Rice is one of the most important food crops and is estimated to provide more than a fifth of the calories consumed by the world's population. For several decades, rice has been modified by conventional breeding methods to produce plants with increased yields and greater resistance to pests and harsh weather conditions. Efforts are also being made to create rice plants with superior yield traits and resistance to biotic and abiotic stresses using genetic engineering techniques.

Genetically modified plants are usually produced using tissue culture. New genes are introduced into plant cells that are growing in a dish, and each cell then replicates to form a mass of genetically identical cells. The application of plant hormones triggers the tissue to produce roots and shoots, giving rise to plantlet clones.

In addition to the genes that comprise its genome, the genetic make-up of an organism also includes its epigenome—a collection of chemical modifications that influence whether or not a given gene is expressed as a protein. The addition of methyl groups to specific sequences within the DNA, for example, acts as an epigenetic signal to reduce the transcription, and thus expression, of the genes concerned.

Now, Stroud et al. reveal that the techniques used to modify a plant's genome—in particular, the process of tissue culture—also affect its epigenome. They prepared high-resolution maps of DNA methylation in several regenerated rice lines, and found that regenerated plants produced in culture showed less methylation than control plants. The changes were relatively over-represented around the promoter sequences of genes—regions of DNA that act as binding sites for the enzymes that transcribe DNA into RNA—and were accompanied by changes in gene expression. Crucially, the plants' descendants frequently also inherited the changes in methylation status. These results are likely part of the explanation for a phenomenon called somaclonal variation, first observed before the era of modern biotechnology, in which plants regenerated from tissue culture sometimes show heritable alterations in the phenotype of the plant.

Rice is one of the world's most important food crops, and genetic modifications are extensively used for various purposes such as to increase yield and tolerate harsh environments. Tissue culture has been heavily used for decades for transformation procedures to generate transgenic crops such as rice and maize (Rao et al., 2009). A previous study has reported that Arabidopsis cell suspension culture has a different epigenomic profile compared to wild-type plants, such that certain transposable elements (TEs) become hypomethylated and certain genes become hypermethylated (Tanurdzic et al., 2008). This raised the question of how tissue culture processes affect the epigenome of regenerated plants derived from tissue culture. Changes in the epigenome have been proposed to be a source of somaclonal variation (i.e., phenotypic variation among regenerated plants) for decades (Kaeppler and Phillips, 1993; Kaeppler et al., 2000; Thorpe, 2006; Rhee et al., 2010; Miguel and Marum, 2011; Neelakandan and Wang, 2012). Indeed, some evidence suggesting changes in the epigenome of regenerated plants have been reported at several specific loci or by methods such as methylation sensitive restrictive enzyme digestion (Neelakandan and Wang, 2012). However, the extent of methylation changes on a genome-wide level has not been previously assessed. Because, unlike most crops, Arabidopsis is almost exclusively transformed via Agrobacterium-mediated floral dip methods that do not utilize tissue culture (Clough and Bent, 1998), Arabidopsis is not a good model for the study of the effect of plant regeneration on the epigenome. The study of the model plant rice, however, may have practical implications for other crop species that are transformed using similar tissue culture methods.

The rice genome is DNA methylated in all three cytosine contexts (CG, CHG, CHH, where H=A, T, or C), with high levels of CG and CHG methylation and very low levels of CHH methylation (Feng et al., 2010; Zemach et al., 2010). Whole genome bisulfite sequencing (BS-seq) enables measurement of DNA methylation at single nucleotide resolution and thus allows one to distinguish DNA methylation in different cytosine contexts (Cokus et al., 2008; Lister et al., 2008).

To investigate the effect that tissue culture processes have on regenerated rice epigenomes, we generated genome-wide, single-nucleotide maps of DNA methylation in several regenerated rice lines that had been transformed with various transgenes, callus, and rice regenerated from tissue culture without transformation. We observed that the tissue culture procedure induced stable changes in DNA methylation in regenerated plants, such that all regenerated lines had ectopic losses of DNA methylation. We found that loss of DNA methylation occurred stochastically, affecting individual plants somewhat differently, was associated with loss of small RNAs, and changes were enriched at promoters of genes. Loss of DNA methylation at promoters was associated with altered expression of particular genes.

