Journal of Genetics

, Volume 93, Issue 2, pp 431–442 | Cite as

Patterns of microsatellite evolution inferred from the Helianthus annuus (Asteraceae) transcriptome

  • SREEPRIYA PRAMOD
  • ANDY D. PERKINS
  • MARK E. WELCH
RESEARCH ARTICLE

Abstract

The distribution of microsatellites in exons, and their association with gene ontology (GO) terms is explored to elucidate patterns of microsatellite evolution in the common sunflower, Helianthus annuus. The relative position, motif, size and level of impurity were estimated for each microsatellite in the unigene database available from the Compositae Genome Project (CGP), and statistical analyses were performed to determine if differences in microsatellite distributions and enrichment within certain GO terms were significant. There are more translated than untranslated microsatellites, implying that many bring about structural changes in proteins. However, the greatest density is observed within the UTRs, particularly 5UTRs. Further, UTR microsatellites are purer and longer than coding region microsatellites. This suggests that UTR microsatellites are either younger and under more relaxed constraints, or that purifying selection limits impurities, and directional selection favours their expansion. GOs associated with response to various environmental stimuli including water deprivation and salt stress were significantly enriched with microsatellites. This may suggest that these GOs are more labile in plant genomes, or that selection has favoured the maintenance of microsatellites in these genes over others. This study shows that the distribution of transcribed microsatellites in H. annuus is nonrandom, the coding region microsatellites are under greater constraint compared to the UTR microsatellites, and that these sequences are enriched within genes that regulate plant responses to environmental stress and stimuli.

Keywords

microsatellite evolution transcriptome selection untranslated regions Helianthus annuus

Notes

Acknowledgements

The authors would like to acknowledge Loren Rieseberg for useful comments on improving this manuscript. Kristen Sauby, Leah Chinchilla and Christopher Brooks helped during the initial stages of this work. Susan Bridges helped with preliminary data analyses. David Chevalier and Donna Gordon provided suggestions for gene ontology analysis. This work was supported by the National Science Foundation under grants to M. E. Welch (NSF MCB-1158521) and A. D. Perkins (NSF EPS-0903787). The Office of Research and Economic Development, the College of Arts and Sciences, and the Department of Biological Sciences at Mississippi State University also funded this research.

Supplementary material

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Copyright information

© Indian Academy of Sciences 2014

Authors and Affiliations

  • SREEPRIYA PRAMOD
    • 1
  • ANDY D. PERKINS
    • 2
  • MARK E. WELCH
    • 1
  1. 1.Department of Biological SciencesMississippi State University 295 Lee BoulevardUSA
  2. 2.Department of Computer Science and EngineeringMississippi State UniversityButler HallUSA

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