Frontiers in Plant Science (Jul 2015)

TAL effectors and activation of predicted host targets distinguish Asian from African strains of the rice pathogen Xanthomonas oryzae pv. oryzicola while strict conservation suggests universal importance of five TAL effectors

  • Katherine E. Wilkins,
  • Katherine E. Wilkins,
  • Nicholas J. Booher,
  • Nicholas J. Booher,
  • Li eWang,
  • Adam J. Bogdanove

DOI
https://doi.org/10.3389/fpls.2015.00536
Journal volume & issue
Vol. 6

Abstract

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Xanthomonas oryzae pv. oryzicola (Xoc) causes the increasingly important disease bacterial leaf streak of rice (BLS) in part by type III delivery of repeat-rich transcription activator-like (TAL) effectors to upregulate host susceptibility genes. By pathogen whole genome, single molecule, real-time sequencing and host RNA sequencing, we compared TAL effector content and rice transcriptional responses across 10 geographically diverse Xoc strains. TAL effector content is surprisingly conserved overall, yet distinguishes Asian from African isolates. Five TAL effectors are conserved across all strains. In a prior laboratory assay in rice cv. Nipponbare, only two contributed to virulence in strain BLS256 but the strict conservation indicates all five may be important, in different rice genotypes or in the field. Concatenated and aligned, TAL effector content across strains largely reflects relationships based on housekeeping genes, suggesting predominantly vertical transmission. Rice transcriptional responses did not reflect these relationships, and on average, only 28% of genes upregulated and 22% of genes downregulated by a strain are up- and downregulated (respectively) by all strains. However, when only known TAL effector targets were considered, the relationships resembled those of the TAL effectors. Toward identifying new targets, we used the TAL effector-DNA recognition code to predict effector binding elements in promoters of genes upregulated by each strain, but found that for every strain, all upregulated genes had at least one. Filtering with a classifier we developed previously decreases the number of predicted binding elements across the genome, suggesting that it may reduce false positives among upregulated genes. Applying this filter and eliminating genes for which upregulation did not strictly correlate with presence of the corresponding TAL effector, we generated testable numbers of candidate targets for four of the five strictly conserved TAL effectors.

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