Theoretical and Applied Genetics

, Volume 113, Issue 5, pp 831–845 | Cite as

Genome-wide transcript analysis of maize hybrids: allelic additive gene expression and yield heterosis

  • Mei Guo
  • Mary A. Rupe
  • Xiaofeng Yang
  • Oswald Crasta
  • Christopher Zinselmeier
  • Oscar S. Smith
  • Ben Bowen
Original Paper

Abstract

Heterosis, or hybrid vigor, has been widely exploited in plant breeding for many decades, but the molecular mechanisms underlying the phenomenon remain unknown. In this study, we applied genome-wide transcript profiling to gain a global picture of the ways in which a large proportion of genes are expressed in the immature ear tissues of a series of 16 maize hybrids that vary in their degree of heterosis. Key observations include: (1) the proportion of allelic additively expressed genes is positively associated with hybrid yield and heterosis; (2) the proportion of genes that exhibit a bias towards the expression level of the paternal parent is negatively correlated with hybrid yield and heterosis; and (3) there is no correlation between the over- or under-expression of specific genes in maize hybrids with either yield or heterosis. The relationship of the expression patterns with hybrid performance is substantiated by analysis of a genetically improved modern hybrid (Pioneer® hybrid 3394) versus a less improved older hybrid (Pioneer® hybrid 3306) grown at different levels of plant density stress. The proportion of allelic additively expressed genes is positively associated with the modern high yielding hybrid, heterosis and high yielding environments, whereas the converse is true for the paternally biased gene expression. The dynamic changes of gene expression in hybrids responding to genotype and environment may result from differential regulation of the two parental alleles. Our findings suggest that differential allele regulation may play an important role in hybrid yield or heterosis, and provide a new insight to the molecular understanding of the underlying mechanisms of heterosis.

Notes

Acknowledgments

We thank S. Zhao, W. Bruce, and B. Zeka for tissue sampling and RNA preparation; R. Luedtke, D. Ritland, and L. Heetland for field experiment support; O. Folkerts, T. Jarvie, P. Pochart, G. Vijayadamodar, and D. Marks for their support in the GeneCalling technology and database development from the CuraGen Corporation. We specially thank D. Duvick and J. Birchler for critical reading of the manuscript.

Supplementary material

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Copyright information

© Springer-Verlag 2006

Authors and Affiliations

  • Mei Guo
    • 1
  • Mary A. Rupe
    • 1
  • Xiaofeng Yang
    • 1
  • Oswald Crasta
    • 2
    • 3
  • Christopher Zinselmeier
    • 1
  • Oscar S. Smith
    • 1
  • Ben Bowen
    • 1
    • 4
  1. 1.Pioneer Hi-Bred International, Inc.JohnstonUSA
  2. 2.CuraGen Corp.New HavenUSA
  3. 3.Virginia Bioinformatics InstituteVirginiaUSA
  4. 4.Gene-fx, Inc.BerkeleyUSA

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