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Qiao L, Li Y, Wang L, Gu C, Luo S, Li X, Yan J, Lu C, Chang Z, Gao W, Zhang X. Identification of Salt-Stress-Responding Genes by Weighted Gene Correlation Network Analysis and Association Analysis in Wheat Leaves. PLANTS (BASEL, SWITZERLAND) 2024; 13:2642. [PMID: 39339617 PMCID: PMC11435117 DOI: 10.3390/plants13182642] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/21/2024] [Revised: 09/15/2024] [Accepted: 09/18/2024] [Indexed: 09/30/2024]
Abstract
The leaf is not only the main site of photosynthesis, but also an important organ reflecting plant salt tolerance. Discovery of salt-stress-responding genes in the leaf is of great significance for the molecular improvement of salt tolerance in wheat varieties. In this study, transcriptome sequencing was conducted on the leaves of salt-tolerant wheat germplasm CH7034 seedlings at 0, 1, 6, 24, and 48 h after NaCl treatment. Based on weighted gene correlation network analysis of differentially expressed genes (DEGs) under salt stress, 12 co-expression modules were obtained, of which, 9 modules containing 4029 DEGs were related to the salt stress time-course. These DEGs were submitted to the Wheat Union database, and a total of 904,588 SNPs were retrieved from 114 wheat germplasms, distributed on 21 wheat chromosomes. Using the R language package and GAPIT program, association analysis was performed between 904,588 SNPs and leaf salt injury index of 114 wheat germplasms. The results showed that 30 single nucleotide polymorphisms (SNPs) from 15 DEGs were associated with salt tolerance. Then, nine candidate genes, including four genes (TaBAM, TaPGDH, TaGluTR, and TaAAP) encoding enzymes as well as five genes (TaB12D, TaS40, TaPPR, TaJAZ, and TaWRKY) encoding functional proteins, were identified by converting salt tolerance-related SNPs into Kompetitive Allele-Specifc PCR (KASP) markers for validation. Finally, interaction network prediction was performed on TaBAM and TaAAP, both belonging to the Turquoise module. Our results will contribute to a further understanding of the salt stress response mechanism in plant leaves and provide candidate genes and molecular markers for improving salt-tolerant wheat varieties.
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Affiliation(s)
- Linyi Qiao
- College of Agronomy, Shanxi Key Laboratory of Crop Genetics and Molecular Improvement, Shanxi Agricultural University, Taiyuan 030031, China
| | - Yijuan Li
- College of Agronomy, Shanxi Key Laboratory of Crop Genetics and Molecular Improvement, Shanxi Agricultural University, Taiyuan 030031, China
| | - Liujie Wang
- College of Agronomy, Shanxi Key Laboratory of Crop Genetics and Molecular Improvement, Shanxi Agricultural University, Taiyuan 030031, China
| | - Chunxia Gu
- College of Agronomy, Shanxi Key Laboratory of Crop Genetics and Molecular Improvement, Shanxi Agricultural University, Taiyuan 030031, China
| | - Shiyin Luo
- College of Agronomy, Shanxi Key Laboratory of Crop Genetics and Molecular Improvement, Shanxi Agricultural University, Taiyuan 030031, China
| | - Xin Li
- College of Agronomy, Shanxi Key Laboratory of Crop Genetics and Molecular Improvement, Shanxi Agricultural University, Taiyuan 030031, China
| | - Jinlong Yan
- Millet Research Institute, Shanxi Agricultural University, Changzhi 046011, China
| | - Chengda Lu
- College of Agronomy, Shanxi Key Laboratory of Crop Genetics and Molecular Improvement, Shanxi Agricultural University, Taiyuan 030031, China
| | - Zhijian Chang
- College of Agronomy, Shanxi Key Laboratory of Crop Genetics and Molecular Improvement, Shanxi Agricultural University, Taiyuan 030031, China
| | - Wei Gao
- College of Agronomy, Shanxi Key Laboratory of Crop Genetics and Molecular Improvement, Shanxi Agricultural University, Taiyuan 030031, China
| | - Xiaojun Zhang
- College of Agronomy, Shanxi Key Laboratory of Crop Genetics and Molecular Improvement, Shanxi Agricultural University, Taiyuan 030031, China
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Huang Z, Chen S, He K, Yu T, Fu J, Gao S, Li H. Exploring salt tolerance mechanisms using machine learning for transcriptomic insights: case study in Spartina alterniflora. HORTICULTURE RESEARCH 2024; 11:uhae082. [PMID: 38766535 PMCID: PMC11101319 DOI: 10.1093/hr/uhae082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/10/2024] [Accepted: 03/12/2024] [Indexed: 05/22/2024]
Abstract
Salt stress poses a significant threat to global cereal crop production, emphasizing the need for a comprehensive understanding of salt tolerance mechanisms. Accurate functional annotations of differentially expressed genes are crucial for gaining insights into the salt tolerance mechanism. The challenge of predicting gene functions in under-studied species, especially when excluding infrequent GO terms, persists. Therefore, we proposed the use of NetGO 3.0, a machine learning-based annotation method that does not rely on homology information between species, to predict the functions of differentially expressed genes under salt stress. Spartina alterniflora, a halophyte with salt glands, exhibits remarkable salt tolerance, making it an excellent candidate for in-depth transcriptomic analysis. However, current research on the S. alterniflora transcriptome under salt stress is limited. In this study we used S. alterniflora as an example to investigate its transcriptional responses to various salt concentrations, with a focus on understanding its salt tolerance mechanisms. Transcriptomic analysis revealed substantial changes impacting key pathways, such as gene transcription, ion transport, and ROS metabolism. Notably, we identified a member of the SWEET gene family in S. alterniflora, SA_12G129900.m1, showing convergent selection with the rice ortholog SWEET15. Additionally, our genome-wide analyses explored alternative splicing responses to salt stress, providing insights into the parallel functions of alternative splicing and transcriptional regulation in enhancing salt tolerance in S. alterniflora. Surprisingly, there was minimal overlap between differentially expressed and differentially spliced genes following salt exposure. This innovative approach, combining transcriptomic analysis with machine learning-based annotation, avoids the reliance on homology information and facilitates the discovery of unknown gene functions, and is applicable across all sequenced species.
