## Main

Ancient polyploidization or whole-genome duplication is a hallmark of most higher-organism genomes1,2, including our own3,4. While most of these organisms are now diploid and show only traces of polyploidy, there are many examples of recent polyploidization, especially among flowering plants5,6,7,8,9. These examples are important because they allow us to study the process of polyploidization.

Widespread naturally occurring polyploid hybrids (that is, allopolyploids) show that natural polyploid species can quickly become successful10,11,12,13,14,15,16,17,18 and even invasive19. However, new allopolyploid species face numerous challenges such as population bottlenecks13,20, competition with their diploid progenitors21, chromosome segregation22,23,24, changes to genome structure25 and genome regulation26,27—potentially leading to a ‘genome shock’28. In agreement with this, genomic and transcriptomic changes tied to the hybridization of diverged genomes have been reported in resynthesized polyploids of wheat29,30,31,32,33,34,35, Brassica napus36,37,38 and cotton39,40,41,42, although exceptions exist43.

The long-term importance of such changes is unclear. Evidence of the transcription and mobilization of transposable elements (TEs) in resynthesized wheat33,44,45,46 is not observed in cultivated wheat47. However, other cultivated crop genomes, like cotton, show evidence consistent with dramatic changes following allopolyploidy5,48,49,50,51,52,53. Strawberry6, peanut8 and the mesopolyploids Brassica rapa54 and maize55 show evidence of subgenome dominance, whereas wheat56, cotton51 and B. napus57 do not. The reasons for these differences are not understood.

Whether allopolyploid crops are representative of natural polyploidization is unclear. Domestication is frequently associated with very strong ‘artificial’ selection, which can markedly alter the fitness landscape58,59,60,61,62, and structural variants have been linked to favourable agronomic traits63,64,65. In addition, polyploid crops are generally evolutionarily recent.

Genomic changes have also been reported in natural allopolyploids such as Tragopogon miscellus66,67, Mimulus pergrinus17 and Spartina anglica68; however, these examples resemble resynthesized allopolyploids in being extremely recent (around 100 years). More-established allopolyploids generally do not show signs of genomic changes12,13,14,16,69,70,71.

Here, we focus on an allopolyploid comparable in age to these examples: the highly selfing72 A. suecica, which was formed through the hybridization of A. thaliana and A. arenosa around 16 thousand years ago, during the Last Glacial Maximum20, and which is currently found in northern Fennoscandia (Fig. 1a). The ancestral species diverged around 6 Ma (ref. 73), and based on organelle sequences, A. thaliana is the maternal and A. arenosa is the paternal parent74. This scenario is supported by A. arenosa being a ploidy-variable species, such that A. suecica could readily be generated by the fusion of an unreduced A. thaliana egg cell and an autotetraploid A. arenosa sperm cell20,75. Despite a severe genetic bottleneck20, most of the genetic variation in A. suecica is shared with the ancestral species, ruling out a unique origin. To study genomic change in A. suecica, we used long-read sequencing to generate a chromosome-level genome sequence, complemented by a partial assembly of a tetraploid A. arenosa, and by short-read genome and transcriptome sequencing data from populations of all three species—including ‘synthetic’ A. suecica. Our main goal was to look for evidence of genome changes (particularly the kind of dramatic changes discussed above) in A. suecica relative to the ancestral species.

## Results and analysis

### The genome is conserved

We assembled a reference genome from a naturally inbred20,72 A. suecica accession (ASS3), using 50× long-read PacBio sequencing (PacBio RSII). The absence of heterozygosity and the substantial (around 11.6%) divergence between the subgenomes facilitated the assembly. By contrast, assembling A. arenosa is complicated by high heterozygosity (around 3.5% nucleotide diversity76) and high repeat content. Our assembly of a tetraploid A. arenosa individual, included in this study, is fragmented: 3,629 contigs; N50 of 331 kb. The A. suecica assembly, however, has an N50 contig size of 9.02 Mb. Contigs totalled 276 Mb (around 90% and around 88% of genome size estimated by flow cytometry and k-mer analysis, respectively; see Extended Data Fig. 1 and Methods). Contigs were placed into scaffolds using chromatin conformation capture (Hi-C) data and using the reference genomes of A. thaliana and Arabidopsis lyrata (as substitute for A. arenosa) as guides. This resulted in 13 chromosome-scale scaffolds (Extended Data Fig. 2). The placement and orientation of each contig within a scaffold was confirmed and corrected using a genetic map for A. suecica (see Methods and Extended Data Fig. 2). The final assembly (Fig. 1b) contains 262 Mb and has an N50 scaffold size of 19.59 Mb. The 5 + 8 chromosomes of the A. thaliana and A. arenosa subgenomes sum to 119 Mb and 143 Mb, respectively.

