Journal
PLANT GENOME
Volume 4, Issue 3, Pages 191-203Publisher
CROP SCIENCE SOC AMER
DOI: 10.3835/plantgenome2011.05.0015
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Funding
- USDA NIFA [2009-65300-05784]
- DOE Great Lakes Bioenergy Research Center (DOE Office of Science BER) [DE-FC02-07ER64494]
- NSF [0905696]
- Direct For Biological Sciences
- Div Of Biological Infrastructure [905696] Funding Source: National Science Foundation
- NIFA [581926, 2009-65300-05784] Funding Source: Federal RePORTER
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Transcriptome sequencing is a powerful method for studying global expression patterns in large, complex genomes. Evaluation of sequence-based expression profiles during reproductive development would provide functional annotation to genes underlying agronomic traits. We generated transcriptome profiles for 12 diverse maize (Zea mays L.) reproductive tissues representing male, female, developing seed, and leaf tissues using high throughput transcriptome sequencing. Overall, similar to 80% of annotated genes were expressed. Comparative analysis between sequence and hybridization-based methods demonstrated the utility of ribonucleic acid sequencing (RNA-seq) for expression determination and differentiation of paralagous genes (similar to 85% of maize genes). Analysis of 4975 gene families across reproductive tissues revealed expression divergence is proportional to family size. In all pairwise comparisons between tissues, 7 (pre- vs. postemergence cobs) to 48% (pollen vs. ovule) of genes were differentially expressed. Genes with expression restricted to a single tissue within this study were identified with the highest numbers observed in leaves, endosperm, and pollen. Coexpression network analysis identified 17 gene modules with complex and shared expression patterns containing many previously described maize genes. The data and analyses in this study provide valuable tools through improved gene annotation, gene family characterization, and a core set of candidate genes to further characterize maize reproductive development and improve grain yield potential.
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