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Yang FS, Liu M, Guo X, Xu C, Jiang J, Mu W, Fang D, Xu YC, Zhang FM, Wang YH, Yang T, Chen H, Sahu SK, Li R, Wang G, Wang Q, Xu X, Ge S, Liu H, Guo YL. Signatures of Adaptation and Purifying Selection in Highland Populations of Dasiphora fruticosa. Mol Biol Evol 2024; 41:msae099. [PMID: 38768215 PMCID: PMC11156201 DOI: 10.1093/molbev/msae099] [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: 08/23/2023] [Revised: 05/07/2024] [Accepted: 05/13/2024] [Indexed: 05/22/2024] Open
Abstract
High mountains harbor a considerable proportion of biodiversity, but we know little about how diverse plants adapt to the harsh environment. Here we finished a high-quality genome assembly for Dasiphora fruticosa, an ecologically important plant distributed in the Qinghai-Tibetan Plateau and lowland of the Northern Hemisphere, and resequenced 592 natural individuals to address how this horticulture plant adapts to highland. Demographic analysis revealed D. fruticosa underwent a bottleneck after Naynayxungla Glaciation. Selective sweep analysis of two pairs of lowland and highland populations identified 63 shared genes related to cell wall organization or biogenesis, cellular component organization, and dwarfism, suggesting parallel adaptation to highland habitats. Most importantly, we found that stronger purging of estimated genetic load due to inbreeding in highland populations apparently contributed to their adaptation to the highest mountain. Our results revealed how plants could tolerate the extreme plateau, which could provide potential insights for species conservation and crop breeding.
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Affiliation(s)
- Fu-Sheng Yang
- State Key Laboratory of Systematic and Evolutionary Botany, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China
- China National Botanical Garden, Beijing 100093, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Min Liu
- State Key Laboratory of Agricultural Genomics, Key Laboratory of Genomics, Ministry of Agriculture, BGI Research, Shenzhen 518083, China
- BGI Research, Wuhan 430074, China
| | - Xing Guo
- State Key Laboratory of Agricultural Genomics, Key Laboratory of Genomics, Ministry of Agriculture, BGI Research, Shenzhen 518083, China
- BGI Research, Wuhan 430074, China
| | - Chao Xu
- State Key Laboratory of Systematic and Evolutionary Botany, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China
- China National Botanical Garden, Beijing 100093, China
| | - Juan Jiang
- State Key Laboratory of Systematic and Evolutionary Botany, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China
- China National Botanical Garden, Beijing 100093, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Weixue Mu
- State Key Laboratory of Agricultural Genomics, Key Laboratory of Genomics, Ministry of Agriculture, BGI Research, Shenzhen 518083, China
| | - Dongming Fang
- State Key Laboratory of Agricultural Genomics, Key Laboratory of Genomics, Ministry of Agriculture, BGI Research, Shenzhen 518083, China
| | - Yong-Chao Xu
- State Key Laboratory of Systematic and Evolutionary Botany, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China
- China National Botanical Garden, Beijing 100093, China
| | - Fu-Min Zhang
- State Key Laboratory of Systematic and Evolutionary Botany, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China
- China National Botanical Garden, Beijing 100093, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Ying-Hui Wang
- State Key Laboratory of Systematic and Evolutionary Botany, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China
- China National Botanical Garden, Beijing 100093, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Ting Yang
- State Key Laboratory of Agricultural Genomics, Key Laboratory of Genomics, Ministry of Agriculture, BGI Research, Shenzhen 518083, China
| | - Hongyun Chen
- State Key Laboratory of Agricultural Genomics, Key Laboratory of Genomics, Ministry of Agriculture, BGI Research, Shenzhen 518083, China
| | - Sunil Kumar Sahu
- State Key Laboratory of Agricultural Genomics, Key Laboratory of Genomics, Ministry of Agriculture, BGI Research, Shenzhen 518083, China
- BGI Research, Wuhan 430074, China
| | - Ruirui Li
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
- State Key Laboratory of Agricultural Genomics, Key Laboratory of Genomics, Ministry of Agriculture, BGI Research, Shenzhen 518083, China
| | - Guanlong Wang
- State Key Laboratory of Agricultural Genomics, Key Laboratory of Genomics, Ministry of Agriculture, BGI Research, Shenzhen 518083, China
| | - Qiang Wang
- State Key Laboratory of Systematic and Evolutionary Botany, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China
- China National Botanical Garden, Beijing 100093, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xun Xu
- State Key Laboratory of Agricultural Genomics, Key Laboratory of Genomics, Ministry of Agriculture, BGI Research, Shenzhen 518083, China
| | - Song Ge
- State Key Laboratory of Systematic and Evolutionary Botany, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China
- China National Botanical Garden, Beijing 100093, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Huan Liu
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