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Affiliation(s)
- Zhangping Huang
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing 100081, China
- Nanfan Research Institute, CAAS, Sanya, Hainan 572024, China
| | - Shoukun Chen
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing 100081, China
- Nanfan Research Institute, CAAS, Sanya, Hainan 572024, China
- Hainan Seed Industry Laboratory, Sanya, Hainan 572024, China
| | - Kunhui He
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing 100081, China
- Nanfan Research Institute, CAAS, Sanya, Hainan 572024, China
| | - Tingxi Yu
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing 100081, China
- Nanfan Research Institute, CAAS, Sanya, Hainan 572024, China
| | - Junjie Fu
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing 100081, China
| | - Shang Gao
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing 100081, China
- Nanfan Research Institute, CAAS, Sanya, Hainan 572024, China
| | - Huihui Li
- State Key Laboratory of Crop Gene Resources and Breeding, Institute of Crop Sciences, Chinese Academy of Agricultural Sciences (CAAS), Beijing 100081, China
- Nanfan Research Institute, CAAS, Sanya, Hainan 572024, China
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Han M, Niu M, Gao T, Shen Y, Zhou X, Zhang Y, Liu L, Chai M, Sun G, Wang Y. Responsive Alternative Splicing Events of Opisthopappus Species against Salt Stress. Int J Mol Sci 2024; 25:1227. [PMID: 38279226 PMCID: PMC10816081 DOI: 10.3390/ijms25021227] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Revised: 12/20/2023] [Accepted: 01/09/2024] [Indexed: 01/28/2024] Open
Abstract
Salt stress profoundly affects plant growth, prompting intricate molecular responses, such as alternative splicing (AS), for environmental adaptation. However, the response of AS events to salt stress in Opisthopappus (Opisthopappus taihangensis and Opisthopappus longilobus) remains unclear, which is a Taihang Mountain cliff-dwelling species. Using RNA-seq data, differentially expressed genes (DEGs) were identified under time and concentration gradients of salt stress. Two types of AS, skipped exon (SE) and mutually exclusive exons (MXE), were found. Differentially alternative splicing (DAS) genes in both species were significantly enriched in "protein phosphorylation", "starch and sucrose metabolism", and "plant hormone signal transduction" pathways. Meanwhile, distinct GO terms and KEGG pathways of DAS occurred between two species. Only a small subset of DAS genes overlapped with DEGs under salt stress. Although both species likely adopted protein phosphorylation to enhance salt stress tolerance, they exhibited distinct responses. The results indicated that the salt stress mechanisms of both Opisthopappus species exhibited similarities and differences in response to salt stress, which suggested that adaptive divergence might have occurred between them. This study initially provides a comprehensive description of salt responsive AS events in Opisthopappus and conveys some insights into the molecular mechanisms behind species tolerance on the Taihang Mountains.
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Affiliation(s)
- Mian Han
- School of Life Science, Shanxi Normal University, Taiyuan 030031, China; (M.H.)
| | - Mengfan Niu
- School of Life Science, Shanxi Normal University, Taiyuan 030031, China; (M.H.)
| | - Ting Gao
- School of Life Science, Shanxi Normal University, Taiyuan 030031, China; (M.H.)
| | - Yuexin Shen
- School of Life Science, Shanxi Normal University, Taiyuan 030031, China; (M.H.)
| | - Xiaojuan Zhou
- School of Life Science, Shanxi Normal University, Taiyuan 030031, China; (M.H.)
| | - Yimeng Zhang
- School of Life Science, Shanxi Normal University, Taiyuan 030031, China; (M.H.)
| | - Li Liu
- School of Life Science, Shanxi Normal University, Taiyuan 030031, China; (M.H.)
| | - Min Chai
- School of Life Science, Shanxi Normal University, Taiyuan 030031, China; (M.H.)
| | - Genlou Sun
- Department of Botany, Saint Mary’s University, Halifax, NS B3H 3C3, Canada
| | - Yiling Wang
- School of Life Science, Shanxi Normal University, Taiyuan 030031, China; (M.H.)