We performed deep BS-seq to map DNA methylation in nine regenerated rice lines in the Nipponbare ecotype background that were transformed by various transgenes and were at various stages of inbreeding after transformation: rice blast resistance lines PiZ-t, PiZ-t-839 (a non-functional PiZ-t), Pi9, and an RNAi line for flowering time regulator Spin1 (Zhou et al., 2006; Vega-Sanchez et al., 2008; Table 1). For the PiZ-t line, both transgenic and non-transgenic T2 and T4 plants were available by genetic segregation of the PiZ-t transgene (Table 1). For comparison, we profiled an untransformed wild-type line, which was used to generate all the regenerated lines, WT2003 (sample 1). WT2003 was also inbred 5–7 generations to produce WT2007 (sample 2), and WT2007 was inbred 5–7 additional generations to produce WT2011 (sample 3). We obtained an average genome coverage of 15× and error rates were low at 1.5%, 1.2%, 0.8%, for CG, CHG, CHH methylation, respectively, indicating high quality data (Table 1).

We observed strong losses of DNA methylation at certain sites in the genome in the regenerated plants but not in wild-type plants (Figure 1A). To further characterize these sites, we defined differentially methylated regions (DMRs) in CG contexts by applying stringent thresholds (see ‘Materials and methods'). We found that all regenerated plants tested were significantly enriched with CG hypomethylation DMRs (Figure 1B). On average, we identified 1344 CG hypomethylation DMRs in the regenerated plants, whose sizes ranged from 100 to 3200 bp (Figure 1C), whereas on average we identified only eight CG hypomethylation DMRs in the inbred wild-type lines (Figure 1—source data 1). Importantly, we observed hypomethylation even in the T2/T4 non-transgenic plants in which the transgenes had been segregated away (samples 5, 7 and 12), suggesting that loss of DNA methylation is likely due to the tissue culture or transformation process, but not due to the fact that the plants contain transgenes. While loss of DNA methylation in different regenerated lines did not always occur at the same sites (Figure 1D), there were significant overlaps of hypomethylation DMRs among regenerated lines (Figure 1E). This suggests that certain sites in the genome are susceptible to loss of DNA methylation in regenerated plants.

Figure 1

Download asset Open asset

Figure 1—source data 1

List of CG, CHG, CHH DMRs identified in this study.

Defined hypomethylation DMRs for each sample are listed.

https://doi.org/10.7554/eLife.00354.005

Download elife-00354-fig1-data1-v1.xlsx

We next investigated the stability of DNA methylation losses across generations. To test this, we analyzed a line for which we had plants in T2, T4, and T6 generations (samples 4, 6, 8). 84% of sites that lost CG methylation in the T2 did not recover methylation in the T4 and T6 generations (Figure 2). This suggests that most sites do not regain DNA methylation over several subsequent generations during the process of inbreeding. Approximately 10% of sites recovered methylation in T4, and this methylation was maintained in T6. In addition, 4.4% of sites recovered methylation in T6 but not in T4. This suggests that certain sites are able to regain methylation over generations. Approximately 2% of sites regained methylation in T4, but methylation was lost again in T6, suggesting that a small fraction of sites are epigenetically unstable and continue to switch states. Our results suggest that most of the DNA hypomethylation in regenerated plants was stable over generations.

Figure 2

Download asset Open asset

Loss of DNA methylation in regenerated plants also occurred in non-CG contexts (Figure 1—source data 1). Loss of CG methylation was generally associated with loss of CHG methylation and to a lesser extent with loss of CHH methylation (Figure 3A,B). Small interfering RNAs of 24-nt in length (24-nt siRNAs) are associated with DNA methylation, and are required to guide CHH methylation to particular sites (Law and Jacobsen, 2010). We performed small RNA sequencing (smRNA-seq) on seven randomly chosen regenerated plants along with wild type (Table 2). We examined the distribution of 24-nt siRNAs over CHH hypomethylation DMRs and found that siRNAs are enriched over these sites in wild type, but eliminated in regenerated plants (Figure 3C). Hence loss of DNA methylation is associated with loss of 24 nt siRNAs. Moreover, these siRNA alterations independently confirm our findings showing loss of epigenetic marks at these loci.