- State Key Laboratory of Agricultural Genomics, Key Laboratory of Genomics, Ministry of Agriculture, BGI Research, Shenzhen 518083, China
| | - Ya-Long Guo
- State Key Laboratory of Systematic and Evolutionary Botany, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China
- China National Botanical Garden, Beijing 100093, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
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Schroeder MM, Gomez MY, McLain N, Gachomo EW. Bradyrhizobium japonicum IRAT FA3 Alters Arabidopsis thaliana Root Architecture via Regulation of Auxin Efflux Transporters PIN2, PIN3, PIN7, and ABCB19. MOLECULAR PLANT-MICROBE INTERACTIONS : MPMI 2022; 35:215-229. [PMID: 34941379 DOI: 10.1094/mpmi-05-21-0118-r] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Beneficial rhizobacteria can stimulate changes in plant root development. Although root system growth is mediated by multiple factors, the regulated distribution of the phytohormone auxin within root tissues plays a principal role. Auxin transport facilitators help to generate the auxin gradients and maxima that determine root structure. Here, we show that the plant-growth-promoting rhizobacterial strain Bradyrhizobium japonicum IRAT FA3 influences specific auxin efflux transporters to alter Arabidopsis thaliana root morphology. Gene expression profiling of host transcripts in control and B. japonicum-inoculated roots of the wild-type A. thaliana accession Col-0 confirmed upregulation of PIN2, PIN3, PIN7, and ABCB19 with B. japonicum and identified genes potentially contributing to a diverse array of auxin-related responses. Cocultivation of the bacterium with loss-of-function auxin efflux transport mutants revealed that B. japonicum requires PIN3, PIN7, and ABCB19 to increase lateral root development and utilizes PIN2 to reduce primary root length. Accelerated lateral root primordia production due to B. japonicum was not observed in single pin3, pin7, or abcb19 mutants, suggesting independent roles for PIN3, PIN7, and ABCB19 during the plant-microbe interaction. Our work demonstrates B. japonicum's influence over host transcriptional reprogramming during plant interaction with this beneficial microbe and the subsequent alterations to root system architecture.[Formula: see text] Copyright © 2022 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.
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Affiliation(s)
- Mercedes M Schroeder
- Department of Microbiology and Plant Pathology, University of California-Riverside, Riverside, CA 92521, U.S.A
| | - Melissa Y Gomez
- Department of Microbiology and Plant Pathology, University of California-Riverside, Riverside, CA 92521, U.S.A
| | - Nathan McLain
- Department of Microbiology and Plant Pathology, University of California-Riverside, Riverside, CA 92521, U.S.A
| | - Emma W Gachomo
- Department of Microbiology and Plant Pathology, University of California-Riverside, Riverside, CA 92521, U.S.A
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Zhou J, Tian L, Wang S, Li H, Zhao Y, Zhang M, Wang X, An P, Li C. Ovary Abortion Induced by Combined Waterlogging and Shading Stress at the Flowering Stage Involves Amino Acids and Flavonoid Metabolism in Maize. FRONTIERS IN PLANT SCIENCE 2021; 12:778717. [PMID: 34887895 PMCID: PMC8649655 DOI: 10.3389/fpls.2021.778717] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Accepted: 11/01/2021] [Indexed: 05/26/2023]
Abstract
Maize (Zea mays L.) crops on the North China Plain are often subject to continuous overcast rain at the flowering stage. This causes waterlogging and shading stresses simultaneously and leads to huge yield losses, but the causes of these yield losses remain largely unknown. To explore the factors contributing to yield loss caused by combined waterlogging and shading stress at the flowering stage, we performed phenotypic, physiological, and quasi-targeted metabolomics analyses of maize plants subjected to waterlogging, shading, and combined waterlogging and shading (WS) treatments. Analyses of phenotypic and physiological indexes showed that, compared with waterlogging or shading alone, WS resulted in lower source strength, more severe inhibition of ovary and silk growth at the ear tip, a reduced number of emerged silks, and a higher rate of ovary abortion. Changes in carbon content and enzyme activity could not explain the ovary abortion in our study. Metabolomic analyses showed that the events occurred in ovaries and silks were closely related to abortion, WS forced the ovary to allocate more resources to the synthesis of amino acids involved in the stress response, inhibited the energy metabolism, glutathione metabolism and methionine salvage pathway, and overaccumulation of H2O2. In silks, WS led to lower accumulation levels of specific flavonoid metabolites with antioxidant capacity, and to over accumulation of H2O2. Thus, compared with each single stress, WS more seriously disrupted the normal metabolic process, and resulted more serious oxidative stress in ovaries and silks. Amino acids involved in the stress response in ovaries and specific flavonoid metabolites with antioxidant capacity in silks play important roles during ovary abortion. These results identify novel traits for selection in breeding programs and targets for genome editing to increase maize yield under WS stress.
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