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Environmental and epigenetic regulation of Rider retrotransposons in tomato

  • Matthias Benoit ,

    Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

    benoit@cshl.edu

    Current address: Howard Hughes Medical Institute, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, United States of America

    Affiliation The Sainsbury Laboratory, University of Cambridge, Cambridge, United Kingdom

  • Hajk-Georg Drost,

    Roles Data curation, Formal analysis, Investigation, Resources, Software, Validation, Visualization, Writing – original draft, Writing – review & editing

    Affiliation The Sainsbury Laboratory, University of Cambridge, Cambridge, United Kingdom

  • Marco Catoni,

    Roles Data curation, Formal analysis, Investigation, Resources, Software, Validation, Visualization, Writing – original draft, Writing – review & editing

    Current address: School of Biosciences, University of Birmingham, Birmingham, United Kingdom

    Affiliation The Sainsbury Laboratory, University of Cambridge, Cambridge, United Kingdom

  • Quentin Gouil,

    Roles Resources, Writing – review & editing

    Current address: Walter and Eliza Hall Institute of Medical Research, 1G Royal Parade, Parkville 3052, Australia

    Affiliation Department of Plant Sciences, University of Cambridge, Cambridge, United Kingdom

  • Sara Lopez-Gomollon,

    Roles Resources, Writing – review & editing

    Affiliation Department of Plant Sciences, University of Cambridge, Cambridge, United Kingdom

  • David Baulcombe,

    Roles Resources, Writing – review & editing

    Affiliation Department of Plant Sciences, University of Cambridge, Cambridge, United Kingdom

  • Jerzy Paszkowski

    Roles Conceptualization, Funding acquisition, Methodology, Project administration, Supervision, Writing – original draft, Writing – review & editing

    Current address: Radachowka, Kolbiel, Poland

    Affiliation The Sainsbury Laboratory, University of Cambridge, Cambridge, United Kingdom

Environmental and epigenetic regulation of Rider retrotransposons in tomato

  • Matthias Benoit, 
  • Hajk-Georg Drost, 
  • Marco Catoni, 
  • Quentin Gouil, 
  • Sara Lopez-Gomollon, 
  • David Baulcombe, 
  • Jerzy Paszkowski
PLOS
x

Abstract

Transposable elements in crop plants are the powerful drivers of phenotypic variation that has been selected during domestication and breeding programs. In tomato, transpositions of the LTR (long terminal repeat) retrotransposon family Rider have contributed to various phenotypes of agronomical interest, such as fruit shape and colour. However, the mechanisms regulating Rider activity are largely unknown. We have developed a bioinformatics pipeline for the functional annotation of retrotransposons containing LTRs and defined all full-length Rider elements in the tomato genome. Subsequently, we showed that accumulation of Rider transcripts and transposition intermediates in the form of extrachromosomal DNA is triggered by drought stress and relies on abscisic acid signalling. We provide evidence that residual activity of Rider is controlled by epigenetic mechanisms involving siRNAs and the RNA-dependent DNA methylation pathway. Finally, we demonstrate the broad distribution of Rider-like elements in other plant species, including crops. Our work identifies Rider as an environment-responsive element and a potential source of genetic and epigenetic variation in plants.

Author summary

Transposons are major constituents of plant genomes and represent a powerful source of internal genetic and epigenetic variation. For example, domestication of maize has been facilitated by a dramatic change in plant architecture, the consequence of a transposition event. Insertion of transposons near genes often confers quantitative phenotypic variation linked to changes in transcriptional patterns, as documented for blood oranges and grapes. In tomato, the most widely grown fruit crop and model for fleshy fruit biology, occurrences of several beneficial traits related to fruit shape and plant architecture are due to the activity of the transposon family Rider. While Rider represents a unique endogenous source of genetic and epigenetic variation, mechanisms regulating Rider activity remain unexplored. By achieving experimentally-controlled activation of the Rider family, we shed light on the regulation of these transposons by drought stress, signalling by phytohormones, as well as epigenetic pathways. Furthermore, we reveal the presence of Rider-like elements in other economically important crops such as rapeseed, beetroot and quinoa. This suggests that drought-inducible Rider activation could be further harnessed to generate genetic and epigenetic variation for crop breeding, and highlights the potential of transposon-directed mutagenesis for crop improvement.

Introduction

Transposable elements (TEs) replicate and move within host genomes. Based on their mechanisms of transposition, TEs are either DNA transposons that use a cut-and-paste mechanism or retrotransposons that transpose through an RNA intermediate via a copy-and-paste mechanism [1]. TEs make up a significant part of eukaryotic chromosomes and are a major source of genetic instability that, when active, can induce deleterious mutations. Various mechanisms have evolved that protect plant genomes, including the suppression of TE transcription by epigenetic silencing that restricts TE movement and accumulation [25].

Chromosomal copies of transcriptionally silenced TEs are typically hypermethylated at cytosine residues and are associated with nucleosomes containing histone H3 di-methylated at lysine 9 (H3K9me2). In addition, they are targeted by 24-nt small interfering RNAs (24-nt siRNAs) that guide RNA-dependent DNA methylation (RdDM), forming a self-reinforcing silencing loop [68]. Interference with these mechanisms can result in the activation of transposons. For example, loss of DNA METHYLTRANSFERASE 1 (MET1), the main methyltransferase maintaining methylation of cytosines preceding guanines (CGs), results in the activation of various TE families in Arabidopsis [911] and in rice [12]. Mutation of CHROMOMETHYLASE 3 (CMT3), mediating DNA methylation outside CGs, triggers the mobilization of several TE families, including CACTA elements in Arabidopsis [10] and Tos17 and Tos19 in rice [13]. Interference with the activity of the chromatin remodelling factor DECREASE IN DNA METHYLATION 1 (DDM1), as well as various components of the RdDM pathway, leads to the activation of specific subsets of TEs in Arabidopsis. These include DNA elements CACTA and MULE, as well as retrotransposons ATGP3, COPIA13, COPIA21, VANDAL21, EVADÉ and DODGER [1417]. Similarly, loss of OsDDM1 genes in rice results in the transcriptional activation of TE-derived sequences [18].

In addition to interference with epigenetic silencing, TE activation can also be triggered by environmental stresses. In her pioneering studies, Barbara McClintock denoted TEs as “controlling elements”, thus suggesting that they are activated by genomic stresses and are able to regulate the activities of genes [19, 20]. In the meantime, a plethora of stress-induced TEs have been described, including retrotransposons. For example, the biotic stress-responsive Tnt1 and Tto1 families in tobacco [21,22], the cold-responsive Tcs family in citrus [23], the virus-induced Bs1 retrotransposon in maize [24], the heat-responsive retrotransposons Go-on in rice [25], and ONSEN in Arabidopsis [26,27]. While heat-stress is sufficient to trigger ONSEN transcription and the formation of extrachromosomal DNA (ecDNA), transposition was observed only after the loss of siRNAs, suggesting that the combination of impaired epigenetic control and environmental stress is a prerequisite for ONSEN transposition [28]. Studies have further shown that stress-responsive TEs can affect the expression of surrounding genes, by providing novel regulatory elements and, in some cases, conferring stress-responsiveness [2830].

The availability of high-quality genomic sequences revealed that LTR (Long Terminal Repeat) retrotransposons make up a significant proportion of plant chromosomes, from approximately 10% in Arabidopsis, 25% in rice, 42% in soybean, and up to 75% in maize [31]. In tomato (Solanum lycopersicum), a model crop plant for research on fruit development, LTR retrotransposons make up about 60% of the genome [32]. Despite the abundance of retrotransposons in the tomato genome, only a limited number of studies have linked TE activities causally to phenotypic alterations. Remarkably, the most striking examples described so far involve the retrotransposon family Rider. For example, fruit shape variation is based on copy number variation of the SUN gene, which underwent Rider-mediated trans-duplication from chromosome 10 to chromosome 7. The new insertion of the SUN gene into chromosome 7 in the variety “Sun1642” results in its overexpression and consequently in the elongated tomato fruits that were subsequently selected by breeders [33,34]. The Rider element generated an additional SUN locus on chromosome 7 that encompassed more than 20 kb of the ancestral SUN locus present on chromosome 10 [33]. This large “hybrid” retroelement landed in the fruit-expressed gene DEFL1, resulting in high and fruit-specific expression of the SUN gene containing the retroelement [34]. The transposition event was estimated to have occurred within the last 200–500 years, suggesting that duplication of the SUN gene occurred after tomato domestication [35].

