Skip to main content

Main menu

  • Home
  • Content
    • Current Issue
    • Archive
    • Preview Papers
  • Info for
    • Instructions for Authors
    • Submit a Manuscript
    • Advertisers
    • Librarians
    • Subscribers
  • About
    • Editorial Board and Staff
    • About the Journal
  • More
    • Alerts
    • Contact Us
  • Other Publications
    • Plant Physiology
    • The Plant Cell
    • Plant Direct
    • The Arabidopsis Book
    • Teaching Tools in Plant Biology
    • ASPB
    • Plantae

User menu

  • My alerts
  • Log in

Search

  • Advanced search
Plant Cell
  • Other Publications
    • Plant Physiology
    • The Plant Cell
    • Plant Direct
    • The Arabidopsis Book
    • Teaching Tools in Plant Biology
    • ASPB
    • Plantae
  • My alerts
  • Log in
Plant Cell

Advanced Search

  • Home
  • Content
    • Current Issue
    • Archive
    • Preview Papers
  • Info for
    • Instructions for Authors
    • Submit a Manuscript
    • Advertisers
    • Librarians
    • Subscribers
  • About
    • Editorial Board and Staff
    • About the Journal
  • More
    • Alerts
    • Contact Us
  • Follow PlantCell on Twitter
  • Visit PlantCell on Facebook
  • Visit Plantae
Research ArticleResearch Article
You have accessRestricted Access

Global Epigenetic and Transcriptional Trends among Two Rice Subspecies and Their Reciprocal Hybrids

Guangming He, Xiaopeng Zhu, Axel A. Elling, Liangbi Chen, Xiangfeng Wang, Lan Guo, Manzhong Liang, Hang He, Huiyong Zhang, Fangfang Chen, Yijun Qi, Runsheng Chen, Xing-Wang Deng
Guangming He
Peking-Yale Joint Center of Plant Molecular Genetics and Agrobiotechnology, National Laboratory of Protein Engineering and Plant Genetic Engineering, College of Life Sciences, Peking University, Beijing 100871, ChinaNational Institute of Biological Sciences, Beijing 102206, ChinaDepartment of Molecular, Cellular, and Developmental Biology, Yale University, New Haven, Connecticut 06520
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Xiaopeng Zhu
Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Axel A. Elling
Department of Molecular, Cellular, and Developmental Biology, Yale University, New Haven, Connecticut 06520
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Liangbi Chen
Department of Botany, College of Life Sciences, Hunan Normal University, Changsha 410081, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Xiangfeng Wang
Peking-Yale Joint Center of Plant Molecular Genetics and Agrobiotechnology, National Laboratory of Protein Engineering and Plant Genetic Engineering, College of Life Sciences, Peking University, Beijing 100871, ChinaDepartment of Molecular, Cellular, and Developmental Biology, Yale University, New Haven, Connecticut 06520
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Lan Guo
Peking-Yale Joint Center of Plant Molecular Genetics and Agrobiotechnology, National Laboratory of Protein Engineering and Plant Genetic Engineering, College of Life Sciences, Peking University, Beijing 100871, ChinaNational Institute of Biological Sciences, Beijing 102206, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Manzhong Liang
Department of Botany, College of Life Sciences, Hunan Normal University, Changsha 410081, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Hang He
Peking-Yale Joint Center of Plant Molecular Genetics and Agrobiotechnology, National Laboratory of Protein Engineering and Plant Genetic Engineering, College of Life Sciences, Peking University, Beijing 100871, ChinaDepartment of Molecular, Cellular, and Developmental Biology, Yale University, New Haven, Connecticut 06520
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Huiyong Zhang
National Institute of Biological Sciences, Beijing 102206, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Fangfang Chen
National Institute of Biological Sciences, Beijing 102206, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Yijun Qi
National Institute of Biological Sciences, Beijing 102206, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Runsheng Chen
Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Xing-Wang Deng
Peking-Yale Joint Center of Plant Molecular Genetics and Agrobiotechnology, National Laboratory of Protein Engineering and Plant Genetic Engineering, College of Life Sciences, Peking University, Beijing 100871, ChinaNational Institute of Biological Sciences, Beijing 102206, ChinaDepartment of Molecular, Cellular, and Developmental Biology, Yale University, New Haven, Connecticut 06520
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: xingwang.deng@yale.edu