Of the A. thaliana and A. arenosa subgenomes of A. suecica, 108 Mb and 135 Mb are in large blocks syntenic to the genomes of the ancestral species: 13 and 40 blocks, respectively (Fig. 1c,d). The majority of these syntenic blocks are colinear, with the exception of five small-scale inversions (around 4.5 Mb) and one translocation (around 244 kb) on the A. arenosa subgenome—which may reflect differences between A. lyrata and A. arenosa, two highly polymorphic species separated by about a million years73,76. We also corrected the described77 misassembly in the A. lyrata reference genome using our genetic map. Overall we find that approximately 93% of the A. suecica genome is syntenic to the ancestral genomes (Fig. 1c,d). This highlights the conservation of the A. suecica genome and contrasts with the major rearrangements that have been observed in several resynthesized polyploids29,32,34,36 and some crops48,50,78. Notably, major rearrangements have also been observed in synthetic A. suecica79.

A total of 45,585 protein-coding genes were annotated for the A. suecica reference, of which 22,232 and 23,353 are located on the A. thaliana and A. arenosa subgenomes, respectively. We assessed completeness of the genome assembly and annotation with the BUSCO set for eudicots and found 2,088 (98.4%) complete genes for both the A. thaliana and A. arenosa subgenomes. Of the protein-coding genes, 18,023 had a one-to-one orthology between the subgenomes of A. suecica and 16,999 genes were conserved single-copy orthologues for each (sub-)genome of A. suecica and the ancestral species (Supplementary Data 2 and Extended Data Fig. 3). We annotated lineage-specific genes in A. suecica (that is, genes in A. suecica with no orthologue) using InterPro. We found significant enrichment in the A. thaliana subgenome for two gene ontology (GO) terms (GO:0008234 and GO:0015074) that are associated with repeat content (Supplementary Data 2). Ancestral genes missing in our annotation were overrepresented for functional categories of defence response. Examining DNA-sequencing coverage for these genes in the ancestral genomes did not confirm any gene loss, suggesting rather misassembly or misannotation, likely because of the repetitive and highly polymorphic nature of resistance genes (R-genes).

### The ribosomal DNA clusters are highly variable

In eukaryotic genomes, genes encoding ribosomal RNA (rRNA) occur as tandem arrays in rDNA clusters. The 45S rDNA clusters are massive, containing hundreds or thousands of copies and spanning millions of base pairs80. The site of pre-ribosome assembly (nucleolus), forms at these clusters if they are actively transcribed. In inter-specific hybrids it was previously observed that the rDNA of only one parent tended to be involved in nucleolus formation, a phenomenon known as ‘nucleolar dominance’81,82,83,84. In A. suecica, it was observed that the rDNA clusters inherited from A. thaliana were silenced81,82,83,84,85,86,87, and structural changes associated with these clusters were also suggested88.

Given this, we examined the composition and transcription of 45S rDNA repeats. Although the large and highly repetitive 45S rDNA clusters are missing from the genome assembly, we can measure the copy number of A. thaliana and A. arenosa 45S rRNA genes using sequencing coverage (see Methods). We find that three accessions have experienced massive loss of the A. thaliana rDNA loci (Fig. 2a), which was confirmed for one of the accessions (AS90a) by fluorescence in situ hybridization (FISH) analysis (Fig. 2b,c). However, there is massive copy number variation for 45S rRNA genes in A. suecica (Fig. 2a), and some accessions (ASS3) have a higher 45S rRNA copy number in A. thaliana than in A. arenosa (Fig. 2d,e).

We find nucleolar dominance to be variable in A. suecica (see Methods and Extended Data Fig. 3). The majority of accessions express both 45S rRNA alleles, five exclusively express A. arenosa 45S rRNA and one exclusively expresses A. thaliana 45S rRNA (Fig. 2a).

This extensive variation in 45S cluster size and expression is consistent with the intraspecific variation seen in A. thaliana89,90, and previous observations made in natural A. suecica91. This suggests that nucleolar dominance may partly be explained by retained ancestral variation. However, the large decrease in rDNA cluster size observed in some accessions may be a consequence of allopolyploidization, as synthetic A. suecica sometimes shows loss of 45S rDNA (even as early as the F1 stage) that varies between siblings and generations (Extended Data Fig. 3). Elimination of rDNA loci has also been previously observed in synthetic wheat92, and loss of rDNA sites has been reported in strawberry93.

### No evidence for abnormal transposon activity

The possibility that allopolyploidization leads to a ‘genome shock’ in the form of increased transposon activity has been discussed27,28,94,95. Evidence for TE proliferation following hybridization has been found for Ty3/Gypsy retrotransposons in hybrid sunflower species96, although this may be due to environmental change97,98. Analysis of TE expression in F1 hybrids between A. thaliana and A. lyrata found strong correlation to the parent species, and little alteration of repressive chromatin marks99—although the F1 generation may be too early to study TE misregulation. Here we examine TE dynamics in A. suecica.