Jointless pedicel is a further example of a Rider-induced tomato phenotype that has been selected during tomato breeding. This phenotypic alteration reduces fruit dropping and thus facilitates mechanical harvesting. Several independent jointless alleles were identified around 1960 [3638]. One of them involves a new insertion of Rider into the first intron of the SEPALLATA MADS-Box gene, Solyc12g038510, that provides an alternative transcription start site and results in an early nonsense mutation [39]. Also, the ancestral yellow flesh mutation in tomato is due to Rider-mediated disruption of the PSY1 gene, which encodes a fruit-specific phytoene synthase involved in carotenoid biosynthesis [40,41]. Similarly, the “potato leaf” mutation is due to a Rider insertion in the C locus controlling leaf complexity [42]. Rider retrotransposition is also the cause of the chlorotic tomato mutant fer, identified in the 1960s [43]. This phenotype has been linked to Rider-mediated disruption of the FER gene encoding a bHLH-transcription factor. Rider landed in the first exon of the gene [44,45]. Sequence analysis of the element revealed that the causative copy of Rider is identical to that involved in the SUN gene duplication [45].

The Rider family belongs to the Copia superfamily and is ubiquitous in the tomato genome [34,45]. Based on partial tomato genome sequences, the number of Rider copies was estimated to be approximately 2000 [34]. Previous DNA blots indicated that Rider is also present in wild tomato relatives but is absent from the genomes of potato, tobacco, and coffee, suggesting that amplification of Rider happened after the divergence of potato and tomato approximately 6.2 mya [45,46]. The presence of Rider in unrelated plant species has also been suggested [47]. However, incomplete sub-optimal sampling and the low quality of genomic sequence assemblies has hindered a comprehensive survey of Rider elements within the plant kingdom.

Considering that the Rider family is a major source of phenotypic variation in tomato, it is surprising that its members and their basic activities, as well as their responsiveness and the possible triggers of environmental super-activation, which explain the evolutionary success of this family, remain largely unknown. Contrary to the majority of TEs characterized to date, previous analyses revealed that Rider is constitutively transcribed and produces full-length transcripts in tomato [34], but the stimulatory conditions promoting reverse transcription of Rider transcripts that results in accumulation as extrachromosomal DNA are unknown.

To fill these gaps, we provide here a refined annotation of full-length Rider elements in tomato using the most recent genome release (SL3.0). We reveal environmental conditions facilitating Rider activation and show that Rider transcription is enhanced by dehydration stress mediated by abscisic acid (ABA) signalling, which also triggers accumulation of extrachromosomal DNA. Moreover, we provide evidence that RdDM controls Rider activity through siRNA production and partially through DNA methylation. Finally, we have performed a comprehensive cross-species comparison of full-length Rider elements in 110 plant genomes, including diverse tomato relatives and major crop plants, in order to characterise species-specific Rider features in the plant kingdom. Together, our findings suggest that Rider is a drought stress-induced retrotransposon ubiquitous in diverse plant species that may have contributed to phenotypic variation through the generation of genetic and epigenetic alterations induced by historical drought periods.

Results

Family structure of Rider retrotransposons in tomato

We used the most recent SL3.0 tomato genome release for de novo annotation of Rider elements. First, we retrieved full-length, potentially autonomous retrotransposons using our functional annotation pipeline (LTRpred, see Materials and Methods). We detected a set of 5844 potentially intact LTR retrotransposons (S1 Table). Homology search among these elements identified 71 elements that share >85% sequence similarity over the entire element with the reference Rider sequence [45] and thus belong to the Rider family. We then determined the distribution of these Rider elements along the tomato chromosomes (Fig 1A) and also estimated their age based on sequence divergence between 5’ and 3’ LTRs (Fig 1A). We classified these elements into three categories according to their LTR similarity: 80–95%, 95–98% and 98–100% (S1A Fig). While the first category contains relatively old copies (last transposition between 10.5 and 3.5 mya), the 95–98% class represents Rider elements that moved between 3.5 and 1.4 mya, and the 98–100% category includes the youngest Rider copies that transposed within the last 1.4 my (S1A Fig). Out of 71 Rider family members, 14 were found in euchromatic chromosome arms (14/71 or 19.7%) and 57 in heterochromatic regions (80.3%) (Table 1). In accordance with previous observations based on partial genomic sequences [34], young Rider elements of the 98–100% class are more likely to reside in the proximity of genes, with 50% within 2 kb of a gene. This was the case for only 37.5% of old Rider members (85–95% class) (Table 2). Such a distribution is consistent with the preferential presence of young elements within euchromatic chromosome arms (50%, 5/10) compared to old Rider elements (9.4%, 3/32) (Table 2 and S1B Fig). In addition, the phylogenetic distance between individual elements is moderately correlated to the age of each element (Fig 1B) (S2 Table).

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Fig 1. Chromosomal location and phylogenetic relationships of de novo annotated full-length Rider elements.

(A) Chromosomal positions of 71 de novo annotated full-length Rider elements in the SL3.0 genome. Rider copies are marked as coloured vertical bars, with colours reflecting similarity between LTRs for each element. Dark grey areas delimitate the centromeres, light grey pericentromeric heterochromatin, and white euchromatin. (B) Phylogenetic relationship of the 71 de novo annotated Rider elements. The phylogenetic tree was constructed using the neighbour-joining method on nucleotide sequences of each Rider copy.

https://doi.org/10.1371/journal.pgen.1008370.g001

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Table 1. Distribution of de novo annotated Rider elements based on chromatin context.

https://doi.org/10.1371/journal.pgen.1008370.t001

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Table 2. Distribution of de novo annotated Rider elements based on gene proximity.

https://doi.org/10.1371/journal.pgen.1008370.t002

Rider is a drought- and ABA-responsive retrotransposon

To better understand the activation triggers and, thus, the mechanisms involved in the accumulation of Rider elements in the tomato genome, we examined possible environmental stresses and host regulatory mechanisms influencing their activity. Transcription of an LTR retroelement initiates in its 5’ LTR and is regulated by an adjacent promoter region that usually contains cis-regulatory elements (CREs) (reviewed in [48]). Therefore, we aligned the sequence of the Rider promoter region against sequences stored in the PLACE database (www.dna.affrc.go.jp/PLACE/) containing known CREs and identified several dehydration-responsive elements (DREs) and sequence motifs linked to ABA signalling (Fig 2A). First, we tested whether these CREs were present in the LTR promoter sequences of the 71 de novo annotated Rider elements (S3 Table). Comparison of Rider LTRs to a set of gene promoter sequences of the same length revealed significant enrichment of several CREs in Rider LTRs (Fisher’s exact test P<0.001) (S4 Table). It is known, for example, that the CGCG sequence motif at position 89–94 (Fig 2A) is recognized by transcriptional regulators binding calmodulin. These are products of signal-responsive genes activated by various environmental stresses and phytohormones such as ABA [49]. We also detected two MYB recognition sequence motifs (CTGTTG at position 176–181 bp, and CTGTTA at position 204–209 bp) (Fig 2A). MYB recognition sequences are usually enriched in the promoters of genes with transcriptional activation during water stress, elevated salinity, and ABA treatments [50,51]. In addition, an ABA-responsive element-like (ABRE-like) was found at position 332–337 bp in the R region of Rider’s LTR, along with a coupling element (CE3) located at position 357–372 bp (Fig 2A). The co-occurrence of ABRE-like and CE3 has often been found in ABA-responsive genes [52,53].

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Fig 2. Rider activation is stimulated by drought and ABA.