Figure 3

Download asset Open asset

We next examined the genomic characteristics of sites that lost DNA methylation in regenerated plants. We tested the extent of overlap between 3597 CG DMRs, 1875 CHG DMRs, and 2298 CHH DMRs defined in the regenerated lines within gene bodies, gene promoters, downstream regions of genes, gene coding sequences, gene introns, and TE genes. Although loss of DNA methylation occurred at a variety of sites, we found the most significant enrichments of DMRs at the promoters of genes (Figure 4A). These genes were not significantly associated with any particular biological processes (data not shown). Rather, they appeared to be a random set of genes involved in different processes (Figure 4—source data 1). Recent studies in Arabidopsis have shown that spontaneous changes in methylation over generations predominantly occurred in gene bodies (Becker et al., 2011; Schmitz et al., 2011). It is possible that hypomethylation observed in regenerated plants occurs through an accelerated process of whatever mechanism causes spontaneous methylation changes over generations. Alternatively, since the DNA methylation changes we observed in regenerated plants was enriched in gene promoters, and was primarily in the direction of methylation loss, it could be a distinct phenomenon from the spontaneously occurring methylation changes in wild type.

Figure 4 with 4 supplements see all

Download asset Open asset

Figure 4—source data 1

List of genes with CG hypomethylation DMRs at promoters and their expression levels.

Genes with CG hypomethylation DMRs at the promoter regions (TSS minus 2 kb to TSS) in samples 4–10 along with their normalized expression levels are listed. Also indicated are whether they were significantly up- or down-regulated based on fourfold and FDR < 0.01 cutoffs. Descriptions of genes were directly taken from the rice genome annotation project website (http://rice.plantbiology.msu.edu/).

https://doi.org/10.7554/eLife.00354.010

Download elife-00354-fig4-data1-v1.xlsx

While the losses of DNA methylation in regenerated plants occurred within a relatively small proportion of the rice genome, they were concentrated near protein-coding gene promoters and therefore in regions of the genome that are more prone to alter gene expression. We therefore examined the impact of hypomethylation on gene expression by performing mRNA-seq on the same seven randomly chosen regenerated plants as well as on wild-type plants (Table 3). We found that loss of DNA methylation at promoters was associated with higher expression levels of certain genes (Figure 4B,C, Figure 4—source data 1, Figure 4—figure supplement 1, 2). Notably, the closer the hypomethylation was to the gene transcription start site, the more likely the gene tended to be misregulated (Figure 4B). Furthermore, the expression of these genes was much more frequently increased, rather than decreased, suggesting that the misexpression of these genes is likely a direct consequence of losses of DNA methylation (Figure 4B). Hence loss of DNA methylation in regenerated plants is associated with deregulated transcription of certain protein-coding genes.

We further sought to determine whether it was the tissue culture process or the transformation process that induced loss of DNA methylation in regenerated plants. To test this, we performed BS-seq on callus and three individual plants regenerated from untransformed callus, all of which were derived from a single parent plant (WT2011; Table 1). We were not able to perform BS-seq on individual calli because calli at the stage of transformation did not yield enough genomic DNA. Instead, we pooled multiple calli, and sequenced two separate batches. We found a strong loss of DNA methylation in plants regenerated from untransformed callus (Figure 5A). Loss of DNA methylation in callus was much more modest, though significant (Figure 5A). This relatively weak loss of DNA methylation may be because individual calli lose DNA methylation at different sites (despite being derived from the same parent plant), and pooling multiple calli diluted the loss of DNA methylation. Consistent with this notion, individual plants regenerated from untransformed callus showed differences in sites that lost DNA methylation (Figure 5B). Furthermore, when examining methylation levels of these samples at CG hypomethylation DMRs that were common in all regenerated plants, we found significant losses of DNA methylation at these sites in callus (Figure 5C,D), indicating that the methylation losses observed in callus were at largely the same sites as those observed in regenerated plants. Like in the regenerated lines, the losses of DNA methylation in the non-transformed regenerated plants occurred stochastically, affecting DNA methylation in each plant somewhat differently (Figure 5A–D). In summary, the loss of DNA methylation in regenerated plants is likely caused by the tissue culture step, and not due to the transformation process.