In A. suecica there are almost twice as many annotated transposons in the A. arenosa compared to the A. thaliana subgenome (66,722 versus 33,420). The difference is likely to be greater given that the A. arenosa subgenome assembly is less complete and TE annotation is biased towards A. thaliana. Whether the combination of these two genomes has led to increased transposon activity is unknown.

The A. thaliana subgenome contains around 3,000 more annotated transposons than the TAIR10 A. thaliana reference genome but could reflect a greater number of transposons in the A. thaliana ancestors rather than increased transposon activity in A. suecica. To investigate TE activity, unique TE jumps that occurred after the species separated are needed. We used the software PoPoolationTE2100 to call presence–absence variation on a population level using 15 natural A. suecica accessions, 18 A. thaliana accessions genetically close to A. suecica, and 9 A. arenosa lines. Of the 24,569 insertion polymorphisms in the A. thaliana subgenome, 8,767 were shared between A. thaliana and A. suecica, 7,196 were unique to A. thaliana and 8,606 were unique to A. suecica. Of the 115,336 insertion polymorphisms in the A. arenosa subgenome, 13,177 were shared with A. arenosa, 83,964 were unique to A. arenosa and 18,195 were unique to A. suecica (Supplementary Data 1a,b and Extended Data Fig. 4). Considering the number of transposons per individual genome (Fig. 3a), most transposon insertions in a typical A. thaliana subgenome are also found in A. thaliana. The slightly higher transposon load in the A. thaliana subgenome is probably due to the population bottleneck. Notably, the number of unique insertions is not higher in the A. thaliana subgenome, suggesting no increase in transposon activity.

Turning to the A. arenosa subgenome, we see that A. suecica contains only about half the number of transposons of A. arenosa on average (Fig. 3a). However, A. arenosa is an outcrossing tetraploid, therefore four randomly chosen A. arenosa subgenomes of A. suecica were used in the comparison (‘A. arenosa in A. suecica (4n)’ in Fig. 3a). This largely accounts for the observed difference, but there are still fewer transposons in A. suecica. A population bottleneck is likely to explain the difference, although decreased transposon activity in A. suecica, related to its transition to selfing101, cannot be ruled out.

In summary, we see no evidence for a burst of transposon activity in A. suecica, a conclusion supported by the analysis of transposon expression for A. suecica, which shows no upregulation relative to the ancestor species (Extended Data Fig. 5). The frequency distribution of polymorphic transposon insertions unique to A. suecica is heavily skewed towards zero, likely because of purifying selection as the distribution is more similar to that of non-synonymous than synonymous single-nucleotide polymorphisms (SNPs) (Fig. 3b,c). However, for both subgenomes, A. suecica also contains a large number of fixed or nearly fixed insertions that are present in the ancestral species at a lower frequency (Fig. 3d,e). These are likely to have reached high frequency as a result of a bottleneck. Shared transposons are enriched in the pericentromeric regions, while unique transposon insertions, generally at low frequency, are more uniformly distributed across the genome, which is consistent with strong selection against transposon insertions in the gene-dense chromosome arms102,103 (Extended Data Fig. 4).

An interesting subset of recent transposon insertions unique to A. suecica are those that have jumped between the subgenomes. We searched for full-length transposon copies that are present in both subgenomes of A. suecica and assigned the transposon sequences to the A. thaliana or the A. arenosa ancestral genome (see Methods). We were able to assign 15 and 56 transposon sequences as belonging to the A. thaliana and A. arenosa ancestral genome, respectively. Using these sequences, we searched our transposon polymorphisms and identified 1,515 A. arenosa transposon polymorphisms on the A. thaliana subgenome, and 496 A. thaliana transposon polymorphisms on the A. arenosa subgenome. Like other private polymorphisms, these are skewed towards rare frequencies, and are uniformly distributed across the (sub-)genome. Most of the transposons that have jumped into the A. thaliana subgenome are helitron and long terminal repeat (LTR) elements (Extended Data Fig. 4). LTR elements also make up most of the A. thaliana transposons segregating in the A. arenosa subgenome. Three times as many transposon jumps from A. arenosa to A. thaliana than vice versa is notable, and suggests higher transposon activity in the A. arenosa subgenome, but we must consider differences in genome size and transposon number. If no differences in activity exist, we would expect the number of jumps to be proportional to the number of potential source elements and the size of the target genome. As the A. arenosa subgenome contains roughly twice as many transposons as the A. thaliana subgenome and is about 20% larger, we expect a 1.7-fold difference, not a three-fold one.

In conclusion, transposon activity in A. suecica appears to be governed by the same processes as in the ancestral species.

