Evolution is fueled by phenotypic diversity, which is in turn due to underlying heritable genetic (and potentially epigenetic) variation. While environmental factors are well known to influence the accumulation of novel variation in microorganisms and human cancer cells, the extent to which the natural environment influences the accumulation of novel variation in plants is relatively unknown. Here we use whole-genome and whole-methylome sequencing to test if a specific environmental stress (high-salinity soil) changes the frequency and molecular profile of accumulated mutations and epimutations (changes in cytosine methylation status) in mutation accumulation (MA) lineages of Arabidopsis thaliana. We first show that stressed lineages accumulate ∼100% more mutations, and that these mutations exhibit a distinctive molecular mutational spectrum (specific increases in relative frequency of transversion and insertion/deletion [indel] mutations). We next show that stressed lineages accumulate ∼45% more differentially methylated cytosine positions (DMPs) at CG sites (CG-DMPs) than controls, and also show that while many (∼75%) of these CG-DMPs are inherited, some can be lost in subsequent generations. Finally, we show that stress-associated CG-DMPs arise more frequently in genic than in nongenic regions of the genome. We suggest that commonly encountered natural environmental stresses can accelerate the accumulation and change the profiles of novel inherited variants in plants. Our findings are significant because stress exposure is common among plants in the wild, and they suggest that environmental factors may significantly alter the rates and patterns of incidence of the inherited novel variants that fuel plant evolution.
|Original language||English (US)|
|Number of pages||9|
|State||Published - Oct 14 2014|
Bibliographical noteKAUST Repository Item: Exported on 2020-10-01
Acknowledged KAUST grant number(s): KUK-I1-002-03
Acknowledgements: This study is based on work supported by King Abdullah University of Science and Technology (KAUST) award no. KUK-I1-002-03; the UK Biotechnological and Biological Sciences Research Council (grants BB/F020759/1 to N.P.H. and BB/F022697/1 to R.M.); St. John's College, Oxford (research support to N.P.H.); the National Natural Science Foundation of China (grant 31470350 to C.J.); LUMS Faculty Startup Grant; and the Wellcome Trust (Core grant 090532/Z/09/Z). We thank Hugh Dickinson (Department of Plant Sciences, University of Oxford, UK), Gilean McVean (Department of Statistics, University of Oxford, UK), and Detlef Weigel (Max Planck Institute for Developmental Biology, Tubingen, Germany) for constructive comments on preliminary versions of our manuscript.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.