(A) Identification of cis-regulatory elements (CREs) within Rider LTRs. Rider LTR U3, R and U5 regions are marked, as well as neighbouring Target Site Duplication (TSD) and Primer Binding Site (PBS) sequences. CREs are marked as coloured vertical bars; their bp positions are given in brackets. (B-C) Quantification of Rider RNA levels by RT-qPCR in tomato seedlings after (B) drought stress or (C) mannitol and NaCl treatments. Bar charts show normalized expression relative to Control, +/- SEM from two to three biological replicates. *P<0.05, two-sided Student’s t-test. (D) Quantification of Rider RNA levels by RT-qPCR in leaves of drought-stressed tomato wild-type plants, flc, not and sit mutants. Bar charts show normalized expression relative to WT Control, +/- SEM from two to three biological replicates. *P<0.05 denotes difference compared to wild-type control; # P<0.05 denotes difference compared to wild-type drought plants, two-sided Student’s t-test. (E) Quantification of Rider RNA levels by RT-qPCR in tomato seedlings after ABA treatment. Bar charts show normalized expression relative to Control, +/- SEM from two to three biological replicates. *P<0.05, ***P<0.001, two-sided Student’s t-test.

https://doi.org/10.1371/journal.pgen.1008370.g002

The simultaneous presence of these five CREs in promoters of Rider elements suggests that Rider transcription may be induced by environmental stresses such as dehydration and salinity that involves ABA mediated signalling. To test whether Rider transcription is stimulated by drought stress, glasshouse-grown tomato plants were subjected to water deprivation and levels of Rider transcripts quantified by RT-qPCR (Fig 2B). When compared to control plants, we observed a 4.4-fold increase in Rider transcript abundance in plants subjected to drought stress. Thus, Rider transcription appears to be stimulated by drought.

To further test this finding, we re-measured levels of Rider transcripts in different experimental setups. In vitro culture conditions with increasing levels of osmotic stress were used to mimic increasing drought severity (Fig 2C). Transcript levels of Rider increased in a dose-dependent fashion with increasing mannitol concentration, corroborating results obtained during direct drought stress in greenhouse conditions. Interestingly, tomato seedlings treated with NaCl also exhibited increased levels of Rider transcripts (Fig 2C).

ABA is a versatile phytohormone involved in plant development and abiotic stress responses, including drought stress [54]. Therefore, we asked whether Rider transcriptional drought-responsiveness is mediated by ABA and whether increased ABA can directly stimulate Rider transcript accumulation. To answer the first question, we exploited tomato mutants defective in ABA biosynthesis. The lines flacca (flc), notabilis (not) and sitiens (sit) have mutations in genes encoding a sulphurylase [55], a 9-cis-epoxy-carotenoid dioxygenase (SlNCED1) [56,57], and an aldehyde oxidase [58], respectively. Both flc and sit are impaired in the conversion of ABA-aldehyde to ABA [55,58], while not is unable to catalyse the cleavage of 9-cis-violaxanthin and/or 9-cis-neoxanthin to xanthoxin, an ABA precursor [57]. Glasshouse-grown flc, not and sit mutants and control wild-type plants were subjected to water deprivation treatment and Rider transcript levels quantified by RT-qPCR (Fig 2D). Rider transcript levels were reduced in flc, not and sit by 43%, 26% and 56%, respectively.

To examine whether ABA stimulates accumulation of Rider transcripts, tomato seedlings were transferred to media supplemented with increasing concentrations of ABA (Fig 2E). The levels of Rider transcripts increased in a dose-dependent manner with increasing ABA concentrations. This suggests that ABA is not only involved in signalling that results in hyper-activation of Rider transcription during drought, but it also directly promotes the accumulation of Rider transcripts. The effectiveness of the treatments was verified by assaying expression of the stress- and ABA-responsive gene SlASR1 (S2A–S2F Fig).

Identification in the U3 region of Rider LTRs of a binding domain for C-repeat binding factors (CBF), which are regulators of the cold-induced transcriptional cascade [52,59], led us to test Rider activation by cold stress. However, Rider transcription was not affected by cold treatment, leaving drought and salinity as the predominant environmental stresses identified so far that stimulate accumulation of Rider transcripts (S2G Fig).

RdDM regulates levels of Rider transcripts

The suppression of transposon-derived transcription by epigenetic mechanisms, which typically include DNA methylation, maintains genome integrity [2,3,5]. We asked whether Rider transcription is also restricted by DNA methylation. Tomato seedlings were grown on media supplemented with 5-azacytidine, an inhibitor of DNA methyltransferases. Rider transcript steady-state levels increased in plants treated with 5-azacytidine compared to controls (Fig 3A). Comparison of Rider transcript accumulation in 5-azacytidine-treated and ABA-treated plants revealed similar levels of transcripts and the levels were similar when the treatments were applied together (P <0.05; Fig 3A).

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Fig 3. Accumulation of Rider transcripts in tomato plants deficient in epigenetic regulation.

(A) Quantification of Rider RNA levels by RT-qPCR in tomato seedlings treated with 5-azacytidine and/or ABA. Bar charts show normalized expression relative to Control, +/- SEM from two to three biological replicates. *P<0.05, two-sided Student’s t-test. (B) Abundance of siRNAs at Rider elements in wild type, slnrpd1 and slnrpe1. Data are expressed as siRNA reads per kb per million mapped reads and represent average normalized siRNA counts on Rider elements +/- SD from 71 de novo annotated Rider copies. ***P<0.001, two-sided Student’s t-test. (C) Quantification of Rider RNA by RT-qPCR in slnrpd1 and slnrpe1. Bar charts show normalized expression relative to WT, +/- SEM from two to four biological replicates. *P<0.05, two-sided Student’s t-test.

https://doi.org/10.1371/journal.pgen.1008370.g003

To further examine the role of DNA methylation in controlling Rider transcription, we took advantage of tomato mutants defective in crucial components of the RdDM pathway, namely SlNRPD1 and SlNRPE1, the major subunits of RNA Pol IV and Pol V, respectively. These mutants exhibit reduced cytosine methylation at CHG and CHH sites (in which H is any base other than G) residing mostly at the chromosome arms, with slnrpd1 showing a dramatic, genome-wide loss of 24-nt siRNAs [60]. To evaluate the role of RdDM in Rider transcript accumulation, we first assessed the consequences of impaired RdDM on siRNA populations at full-length Rider elements. Deficiency in SlNRPD1 resulted in a complete loss of 24-nt siRNAs that target Rider elements (Fig 3B). This loss was accompanied by a dramatic increase (approximately 80-fold) in 21-22-nt siRNAs at Rider loci (Fig 3B). In contrast, the mutation in SlNRPE1 triggered increases in both 21-22-nt and 24-nt siRNAs targeting Rider elements (Fig 3B). We then asked whether altered distribution of these siRNA classes is related to the age of the Rider elements and/or their chromosomal position, and thus local chromatin properties. Compilation of the genomic positions and siRNA data in RdDM mutants didn’t reveal preferential accumulation of 21-22-nt siRNAs (S3A Fig) or 24-nt siRNAs (S3B Fig) over specific Rider classes. Subsequently, we examined whether loss of SlNRPD1 or SlNRPE1 was sufficient to increase levels of Rider transcripts and observed increased accumulation of Rider transcripts in both slnrpd1 and slnrpe1 compared to WT (Fig 3C).

We assessed whether this increase in Rider transcript levels is linked to changes in DNA methylation levels in Rider elements of RdDM mutants. There was no significant change in global DNA methylation in the three sequence contexts in the 71 de novo annotated Rider elements (S3C Fig), despite a tendency for young Rider elements to lose CHH in slnrpd1 and slnrpe1 (S3D Fig). Thus, the RdDM pathway affects the levels of Rider transcripts. Also, features of Rider copies such as age and chromatin location alone cannot predict potential for activation based on DNA methylation levels.

Extrachromosomal circular DNA of Rider accumulates during drought stress and in slnrpd1 and slnrpe1 mutants

The life cycle of LTR retrotransposons starts with transcription of the element, then the synthesis and maturation of accessory proteins including reverse transcriptase and integrase, reverse transcription, and the production of extrachromosomal linear (ecl) DNA that integrates into a new genomic location [61]. In addition, eclDNA can be a target of DNA repair and can be circularised by a non-homologous end-joining mechanism or homologous recombination between LTRs, resulting in extrachromosomal circular DNA (eccDNA) [6265]. We searched for eccDNA to evaluate the consequences of increased Rider transcript accumulation due to drought stress or an impaired RdDM pathway on subsequent steps of the transposition cycle. After exonuclease-mediated elimination of linear dsDNA and circular ssDNA, Rider eccDNA was amplified by sequence-specific inverse PCR (Fig 4A). Rider eccDNA was absent in plants grown in control conditions but was detected in plants subjected to drought stress (Fig 4A). Sanger sequencing of the inverse PCR products showed that the amplified eccDNA probably originates from the Rider_08_3 copy, which has 98.2% sequence homology of the 5’ and 3’ LTR sequences (S4A Fig). Residual sequence divergence may be due to genotypic differences between the reference genomic sequence and the genome of our experimental material. Analysis of CREs in the LTR of the eccDNA revealed the presence of all elements identified previously with the exception of a single nucleotide mutation located in the CGCGBOXAT box (S4A Fig).

