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Govta N, Fatiukha A, Govta L, Pozniak C, Distelfeld A, Fahima T, Beckles DM, Krugman T. Nitrogen deficiency tolerance conferred by introgression of a QTL derived from wild emmer into bread wheat. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2024; 137:187. [PMID: 39020219 PMCID: PMC11255033 DOI: 10.1007/s00122-024-04692-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/21/2024] [Accepted: 07/04/2024] [Indexed: 07/19/2024]
Abstract
KEY MESSAGE Genetic dissection of a QTL from wild emmer wheat, QGpc.huj.uh-5B.2, introgressed into bread wheat, identified candidate genes associated with tolerance to nitrogen deficiency, and potentially useful for improving nitrogen-use efficiency. Nitrogen (N) is an important macronutrient critical to wheat growth and development; its deficiency is one of the main factors causing reductions in grain yield and quality. N availability is significantly affected by drought or flooding, that are dependent on additional factors including soil type or duration and severity of stress. In a previous study, we identified a high grain protein content QTL (QGpc.huj.uh-5B.2) derived from the 5B chromosome of wild emmer wheat, that showed a higher proportion of explained variation under water-stress conditions. We hypothesized that this QTL is associated with tolerance to N deficiency as a possible mechanism underlying the higher effect under stress. To validate this hypothesis, we introgressed the QTL into the elite bread wheat var. Ruta, and showed that under N-deficient field conditions the introgression IL99 had a 33% increase in GPC (p < 0.05) compared to the recipient parent. Furthermore, evaluation of IL99 response to severe N deficiency (10% N) for 14 days, applied using a semi-hydroponic system under controlled conditions, confirmed its tolerance to N deficiency. Fine-mapping of the QTL resulted in 26 homozygous near-isogenic lines (BC4F5) segregating to N-deficiency tolerance. The QTL was delimited from - 28.28 to - 1.29 Mb and included 13 candidate genes, most associated with N-stress response, N transport, and abiotic stress responses. These genes may improve N-use efficiency under severely N-deficient environments. Our study demonstrates the importance of WEW as a source of novel candidate genes for sustainable improvement in tolerance to N deficiency in wheat.
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Affiliation(s)
- Nikolai Govta
- Wild Cereal Gene Bank, Institute of Evolution, University of Haifa, Abba Khoushy Ave 199, 3498838, Haifa, Israel
- Department of Evolutionary and Environmental Biology, University of Haifa, Abba Khoushy Ave 199, 3498838, Haifa, Israel
| | - Andrii Fatiukha
- Department of Evolutionary and Environmental Biology, University of Haifa, Abba Khoushy Ave 199, 3498838, Haifa, Israel
- Crop Development Centre and Department of Plant Sciences, University of Saskatchewan, Saskatoon, Canada
| | - Liubov Govta
- Department of Evolutionary and Environmental Biology, University of Haifa, Abba Khoushy Ave 199, 3498838, Haifa, Israel
| | - Curtis Pozniak
- Crop Development Centre and Department of Plant Sciences, University of Saskatchewan, Saskatoon, Canada
| | - Assaf Distelfeld
- Department of Evolutionary and Environmental Biology, University of Haifa, Abba Khoushy Ave 199, 3498838, Haifa, Israel
| | - Tzion Fahima
- Department of Evolutionary and Environmental Biology, University of Haifa, Abba Khoushy Ave 199, 3498838, Haifa, Israel
| | - Diane M Beckles
- Department of Plant Sciences, University of California, Davis, CA, 95616, USA
| | - Tamar Krugman
- Wild Cereal Gene Bank, Institute of Evolution, University of Haifa, Abba Khoushy Ave 199, 3498838, Haifa, Israel.
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Wang Y, Li P, Zhu Y, Shang Y, Wu Z, Tao Y, Wang H, Li D, Zhang C. Transcriptome Profiling Reveals the Gene Network Responding to Low Nitrogen Stress in Wheat. PLANTS (BASEL, SWITZERLAND) 2024; 13:371. [PMID: 38337903 PMCID: PMC10856819 DOI: 10.3390/plants13030371] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/29/2023] [Revised: 01/18/2024] [Accepted: 01/22/2024] [Indexed: 02/12/2024]
Abstract
As one of the essential nutrients for plants, nitrogen (N) has a major impact on the yield and quality of wheat worldwide. Due to chemical fertilizer pollution, it has become increasingly important to improve crop yield by increasing N use efficiency (NUE). Therefore, understanding the response mechanisms to low N (LN) stress is essential for the regulation of NUE in wheat. In this study, LN stress significantly accelerated wheat root growth, but inhibited shoot growth. Further transcriptome analysis showed that 8468 differentially expressed genes (DEGs) responded to LN stress. The roots and shoots displayed opposite response patterns, of which the majority of DEGs in roots were up-regulated (66.15%; 2955/4467), but the majority of DEGs in shoots were down-regulated (71.62%; 3274/4565). GO and KEGG analyses showed that nitrate reductase activity, nitrate assimilation, and N metabolism were significantly enriched in both the roots and shoots. Transcription factor (TF) and protein kinase analysis showed that genes such as MYB-related (38/38 genes) may function in a tissue-specific manner to respond to LN stress. Moreover, 20 out of 107 N signaling homologous genes were differentially expressed in wheat. A total of 47 transcriptome datasets were used for weighted gene co-expression network analysis (17,840 genes), and five TFs were identified as the potential hub regulatory genes involved in the response to LN stress in wheat. Our findings provide insight into the functional mechanisms in response to LN stress and five candidate regulatory genes in wheat. These results will provide a basis for further research on promoting NUE in wheat.
