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Related Experiment Video

Updated: Mar 8, 2026

Inhibition of Aspergillus flavus Growth and Aflatoxin Production in Transgenic Maize Expressing the α-amylase Inhibitor from Lablab purpureus L.

Inhibition of Aspergillus flavus Growth and Aflatoxin Production in Transgenic Maize Expressing the α-amylase Inhibitor from Lablab purpureus L.

Published on: February 15, 2019

Integrated genomics-based mapping reveals the genetics underlying maize flavonoid biosynthesis.

Min Jin¹, Xuehai Zhang¹, Mingchao Zhao¹

¹National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China.

BMC Plant Biology

|January 20, 2017

Summary

This study identifies genes controlling flavonoid biosynthesis in maize using genetic mapping and metabolite profiling. These findings enhance our understanding of flavonoid variation in maize and aid in selecting candidate genes.

Keywords:

Association analysis Co-expression network Flavonoid Linkage mapping Maize Natural variation

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Annotation of Plant Gene Function via Combined Genomics, Metabolomics and Informatics

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Annotation of Plant Gene Function via Combined Genomics, Metabolomics and Informatics

Annotation of Plant Gene Function via Combined Genomics, Metabolomics and Informatics

Published on: June 17, 2012

Area of Science:

Plant genetics
Metabolomics
Biochemistry

Background:

Flavonoids are vital plant compounds with health benefits and roles in plant development.
Maize flavonoid content variation and biosynthesis genes are not well understood.
This study investigates maize flavonoid biosynthesis using integrated approaches.

Purpose of the Study:

To identify quantitative trait loci (QTL) associated with flavonoid accumulation in maize.
To discover genes involved in the maize flavonoid biosynthesis pathway.
To characterize candidate genes functionally.

Main Methods:

Quantitative trait loci (QTL) mapping
Metabolite profiling of flavonoids
Gene expression network analysis
Molecular functional characterization of candidate genes

Main Results:

Identified 25 QTL for 23 distinct flavonoids across environments and populations.
Discovered 39 candidate genes through expression network analysis and genetic mapping.
Functionally characterized three genes, including two UDP-glycosyltransferases (UGTs) and an oxygenase.

Conclusions:

Integrated genomics, transcriptomics, and metabolomics reveal genetic influences on maize flavonoid biosynthesis.
This strategy efficiently identifies candidate genes and regulatory networks.
The approach aids in selecting genes for further validation, streamlining research.