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United States Department of Agriculture

Agricultural Research Service

Research Project: BIOINFORMATIC METHODS AND TOOLS TO PREDICT SMALL GRAIN FIELD PERFORMANCE

Location: Plant, Soil and Nutrition Research

Title: Digital gene expression signatures for maize development

Authors
item Eveland, Andrea -
item Nagasawa, Namiko -
item Goldshmidt, Alexander -
item Meyer, Sandra -
item Beatty, Mary -
item Sakai, Hajime -
item Ware, Doreen
item Jackson, Dave -

Submitted to: Plant Physiology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: August 23, 2010
Publication Date: September 10, 2010
Citation: Eveland, A.L., Nagasawa, N., Goldshmidt, A., Meyer, S., Beatty, M., Sakai, H., Ware, D., Jackson, D. 2010. Digital gene expression signatures for maize development. Plant Physiology. 154(3):1024-1039.

Interpretive Summary: The ability to profile quantitative changes in expression for all genes simultaneously can help us understand genes that work together to coordinate plant development. Comparing the differences in expression between a normal plant and one that has had a change to in a gene allows us to compare and contrast differences that result from this single change. In immature maize (Zea mays) ears, mutations in the RAMOSA (RA) genes affect developmental fate of axillary meristems, which are comprised of organized stem cell populations, and consequently alter branching patterns. Genetic control of branching, especially in ears where kernels are born, has clear relevance to crop improvement with respect to seed number and harvesting ability. In this work, we developed and tested a framework for analysis of digital gene expression (DGE) profiles using ultra high-throughput sequencing technology and the newly-assembled B73 maize reference genome. We also used a mutation in the RA3 gene, which encodes a trehalose-6-phosphate-phosphatase, to identify putative expression patterns specific to stem cell fate in axillary meristems. Six libraries, representing three biological replicate ear samples from wild-type and ra3 plants, were sequenced and yielded 27 million short read sequences. Overall, 86% of reads aligned to the maize genome sequence and 37,117 known genes were identified, 66% of which were detected above our threshold for statistical testing. We used comparative genomics to leverage existing information from Arabidopsis and rice in functional analyses of differentially expressed maize genes. Results from this study provide a basis for analysis of short-read expression data in maize and resolved specific expression signatures that will help define mechanisms of action for the RA3 gene.

Technical 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 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 (DGE) 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 determinacy of axillary meristems. The RA3 gene encodes a trehalose-6-phosphate-phosphatase and may act at the interface between developmental and metabolic processes. Deep sequencing of DGE libraries, representing three biological replicate ear samples from wild-type and ra3 plants, generated 27 million 20-21nt reads with frequencies spanning four 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 non-redundant signature tags to the maize genome, which associated with 37,117 working gene models and un-annotated regions of expression. 66% of maize genes were detected at = nine reads in immature maize ears. We used comparative genomics to leverage existing information from Arabidopsis and rice in functional analyses of differentially expressed maize genes. Results from this study provide a basis for analysis of short-read expression data in maize and resolved specific expression signatures that will help define mechanisms of action for the RA3 gene.

Last Modified: 4/20/2014
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