Figure 5

Download asset Open asset

Previous reports have indicated that certain genes are hypermethylated in Arabidopsis cell suspension culture and callus (Berdasco et al., 2008; Tanurdzic et al., 2008). Consistent with those data we found that rice callus showed hypermethylation throughout the genome (Figure 6A). Interestingly we found that the hypermethylation occurred specifically in CHH contexts (Figure 6A,B, Figure 6—figure supplement 1A), and showed high coincidence between the two callus samples (13 and 14) (Figure 6—figure supplement 1B). These CHH hypermethylated regions mostly corresponded to promoter regions (Figure 6C, Figure 6—figure supplement 1A). Hence in callus, certain promoters are CHH hypermethylated, while others are hypomethylated in all cytosine contexts. Interestingly, CHH hypermethylation observed in callus was completely lost in regenerated plants (Figure 6A,B, Figure 6—figure supplement 1A). This suggests that unlike tissue culture-induced DNA hypomethylation that is largely stable after regeneration, CHH hypermethylation is eliminated after regeneration.

Figure 6 with 1 supplement see all

Download asset Open asset

In this report, we have investigated the effect that tissue culture processes have on the epigenome of regenerated plants by generating high-resolution maps of DNA methylation. Consistent with a previous study in Arabidopsis cell culture using microarray hybridization on chromosome 4 (Tanurdzic et al., 2008), we observed hypermethylation at certain genes in rice callus. We extend this observation by showing that hypermethylation predominantly occurs in CHH sequence contexts, most notably occurring at the promoters of genes. Interestingly, we found that this CHH hypermethylation was completely eliminated upon regeneration, suggesting that CHH hypermethylation may be linked specifically to the dedifferentiated state.

In contrast to Arabidopsis cell culture, we did not observe global hypomethylation at TEs in rice callus. Instead, we found that DNA methylation was specifically lost at certain sites in the genome, appearing to affect individual plants somewhat differently despite coming from the same parent plant. We found that loss of DNA methylation was maintained upon plant regeneration, and was largely stable over subsequent generations. It is possible that some of the DMRs affected only one homologous chromosome and were segregating. However, because we required DMRs to have at least 70% reduction in DNA methylation compared to wild-type, the sites we analyzed in Figure 2 are likely homozygous for loss of DNA methylation, consistent with their stability across generations. Loss of DNA methylation occurred in all sequence contexts, and was associated with loss of 24-nt siRNAs. Notably, these sites were frequently associated with promoters of genes, and loss of DNA methylation was associated with misregulation of expression of proximal protein-coding genes, indicating a biological importance of this phenomenon. Interestingly, genes significantly up-regulated (fourfold upregulated compared to wild type, p<0.01) in each regenerated line were somewhat different (Figure 4—figure supplement 3). For this reason, it is difficult to assess the severity of impact of misregulated gene expression for any particular regenerated line, since some lines may have more biologically important genes affected than others. This would correlate with the observation that somoclonal variation affects only a proportion of plants that arise from regeneration experiments (Kaeppler and Phillips, 1993; Kaeppler et al., 2000; Thorpe, 2006; Rhee et al., 2010; Miguel and Marum, 2011; Neelakandan and Wang, 2012).

Previous studies have shown that certain TEs such as Tos17 and mPing are reactivated in tissue culture, and are associated with changes in DNA methylation (Neelakandan and Wang, 2012). While our results suggest that most DNA hypomethylation occurs near genes and are relatively depleted at TE related sequences (Figure 4A), some of the hypomethylation did occur proximal to TE genes (average of 62.1 TE genes per line). The association of loss of methylation with TE gene reactivation was not clear (data not shown), however very subtle depletion of DNA methylation was observed over reactivated TE genes (Figure 4—figure supplement 4), suggesting that loss of methylation may in part be responsible for reactivation of TEs.

