Epigenomic diversity in a global collection of Arabidopsis thaliana accessions
By Taiji Kawakatsu, S. C. Huang, Florian Jupe, Eriko Sasaki, Robert J. Schmitz, M. Urich, R. Castanon, Joseph R. Nery, Cesar Barragan, Yupeng He and 13 more. Cell, 2016
646 citations recorded by the source corpus.
SUMMARY The epigenome orchestrates genome accessibility, functionality and three-dimensional structure. Because epigenetic variation can impact transcription and thus phenotypes, it may contribute to adaptation. Here we report 1,107 high-quality single-base resolution methylomes and 1,203 transcriptomes from the 1001 Genomes collection of Arabidopsis thaliana. Although the genetic basis of methylation variation is highly complex, geographic origin is a major predictor of genome-wide DNA methylation levels and of altered gene expression caused by epialleles. Comparison to cistrome and epicistrome datasets identifies associations between transcription factor binding sites, methylation, nucleotide variation and co-expression modules. Physical maps for nine of the most diverse genomes reveals how transposons and other structural variants shape the epigenome, with dramatic effects on immunity genes. The 1001 Epigenomes Project provides a comprehensive resource for understanding how variation in DNA methylation contributes to molecular and non-molecular phenotypes in natural populations of the most studied model plant.
Subfields: Molecular Biology, Plant Science
View Paper: https://www.semanticscholar.org/paper/73eb873869d5bb2f68c0c9680ee1abd573bc2c31
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Molecular Biology
In Plant Science
Citations in the corpus
- Major impacts of widespread structural variation on gene expression and crop improvement in tomato (2020, neutral): “Knowing that a substantial fraction of population-scale expression variation is explained by cis-eQTL (Battle et al., 2017; Kawakatsu et al., 2016), we next formulated a classification task that uses changes in gene expression to predict the presence of a nearby SV (see STAR Methods; Figure S4B).”
- Mapping genome-wide transcription-factor binding sites using DAP-seq (2017, background): “DAP-seq can also be modified to study the effects of various perturbations such as nucleotide variation in DNA-binding domains (genetic variants) or TF binding variation due to DNA methylation (epigenomic variants) 24 .”
- Genome evolution in fungal plant pathogens: looking beyond the two-speed genome model (2020, neutral): “In plants and animals, for example, genes with roles in immunity often cluster and are located in dynamic regions (Gokcumen et al. , 2011; Kawakatsu et al. , 2016; Laun et al. , 2006; Leister, 2004; Mascher et al. , 2017; Roach et al. , 2005; Seidl and Thomma, 2017).”