Multiple abiotic stimuli are integrated in the regulation of rice gene expression under field conditions

  1. Anne Plessis
  2. Christoph Hafemeister
  3. Olivia Wilkins
  4. Zennia Jean Gonzaga
  5. Rachel Sarah Meyer
  6. Inês Pires
  7. Christian Müller
  8. Endang M Septiningsih
  9. Richard Bonneau
  10. Michael Purugganan  Is a corresponding author
  1. Plymouth University, United Kingdom
  2. New York University, United States
  3. International Rice Research Institute, Philippines
  4. Simons Foundation, New York, United States
  5. Texas A&M University, United States

Abstract

Plants rely on transcriptional dynamics to respond to multiple climatic fluctuations and contexts in nature. We analyzed genome-wide gene expression patterns of rice (Oryza sativa) growing in rainfed and irrigated fields during two distinct tropical seasons and determined simple linear models that relate transcriptomic variation to climatic fluctuations. These models combine multiple environmental parameters to account for patterns of expression in the field of co-expressed gene clusters. We examined the correspondence of our environmental models between tropical and temperate field conditions, using previously published data. We found that field type and macroclimate had broad impacts on transcriptional responses to environmental fluctuations, especially for genes involved in photosynthesis and development. Nevertheless, variation in solar radiation and temperature at the timescale of hours had reproducible effects across environmental contexts. These results provide a basis for broad-based predictive modeling of plant gene expression in the field.

Article and author information

Author details

  1. Anne Plessis

    School of Biological Sciences, Plymouth University, Plymouth, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  2. Christoph Hafemeister

    Department of Biology, Center for Genomics and Systems Biology, New York University, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Olivia Wilkins

    Department of Biology, Center for Genomics and Systems Biology, New York University, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Zennia Jean Gonzaga

    International Rice Research Institute, Metro Manila, Philippines
    Competing interests
    The authors declare that no competing interests exist.
  5. Rachel Sarah Meyer

    Department of Biology, Center for Genomics and Systems Biology, New York University, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
  6. Inês Pires

    Department of Biology, Center for Genomics and Systems Biology, New York University, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
  7. Christian Müller

    Simons Center for Data Analysis, Simons Foundation, New York, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
  8. Endang M Septiningsih

    Department of Soil and Crop Sciences, Texas A&M University, College Station, United States
    Competing interests
    The authors declare that no competing interests exist.
  9. Richard Bonneau

    Department of Biology, Center for Genomics and Systems Biology, New York University, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
  10. Michael Purugganan

    Department of Biology, Center for Genomics and Systems Biology, New York University, New York, United States
    For correspondence
    mp132@nyu.edu
    Competing interests
    The authors declare that no competing interests exist.

Reviewing Editor

  1. Daniel J Kliebenstein, University of California, Davis, Denmark

Version history

  1. Received: April 29, 2015
  2. Accepted: November 25, 2015
  3. Accepted Manuscript published: November 26, 2015 (version 1)
  4. Version of Record published: December 31, 2015 (version 2)

Copyright

© 2015, Plessis et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 3,727
    views
  • 810
    downloads
  • 36
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Anne Plessis
  2. Christoph Hafemeister
  3. Olivia Wilkins
  4. Zennia Jean Gonzaga
  5. Rachel Sarah Meyer
  6. Inês Pires
  7. Christian Müller
  8. Endang M Septiningsih
  9. Richard Bonneau
  10. Michael Purugganan
(2015)
Multiple abiotic stimuli are integrated in the regulation of rice gene expression under field conditions
eLife 4:e08411.
https://doi.org/10.7554/eLife.08411

Share this article

https://doi.org/10.7554/eLife.08411

Further reading

    1. Computational and Systems Biology
    2. Physics of Living Systems
    Taegon Chung, Iksoo Chang, Sangyeol Kim
    Research Article

    Locomotion is a fundamental behavior of Caenorhabditis elegans (C. elegans). Previous works on kinetic simulations of animals helped researchers understand the physical mechanisms of locomotion and the muscle-controlling principles of neuronal circuits as an actuator part. It has yet to be understood how C. elegans utilizes the frictional forces caused by the tension of its muscles to perform sequenced locomotive behaviors. Here, we present a two-dimensional rigid body chain model for the locomotion of C. elegans by developing Newtonian equations of motion for each body segment of C. elegans. Having accounted for friction-coefficients of the surrounding environment, elastic constants of C. elegans, and its kymogram from experiments, our kinetic model (ElegansBot) reproduced various locomotion of C. elegans such as, but not limited to, forward-backward-(omega turn)-forward locomotion constituting escaping behavior and delta-turn navigation. Additionally, ElegansBot precisely quantified the forces acting on each body segment of C. elegans to allow investigation of the force distribution. This model will facilitate our understanding of the detailed mechanism of various locomotive behaviors at any given friction-coefficients of the surrounding environment. Furthermore, as the model ensures the performance of realistic behavior, it can be used to research actuator-controller interaction between muscles and neuronal circuits.

    1. Computational and Systems Biology
    2. Genetics and Genomics
    Lauren Kuffler, Daniel A Skelly ... Gregory W Carter
    Research Article

    Gene expression is known to be affected by interactions between local genetic variation and DNA accessibility, with the latter organized into three-dimensional chromatin structures. Analyses of these interactions have previously been limited, obscuring their regulatory context, and the extent to which they occur throughout the genome. Here, we undertake a genome-scale analysis of these interactions in a genetically diverse population to systematically identify global genetic–epigenetic interaction, and reveal constraints imposed by chromatin structure. We establish the extent and structure of genotype-by-epigenotype interaction using embryonic stem cells derived from Diversity Outbred mice. This mouse population segregates millions of variants from eight inbred founders, enabling precision genetic mapping with extensive genotypic and phenotypic diversity. With 176 samples profiled for genotype, gene expression, and open chromatin, we used regression modeling to infer genetic–epigenetic interactions on a genome-wide scale. Our results demonstrate that statistical interactions between genetic variants and chromatin accessibility are common throughout the genome. We found that these interactions occur within the local area of the affected gene, and that this locality corresponds to topologically associated domains (TADs). The likelihood of interaction was most strongly defined by the three-dimensional (3D) domain structure rather than linear DNA sequence. We show that stable 3D genome structure is an effective tool to guide searches for regulatory elements and, conversely, that regulatory elements in genetically diverse populations provide a means to infer 3D genome structure. We confirmed this finding with CTCF ChIP-seq that revealed strain-specific binding in the inbred founder mice. In stem cells, open chromatin participating in the most significant regression models demonstrated an enrichment for developmental genes and the TAD-forming CTCF-binding complex, providing an opportunity for statistical inference of shifting TAD boundaries operating during early development. These findings provide evidence that genetic and epigenetic factors operate within the context of 3D chromatin structure.