Our results suggest that each regenerated plant has distinct DNA methylation profiles despite coming from the same parent (Figure 5A–D). It therefore appears that the tissue culture step induces DNA hypomethylation in a rather stochastic manner affecting individual plants differently. We further show that descendants of regenerated plants stably maintain most hypomethylation across plant generations (Figure 2). Indeed, lines derived from the same original regenerated plant show very similar methylation profiles (Figure 1E; samples 4–8 and 11–12). It has long been proposed that changes in the epigenome may be a source of somaclonal variation (Thorpe, 2006; Rhee et al., 2010; Miguel and Marum, 2011; Neelakandan and Wang, 2012). Our genome-wide data support this notion since we show that stochastic hypomethylation in individual regenerants is associated with misregulated expression of certain genes. These epigenetic changes likely explain a component of somaclonal variation that has been observed for decades in a number of plant species.

In summary, our results suggest that use of tissue culture leaves behind an epigenetic footprint in regenerated plants that is stable over multiple generations and may partially explain somaclonal variation. Whereas the material used in this study were self-fertilized plants, a common practice in the development of agricultural biotechnology traits is to introgress new transgene loci into commercial genetic backgrounds, meaning that the plants used in agriculture are many generations removed from the initial regenerated plants (Bregitzer et al., 2008; Bennetzen and Hake, 2009; Johnson, 2009; Yang et al., 2012). The crosses utilized in these introgression schemes are likely to correct the vast majority of tissue culture-induced epigenetic changes.

1. 1. Stroud H
   2. Feng S
   3. Jacobsen SE
   4. Simon SA
   5. Meyers BC

   (2013) Plants regenerated from tissue culture contain stable epigenome changes in rice

   ID GSE42410. In the public domain at GEO: http://www.ncbi.nlm.nih.gov/geo/.

   http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE42410

1. 1. Becker C
   2. Hagmann J
   3. Muller J
   4. Koenig D
   5. Stegle O
   6. Borgwardt K

   et al. (2011) Spontaneous epigenetic variation in the Arabidopsis thaliana methylome

   Nature 480:245–249.

   https://doi.org/10.1038/nature10555

   • Google Scholar
2. 1. Bennetzen JLH
   2. Hake SC

   (2009)

   Handbook of Maize

   (Eds), Handbook of Maize, New York, Springer.

   • Google Scholar
3. 1. Berdasco M
   2. Alcazar R
   3. Garcia-Ortiz MV
   4. Ballestar E
   5. Fernandez AF
   6. Roldan-Arjona T

   et al. (2008) Promoter DNA hypermethylation and gene repression in undifferentiated Arabidopsis cells

   PLoS One 3:e3306.

   https://doi.org/10.1371/journal.pone.0003306

   • Google Scholar
4. 1. Bregitzer P
   2. Dahleen LS
   3. Neate S
   4. Schwarz P
   5. Manoharan M

   (2008) A single backcross is an effective tool for the elimination of agronomic and quality alterations caused by somaclonal variation in barley

   Crop Sci 48:471–479.

   https://doi.org/10.2135/cropsci2007.06.0370

   • Google Scholar
5. 1. Chen PY
   2. Cokus SJ
   3. Pellegrini M

   (2010) BS Seeker: precise mapping for bisulfite sequencing

   BMC Bioinformatics 11:203.

   https://doi.org/10.1186/1471-2105-11-203

   • Google Scholar
6. 1. Clough SJ
   2. Bent AF

   (1998) Floral dip: a simplified method for Agrobacterium-mediated transformation of Arabidopsis thaliana

   Plant J 16:735–743.

   https://doi.org/10.1046/j.1365-313x.1998.00343.x

   • Google Scholar
7. 1. Cokus SJ
   2. Feng S
   3. Zhang X
   4. Chen Z
   5. Merriman B
   6. Haudenschild CD

   et al. (2008) Shotgun bisulphite sequencing of the Arabidopsis genome reveals DNA methylation patterning

   Nature 452:215–219.

   https://doi.org/10.1038/nature06745

   • Google Scholar
8. 1. Feng S
   2. Cokus SJ
   3. Zhang X
   4. Chen PY
   5. Bostick M
   6. Goll MG

   et al. (2010) Conservation and divergence of methylation patterning in plants and animals

   Proc Natl Acad Sci USA 107:8689–8694.

   https://doi.org/10.1073/pnas.1002720107

   • Google Scholar
9. 1. Feng S
   2. Rubbi L
   3. Jacobsen SE
   4. Pellegrini M

   (2011) Determining DNA methylation profiles using sequencing

   Methods Mol Biol 733:223–238.

   https://doi.org/10.1007/978-1-61779-089-8_16

   • Google Scholar
10. Book

    1. Johnson GR
    2. McCuddin ZP

    (2009)

    Maize and biotech industry

    In: Bennetzen JLH, Hake SC, editors. Handbook of Maize. New York: Springer. pp. 115–140.