Published January 2010. DOI: https://doi.org/10.1105/tpc.109.072041

  • Article
  • Figures & Data
  • Info & Metrics
  • PDF
Loading

Article Figures & Data

Figures

  • Additional Files
  • Figure 1.
    • Download figure
    • Open in new tab
    • Download powerpoint
    Figure 1.

    Integrated Profiling of the Rice Transcriptome and Epigenome by High-Throughput Sequencing.

    (A) Distribution of mapped reads for mRNA-Seq library in the rice genome.

    (B) Proportion of mRNA transcripts identified by mRNA-Seq according to gene annotations supported by EST or full-length cDNA data.

    (C) Identification of genomic regions associated with DNA methylation (DNA methyl), H3K4me3, H3K9ac, and H3K27me3.

    (D) Comparisons of DNA methylation and H3K4me3 modification patterns in a representative region on rice chromosome 4 using Solexa sequencing (this study) and microarray technology (Li et al., 2008b). The predicted coding sequences are shown in blue above.

    (E) Frequencies of epigenetically modified regions in genic and intergenic regions.

    (F) Number and percentage of non-TE genes and TE-related genes identified with expression or epigenetic modifications.

  • Figure 2.
    • Download figure
    • Open in new tab
    • Download powerpoint
    Figure 2.

    Relationships among Gene Expression and Epigenetic Modifications.

    (A) Frequencies of concurrent epigenetic modifications and gene expression. Numbers indicate the percentage of genes that were detected with X and were also detected with Y.

    (B) Correlation between DNA methylation and gene expression. Red, TE-related genes; blue, non-TE genes.

    (C) Correlation between H3K4me3 and H3K27me3 modifications. Only data of genes with a transcript level <10 reads (red, low-expressed) or >100 reads (blue, high-expressed) per kilobase of predicted mRNA were plotted here.

    (D) A permutation table for all combinations of DNA methylation, H3K4me3, and H3K27me3 modifications and gene expression. The number and percentage of TE-related or non-TE genes in each possible combination were calculated. Color scale indicates the proportion (from high to low) of genes. Typical examples from the predominant clusters visualized in the UCSC genome browser. Left, genes without DNA methylation and for which H3K4me3 modification was dominant were transcriptionally active. Middle, genes for which DNA methylation was dominant were depleted in H3K4me3 and H3K27me3 and were transcriptionally repressive. Right, genes without DNA methylation and for which H3K27me3 modification was dominant were transcriptionally repressive.

    (E) Heat map of epigenetic modification levels and the ratio (K4/K27) between H3K4me3 and H3K27me3 levels (normalized by total mapped reads) on all annotated rice genes sorted by their expression level measured by mRNA-Seq. K4, H3K4me3; K27, H3K27me3.

  • Figure 3.
    • Download figure
    • Open in new tab
    • Download powerpoint
    Figure 3.

    Correlations between Epigenetic Natural Variations and Changes in Transcript Abundance between Two Parental Lines.

    (A) and (B) Number and percentage of non-TE and TE-related genes exhibiting differences in gene expression or epigenetic modifications between Nipponbare (Nip) and 93-11. Red, number or percentage of genes for which the levels of expression or epigenetic modifications is higher in Nipponbare than in 93-11. Blue, number or percentage of genes for which the levels of expression or epigenetic modifications is lower in Nipponbare than in 93-11.

    (C) Frequencies of concurrence between differences in gene expression and differences in epigenetic modifications. Numbers indicate the percentage of genes that were differentially modified and that were also differentially expressed. Color scale indicates the proportion (from high to low) of genes.

