The Rice Microbiome: A Model Platform for Crop Holobiome

被引:51
|
作者
Kim, Hyun [1 ]
Lee, Yong-Hwan [1 ,2 ,3 ]
机构
[1] Seoul Natl Univ, Dept Agr Biotechnol, Seoul 08826, South Korea
[2] Seoul Natl Univ, Ctr Fungal Genet Resources, Interdisciplinary Program Agr Genom, Plant Immun Res Ctr, Seoul 08826, South Korea
[3] Seoul Natl Univ, Res Inst Agr & Life Sci, Seoul 08826, South Korea
来源
PHYTOBIOMES JOURNAL | 2020年 / 4卷 / 01期
基金
新加坡国家研究基金会;
关键词
agriculture; crop microbiome; microbial ecology; plant microbiome; rice; ORYZA-SATIVA; BACTERIAL COMMUNITY; FUNGAL COMMUNITIES; RHIZOSPHERE MICROBIOME; ENDOPHYTIC BACTERIAL; ROOT MICROBIOME; WILD RELATIVES; GUT MICROBIOTA; PLANT-GROWTH; HUMAN HEALTH;
D O I
10.1094/PBIOMES-07-19-0035-RVW
中图分类号
Q94 [植物学];
学科分类号
071001 ;
摘要
The plant microbiome, the consortium of microbes surrounding a plant, has potential for improving crop productivity and sustainability. Despite the necessity of agriculturally applicable microbiomes, plant microbiome studies have been conducted in noncrop plants because of the relative easiness of research. However, in order to make plant microbiomes useful for agriculture, a crop plant-based model is needed. In parallel, overlooked parts of microbiomes other than the bacteria-centered research need to be considered to expand our understandings on microbiomes to the ecosystem level. Beyond the microbial composition, functional properties of microbiomes over time and space will help us to select appropriate microbes that can support crop plants by providing stage-specific functions. Less explored communities such as fungi and protists also can provide novel insights on compositional and functional dynamics of each community, including interkingdom or multitrophic interactions. Finally, identification of host factors on functional microbiomes using genetic information of both the host and the microbiomes will shift host-centered breeding to parallel breeding of host and microbiome. This review will give basic and collective information on the rice microbiome and foster the establishment of a crop plant-based model to meet agricultural needs.
引用
收藏
页码:5 / 18
页数:14
相关论文
共 50 条
  • [31] Accounting for both parameter and model structure uncertainty in crop model predictions of phenology: A case study on rice
    Wallach, Daniel
    Nissanka, Sarath P.
    Karunaratne, Asha S.
    Weerakoon, W. M. W.
    Thorburn, Peter J.
    Boote, Kenneth J.
    Jones, James W.
    EUROPEAN JOURNAL OF AGRONOMY, 2017, 88 : 53 - 62
  • [32] Using a crop/soil simulation model and GIS techniques to assess methane emissions from rice fields in Asia. I. Model development
    Matthews, RB
    Wassmann, R
    Arah, J
    NUTRIENT CYCLING IN AGROECOSYSTEMS, 2000, 58 (1-3) : 141 - 159
  • [33] Predicting rice phenology across China by integrating crop phenology model and machine learning
    Zhang, Jinhan
    Lin, Xiaomao
    Jiang, Chongya
    Hu, Xuntao
    Liu, Bing
    Liu, Leilei
    Xiao, Liujun
    Zhu, Yan
    Cao, Weixing
    Tang, Liang
    SCIENCE OF THE TOTAL ENVIRONMENT, 2024, 951
  • [34] Calibration of the Jensen' Yield Prediction Model for Rice Crop Cultivated in the Northern Region of Vietnam
    Tran Van Dat
    Hasan, Md. Mainul
    PERTANIKA JOURNAL OF SCIENCE AND TECHNOLOGY, 2019, 27 (03): : 1169 - 1180
  • [35] Functional characterization of a new metallochaperone for reducing cadmium concentration in rice crop
    Khan, Irfan Ullah
    Rono, Justice Kipkorir
    Liu, Xue Song
    Feng, Sheng Jun
    Li, He
    Chen, Xi
    Yang, Zhi Min
    JOURNAL OF CLEANER PRODUCTION, 2020, 272
  • [36] Awn Reduction and the Domestication of Asian Rice: A Syndrome or Crop Improvement Trait?
    Svizzero, Serge
    Ray, Avik
    Chakraborty, Debarati
    ECONOMIC BOTANY, 2019, 73 (04) : 477 - 488
  • [37] Rice functional genomics research: Progress and implications for crop genetic improvement
    Jiang, Yunhe
    Cai, Zhaoxia
    Xie, Weibo
    Long, Tuan
    Yu, Huihui
    Zhang, Qifa
    BIOTECHNOLOGY ADVANCES, 2012, 30 (05) : 1059 - 1070
  • [38] Rice Plant-Soil Microbiome Interactions Driven by Root and Shoot Biomass
    Fernandez-Baca, Cristina P.
    Rivers, Adam R.
    Maul, Jude E.
    Kim, Woojae
    Poudel, Ravin
    McClung, Anna M.
    Roberts, Daniel P.
    Reddy, Vangimalla R.
    Barnaby, Jinyoung Y.
    DIVERSITY-BASEL, 2021, 13 (03):
  • [39] Rhizosphere Microbiome Cooperations: Strategies for Sustainable Crop Production
    Babalola, Olubukola O.
    Emmanuel, Obianuju C.
    Adeleke, Bartholomew S.
    Odelade, Kehinde A.
    Nwachukwu, Blessing C.
    Ayiti, Oluwatobi E.
    Adegboyega, Taofeek T.
    Igiehon, Nicholas O.
    CURRENT MICROBIOLOGY, 2021, 78 (04) : 1069 - 1085
  • [40] Exploiting the microbiome associated with normal and abnormal sprouting rice (Oryza sativa L.) seed phenotypes through a metabarcoding approach
    Nanfack, Albert Dongmo
    Nguefack, Julienne
    Musonerimana, Samson
    La China, Salvatore
    Giovanardi, Davide
    Stefani, Emilio
    MICROBIOLOGICAL RESEARCH, 2024, 279