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Affiliation(s)
- Yiwei Wang
- College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan 030024, China;
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Synthetic Biology, Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China; (P.L.); (Y.Z.); (Y.S.); (Z.W.); (Y.T.); (H.W.)
| | - Pengfeng Li
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Synthetic Biology, Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China; (P.L.); (Y.Z.); (Y.S.); (Z.W.); (Y.T.); (H.W.)
- College of Life Sciences, South China Agricultural University, Guangzhou 510642, China
| | - Yiwang Zhu
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Synthetic Biology, Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China; (P.L.); (Y.Z.); (Y.S.); (Z.W.); (Y.T.); (H.W.)
| | - Yuping Shang
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Synthetic Biology, Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China; (P.L.); (Y.Z.); (Y.S.); (Z.W.); (Y.T.); (H.W.)
- College of Agronomy, Shanxi Agricultural University, Jinzhong 030801, China
| | - Zhiqiang Wu
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Synthetic Biology, Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China; (P.L.); (Y.Z.); (Y.S.); (Z.W.); (Y.T.); (H.W.)
| | - Yongfu Tao
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Synthetic Biology, Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China; (P.L.); (Y.Z.); (Y.S.); (Z.W.); (Y.T.); (H.W.)
| | - Hongru Wang
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Synthetic Biology, Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China; (P.L.); (Y.Z.); (Y.S.); (Z.W.); (Y.T.); (H.W.)
| | - Dongxi Li
- College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan 030024, China;
| | - Cuijun Zhang
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Synthetic Biology, Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China; (P.L.); (Y.Z.); (Y.S.); (Z.W.); (Y.T.); (H.W.)
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Naqvi RZ, Mahmood MA, Mansoor S, Amin I, Asif M. Omics-driven exploration and mining of key functional genes for the improvement of food and fiber crops. FRONTIERS IN PLANT SCIENCE 2024; 14:1273859. [PMID: 38259913 PMCID: PMC10800452 DOI: 10.3389/fpls.2023.1273859] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Accepted: 12/08/2023] [Indexed: 01/24/2024]
Abstract
The deployment of omics technologies has obtained an incredible boost over the past few decades with the advances in next-generation sequencing (NGS) technologies, innovative bioinformatics tools, and the deluge of available biological information. The major omics technologies in the limelight are genomics, transcriptomics, proteomics, metabolomics, and phenomics. These biotechnological advances have modernized crop breeding and opened new horizons for developing crop varieties with improved traits. The genomes of several crop species are sequenced, and a huge number of genes associated with crucial economic traits have been identified. These identified genes not only provide insights into the understanding of regulatory mechanisms of crop traits but also decipher practical grounds to assist in the molecular breeding of crops. This review discusses the potential of omics technologies for the acquisition of biological information and mining of the genes associated with important agronomic traits in important food and fiber crops, such as wheat, rice, maize, potato, tomato, cassava, and cotton. Different functional genomics approaches for the validation of these important genes are also highlighted. Furthermore, a list of genes discovered by employing omics approaches is being represented as potential targets for genetic modifications by the latest genome engineering methods for the development of climate-resilient crops that would in turn provide great impetus to secure global food security.
