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A Potential Role for CHH DNA Methylation in Cotton Fiber Growth Patterns

Overview of attention for article published in PLOS ONE, April 2013
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Title
A Potential Role for CHH DNA Methylation in Cotton Fiber Growth Patterns
Published in
PLOS ONE, April 2013
DOI 10.1371/journal.pone.0060547
Pubmed ID
Authors

Xiang Jin, Yu Pang, Fangxing Jia, Guanghui Xiao, Qin Li, Yuxian Zhu

Abstract

DNA methylation controls many aspects of plant growth and development. Here, we report a novel annual growth potential change that may correlate with changes in levels of the major DNA demethylases and methyltransferases in cotton ovules harvested at different times of the year. The abundances of DNA demethylases, at both the mRNA and protein levels, increased significantly from February to August and decreased during the remainder of the 12-month period, with the opposite pattern observed for DNA methyltransferases. Over the course of one year, substantial changes in methylcytosine content was observed at certain CHH sites (H = A, C, or T) in the promoter regions of the ETHYLENE RESPONSIVE FACTOR 6 (ERF6), SUPPRESSION OF RVS 161 DELTA 4 (SUR4) and 3-KETOACYL-COA SYNTHASE 13 (KCS13), which regulate cotton fiber growth. Three independent techniques were used to confirm the annual fluctuations in DNA methylation. Furthermore, in homozygous RNAi lines specifically targeting REPRESSOR OF SILENCING 1 (ROS1, a conserved DNA demethylase domain), promotion of DNA methylation significantly reduced fiber growth during August.

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Mendeley readers

The data shown below were compiled from readership statistics for 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 27 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 6 22%
Student > Ph. D. Student 4 15%
Professor 3 11%
Professor > Associate Professor 3 11%
Student > Bachelor 2 7%
Other 4 15%
Unknown 5 19%
Readers by discipline Count As %
Agricultural and Biological Sciences 16 59%
Biochemistry, Genetics and Molecular Biology 2 7%
Environmental Science 1 4%
Immunology and Microbiology 1 4%
Engineering 1 4%
Other 0 0%
Unknown 6 22%