Prediction of hybrid biomass in Arabidopsis thaliana by selected parental SNP and metabolic markers
- A recombinant inbred line (RIL) population, derived from two Arabidopsis thaliana accessions, and the corresponding testcrosses with these two original accessions were used for the development and validation of machine learning models to predict the biomass of hybrids. Genetic and metabolic information of the RILs served as predictors. Feature selection reduced the number of variables (genetic and metabolic markers) in the models by more than 80% without impairing the predictive power. Thus, potential biomarkers have been revealed. Metabolites were shown to bear information on inherited macroscopic phenotypes. This proof of concept could be interesting for breeders. The example population exhibits substantial mid-parent biomass heterosis. The results of feature selection could therefore be used to shed light on the origin of heterosis. In this respect, mainly dominance effects were detected.
Author details: | Matthias SteinfathORCiD, Tanja Gärtner, Jan LisecORCiD, Rhonda Christiane Meyer, Thomas AltmannORCiD, Lothar WillmitzerORCiDGND, Joachim SelbigGND |
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DOI: | https://doi.org/10.1007/s00122-009-1191-2 |
ISSN: | 0040-5752 |
ISSN: | 1432-2242 |
Title of parent work (English): | Theoretical and applied genetics : TAG ; international journal of plant breeding research |
Publisher: | Springer |
Place of publishing: | Berlin |
Publication type: | Article |
Language: | English |
Date of first publication: | 2009/11/13 |
Publication year: | 2009 |
Release date: | 2023/06/22 |
Tag: | Partial Little Square; Quantitative Trait Locus; Quantitative Trait Locus analysis; feature selection; recombinant inbred line |
Volume: | 120 |
Number of pages: | 9 |
First page: | 239 |
Last Page: | 247 |
Organizational units: | Mathematisch-Naturwissenschaftliche Fakultät / Institut für Biochemie und Biologie |
Extern / Extern | |
DDC classification: | 5 Naturwissenschaften und Mathematik / 57 Biowissenschaften; Biologie / 570 Biowissenschaften; Biologie |
Peer review: | Referiert |
Publishing method: | Open Access / Hybrid Open-Access |
License (German): | Creative Commons - Namensnennung-Nicht kommerziell 2.0 Generic |
External remark: | Zweitveröffentlichung in der Schriftenreihe Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe ; 1324 |