    (D) to (F) Correlations between differential epigenetic modifications (P value < 0.001) and differential gene expression (P value < 0.001).

    (G) Typical examples of genes showing correlations between differential H3K4me3 modification and differential gene expression.

  • Figure 4.
    • Download figure
    • Open in new tab
    • Download powerpoint
    Figure 4.

    Variation Patterns of Gene Expression and Epigenetic Modifications in Reciprocal Hybrids.

    (A) Modes of gene action in hybrid. Red bar, gene expression levels in parent 1 (P1). Green bar, gene expression levels in parent 2 (P2). Blue horizontal line, gene expression levels in hybrid cross between P1 and P2. x axis, comparisons of gene expression levels between P1 and P2. y axis, comparisons of gene expression levels between parents and hybrid and the patterns for each case.

    (B) Additive and nonadditive variation in gene expression and epigenetic modifications in hybrids. Additive, hybrids show a transcript or modification level equal to the mid-parent value (average of the two parents). Nonadditive, hybrids show a transcript or modification level deviating from the mid-parent value.

    (C) Subdivided patterns of nonadditive variation in gene expression (high-parent, above high-parent, low-parent, and below low-parent) in reciprocal hybrids. High-parent or low-parent patterns, the gene expression level in hybrids is similar to the higher parent or to the lower parent, respectively. Above high-parent or below low-parent patterns, the gene expression level in hybrids is above the higher parent or below the lower parent, respectively.

    (D) to (F) Subdivided patterns of non-additive variation in DNA methylation and histone modifications in hybrids.

  • Figure 5.
    • Download figure
    • Open in new tab
    • Download powerpoint
    Figure 5.

    Allelic Bias of Gene Expression and Epigenetic Modifications in Reciprocal Hybrids.

    (A) Detection of allelic bias in gene expression and epigenetic modifications in hybrids using SNPs between parental lines. Only SNPs identified with a significant allelic bias at a P value cutoff of 0.01 in both reciprocal hybrids were included. Nipa, Nipponbare allele; 93-11a, 93-11 allele.

    (B) An example of a gene exhibiting allelic expression bias in Nip/93-11 hybrid. Read number of alleles detected by SNPs at each position was plotted.

    (C) Correlation of allelic expression bias between reciprocal hybrids.

    (D) Allelic expression bias in hybrids according to their differences between parents. Nips, gene expression level in Nipponbare represented by the number of reads covering a SNP; 93-11s, gene expression level in 93-11 represented by the number of reads covering a SNP.

    (E) Correlation between differential parental expression (represented by the number of reads covering a SNP) and allelic expression bias in Nip/93-11 hybrid.

  • Figure 6.
    • Download figure
    • Open in new tab
    • Download powerpoint
    Figure 6.

    Diversity of Small RNAs in Composition and Expression between Parents and Hybrids.

    (A) Distribution of small RNAs on rice chromosome 1. The y axis represents the added small RNA reads per 100 genomic region. Blue vertical lines, >2000 reads per 100-kb genomic regions. Black bar, pericentromeric region.

    (B) Classes of genomic features (the genic or transcribed regions of annotated rice genes, 2 kb upstream or 2 kb downstream of the genic regions) matched by rice small RNAs. The average number of small RNA reads per kilobase region of each genomic feature is counted.

    (C) Distribution of small RNAs (mapped reads after the removal of rRNAs, tRNAs, snRNA, and snoRNA) among genic (TE- and non-TE) and intergenic regions in the rice genome.

    (D) Small RNA length distribution in two parental inbred lines and their reciprocal hybrids.

    (E) Differential expression of siRNA clusters between F1 hybrids and their parents. MP, mid-parent value.

    (F) Expression patterns of siRNA clusters in Nip/93-11 hybrid.

    (G) Negative correlation between the expression of 14 miRNAs and their 20 targets that are both exhibiting nonadditive variation in both reciprocal hybrids. Multiple targets of a single miRNA are indicated by a vertical line.

