T-DNA-Genome junctions form early after infection and are influenced by the chromatin state of the host genome

Shay Shilo, Pooja Tripathi, Cathy Melamed-Bessudo, Oren Tzfadia, Theodore R. Muth, Avraham Levy

Research output: Contribution to journalArticlepeer-review

32 Citations (Scopus)

Abstract

Agrobacterium tumefaciens mediated T-DNA integration is a common tool for plant genome manipulation. However, there is controversy regarding whether T-DNA integration is biased towards genes or randomly distributed throughout the genome. In order to address this question, we performed high-throughput mapping of T-DNA-genome junctions obtained in the absence of selection at several time points after infection. T-DNA-genome junctions were detected as early as 6 hours post-infection. T-DNA distribution was apparently uniform throughout the chromosomes, yet local biases toward AT-rich motifs and T-DNA border sequence micro-homology were detected. Analysis of the epigenetic landscape of previously isolated sites of T-DNA integration in Kanamycin-selected transgenic plants showed an association with extremely low methylation and nucleosome occupancy. Conversely, non-selected junctions from this study showed no correlation with methylation and had chromatin marks, such as high nucleosome occupancy and high H3K27me3, that correspond to three-dimensional-interacting heterochromatin islands embedded within euchromatin. Such structures may play a role in capturing and silencing invading T-DNA.

Original languageEnglish
Article numbere1006875
JournalPLoS Genetics
Volume13
Issue number7
DOIs
Publication statusPublished - 24 Jul 2017

Funding

ERC grant (TRACTAR)This work was supported by an ERC grant (TRACTAR) to ML. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. This work was supported by an ERC grant (TRACTAR) to ML. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. We would like to thank Dr. Naama Kopelman, Dana Averbuch and Veronika Berman for their help in the data analysis.

All Science Journal Classification (ASJC) codes

  • Genetics(clinical)
  • Genetics
  • Ecology, Evolution, Behavior and Systematics
  • Molecular Biology
  • Cancer Research

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