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Chen J, Zhang L, Liu Y, Shen X, Guo Y, Ma X, Zhang X, Li X, Cheng T, Wen H, Qiao L, Chang Z. RNA-Seq-Based WGCNA and Association Analysis Reveal the Key Regulatory Module and Genes Responding to Salt Stress in Wheat Roots. PLANTS (BASEL, SWITZERLAND) 2024; 13:274. [PMID: 38256827 PMCID: PMC10818790 DOI: 10.3390/plants13020274] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Revised: 01/13/2024] [Accepted: 01/15/2024] [Indexed: 01/24/2024]
Abstract
Soil salinization is the main abiotic stressor faced by crops. An improved understanding of the transcriptional response to salt stress in roots, the organ directly exposed to a high salinity environment, can inform breeding strategies to enhance tolerance and increase crop yield. Here, RNA-sequencing was performed on the roots of salt-tolerant wheat breeding line CH7034 at 0, 1, 6, 24, and 48 h after NaCl treatment. Based on transcriptome data, a weighted gene co-expression network analysis (WGCNA) was constructed, and five gene co-expression modules were obtained, of which the blue module was correlated with the time course of salt stress at 1 and 48 h. Two GO terms containing 249 differentially expressed genes (DEGs) related to osmotic stress response and salt-stress response were enriched in the blue module. These DEGs were subsequently used for association analysis with a set of wheat germplasm resources, and the results showed that four genes, namely a Walls Are Thin 1-related gene (TaWAT), an aquaporin gene (TaAQP), a glutathione S-transfer gene (TaGST), and a zinc finger gene (TaZFP), were associated with the root salt-tolerance phenotype. Using the four candidate genes as hub genes, a co-expression network was constructed with another 20 DEGs with edge weights greater than 0.6. The network showed that TaWAT and TaAQP were mainly co-expressed with fifteen interacting DEGs 1 h after salt treatment, while TaGST and TaZFP were mainly co-expressed with five interacting DEGs 48 h after salt treatment. This study provides key modules and candidate genes for understanding the salt-stress response mechanism in wheat roots.
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Affiliation(s)
- Jiating Chen
- College of Agronomy, Shanxi Key Laboratory of Crop Genetics and Molecular Improvement, Shanxi Agricultural University, Taiyuan 030031, China; (J.C.); (X.Z.); (X.L.); (T.C.); (H.W.)
| | - Lei Zhang
- Department of Biology, Taiyuan Normal University, Taiyuan 030031, China;
| | - Yingxi Liu
- College of Agronomy, Shanxi Key Laboratory of Crop Genetics and Molecular Improvement, Shanxi Agricultural University, Taiyuan 030031, China; (J.C.); (X.Z.); (X.L.); (T.C.); (H.W.)
| | - Xinyao Shen
- College of Agronomy, Shanxi Key Laboratory of Crop Genetics and Molecular Improvement, Shanxi Agricultural University, Taiyuan 030031, China; (J.C.); (X.Z.); (X.L.); (T.C.); (H.W.)
| | - Yujing Guo
- College of Agronomy, Shanxi Key Laboratory of Crop Genetics and Molecular Improvement, Shanxi Agricultural University, Taiyuan 030031, China; (J.C.); (X.Z.); (X.L.); (T.C.); (H.W.)
| | - Xiaofei Ma
- Institute of Wheat Research, Shanxi Agricultural University, Linfen 041000, China
| | - Xiaojun Zhang
- College of Agronomy, Shanxi Key Laboratory of Crop Genetics and Molecular Improvement, Shanxi Agricultural University, Taiyuan 030031, China; (J.C.); (X.Z.); (X.L.); (T.C.); (H.W.)
| | - Xin Li
- College of Agronomy, Shanxi Key Laboratory of Crop Genetics and Molecular Improvement, Shanxi Agricultural University, Taiyuan 030031, China; (J.C.); (X.Z.); (X.L.); (T.C.); (H.W.)
| | - Tianling Cheng
- College of Agronomy, Shanxi Key Laboratory of Crop Genetics and Molecular Improvement, Shanxi Agricultural University, Taiyuan 030031, China; (J.C.); (X.Z.); (X.L.); (T.C.); (H.W.)
| | - Huiqin Wen
- College of Agronomy, Shanxi Key Laboratory of Crop Genetics and Molecular Improvement, Shanxi Agricultural University, Taiyuan 030031, China; (J.C.); (X.Z.); (X.L.); (T.C.); (H.W.)
| | - Linyi Qiao
- College of Agronomy, Shanxi Key Laboratory of Crop Genetics and Molecular Improvement, Shanxi Agricultural University, Taiyuan 030031, China; (J.C.); (X.Z.); (X.L.); (T.C.); (H.W.)
| | - Zhijian Chang
- College of Agronomy, Shanxi Key Laboratory of Crop Genetics and Molecular Improvement, Shanxi Agricultural University, Taiyuan 030031, China; (J.C.); (X.Z.); (X.L.); (T.C.); (H.W.)
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