Literature DB >> 28122143

Metabolic robustness in young roots underpins a predictive model of maize hybrid performance in the field.

Francisco de Abreu E Lima1, Matthias Westhues2, Álvaro Cuadros-Inostroza3, Lothar Willmitzer1, Albrecht E Melchinger2, Zoran Nikoloski1.   

Abstract

Heterosis has been extensively exploited for yield gain in maize (Zea mays L.). Here we conducted a comparative metabolomics-based analysis of young roots from in vitro germinating seedlings and from leaves of field-grown plants in a panel of inbred lines from the Dent and Flint heterotic patterns as well as selected F1 hybrids. We found that metabolite levels in hybrids were more robust than in inbred lines. Using state-of-the-art modeling techniques, the most robust metabolites from roots and leaves explained up to 37 and 44% of the variance in the biomass from plants grown in two distinct field trials. In addition, a correlation-based analysis highlighted the trade-off between defense-related metabolites and hybrid performance. Therefore, our findings demonstrated the potential of metabolic profiles from young maize roots grown under tightly controlled conditions to predict hybrid performance in multiple field trials, thus bridging the greenhouse-field gap.
© 2017 The Authors The Plant Journal © 2017 John Wiley & Sons Ltd.

Entities:  

Keywords:  zzm321990Zea mayszzm321990; hybrid performance; metabolomics; prediction; robustness

Mesh:

Year:  2017        PMID: 28122143     DOI: 10.1111/tpj.13495

Source DB:  PubMed          Journal:  Plant J        ISSN: 0960-7412            Impact factor:   6.417


  13 in total

1.  Beyond Genomic Prediction: Combining Different Types of omics Data Can Improve Prediction of Hybrid Performance in Maize.

Authors:  Tobias A Schrag; Matthias Westhues; Wolfgang Schipprack; Felix Seifert; Alexander Thiemann; Stefan Scholten; Albrecht E Melchinger
Journal:  Genetics       Date:  2018-01-23       Impact factor: 4.562

2.  Omics-based hybrid prediction in maize.

Authors:  Matthias Westhues; Tobias A Schrag; Claas Heuer; Georg Thaller; H Friedrich Utz; Wolfgang Schipprack; Alexander Thiemann; Felix Seifert; Anita Ehret; Armin Schlereth; Mark Stitt; Zoran Nikoloski; Lothar Willmitzer; Chris C Schön; Stefan Scholten; Albrecht E Melchinger
Journal:  Theor Appl Genet       Date:  2017-06-24       Impact factor: 5.699

3.  A metabolome-based core hybridisation strategy for the prediction of rice grain weight across environments.

Authors:  Zhiwu Dan; Yunping Chen; Yanghong Xu; Junran Huang; Jishuai Huang; Jun Hu; Guoxin Yao; Yingguo Zhu; Wenchao Huang
Journal:  Plant Biotechnol J       Date:  2018-11-12       Impact factor: 9.803

4.  Dissecting Heterosis During the Ear Inflorescence Development Stage in Maize via a Metabolomics-based Analysis.

Authors:  Xia Shi; Xuehai Zhang; Dakun Shi; Xiangge Zhang; Weihua Li; Jihua Tang
Journal:  Sci Rep       Date:  2019-01-18       Impact factor: 4.379

5.  Nonlinear phenotypic variation uncovers the emergence of heterosis in Arabidopsis thaliana.

Authors:  François Vasseur; Louise Fouqueau; Dominique de Vienne; Thibault Nidelet; Cyrille Violle; Detlef Weigel
Journal:  PLoS Biol       Date:  2019-04-24       Impact factor: 8.029

6.  Alternative Oxidase (AOX) Senses Stress Levels to Coordinate Auxin-Induced Reprogramming From Seed Germination to Somatic Embryogenesis-A Role Relevant for Seed Vigor Prediction and Plant Robustness.

Authors:  Gunasekaran Mohanapriya; Revuru Bharadwaj; Carlos Noceda; José Hélio Costa; Sarma Rajeev Kumar; Ramalingam Sathishkumar; Karine Leitão Lima Thiers; Elisete Santos Macedo; Sofia Silva; Paolo Annicchiarico; Steven P C Groot; Jan Kodde; Aprajita Kumari; Kapuganti Jagadis Gupta; Birgit Arnholdt-Schmitt
Journal:  Front Plant Sci       Date:  2019-09-20       Impact factor: 5.753

7.  Metabolome Profiling Supports the Key Role of the Spike in Wheat Yield Performance.

Authors:  Omar Vergara-Diaz; Thomas Vatter; Rubén Vicente; Toshihiro Obata; Maria Teresa Nieto-Taladriz; Nieves Aparicio; Shawn Carlisle Kefauver; Alisdair Fernie; José Luis Araus
Journal:  Cells       Date:  2020-04-21       Impact factor: 6.600

8.  Genotype-by-environment interactions affecting heterosis in maize.

Authors:  Zhi Li; Lisa Coffey; Jacob Garfin; Nathan D Miller; Michael R White; Edgar P Spalding; Natalia de Leon; Shawn M Kaeppler; Patrick S Schnable; Nathan M Springer; Candice N Hirsch
Journal:  PLoS One       Date:  2018-01-17       Impact factor: 3.240

9.  Classification-driven framework to predict maize hybrid field performance from metabolic profiles of young parental roots.

Authors:  Francisco de Abreu E Lima; Lothar Willmitzer; Zoran Nikoloski
Journal:  PLoS One       Date:  2018-04-26       Impact factor: 3.240

10.  Metabolome-based prediction of yield heterosis contributes to the breeding of elite rice.

Authors:  Zhiwu Dan; Yunping Chen; Weibo Zhao; Qiong Wang; Wenchao Huang
Journal:  Life Sci Alliance       Date:  2019-12-13
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