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Fig 4. Accumulation of Rider extrachromosomal DNA in drought-stressed plants and in slnrpd1 and slnrpe1 mutants.

(A) Assay by inverse PCR of Rider extrachromosomal circular DNA in drought-stressed wild-type plants and stressed sit mutants. Primer localization shown on the left (grey bar: Rider element, black box: LTR, arrowheads: PCR primers). Upper gel: specific PCR amplification of Rider circles after DNase treatment, lower gel: control PCR for Rider detection without DNase treatment. (B) Quantification of Rider DNA copy number, including both chromosomal and extrachromosomal copies, by qPCR in leaves of tomato plants subjected to drought-stress. Bar charts show normalized expression +/- SEM from two to three biological replicates. *P<0.05, two-sided Student’s t-test. (C) Assay by inverse PCR of Rider extrachromosomal circular DNA in slnrpd1 and slnrpe1 leaves. Upper gel: PCR amplification of Rider circles after DNase treatment, lower gel: control PCR for Rider detection without DNase treatment. (D) Quantification of Rider DNA copy number, including both chromosomal and extrachromosomal copies, by qPCR in slnrpd1 and slnrpe1 leaves. Bar charts show normalized expression +/- SEM from two to four biological replicates. *P<0.05, two-sided Student’s t-test. (E) Quantification of CHH DNA methylation levels at Rider_08_3 and Rider_07_2 in wild type, slnrpd1 and slnrpe1. Levels expressed as % of methylated CHH sites. (F) Normalized siRNA count of 21-22-nt and 24-nt siRNAs at Rider_08_3 and Rider_07_2 in wild type, slnrpd1 and slnrpe1. Data are expressed as siRNA reads per kb per million mapped reads.

https://doi.org/10.1371/journal.pgen.1008370.g004

Examination by quantitative PCR of the accumulation of Rider DNA, which included extrachromosomal and genomic copies, in drought-stressed plants also revealed an increase in Rider copy number due to eccDNA (Fig 4B). Importantly, Rider eccDNA was not detected in sit mutants subjected to drought stress (Fig 4A), suggesting that induced transcription of Rider by drought stress triggers production of extrachromosomal DNA and this response requires ABA biosynthesis.

We also examined the accumulation of Rider eccDNA in plants impaired in RdDM. Interestingly, Rider eccDNA was detected in slnrpd1 and slnrpe1 (Fig 4C) and increase in Rider DNA copy number due to eccDNA accumulation was confirmed by qPCR (Fig 4D). Absence of newly integrated genomic copies has been further validated by genome sequencing. The eccDNA forms differed between the mutants (Fig 4C). Sequencing of Rider eccDNA in slnrpd1 showed a sequence identical to the Rider eccDNA of wild-type plants subjected to drought stress. Thus, the Rider_08_3 copy is probably the main contributor to eccDNA in drought and in slnrpd1. In contrast, eccDNA recovered from slnrpe1 had a shorter LTR (287 bp) and the highest sequence similarity with Rider_07_2 (89.2%) (S4B Fig). Shortening of the LTR in this particular element results in the loss of the upstream MYBCORE as well as the CGCGBOXAT elements (S4B Fig).

We then asked whether DNA methylation and siRNA distribution at these particular Rider copies had changed in the mutants. DNA methylation at CHH sites, but not CG nor CHG, was drastically reduced at Rider_08_3 in slnrpd1 (Fig 4E, S4C–S4E Fig and S5A Fig) together with a complete loss of 24-nt siRNAs at this locus (Fig 4F and S4F Fig) but DNA methylation at Rider_07_2 was not affected, despite the deficiency of SlNRPD1 or SlNRPE1 (Fig 4E, S4C–S4E Fig and S5B Fig). Levels of 21-22-nt siRNAs in both mutants and 24-nt siRNA in slnrpe1 were increased (Fig 4F and S4F and S4G Fig). Altogether, this suggests that RdDM activity on Rider is highly copy-specific and that different components of the RdDM pathway differ in their effects on Rider silencing.

Rider families in other plant species

To examine the distribution of Rider retrotransposons in other plant species, we searched for Rider-related sequences across the genomes of further Solanaceae species, including wild tomatoes, potato (Solanum tuberosum), and pepper (Capsicum annuum). We used the Rider reference sequence [45] as the query against genome sequences of Solanum arcanum, S. habrochaites, S. lycopersicum, S. pennellii, S. pimpinellifolium, S. tuberosum, and Capsicum annuum (genome versions are listed in Materials and Methods). Two BLAST searches were performed, one using the entire Rider sequence as the query and the other using only the Rider LTR. Consistent with previous reports, Rider-like elements are present in wild relatives of tomato such as S. arcanum, S. pennellii and S. habrochaites; however, the homology levels and their lengths vary significantly between species (Fig 5A). While S. arcanum and S. habrochaites exhibit high peak densities at 55% and 61% homology, respectively, S. pennellii show a high peak density at 98% over the entire Rider reference sequence (Fig 5A). This suggests that the S. arcanum and S. habrochaites genomes harbour mostly Rider-like elements with relatively low sequence similarity, while S. pennellii retains full-length Rider elements.

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Fig 5. Distribution of Rider in other Solanaceae species.

(A) In silico identification of Rider elements in Solanaceae species based on the density of high homology BLAST hits over the full-length reference Rider sequence. (B) Alignment length of high homology BLAST hits obtained in (A). (C) In silico identification of Rider elements in Solanaceae species based on the density of high homology BLAST hits over the reference Rider LTR sequence. (D) Alignment length of high homology BLAST hits obtained in (C). Left panels (A) and (C): phylogenetic trees of the species examined.

https://doi.org/10.1371/journal.pgen.1008370.g005

To better visualize this situation, we aligned the BLAST hits to the reference Rider copy (Fig 5B). This confirmed that Rider elements in S. pennellii are indeed mostly full-length Rider homologs showing high density of hits throughout their lengths, while BLAST hits in the S. arcanum and S. habrochaites genomes showed only partial matches over the 4867 bp of the reference Rider sequence (Fig 5B). Unexpectedly, this approach failed to detect either full-length or truncated Rider homologs in the close relative of tomato, S. pimpinellifolium. Extension of the same approaches to the genomes of the evolutionary more distant S. tuberosum and Capsicum annuum failed to detect substantial Rider homologs (Fig 5A and 5B), confirming the absence of Rider in the potato and pepper genomes [45]. As a control, we also analysed Arabidopsis thaliana, since previous studies reported the presence of Rider homologs in this model plant [45]. Using the BLAST approach above, we repeated the results provided in [45] and found BLAST hits of high sequence homology to internal sequences of Rider in the Arabidopsis thaliana genome. However, we did not detect sequence homologies to Rider LTRs (Fig 5C and 5D). Motivated by this finding and the possibility that Rider homologs in other species may have highly divergent LTRs, we screened for Rider LTRs that would have been missed in the analysis shown in Fig 5A and 5B due to the use of the full-length sequence of Rider as the query. Using the Rider LTR as a query revealed that S. pennellii, S. arcanum and S. habrochaites retain intact Rider LTR homologs, but S. pimpinellifolium exhibits a high BLAST hit density exclusively at approximately 60% homology. This suggests strong divergence of Rider LTRs in this species (Fig 5C and 5D). Overall, the results indicate intact Rider homologs in some Solanaceae species, whereas sequence similarities to Rider occur only within the coding area of the retrotransposons in more distant plants such as Arabidopsis thaliana. Therefore, LTRs, which include the cis-regulatory elements conferring stress-responsiveness, diverge markedly between species. Finally, we performed a reciprocal BLAST against tomato using Rider-like hits from all other species having sequence similarity over the entire element between 50% - 84% and confirmed that all Rider loci in tomato were among the top reciprocal BLAST hits.

