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International Journal of Genomics
Volume 2018, Article ID 6897032, 13 pages
Research Article

Identification of Wheat Inflorescence Development-Related Genes Using a Comparative Transcriptomics Approach

The Applied Plant Genomics Laboratory of Crop Genomics and Bioinformatics Centre, Nanjing Agricultural University, Jiangsu 210095, China

Correspondence should be addressed to Haiyan Jia; nc.ude.uajn@aijyh

Received 3 August 2017; Revised 26 November 2017; Accepted 3 December 2017; Published 8 February 2018

Academic Editor: Marco Gerdol

Copyright © 2018 Lingjie Ma et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Inflorescence represents the highly specialized plant tissue producing the grains. Although key genes regulating flower initiation and development are conserved, the mechanism regulating fertility is still not well explained. To identify genes and gene network underlying inflorescence morphology and fertility of bread wheat, expressed sequence tags (ESTs) from different tissues were analyzed using a comparative transcriptomics approach. Based on statistical comparison of EST frequencies of individual genes in EST pools representing different tissues and verification with RT-PCR and RNA-seq data, 170 genes of 59 gene sets predominantly expressed in the inflorescence were obtained. Nearly one-third of the gene sets displayed differentiated expression profiles in terms of their subgenome orthologs. The identified genes, most of which were predominantly expressed in anthers, encode proteins involved in wheat floral identity determination, anther and pollen development, pollen-pistil interaction, and others. Particularly, 25 annotated gene sets are associated with pollen wall formation, of which 18 encode enzymes or proteins participating in lipid metabolic pathway, including fatty acid ω-hydroxylation, alkane and fatty alcohol biosynthesis, and glycerophospholipid metabolism. We showed that the comparative transcriptomics approach was effective in identifying genes for reproductive development and found that lipid metabolism was particularly active in wheat anthers.