the Special Issue Rice Germplasm Innovation and Tolerance to Abiotic Stress)
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Figure 1

Figure 1
<p>Study area.</p> Full article ">Figure 2
<p>Diurnal variation in rainfall and temperature during rice growth period.</p> Full article ">Figure 3
<p>Test layout diagram (The green in the figure is rice plant).</p> Full article ">Figure 4
<p>Tiller number. The different lowercase letters indicate significant differences (<span class="html-italic">p</span> ≤ 0.05) according to the least significant difference test.</p> Full article ">Figure 5
<p>Plant height. The different lowercase letters indicate significant differences (<span class="html-italic">p</span> ≤ 0.05) according to the least significant difference test.</p> Full article ">Figure 6
<p>Rice <span class="html-italic">LAI</span>. The different lowercase letters indicate significant differences (<span class="html-italic">p</span> ≤ 0.05) according to the least significant difference test.</p> Full article ">Figure 7
<p>Dry matter accumulation. The different lowercase letters indicate significant differences (<span class="html-italic">p</span> ≤ 0.05) according to the least significant difference test.</p> Full article ">Figure 8
<p>Rice yield components. The different lowercase letters indicate significant differences (<span class="html-italic">p</span> ≤ 0.05) according to the least significant difference test.</p> Full article ">Figure 9
<p>Rice yield. The different lowercase letters indicate significant differences (<span class="html-italic">p</span> ≤ 0.05) according to the least significant difference test.</p> Full article ">
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