To address the specificity of this divergence in Solanaceae species, we examined whether the CREs enriched in S. lycopersicum (Fig 2A) are present in LTR sequences of the Rider elements in S. pennellii, S. arcanum, S. habrochaites and S. pimpinellifolium (Fig 5C). While the LTRs identified in S. pennellii, S. arcanum and S. habrochaites retained all five previously identified CREs, more distant LTRs showed shortening of the U3 region associated with loss of the CGCG box (S6 Fig and S5 Table). This was observed already in S. pimpinellifolium, where all identified Rider LTRs lacked part of the U3 region containing the CGCG box (S6 Fig). Thus, Rider distribution and associated features differ even between closely related Solanaceae species, correlated with the occurrence of a truncated U3 region and family-wide loss of CREs.

Finally, to test the evolutionary conservation of Rider elements across the plant kingdom, we performed Rider BLAST searches against all 110 plant genomes available at the NCBI Reference Sequence (RefSeq) database (www.ncbi.nlm.nih.gov/refseq). Using the entire Rider sequence as the query to measure the abundance of Rider homologs throughout these genomes, we found Rider homologs in 14 diverse plant species (S7 Fig). The limited conservation of Rider LTR sequences in the same 14 species, revealed using the LTR sequence as the query, suggests that Rider LTRs are highly polymorphic and that drought-responsive CREs may nevertheless be restricted to Solanaceae (S8 Fig).

Discussion

High-resolution map of full-length Rider elements in the tomato genome

Comprehensive analysis of individual LTR retrotransposon families in complex plant genomes has been facilitated and become more accurate with the increasing availability of high-quality genome assemblies. Here, we took advantage of the most recent tomato genome release (SL3.0) to characterize with improved resolution the high-copy-number Rider retrotransposon family. Although Rider activity has been causally linked to the emergence of important agronomic phenotypes in tomato, the triggers of Rider have remained elusive. Despite the relatively low proportion (approximately 20%) of euchromatic chromosomal regions in the tomato genome [32]), our de novo functional annotation of full-length Rider elements revealed preferential compartmentalization of recent Rider insertions within euchromatin compared to aged insertions. Mapping analyses further revealed that recent rather than aged Rider transposition events are more likely to modify the close vicinity of genes. However, Rider copies inserted into heterochromatin have been passively maintained for longer periods. This differs significantly from other retrotransposon families in tomato such as Tnt1, ToRTL1 and T135, which show initial, preferential insertions into heterochromatic regions [66]. TARE1, a high-copy-number Copia-like element, is present predominantly in pericentromeric heterochromatin [67]. Another high-copy-number retrotransposon, Jinling, is also enriched in heterochromatic regions, making up about 2.5% of the tomato nuclear genome [68]. The Rider propensity to insert into gene-rich areas mirrors the insertional preferences of the ONSEN family in Arabidopsis. Since new ONSEN insertions confer heat-responsiveness to neighbouring genes [28,69], it is tempting to speculate that genes in the vicinity of new Rider insertions may acquire, at least transiently, drought-responsiveness.

Environmental and epigenetic regulation of Rider activity

We found that Rider transcript levels are elevated during dehydration stress mediated by ABA-dependent signalling. The activation of retrotransposons upon environmental cues has been shown extensively to rely on the presence of cis-regulatory elements within the retrotransposon LTRs [48]. The heat-responsiveness of ONSEN in Arabidopsis [26,27,70], Go-on in rice [25], and Copia in Drosophila [71] is conferred by the presence in their LTRs of consensus sequences found in the promoters of heat-shock responsive genes. Thus, the host’s heat-stress signalling appears to induce transcriptional activation of the transposon and promote transposition [70]. While ONSEN and Go-on are transcriptionally inert in the absence of a triggering stress, transcripts of Drosophila Copia are found in control conditions, resembling the regulatory situation in Rider. Due to relatively high constitutive expression, increase in transcript levels of Drosophila Copia following stress appears modest compared to ONSEN or Go-on, which are virtually silent in control conditions [2527,70]. Regulation of Drosophila Copia mirrors that of Rider, where transcript levels during dehydration stress are very high but the relative increase compared to control conditions is rather modest.

The presence of MYB recognition sequences within Rider LTRs suggests that MYB transcription factors participate in transcriptional activation of Rider during dehydration. Multiple MYB subfamilies are involved in ABA-dependent stress responses in tomato, but strong enrichment of the MYB core element CTGTTA within Rider LTRs suggests involvement of R2R3-MYB transcription factors, which are markedly amplified in Solanaceae [72]. Members of this MYB subfamily are involved in the ABA signalling-mediated drought-stress response [73] and salt-stress signalling [74]. This possible involvement of R2R3-MYBs in Rider is reminiscent of the transcriptional activation of the tobacco retrotransposon Tto1 by the R2R3-MYB, member NtMYB2 [75]. Drought-responsiveness has been observed for Rider_08_3 only, despite other individual Rider copies displaying intact MYB core element (S3 Table). This suggests that presence of this CRE is not the only feature required for drought-responsiveness, and other factors, such as genomic location, influence Rider activity. Indeed, Rider_08_3 is located within a gene-rich area, with low TE content that might facilitate its activation. This is strikingly different from Rider_07_2 that is nested in a TE-rich area and isolated from genes (S6 Table).

In addition to environmental triggers, Rider transcript levels are regulated by the RdDM pathway. Depletion of SlNRPD1 and SlNRPE1 increases Rider transcript abundance, resulting in production of extrachromosomal circular DNA. Analysis of Rider-specific siRNA populations revealed that siRNA targeting of Rider elements is mostly independent of their chromatin context. This is somewhat unexpected since RdDM activity in tomato seems to be restricted to gene-rich euchromatin and it was postulated that accessibility of RNA Pol IV to heterochromatin is hindered by the compact chromatin structure [60,76,77]. We identified Rider copies targeted by RdDM, which potentially influences local epigenetic features. Loss of SlNRPD1 and SlNRPE1 leads to over-accumulation of 21-22-nt siRNAs at Rider copies, suggesting that inactivation of canonical RdDM pathway-dependent transcriptional gene silencing triggers the activity of the non-canonical RDR6 RdDM pathway at Rider [7880].

It is noteworthy that, despite clear effects on Rider transcript accumulation and siRNA accumulation, loss of SlNRPD1 and SlNRPE1 is not manifested by drastic changes in total DNA methylation levels of Rider at the family level. This is in accordance with the modest decrease in genome-wide CHH and CHG methylation described in tomato RdDM mutants, with most of the changes happening on the euchromatic arms while the pericentromeric heterochromatin is unaffected [60]. Distribution of the 71 intact Rider elements in both euchromatic and heterochromatic compartments thus likely hampers detection of major changes DNA methylation over the Rider family. Only young euchromatic Rider elements marginally lose CHH methylation in the slnrpd1 mutant, but this is modest compared to the general decrease in mCHH observed throughout the chromosome arms [60]. As expected, CHH methylation at heterochromatic Rider is not affected. This suggests that SlCMT2 is involved in maintenance of mCHH at heterochromatic Rider copies in the absence of SlNRPD1, as observed previously for pericentromeric heterochromatin [60]. In general, our observations suggest that epigenetic silencing of Rider retrotransposons is particularly robust and involves compensatory pathways.

We identified extrachromosomal circular DNA originating from the Rider copies Rider_08_3 and Rider_07_2 in slnrpd1 and slnrpe1, respectively. In terms of DNA methylation and siRNA distribution at these two specific copies, loss of SlNRPD1 and SlNRPE1 brought different copy-specific outcomes. Rider_08_3, the main contributor to eccDNA in slnrpd1, displayed a reduction in CHH methylation that may contribute to increased transcription and the accumulation of eccDNA. In Rider_07_2, that provides a template for eccDNA in slnrpe1, there was no change in DNA methylation levels. Therefore, transcription and the production of eccDNA from this Rider copy is not regulated by DNA methylation. Consequently, eccDNA from Rider_07_2 was not detected in slnrpd1 despite drastic loss of CHH methylation.

