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Updated: Jun 25, 2025

Experimental Design for Laser Microdissection RNA-Seq: Lessons from an Analysis of Maize Leaf Development
Published on: March 5, 2017
Population-level gene expression can repeatedly link genes to functions in maize
J Vladimir Torres-Rodríguez1,2,3, Delin Li4, Jonathan Turkus1,2,3
1Quantitative Life Sciences Initiative, University of Nebraska-Lincoln, Lincoln, Nebraska, 68588, USA.
Abstract:
Transcriptome-wide association studies (TWAS) can provide single gene resolution for candidate genes in plants, complementing genome-wide association studies (GWAS) but efforts in plants have been met with, at best, mixed success. We generated expression data from 693 maize genotypes, measured in a common field experiment, sampled over a 2-h period to minimize diurnal and environmental effects, using full-length RNA-seq to maximize the accurate estimation of transcript abundance. TWAS could identify roughly 10 times as many genes likely to play a role in flowering time regulation as GWAS conducted data from the same experiment. TWAS using mature leaf tissue identified known true-positive flowering time genes known to act in the shoot apical meristem, and trait data from a new environment enabled the identification of additional flowering time genes without the need for new expression data. eQTL analysis of TWAS-tagged genes identified at least one additional known maize flowering time gene through trans-eQTL interactions. Collectively these results suggest the gene expression resource described here can link genes to functions across different plant phenotypes expressed in a range of tissues and scored in different experiments.
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