Digital Gene Expression Signatures for Maize Development

Author:

Eveland Andrea L.1,Satoh-Nagasawa Namiko1,Goldshmidt Alexander1,Meyer Sandra1,Beatty Mary1,Sakai Hajime1,Ware Doreen1,Jackson David1

Affiliation:

1. Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724 (A.L.E., A.G., D.W., D.J.); DuPont Agricultural Biotechnology Experimental Station E353, Wilmington, Delaware 19880 (N.S.-N., H.S.); Pioneer Hi-Bred International, Johnston, Iowa 50131–1004 (S.M., M.B.); United States Department of Agriculture-Agricultural Research Service, Robert W. Holley Center for Agriculture and Health, Ithaca

Abstract

Abstract Genome-wide expression signatures detect specific perturbations in developmental programs and contribute to functional resolution of key regulatory networks. In maize (Zea mays) inflorescences, mutations in the RAMOSA (RA) genes affect the determinacy of axillary meristems and thus alter branching patterns, an important agronomic trait. In this work, we developed and tested a framework for analysis of tag-based, digital gene expression profiles using Illumina’s high-throughput sequencing technology and the newly assembled B73 maize reference genome. We also used a mutation in the RA3 gene to identify putative expression signatures specific to stem cell fate in axillary meristem determinacy. The RA3 gene encodes a trehalose-6-phosphate phosphatase and may act at the interface between developmental and metabolic processes. Deep sequencing of digital gene expression libraries, representing three biological replicate ear samples from wild-type and ra3 plants, generated 27 million 20- to 21-nucleotide reads with frequencies spanning 4 orders of magnitude. Unique sequence tags were anchored to 3′-ends of individual transcripts by DpnII and NlaIII digests, which were multiplexed during sequencing. We mapped 86% of nonredundant signature tags to the maize genome, which associated with 37,117 gene models and unannotated regions of expression. In total, 66% of genes were detected by at least nine reads in immature maize ears. We used comparative genomics to leverage existing information from Arabidopsis (Arabidopsis thaliana) and rice (Oryza sativa) in functional analyses of differentially expressed maize genes. Results from this study provide a basis for the analysis of short-read expression data in maize and resolved specific expression signatures that will help define mechanisms of action for the RA3 gene.

Publisher

Oxford University Press (OUP)

Subject

Plant Science,Genetics,Physiology

Reference75 articles.

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