    • Google Scholar
11. 1. Kaeppler SM
    2. Kaeppler HF
    3. Rhee Y

    (2000) Epigenetic aspects of somaclonal variation in plants

    Plant Mol Biol 43:179–188.

    https://doi.org/10.1023/A:1006423110134

    • Google Scholar
12. 1. Kaeppler SM
    2. Phillips RL

    (1993) Tissue culture-induced DNA methylation variation in maize

    Proc Natl Acad Sci USA 90:8773–8776.

    https://doi.org/10.1073/pnas.90.19.8773

    • Google Scholar
13. 1. Langmead B
    2. Trapnell C
    3. Pop M
    4. Salzberg SL

    (2009) Ultrafast and memory-efficient alignment of short DNA sequences to the human genome

    Genome Biol 10:R25.

    https://doi.org/10.1186/gb-2009-10-3-r25

    • Google Scholar
14. 1. Law JA
    2. Jacobsen SE

    (2010) Establishing, maintaining and modifying DNA methylation patterns in plants and animals

    Nat Rev Genet 11:204–220.

    https://doi.org/10.1038/nrg2719

    • Google Scholar
15. 1. Lister R
    2. O'Malley RC
    3. Tonti-Filippini J
    4. Gregory BD
    5. Berry CC
    6. Millar AH

    et al. (2008) Highly integrated single-base resolution maps of the epigenome in Arabidopsis

    Cell 133:523–536.

    https://doi.org/10.1016/j.cell.2008.03.029

    • Google Scholar
16. 1. Miguel C
    2. Marum L

    (2011) An epigenetic view of plant cells cultured in vitro: somaclonal variation and beyond

    J Exp Bot 62:3713–3725.

    https://doi.org/10.1093/jxb/err155

    • Google Scholar
17. 1. Neelakandan AK
    2. Wang K

    (2012) Recent progress in the understanding of tissue culture-induced genome level changes in plants and potential applications

    Plant Cell Rep 31:597–620.

    https://doi.org/10.1007/s00299-011-1202-z

    • Google Scholar
18. 1. Rao AQ
    2. Bakhsh A
    3. Kiani S
    4. Shahzad K
    5. Shahid AA
    6. Husnain T

    et al. (2009) The myth of plant transformation

    Biotechnol Adv 27:753–763.

    https://doi.org/10.1016/j.biotechadv.2009.04.028

    • Google Scholar
19. 1. Rhee Y
    2. Sekhon RS
    3. Chopra S
    4. Kaeppler S

    (2010) Tissue culture-induced novel epialleles of a Myb transcription factor encoded by pericarp color1 in maize

    Genetics 186:843–855.

    https://doi.org/10.1534/genetics.110.117929

    • Google Scholar
20. 1. Schmitz RJ
    2. Schultz MD
    3. Lewsey MG
    4. O'Malley RC
    5. Urich MA
    6. Libiger O

    et al. (2011) Transgenerational epigenetic instability is a source of novel methylation variants

    Science 334:369–373.

    https://doi.org/10.1126/science.1212959

    • Google Scholar
21. 1. Stroud H
    2. Hale CJ
    3. Feng S
    4. Caro E
    5. Jacob Y
    6. Michaels SD

    et al. (2012) DNA methyltransferases are required to induce heterochromatic re-replication in Arabidopsis

    PLoS Genet 8:e1002808.

    https://doi.org/10.1371/journal.pgen.1002808

    • Google Scholar
22. 1. Tanurdzic M
    2. Vaughn MW
    3. Jiang H
    4. Lee TJ
    5. Slotkin RK
    6. Sosinski B

    et al. (2008) Epigenomic consequences of immortalized plant cell suspension culture

