Abstract
How to mine the gene locus for maize carotenoid components is an important research problem in biology study. Along with the rapid development of high-throughput biotechnologies, we have produced a large number of maize multi-omics data, including genome, transcriptome, metabolome, phenotype, etc. How to conjointly analyze these continuous and discrete data, and thus to mine the genetic loci that control the maize carotenoid components have a very important biological significance. In this work, we use the conditional Gaussian Bayesian network learning method to construct the network of maize gene, SNP locus and carotenoid components, aim to get the possible significant loci about four reported genes for the carotenoid component traits. The method is validated using the multi-omics data of maize global germplasm collection with 368 elite inbred lines. Four algorithms are used to do the comparison, and experiment results show the method can mine the effective locus for the phenotype traits. It is concluded that the conditional Gaussian Bayesian network learning method is an effective way of analyzing multi-omics data conjointly, mining the possible gene locus for maize carotenoid component traits, and thus to provide genetic resources and useful information for molecular breeding of maize.
Highlights
Carotenoid is one of the most important natural pigments, exists widely in fruits and vegetables
A: COMPARISON OF LEARNING EFFICIENCY We use the algorithms of PC, K2, GS and SA to construct the network which includes the nodes of SNP locus of 4 genes and 5 carotenoid component traits
When to construct the network of genes and carotenoid component traits, experiment results show the methods can effectively learn the correlations between the 4 reported genes and 5 carotenoid component traits
Summary
Carotenoid is one of the most important natural pigments, exists widely in fruits and vegetables. Besides having the function of coloring and participating in the process of light absorption in photosynthesis, it has a protective effect on human cardiovascular system. It can scavenge free radicals and enhance immunity, and has a good preventive effect on eye, skin diseases and gastric cancer. Carotenoids, such as alpha-carotene, beta-carotene and betacryptoxanthine can transform into vitamin A in human body [1]. It is of great importance to improve the content of carotenoids in maize. We have produced a large number of maize multi-omics data, including genome, transcriptome, metabolome, phenotype, The associate editor coordinating the review of this manuscript and approving it for publication was Sungroh Yoon
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