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United States Department of Agriculture

Agricultural Research Service

Research Project: IMPROVING RUST AND FHB RESISTANCE IN HARD RED SPRING WHEAT THROUGH GENETICS AND GENOMICS Title: Analysis, annotation, and profiling of the oat seed transcriptome

item Gutierrezgonzalez, Juan
item Garvin, David

Submitted to: Plant and Animal Genome Conference
Publication Type: Abstract Only
Publication Acceptance Date: November 1, 2012
Publication Date: January 15, 2013
Citation: Gutierrez-Gonzalez, J.J., Garvin, D.F. 2013. Analysis, annotation, and profiling of the oat seed transcriptome [abstract]. Plant and Animal Genome Conference, January 12-16, 2013, San Diego, California. Available:

Technical Abstract: Novel high-throughput next generation sequencing (NGS) technologies are providing opportunities to explore genomes and transcriptomes in a cost-effective manner. To construct a gene expression atlas of developing oat (Avena sativa) seeds, two software packages specifically designed for RNA-seq (Trinity and Velvet/Oases) were employed for de novo assembly of nearly 134 million quality-filtered 100-bp paired-end reads sequenced from RNA extracted at four stages of seed development. Based on the quality-parameters assessed, Velvet/Oases assemblies were more accurate, produced longer transcripts, and contained more putative unique genes. The final assembly, termed dnOSt (de novo Oat Seed transcriptome), is more than 55 million nucleotides in length, contained 53,339 transcript isoforms, and was constructed with approximately 43 million reads, which represents an estimated 74.8x sequencing depth with an average transcript length of 1,043 nucleotides. To assess the accuracy and completeness of dnOSt, we investigated the presence of transcripts associated with the biosynthesis of three compounds with health-promoting properties: avenanthramides, tocols (vitamin E), and Beta-glucans. Homologs to all investigated genes were present in dnOSt, demonstrating that it is a robust and useful new tool for oat research. Currently, we are independently assembling transcripts from the four sampled time-points for use in characterizing temporal gene expression patterns during the course of seed development. Results of these analyses will also be presented.

Last Modified: 8/27/2016
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