Back

Zea Lip: An atlas of glycerolipid profiles across leaf development in maize

Juarez Nunez, K. A.; Lobet, G.; Tandukar, N.; Jadidzadeh, E.; Pasha, A.; Provart, N. J.; Holland, J. B.; Rellan-Alvarez, R.; Barnes, A. C.

2026-05-08 plant biology
10.64898/2026.05.07.723536 bioRxiv
Show abstract

Lipids are the predominant building blocks of plant membranes and are essential for plant growth and development. They are crucial for survival during times of stress as lipids are involved in multiple signaling pathways, and their relative abundances can change in response to environmental factors. To better characterize the lipid composition of the vital food crop maize, we generated a comprehensive glycerolipid atlas using ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry. We surveyed the lipid profiles of three different maize genotypes: B73, a temperate inbred; CML312, a subtropical inbred; and Palomero Toluqueno, an open-pollinated variety from the Mexican highlands. We collected leaf samples from 4 developmental stages and 6 leaves. From one growth stage, we also sampled along with three leaf zones: base, center, and tip. The genotype and leaf number were the major drivers of lipid differences. Phosphatidylcholine, lysophosphatidylcholine, and triacylglycerol genotypic differences were particularly high. We generated an eFP browser to be integrated into the maize genome browser, as well as a separate web interface to easily browse and compare lipid levels across tissues and genotypes, available at https://rrellan.shinyapps.io/Zea-Lip/. SIGNIFICANCE STATEMENTThis work creates a spatial map of lipids in maize leaves across four growth stages for three genotypes: a lowland, a sub-tropical, and a highland. The resources generated here will directly benefit both the maize and lipid communities by creating a large dataset that can be used to generate new hypotheses in understanding lipid metabolism and environmental responses in maize.

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

1
Plant Direct
95 papers in training set
Top 0.1%
21.7%
2
The Plant Journal
215 papers in training set
Top 0.3%
11.8%
3
Plant Physiology
238 papers in training set
Top 0.7%
8.8%
4
GigaScience
212 papers in training set
Top 0.7%
4.8%
5
Frontiers in Plant Science
256 papers in training set
Top 2%
4.3%
50% of probability mass above
6
Scientific Data
209 papers in training set
Top 0.7%
3.5%
7
G3: Genes|Genomes|Genetics
35 papers in training set
Top 0.1%
2.8%
8
Communications Biology
993 papers in training set
Top 7%
2.7%
9
Plant Biotechnology Journal
64 papers in training set
Top 0.5%
2.6%
10
BMC Genomics
406 papers in training set
Top 3%
2.4%
11
BMC Plant Biology
57 papers in training set
Top 0.6%
2.1%
12
Plant Communications
36 papers in training set
Top 0.4%
2.1%
13
PLOS ONE
5266 papers in training set
Top 45%
2.1%
14
eLife
5828 papers in training set
Top 44%
2.1%
15
New Phytologist
346 papers in training set
Top 3%
2.1%
16
The Plant Genome
57 papers in training set
Top 0.5%
2.1%
17
Scientific Reports
3612 papers in training set
Top 55%
1.7%
18
Journal of Experimental Botany
219 papers in training set
Top 2%
1.7%
19
G3: Genes, Genomes, Genetics
252 papers in training set
Top 3%
1.5%
20
Nature Communications
5641 papers in training set
Top 54%
1.0%
21
The Plant Cell
161 papers in training set
Top 2%
0.8%
22
Proceedings of the National Academy of Sciences
2444 papers in training set
Top 45%
0.6%
23
Genome Research
468 papers in training set
Top 7%
0.6%
24
Plants
43 papers in training set
Top 2%
0.6%
25
Genome Biology
637 papers in training set
Top 10%
0.6%