Despite our efforts, we were unable to apply either drought or ABA treatment to the slnrpd1 and slnrpe1 mutants. In contrast to Arabidopsis [81,82], RdDM mutants in tomato are showing severe developmental defects and are sterile [60]. They are particularly difficult to maintain even in optimal growth conditions, precluding the application of stress treatments. Altogether, it appears that transcriptional control and reverse transcription of Rider copies occurs via multiple layers of regulation, possibly specific for individual Rider elements according to age, sequence and genomic location, that are targeted by parallel silencing pathways, including non-canonical RdDM [83,84].

Rider retrotransposons in other plant species

The presence of Rider in tomato relatives as well as in more distantly related plant species has been described previously [34,45,47]. However, the de novo identification of Rider elements in the sampling provided here shows the distribution of the Rider family within plant species to be more complex than initially suggested. Surprisingly, mining for sequences with high similarity, overlapping more than 85% of the entire reference sequence of Rider, detected no full-length Rider elements in Solanum pimpinellifolium but in all other wild tomato species tested. Furthermore, the significant accumulation of only partial Rider copies in Solanum pimpinellifolium, the closest relative of tomato, does not match the established phylogeny of the Solanaceae. The cause of these patterns is unresolved but two scenarios can be envisaged. First, the absence of full-length Rider elements may be due to the suboptimal quality of genome assembly that may exclude a significant proportion of highly repetitive sequences such as Rider. This is supported by the N50 values within the Solanaceae, where the quality of genome assemblies varies significantly between species, with S. pimpinellifolium showing the lowest (S7 Table). An improved genome assembly would allow a refined analysis of Rider in this species. Alternatively, active Rider copies may have been lost in S. pimpinellifolium since the separation from the last common ancestor but not in the S. lycopersicum and S. pennellii lineages. The high-density of solo-LTRs and truncated elements in S. pimpinellifolium is in agreement with this hypothesis.

Comparing the sequences of Rider LTRs in the five tomato species, the unique occurrence of LTRs lacking most of the U3 region in S. pimpinellifolium suggests that loss of important regulatory sequences has impeded maintenance of intact Rider elements. Interestingly, part of the U3 region missing in S. pimpinellifolium contains the CGCG box, which is involved in response to environmental signals [49], as well as a short CpG-island-like structure (position 52–155 bp on reference Rider). CpG islands are usually enriched 5’ of transcriptionally active genes in vertebrates [85] and plants [86]. Despite the presence of truncated Rider LTRs, the occurrence of intact, full-length LTRs in other wild tomato species indicates that Rider is still potentially active in these genomes.

Altogether, our findings suggest that inter- and intra-species TE distribution can be uncoupled and that the evolution of TE families in present crop plants was more complex than initially anticipated. We have further opened interesting perspectives for harnessing transposon activities in crop breeding. Potentially active TE families that react to environmental stimuli, such as Rider, provide an unprecedented opportunity to generate genetic and epigenetic variation from which desirable agronomical traits may emerge. Notably, rewiring of gene expression networks regulating the drought-stress responses of new Rider insertions is an interesting strategy to engineer drought-resilient crops.

Materials and methods

Plant material and growth conditions

Tomato plants were grown under standard greenhouse conditions (16 h at 25°C with supplemental lighting of 88 w/m2 and 8 h at 15°C without). flacca (flc), notabilis (not), and sitiens (sit) seeds (cv. Ailsa Craig) were obtained from Andrew Thompson, Cranfield University; the slnrpd1 and slnrpe1 plants (cv. M82) were described before [60]. For aseptic growth, seeds of Solanum lycopersicum were surface-sterilized in 20% bleach for 10 min, rinsed three times with sterile H2O, germinated and grown on half-strength MS media (16 h light and 8 h dark at 24°C).

Stress treatments

For dehydration stress, two-week-old greenhouse-grown plants were subjected to water deprivation for two weeks. For NaCl and mannitol treatments, tomato seedlings were grown aseptically for two weeks prior to transfer into half-strength MS solution containing 100, 200 or 300 nM NaCl or mannitol (Sigma) for 24 h. For abscisic acid (ABA) treatments, tomato seedlings were grown aseptically for two weeks prior to transfer into half-strength MS solution containing 0.5, 5, 10 or 100 μM ABA (Sigma) for 24 h. For 5-azacytidine treatments, tomato seedlings were germinated and grown aseptically on half-strength MS media containing 50 nM 5-azacytidine (Sigma) for two weeks. For cold stress experiments, two-week-old aseptically grown plants were transferred to 4°C for 24 h prior to sampling.

RNA extraction and quantitative RT-PCR analysis

Total RNA was extracted from 200 mg quick-frozen tissue using the TRI Reagent (Sigma) according to the manufacturer’s instructions and resuspended in 50 μL H2O. The RNA concentration was estimated using the Qubit Fluorometric Quantitation system (Thermo Fisher). cDNAs were synthesized using a SuperScript VILO cDNA Synthesis Kit (Invitrogen). Real-time quantitative PCR was performed in the LightCycler 480 system (Roche) using primers listed in S8 Table. Selected Rider primers amplify 64 out of the 71 copies, with 3 mismatches allowed. Localization of Rider primers is shown in S9 Fig. LightCycler 480 SYBR Green I Master premix (Roche) was used to prepare the reaction mixture in a volume of 10 μL. Transcript levels were normalized to SlACTIN (Solyc03g078400). The results were analysed by the ΔΔCt method.

DNA extraction and copy number quantification

Tomato DNA was extracted using the Qiagen DNeasy Plant Mini Kit (Qiagen) following the manufacturer’s instructions and resuspended in 30 μL H2O. DNA concentration was estimated using the Qubit Fluorometric Quantitation system (Thermo Fisher). Quantitative PCR was performed in the LightCycler 480 system (Roche) using primers listed in S8 Table. Selected Rider primers amplify 64 out of the 71 copies, with 3 mismatches allowed. Localization of Rider primers is shown in S9 Fig. LightCycler 480 SYBR Green I Master premix (Roche) was used to prepare the reaction in a volume of 10 μL. DNA copy number was normalized to SlACTIN (Solyc03g078400). Results were analysed by the ΔΔCt method.

Extrachromosomal circular DNA detection

Extrachromosomal circular DNA amplification was derived from the previously published mobilome analysis [11]. In brief, extrachromosomal circular DNA was separated from chromosomal DNA using PlasmidSafe ATP-dependent DNase (EpiCentre) according to the manufacturer’s instructions with the incubation at 37°C extended to 17 h. The PlasmidSafe exonuclease degrades linear DNA and thus safeguards circular DNA molecules. Circular DNA was precipitated overnight at -20°C in 0.1 v/v 3 M sodium acetate (pH 5.2), 2.5 v/v EtOH and 1 μL glycogen (Sigma). The pellet was resuspended in 20 μL H2O. Inverse PCR reactions were carried out with 2 μL of DNA solution in a final volume of 20 μL using the GoTaq enzyme (Promega). The PCR conditions were as follows: denaturation at 95°C for 5 min, followed by 30 cycles at 95°C for 30 s, an annealing step for 30 s, an elongation step at 72°C for 60 s, and a final extension step at 72°C for 5 min. Selected primers amplify 68 out of the 71 Rider copies, with 3 mismatches allowed. Primer localization is shown on Fig 4A and 4C, left panel (grey bar: Rider element, black box: LTR, arrowheads: PCR primers) and sequences are listed in S8 Table. PCR products were separated in 1% agarose gels and developed by NuGenius (Syngene). Bands were extracted using the Qiagen Gel Extraction Kit and eluted in 30 μL H2O. Purified amplicons were subjected to Sanger sequencing. Five amplicons, obtained from two independent experiments, were sequenced for each eccDNA form.

Phylogenetic analysis of de novo identified Rider elements

A phylogenetic tree was constructed from the nucleotide sequences of the 71 Rider elements using Geneious 9.1.8 (www.geneious.com) and built with the Tamura-Nei neighbor joining method. Pairwise alignment for the building distance matrix was obtained using a global alignment with free end gaps and a cost matrix of 51% similarity.