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Affiliation(s)
- Rubab Zahra Naqvi
- Agricultural Biotechnology Division, National Institute for Biotechnology and Genetic Engineering College Pakistan Institute of Engineering and Applied Sciences, Faisalabad, Pakistan
| | - Muhammad Arslan Mahmood
- Agricultural Biotechnology Division, National Institute for Biotechnology and Genetic Engineering College Pakistan Institute of Engineering and Applied Sciences, Faisalabad, Pakistan
| | - Shahid Mansoor
- Agricultural Biotechnology Division, National Institute for Biotechnology and Genetic Engineering College Pakistan Institute of Engineering and Applied Sciences, Faisalabad, Pakistan
- International Center for Chemical and Biological Sciences, University of Karachi, Karachi, Pakistan
| | - Imran Amin
- Agricultural Biotechnology Division, National Institute for Biotechnology and Genetic Engineering College Pakistan Institute of Engineering and Applied Sciences, Faisalabad, Pakistan
| | - Muhammad Asif
- Agricultural Biotechnology Division, National Institute for Biotechnology and Genetic Engineering College Pakistan Institute of Engineering and Applied Sciences, Faisalabad, Pakistan
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Abbas ZN, Al-Saffar AZ, Jasim SM, Sulaiman GM. Comparative analysis between 2D and 3D colorectal cancer culture models for insights into cellular morphological and transcriptomic variations. Sci Rep 2023; 13:18380. [PMID: 37884554 PMCID: PMC10603139 DOI: 10.1038/s41598-023-45144-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Accepted: 10/16/2023] [Indexed: 10/28/2023] Open
Abstract
Drug development is a time-consuming and expensive process, given the low success rate of clinical trials. Now, anticancer drug developments have shifted to three-dimensional (3D) models which are more likely to mimic tumor behavior compared to traditional two-dimensional (2D) cultures. A comparative study among different aspects was conducted between 2D and 3D cultures using colorectal cancer (CRC) cell lines, in addition, Formalin-Fixed Paraffin-Embedded (FFPE) block samples of patients with CRC were used for evaluation. Compared to the 2D culture, cells grown in 3D displayed significant (p < 0.01) differences in the pattern of cell proliferation over time, cell death phase profile, expression of tumorgenicity-related genes, and responsiveness to 5-fluorouracil, cisplatin, and doxorubicin. Epigenetically, 3D cultures and FFPE shared the same methylation pattern and microRNA expression, while 2D cells showed elevation in methylation rate and altered microRNA expression. Lastly, transcriptomic study depending on RNA sequencing and thorough bioinformatic analyses showed significant (p-adj < 0.05) dissimilarity in gene expression profile between 2D and 3D cultures involving thousands of genes (up/down-regulated) of multiple pathways for each cell line. Taken together, the study provides insights into variations in cellular morphologies between cells cultured in 2D and 3D models.
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Affiliation(s)
- Zaid Nsaif Abbas
- Department of Molecular and Medical Biotechnology, College of Biotechnology, Al-Nahrain University, Jadriya, Baghdad, Iraq
| | - Ali Z Al-Saffar
- Department of Molecular and Medical Biotechnology, College of Biotechnology, Al-Nahrain University, Jadriya, Baghdad, Iraq.
| | - Saba Mahdi Jasim
- Oncology Teaching Hospital, Medical City, Ministry of Health, Baghdad, Iraq
| | - Ghassan M Sulaiman
- Division of Biotechnology, Department of Applied Sciences, University of Technology, Baghdad, Iraq
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Mahto A, Yadav A, P V A, Parida SK, Tyagi AK, Agarwal P. Cytological, transcriptome and miRNome temporal landscapes decode enhancement of rice grain size. BMC Biol 2023; 21:91. [PMID: 37076907 PMCID: PMC10116700 DOI: 10.1186/s12915-023-01577-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Accepted: 03/27/2023] [Indexed: 04/21/2023] Open
Abstract
BACKGROUND Rice grain size (GS) is an essential agronomic trait. Though several genes and miRNA modules influencing GS are known and seed development transcriptomes analyzed, a comprehensive compendium connecting all possible players is lacking. This study utilizes two contrasting GS indica rice genotypes (small-grained SN and large-grained LGR). Rice seed development involves five stages (S1-S5). Comparative transcriptome and miRNome atlases, substantiated with morphological and cytological studies, from S1-S5 stages and flag leaf have been analyzed to identify GS proponents. RESULTS Histology shows prolonged endosperm development and cell enlargement in LGR. Stand-alone and comparative RNAseq analyses manifest S3 (5-10 days after pollination) stage as crucial for GS enhancement, coherently with cell cycle, endoreduplication, and programmed cell death participating genes. Seed storage protein and carbohydrate accumulation, cytologically and by RNAseq, is shown to be delayed in LGR. Fourteen transcription factor families influence GS. Pathway genes for four phytohormones display opposite patterns of higher expression. A total of 186 genes generated from the transcriptome analyses are located within GS trait-related QTLs deciphered by a cross between SN and LGR. Fourteen miRNA families express specifically in SN or LGR seeds. Eight miRNA-target modules display contrasting expressions amongst SN and LGR, while 26 (SN) and 43 (LGR) modules are differentially expressed in all stages. CONCLUSIONS Integration of all analyses concludes in a "Domino effect" model for GS regulation highlighting chronology and fruition of each event. This study delineates the essence of GS regulation, providing scope for future exploits. The rice grain development database (RGDD) ( www.nipgr.ac.in/RGDD/index.php ; https://doi.org/10.5281/zenodo.7762870 ) has been developed for easy access of data generated in this paper.
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Affiliation(s)
- Arunima Mahto
- National Institute of Plant Genome Research, New Delhi, India
| | - Antima Yadav
- National Institute of Plant Genome Research, New Delhi, India
| | - Aswathi P V
- National Institute of Plant Genome Research, New Delhi, India
| | - Swarup K Parida
- National Institute of Plant Genome Research, New Delhi, India
| | - Akhilesh K Tyagi
- Interdisciplinary Centre for Plant Genomics and Department of Plant Molecular Biology, University of Delhi South Campus, New Delhi, India
| | - Pinky Agarwal
- National Institute of Plant Genome Research, New Delhi, India.
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