Unraveling lipid metabolism in maize with time‐resolved multi‐omics data

Abstract

Maize is the cereal crop with the highest production worldwide, and its oil is a key energy resource. Improving the quantity and quality of maize oil requires a better understanding of lipid metabolism. To predict the function of maize genes involved in lipid biosynthesis, we assembled transcriptomic and lipidomic data sets from leaves of B73 and the high-oil line By804 in two distinct time-series experiments. The integrative analysis based on high-dimensional regularized regression yielded lipid-transcript associations indirectly validated by Gene Ontology and promoter motif enrichment analyses. The co-localization of lipid-transcript associations using the genetic mapping of lipid traits in leaves and seedlings of a B73 × By804 recombinant inbred line population uncovered 323 genes involved in the metabolism of phospholipids, galactolipids, sulfolipids and glycerolipids. The resulting association network further supported the involvement of 50 gene candidates in modulating levels of representatives from multiple acyl-lipid classes. Therefore, the proposed approach provides high-confidence candidates for experimental testing in maize and model plant species.

Metabolomics 20 years on: what have we learned and what hurdles remain?

“…Although a recently created backcrossed inbred line generated from the same parental lines affords far greater genetic resolution, and has already been applied to the study of cuticle composition, acyl sugar and primary metabolism (Ning et al ., ; Fan et al ., ; Ofner et al ., ; Alseekh et al ., ). QTL analysis has subsequently been carried out for a range of other important crops, including Oryza sativa (rice; Matsuda et al ., ), Triticum aestivum (wheat; Hill et al ., ), Zea mays (maize; de Abreu E Lima et al ., ; Wen et al ., ), Hordeum vulgare (barley; Templer et al ., ) and potato (Carreno‐Quintero et al ., ). These studies collectively identified a large number of structural and regulatory genes involved in the control of metabolite abundance in crops, and massively improved our understanding of the structure of the metabolic pathways as well as defined important leads for metabolic engineering (Wen et al ., ).…”

Large‐scale metabolite quantitative trait locus analysis provides new insights for high‐quality maize improvement

“…Metabolomics has recently made several important contributions to our understanding of fundamental aspects of maize biology, including metabolic responses to climate change, pathogen attack, microorganism resistance and dynamic development of plants (Walker et al ., ; Marti et al ., ; Sun et al ., ; de Abreu e Lima et al ., ; Wen et al ., ). To date, comparisons of the metabolic differences between cultivated maize and teosinte have, however, been relatively limited (Flint‐Garcia et al ., ).…”

Systematic Multi-Omics Integration (MOI) Approach in Plant Systems Biology

“…The study successfully identified metabolic differences between the two, in particular, sugar metabolism and polyamine biosynthesis ( Mesnage et al., 2016 ). Another study in maize further illustrates the use of multivariate analysis such as GFLASSO to integrate transcriptome and metabolome in deciphering its lipid biosynthesis ( De Abreu E Lima et al., 2018 ).…”