Distribution analysis

Genomic coordinates of each of the 71 Rider elements identified by de novo annotation using LTRpred (https://github.com/HajkD/LTRpred) have been used to establish their chromosomal locations. Coordinates for centromeres were provided before [32] and pericentromeric regions were defined by high levels of DNA methylation and H3K9me2 ([60] and David Baulcombe, personal communication).

Accession numbers

The Genbank accession number of the reference Rider nucleotide sequence identified in [45] is EU195798.2. We used Solanum lycopersicum bisulfite and small RNA sequencing data (SRP081115) generated in [60].

Dating of insertion time

Insertion times of Rider elements were estimated using the method described in [45]. Degrees of divergence between LTRs of each individual element were determined using LTRpred. LTR divergence rates were then converted into dates using the average substitution rate of 6.96 x 10−9 substitutions per synonymous site per year for tomato [87].

Bisulfite sequencing analysis

We collected data from previously published BS-seq libraries of tomato mutants of RNA polymerase IV and V and controls [60]: slnrpe1 (SRR4013319), slnrpd1 (SRR4013316), wild type CAS9 (SRR4013314) and not transformed wild type (SRR4013312). The raw reads were analysed using our previously established pipeline [88] and aligned to the Solanum lycopersicum reference version SL3.0 (www.solgenomics.net/organism/Solanum_lycopersicum/genome). The chloroplast sequence (NC_007898) was used to estimate the bisulfite conversion (on average above 99%). The R package DMRcaller [89] was used to summarize the level of DNA methylation in the three cytosine contexts for each Rider copy.

Small RNA sequencing analysis

Tomato siRNA libraries were obtained from [60] and analysed using the same analysis pipeline to align reads to the tomato genome version SL3.0. Briefly, the reads were trimmed with Trim Galore! (www.bioinformatics.babraham.ac.uk/projects/trim_galore) and mapped using the ShortStack software v3.6 [90]. The siRNA counts on the loci overlapping Rider copies were calculated with R and the package GenomicRanges.

Genome sequence data

Computationally reproducible analysis and annotation scripts for the following sections can be found at http://github.com/HajkD/RIDER.

Genomic data retrieval

We retrieved genome assemblies for 110 plant species (S9 Table) from NCBI RefSeq [91] using the meta.retrieval function from the R package biomartr [92]. For Solanum lycopersicum, we retrieved the most recent genome assembly version SL3.0 from the Sol Genomics Network ftp://ftp.solgenomics.net/tomato_genome/assembly/build_3.00/S_lycopersicum_chromosomes.3.00.fa [93].

Functional de novo annotation of LTR retrotransposons in Solanaceae genomes

Functional de novo annotations of LTR retrotransposons for seventeen genomes from the Asterids, Rosids, and monocot clades (Asterids: Capsicum annuum, C. baccatum MLFT02_5, C. chinense MCIT02_5, Coffea canephora, Petunia axillaris, Phytophthora inflata, Solanum arcanum, S. habrochaites, S. lycopersicum, S. melongena, S. pennellii, S. pimpinellifolium, S. tuberosum; Rosids: Arabidopsis thaliana, Vitis vinifera, and Cucumis melo; Monocots: Oryza sativa) were generated using the LTRpred.meta function from the LTRpred annotation pipeline (https://github.com/HajkD/LTRpred; also used in [25]). To retrieve a consistent and comparable set of functional annotations for all genomes, we consistently applied the following LTRpred parameter configurations to all Solanaceae genomes: minlenltr = 100, maxlenltr = 5000, mindistltr = 4000, maxdisltr = 30000, mintsd = 3, maxtsd = 20, vic = 80, overlaps = “no”, xdrop = 7, motifmis = 1, pbsradius = 60, pbsalilen = c(8,40), pbsoffset = c(0,10), quality.filter = TRUE, n.orf = 0. The plant-specific tRNAs used to screen for primer binding sites (PBS) were retrieved from GtRNAdb [94] and plant RNA [95] and combined in a custom fasta file. The hidden Markov model files for gag and pol protein conservation screening were retrieved from Pfam [96] using the protein domains RdRP_1 (PF00680), RdRP_2 (PF00978), RdRP_3 (PF00998), RdRP_4 (PF02123), RVT_1 (PF00078), RVT_2 (PF07727), Integrase DNA binding domain (PF00552), Integrase zinc binding domain (PF02022), Retrotrans_gag (PF03732), RNase H (PF00075), and Integrase core domain (PF00665).

Sequence clustering of functional LTR retrotransposons from 17 genomes

We combined the de novo annotated LTR retrotransposons of the 17 species mentioned in the previous section in a large fasta file and used the cluster program VSEARCH [97] with parameter configurations: vsearch—cluster_fast—qmask none–id 0.85—clusterout_sort—clusterout_id—strand both—blast6out—sizeout to cluster LTR retrotransposons by nucleotide sequence homology (global sequence alignments). Next, we retrieved the 85% sequence homology clusters from the VSEARCH output and screened for clusters containing Rider sequences. This procedure enabled us to detect high sequence homology (>85%) sequences of Rider across diverse species.

Nucleotide BLAST search of Rider against 110 plant genomes

To determine the distribution of Rider related sequences across the plant kingdom, we performed BLASTN [98] searches of Rider (= query sequence) using the function blast_genomes from the R package metablastr (https://github.com/HajkD/metablastr) against 110 plant genomes (S9 Table) and the parameter configuration: blastn -eval 1E-5 -max_target_seqs 5000. As a result, we retrieved a BLAST hit table containing 11,748,202 BLAST hits. Next, we filtered for hits that contained at least 50% sequence coverage (= sequence homology) and throughout at least 50% sequence length homology to the reference Rider sequence. This procedure reduced the initial 11,748,202 BLAST hits to 57,845 hits, which we further refer to as Rider-like elements. These 57,845 Rider-like elements are distributed across 21 species with various abundance frequencies. In a second step, we performed an analogous BLASTN search using only the 5’ LTR sequence of Rider to determine the distribution of Rider-like LTR across the plant kingdom. Using the same BLASTN search strategy described above, we retrieved 9,431 hits. After filtering for hits that contained at least 50% percent sequence coverage (= sequence homology) and at least 50% sequence length homology to the reference Rider LTR sequence, we obtained 2,342 BLAST hits distributed across five species.

Motif enrichment analysis

We tested the enrichment of cis-regulatory elements (CREs) in Rider using two approaches. In the first approach, we compared Rider CREs to promoter sequences of all 35,092 protein coding genes from the tomato reference genome. We retrieved promoter sequences 400 bp upstream of the TSS of the respective genes. We constructed a 2x2 contingency table containing the respective motif count data of CRE observations in true Rider sequences versus counts in promoter sequences. We performed a Fisher’s exact test for count data to assess the statistical significance of enrichment between the motif count data retrieved from Rider sequences and the motif count data retrieved from promoter sequences. In the second approach, due to the unavailability of gene annotation for Solanum arcanum, Solanum habrochaites and Solanum pimpinellifolium we compared Rider CREs to randomly sampled sequence loci from the same genome using the following two step procedure: in step one, we sampled 1000 DNA sequences with the same length as the reference Rider sequence from 1000 randomly sampled loci in the tomato reference genome. When sampling, we also considered the strand direction of the reference Rider sequence. Whenever a Rider sequence was annotated in the plus direction, we also sampled the corresponding set of random sequences in the plus direction of the respective randomly drawn locus. In contrast, when a Rider sequence was annotated in the minus direction, we also sampled the corresponding set of random sequences in the minus direction. In step two, we counted CRE occurrences for each Rider sequence independently and for a set of different CREs. Next, we counted the number of the same CRE occurrences for each random sequence independently to assess how often these CREs were found in random sequences. We then, analogous to the first approach, constructed a 2x2 contingency table containing the respective motif count data of CRE observations in true Rider sequences versus counts in random sequences. We performed a Fisher’s exact test for count data to assess the statistical significance of enrichment between the motif count data retrieved from Rider sequences and the motif count data retrieved from random sequences. The resulting P-values are shown in S4 Table for the first approach and in S5 Table for the second approach. Computationally reproducible scripts to perform the motif count analysis can be found at https://github.com/HajkD/RIDER.