    PLoS Biol 6:2880–2895.

    https://doi.org/10.1371/journal.pbio.0060302

    • Google Scholar
23. 1. Thorpe TA

    (2006) History of plant tissue culture

    Methods Mol Biol 318:9–32.

    https://doi.org/10.1385/1-59259-959-1:009

    • Google Scholar
24. 1. Vega-Sanchez ME
    2. Zeng L
    3. Chen S
    4. Leung H
    5. Wang GL

    (2008) SPIN1, a K homology domain protein negatively regulated and ubiquitinated by the E3 ubiquitin ligase SPL11, is involved in flowering time control in rice

    Plant Cell 20:1456–1469.

    https://doi.org/10.1105/tpc.108.058610

    • Google Scholar
25. 1. Yang C
    2. Chen H
    3. Tang W
    4. Lin Y-J

    (2012)

    Effect of successive backcrossing on eliminating somaclonal variation caused by Agrobacterium-mediated transformation in rice

    Acta Agron Sin 38:814–819.

    • Google Scholar
26. 1. Zemach A
    2. McDaniel IE
    3. Silva P
    4. Zilberman D

    (2010) Genome-wide evolutionary analysis of eukaryotic DNA methylation

    Science 328:916–919.

    https://doi.org/10.1126/science.1186366

    • Google Scholar
27. 1. Zhou B
    2. Qu S
    3. Liu G
    4. Dolan M
    5. Sakai H
    6. Lu G

    et al. (2006) The eight amino-acid differences within three leucine-rich repeats between Pi2 and Piz-t resistance proteins determine the resistance specificity to Magnaporthe grisea

    Mol Plant Microbe Interact 19:1216–1228.

    https://doi.org/10.1094/MPMI-19-1216

    • Google Scholar

Author details

1. Hume Stroud

   Department of Molecular, Cell and Developmental Biology, University of California, Los Angeles, Los Angeles, United States

   Contribution

   HS, Conception and design, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article

   Competing interests

   No competing interests declared.

2. Bo Ding

   Department of Plant Pathology, Ohio State University, Columbus, United States

   Contribution

   BD, Contributed unpublished essential data or reagents

   Competing interests

   No competing interests declared.

3. Stacey A Simon

   Department of Plant and Soil Sciences, Delaware Biotechnology Institute, University of Delaware, Newark, United States

   Contribution

   SAS, Acquisition of data

   Competing interests

   No competing interests declared.

4. Suhua Feng

   1. Department of Molecular, Cell and Developmental Biology, University of California, Los Angeles, Los Angeles, United States
   2. Howard Hughes Medical Institute, University of California, Los Angeles, Los Angeles, United States

   Contribution

   SF, Acquisition of data

   Competing interests

   No competing interests declared.

5. Maria Bellizzi

   Department of Plant Pathology, Ohio State University, Columbus, United States

   Contribution

   MB, Contributed unpublished essential data or reagents

   Competing interests

   No competing interests declared.

6. Matteo Pellegrini

   Department of Molecular, Cell and Developmental Biology, University of California, Los Angeles, Los Angeles, United States

   Contribution

   MP, Conception and design

   Competing interests

   No competing interests declared.

7. Guo-Liang Wang

   Department of Plant Pathology, Ohio State University, Columbus, United States

   Contribution

   G-LW, Conception and design

   Competing interests

   No competing interests declared.

8. Blake C Meyers

   Department of Plant and Soil Sciences, Delaware Biotechnology Institute, University of Delaware, Newark, United States

   Contribution

   BCM, Conception and design

   Competing interests

   No competing interests declared.

9. Steven E Jacobsen

   1. Department of Molecular, Cell and Developmental Biology, University of California, Los Angeles, Los Angeles, United States
   2. Howard Hughes Medical Institute, University of California, Los Angeles, Los Angeles, United States

   Contribution

   SEJ, Conception and design, Drafting or revising the article

   For correspondence

   jacobsen@ucla.edu

   Competing interests

   SEJ: Serves on an epigenetics advisory board for Syngenta.

• 5,669

  views

• 1,277

  downloads

• 217

  citations

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