Publication detail

Metabolite Genome-wide Association Studies of Arabidopsis Thaliana

SCHWARZEROVÁ, J.

Original Title

Metabolite Genome-wide Association Studies of Arabidopsis Thaliana

Type

conference paper

Language

English

Original Abstract

Current research based on the edge of bioinformatics and ecology engineering has huge potential due to combination of laboratory analyses and advanced bioinformatics algorithms. The paper deals with a combination of GC-MS and LC-MS based metabolomic analysis for identification and quantitation of metabolites in environmental perturbations with advanced bioinformatics approach of metabolite genome-wide association studies (mGWAS). This complex view is applied to Arabidopsis thaliana. The main goal is to obtain genetic predictions focused on A. thaliana under different environmental conditions. Currently, important ecological issues such as climate change, pollution etc. have impact on the change of environment. It has a great effect on plants which serves as producers of oxygen or food. While simple observation reveals only a phenotype change, changes in genotypes of organisms can be captured using mGWAS and further utilized in industrial ecology and biotechnology.

Keywords

Metabolomics, Systems biology, Ecology, Single nucleotide polymorphism, Genetic prediction

Authors

SCHWARZEROVÁ, J.

Released

27. 4. 2021

Publisher

Brno University of Technology, Faculty of Electrical Engineering and Communication

Location

Brno

ISBN

978-80-214-5943-4

Book

Proceedings of the 27th Conference STUDENT EEICT 2021 selected papers

Edition

1

Pages from

41

Pages to

44

Pages count

4

URL

BibTex

@inproceedings{BUT172026,
  author="Jana {Schwarzerová}",
  title="Metabolite Genome-wide Association Studies of Arabidopsis Thaliana",
  booktitle="Proceedings of the 27th Conference STUDENT EEICT 2021 selected papers",
  year="2021",
  series="1",
  pages="41--44",
  publisher="Brno University of Technology, Faculty of Electrical Engineering and Communication",
  address="Brno",
  doi="10.13164/eeict.2021.41",
  isbn="978-80-214-5943-4",
  url="https://www.fekt.vut.cz/conf/EEICT/archiv/sborniky/EEICT_2021_sbornik_2.pdf"
}