Calculation of N50 metric

To assess the genome quality of Solanaceae species, we calculated the N50 metric for the genome assemblies of Solanum lycopersicum, S. pimpinellifolium, S. arcanum, S. pennellii, S. habrochaites, and S. tuberosum using the following procedure. First, we imported the scaffolds or chromosomes of each respective genome assembly using the R function read_genome() from the biomartr package. Next, for each species individually we determined the sequence length for each scaffold or chromosome and sorted them according to length in descending order. The N50 value in Mbp was then calculated in R as follows: N50 <- len.sorted[cumsum(len.sorted) > = sum(len.sorted)*0.5][1] / 1000000, where the variable len.sorted denotes the vector storing the ordered scaffold or chromosome lengths of a genome assembly.

Availability of data and materials

SRAtoolkit, v2.8.0 (https://github.com/ncbi/sra-tools) and Biomartr 0.9.9000 (https://ropensci.github.io/biomartr/index.html) were used for data collection.

Phylogenetic trees were constructed using Geneious 9.1.8 (www.geneious.com).

The de novo retrotransposon annotation pipeline LTRpred is available in the GitHub repository (https://github.com/HajkD/LTRpred).

Rider annotation and analysis pipeline is available in the GitHub repository (https://github.com/HajkD/RIDER).

Distribution of Rider elements was done using the R package metablastr (https://github.com/HajkD/metablastr).

DNA methylation levels were assessed using the R package DMRcaller (http://bioconductor.org/packages/release/bioc/html/DMRcaller.html).

Small RNA analysis was done using Trim Galore! (www.bioinformatics.babraham.ac.uk/projects/trim_galore), ShortStack v3.6 (https://github.com/MikeAxtell/ShortStack) and GenomicRanges v3.8 (https://bioconductor.org/packages/release/bioc/html/GenomicRanges.html).

Reference Rider nucleotide sequence (accession number EU195798) is available here (https://www.ncbi.nlm.nih.gov/nuccore/EU195798).

The datasets supporting the conclusions of this article are available at Sequence Read Archive (SRA) (https://www.ncbi.nlm.nih.gov/sra/) under accession numbers "SRP081115", "SRR4013319", "SRR4013316", "SRR4013314" and "SRR4013312".

Supporting information

S1 Fig. Distribution of 71 de novo annotated Rider elements based on LTR similarity and chromatin context.

(A) Age distribution of total Rider elements based on LTR similarity and corresponding classes. (B) Age distribution of Rider elements inserted in heterochromatic (HC) and euchromatic (EC) regions based on LTR similarity.

https://doi.org/10.1371/journal.pgen.1008370.s001

(EPS)

S2 Fig. Rider transcripts levels are unaffected by cold stress.

(A-D) Quantification of SlASR1 RNA levels by RT-qPCR in wild-type tomato seedlings after (A) drought stress (B) mannitol, (C) NaCl or (D) ABA treatments. (E) Quantification of SlASR1 RNA levels in leaves of drought-stressed tomato wild-type plants, flc, not and sit mutants. (F) Quantification of SlASR1 RNA levels by RT-qPCR in wild-type tomato seedlings after 5-azacytidine and ABA treatments. (G) Quantification of Rider RNA levels by RT-qPCR in wild-type tomato seedlings after cold stress. Bar charts show normalized expression +/- SEM from three to five biological replicates.

https://doi.org/10.1371/journal.pgen.1008370.s002

(EPS)

S3 Fig. Distribution of siRNAs and DNA methylation within Rider sub-groups.

(A) 21-22-nt and (B) 24-nt siRNAs normalized counts at distinct Rider sub-groups in wild type, wild type with CAS9, slnrpd1 and slnrpe1. Rider elements are classified based on LTR similarity (80–95%, 95–98% and 98–100%), while Rider (Euchromatin) denotes copies located on euchromatic arms and Rider (Heterochromatin) copies located in pericentromeric heterochromatin. Data are expressed as siRNA reads per kb per million mapped reads, and represent average normalized siRNA counts on Rider elements +/- SD from Rider copies in the sub-group. (C) Quantification of DNA methylation levels in the CG, CHG and CHH contexts at Rider in wild type, slnrpd1 and slnrpe1. The levels are averages of DNA methylation (%) in each context over the 71 de novo annotated Rider copies. (D) Quantification of CHH DNA methylation levels at Rider sub-groups in wild type, slnrpd1 and slnrpe1. The levels are averages of DNA methylation (%) in the CHH context over Rider sub-groups.

https://doi.org/10.1371/journal.pgen.1008370.s003

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S4 Fig. Distinct Rider copies contribute to the production of extrachromosomal circular DNA.

Comparison of the LTR nucleotide sequence from Rider extrachromosomal circular DNA detected after drought, or in slnrpd1 (A) or slnrpe1 (B), with the reference Rider LTR using EMBOSS Needle (www.ebi.ac.uk/Tools/psa/emboss_needle). CREs are marked as coloured boxes. (C) Quantification of CHH DNA methylation levels at LTRs and body of Rider_08_3 and Rider_07_2 in wild type, slnrpd1 and slnrpe1. Levels expressed as % of methylated CHH sites. (D-E) Quantification of CG (D) and CHG (E) contexts DNA methylation levels at Rider_08_3 and Rider_07_2 in wild type, slnrpd1 and slnrpe1. Levels expressed as % of methylated sites. (F-G) Normalized siRNA count of 24-nt (F) and 21-22-nt (G) siRNAs at LTRs and body of Rider_08_3 and Rider_07_2 in wild type, slnrpd1 and slnrpe1. Data are expressed as siRNA reads per kb per million mapped reads.

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S5 Fig. DNA methylation status of Rider elements producing eccDNA.

DNA methylation status of Rider_08_3 (A) and Rider_07_2 (B). Snapshots from IGV are shown. CG (blue track), CHG (red track) and CHH (green track) methylation coverage are shown for WT, slnrpd1 and slnrpe1. Rider is identified as a blue block in the LTRpred track.

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S6 Fig. Characterization of Rider sub-populations in Solanaceae based on LTR sequences.

Coverage over reference Rider LTR of high homology sequences identified by BLAST in Fig 5C. Sequences classified as “long LTR” were selected by filtering for BLAST hits with alignment lengths between 350–450 bp and >50% sequence and length homology to reference Rider. Sequences classified as “short LTR” were selected by filtering for BLAST hits with alignment lengths between 150–300 bp and >50% sequence and length homology to reference Rider.

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S7 Fig. Identification of Rider homologs in 14 plant species.

In silico identification of Rider homologs in 14 plant species based on the density of high homology BLAST hits over the full-length reference Rider sequence (left) and alignment length of BLAST hits obtained (right). Species are ordered by evolutionary distance to Solanum lycopersicum according to www.timetree.org, www.genome.jp and references in S1 Text.

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S8 Fig. Non-Solanaceae Rider homologs lack LTR sequence conservation.

In silico identification of Rider LTR homologs in 14 plant species based on the density of high homology BLAST hits over the reference Rider LTR sequence only. Species are ordered by evolutionary distance to Solanum lycopersicum according to www.timetree.org, www.genome.jp and references in S1 Text.

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S9 Fig. Localization of primers within Rider LTRs.

Binding sites of qPCR primers within Rider LTRs are shown as purple arrows. Rider LTR U3, R and U5 regions are marked, as well as neighbouring Target Site Duplication (TSD) and Primer Binding Site (PBS) sequences. CREs are marked as coloured vertical bars.

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S1 Table. De novo annotation of LTR retrotransposons in the SL3.0 genome by LTRpred.

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S2 Table. Patristic distances between 71 de novo annotated Rider copies.

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S3 Table. Presence of cis-regulatory elements in individual Rider copies.

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S4 Table. Identification and enrichment analysis of cis-regulatory elements in Rider LTRs.

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S5 Table. Enrichment analysis of cis-regulatory elements in Rider LTRs in four Solanaceae species.

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S6 Table. Characteristics of Rider_08_3 and Rider_07_2 loci.

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S7 Table. N50 metric for six Solanaceae species.

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S9 Table. List of the 110 plant genomes used for the large-scale Rider BLAST search.

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Acknowledgments

The authors thank all members of Dr. Paszkowski lab for fruitful discussions during the development of this project as well as the SLCU support staff.

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