  • Figure 7.
    • Download figure
    • Open in new tab
    • Download powerpoint
    Figure 7.

    Interactions among Epigenetic Modifications, Small RNA Transcription, and Gene Expression and Their Variation in Hybrids.

    (A) Description of the source of gene expression variation in hybrids.

    (B) A representative genomic region on rice chromosome 1 showing integrated maps of predicted gene models with mRNA, small RNA, and epigenetic landscapes in two rice subspecies and their reciprocal hybrids.

Additional Files

  • Figures
  • Supplemental Data

    Files in this Data Supplement:

    • Supplemental Figures, Tables and Methods
PreviousNext
Back to top

Table of Contents

Print
Download PDF
Article Alerts
Sign In to Email Alerts with your Email Address
Email Article

Thank you for your interest in spreading the word on Plant Cell.

NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail. We do not capture any email address.

Enter multiple addresses on separate lines or separate them with commas.
Global Epigenetic and Transcriptional Trends among Two Rice Subspecies and Their Reciprocal Hybrids
(Your Name) has sent you a message from Plant Cell
(Your Name) thought you would like to see the Plant Cell web site.
Citation Tools
Global Epigenetic and Transcriptional Trends among Two Rice Subspecies and Their Reciprocal Hybrids
Guangming He, Xiaopeng Zhu, Axel A. Elling, Liangbi Chen, Xiangfeng Wang, Lan Guo, Manzhong Liang, Hang He, Huiyong Zhang, Fangfang Chen, Yijun Qi, Runsheng Chen, Xing-Wang Deng
The Plant Cell Jan 2010, 22 (1) 17-33; DOI: 10.1105/tpc.109.072041

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Share
Global Epigenetic and Transcriptional Trends among Two Rice Subspecies and Their Reciprocal Hybrids
Guangming He, Xiaopeng Zhu, Axel A. Elling, Liangbi Chen, Xiangfeng Wang, Lan Guo, Manzhong Liang, Hang He, Huiyong Zhang, Fangfang Chen, Yijun Qi, Runsheng Chen, Xing-Wang Deng
The Plant Cell Jan 2010, 22 (1) 17-33; DOI: 10.1105/tpc.109.072041
del.icio.us logo Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Jump to section

  • Article
    • Abstract
    • INTRODUCTION
    • RESULTS
    • DISCUSSION
    • METHODS
    • Acknowledgments
    • Footnotes
    • References
  • Figures & Data
  • Info & Metrics
  • PDF

In this issue

The Plant Cell Online: 22 (1)
The Plant Cell
Vol. 22, Issue 1
Jan 2010
  • Table of Contents
  • Table of Contents (PDF)
  • About the Cover
  • Index by author
  • Advertising (PDF)
  • Front Matter (PDF)
View this article with LENS

More in this TOC Section

  • Crystal Structure of Plant Legumain Reveals a Unique Two-Chain State with pH-Dependent Activity Regulation
  • TEOSINTE BRANCHED1 Regulates Inflorescence Architecture and Development in Bread Wheat (Triticum aestivum)
  • A Functional Study of AUXILIN-LIKE1 and 2, Two Putative Clathrin Uncoating Factors in Arabidopsis
Show more RESEARCH ARTICLES

Similar Articles

Our Content

  • Home
  • Current Issue
  • Plant Cell Preview
  • Archive
  • Teaching Tools in Plant Biology
  • Plant Physiology
  • Plant Direct
  • Plantae
  • ASPB

For Authors

  • Instructions
  • Submit a Manuscript
  • Editorial Board and Staff
  • Policies
  • Recognizing our Authors

For Reviewers

  • Instructions
  • Peer Review Reports
  • Journal Miles
  • Transfer of reviews to Plant Direct
  • Policies

Other Services

  • Permissions
  • Librarian resources
  • Advertise in our journals
  • Alerts
  • RSS Feeds
  • Contact Us

Copyright © 2018 by The American Society of Plant Biologists

Powered by HighWire