### No global dominance in expression between the subgenomes

Over time the traces of polyploidy are erased through an evolutionary process referred to as fractionation or re-diploidization104,105,106,107,108. Analyses of retained homeologues in ancient allopolyploids such as A. thaliana109, maize55, B. rapa54 and Gossypium raimondii110 have revealed that one ‘dominant’ subgenome remains more intact, with more highly expressed homeologues compared to the ‘submissive’ genome(s)109. This pattern of biased fractionation has not been observed in ancient autopolyploids111,112, and is believed to be allopolyploid-specific.

Studying genome expression dominance in allopolyploids is useful for understanding or predicting which of the subgenomes will likely be refractory to, and which will likely experience this fractionation process more, over time55. Subgenome dominance in expression has been reported for a number of recent allopolyploids such as strawberry6, peanut8, Spartina68, T. miscellus113, monkeyflower17 and synthetic B. napus114. However, some allopolyploids display even subgenome expression: Capsella bursa-pastoris10,12, Trifolium repens13, Arabidopsis kamachatica70 and Brachypodium hybridum14.

Subgenome dominance is linked to differences in transposon content6 and/or large genetic differences between subgenomes115. This makes A. suecica, with 6 Ma divergence between the gene-dense A. thaliana and the transposon-rich A. arenosa, a promising candidate to study this phenomenon. Previous reports on subgenome dominance in A. suecica are conflicting, suggesting a bias to either the A. thaliana116 or the A. arenosa117 subgenome.

To investigate the evolution of gene expression in A. suecica, we generated RNA sequencing (RNA-seq) data for 15 natural A. suecica accessions, 15 closely related A. thaliana accessions, 4 A. arenosa individuals, a synthetically generated A. suecica from a lab cross (the second and third hybrid generations) and the parental lines of this cross. Each sample had 2–3 biological replicates (Supplementary Data 2). On average, we obtained 10.6 million raw reads per replicate, of which 7.6 million reads were uniquely mapped to the A. suecica reference genome and 14,041 homeologous gene pairs (see Methods). On average, around 1% of A. thaliana and around 6% of A. arenosa RNA reads cross-mapped between the subgenomes of A. suecica. The approximately 6% of cross-mapping in A. arenosa is likely to be because of the high level of polymorphism in this outcrossing species. However, diversity within A. suecica is massively lower, meaning that transcripts from the A. arenosa subgenome will probably map correctly (see Methods and Extended Data Fig. 6).

Examining expression differences between homeologous gene pairs, we found no general bias towards a subgenome of A. suecica (that is, the mean log fold change is 0), for any sample or tissue, including synthetic A. suecica (Fig. 4a and Extended Data Fig. 7). This suggests that the expression differences between the subgenomes have not changed systematically through polyploidization, and is in contrast to previous studies, which reported a bias towards the A. thaliana116 or the A. arenosa117 subgenome, likely because RNA-seq reads were not mapped to an appropriate reference genome.

The set of genes that show large expression differences between the subgenomes are not biased towards any particular GO category, and are not consistent between accessions and individuals (Fig. 4b and Extended Data Fig. 7). This suggests that many large subgenome expression differences are due to genetic polymorphisms within A. suecica rather than fixed differences between the ancestral species.

Levels of expression dominance were reported to vary across tissues in natural C. bursa-pastoris11 and resynthesized cotton118. To test whether expression dominance can vary for tissue-specific genes, we examined homeologous gene pairs in which at least one gene in the pair showed tissue-specific expression, in whole rosettes and floral buds. We do not find evidence for dominance between subgenomes in tissue-specific expression (Fig. 4b). A total of 897 genes with significant expression in whole rosettes for both homeologues showed GO overrepresentation that included both photosynthesis- and chloroplast-related functions (Supplementary Table 1). This result suggests that the A. arenosa subgenome has established important cyto-nuclear communication with the chloroplast inherited from A. thaliana, rather than being silenced. A total of 2,176 gene pairs with floral-bud-specific expression for both homeologues were overrepresented for GO terms related to responses to auxin and jasmonic acid that may reflect early developmental changes in this young tissue (Supplementary Table 1). Although flowers of selfing A. thaliana and A. suecica are scentless and are much smaller than those of the outcrosser A. arenosa72, this result suggests that the ‘selfing syndrome’119 has not hugely affected the transcriptome of floral buds in A. suecica at this stage of development.

In summary, we find no evidence that one subgenome is dominant and contributes more to the functioning of A. suecica. On the contrary, homeologous gene pairs are strongly correlated in expression across tissues.

### Evolving gene expression in A. suecica

The previous section focused on differences in expression between the subgenomes within the same individual. This section will focus on differences between individuals. To provide an overview of expression differences between individuals we performed a principal component analysis (PCA) on gene expression separately for each (sub-)genome. For both subgenomes, the first principal component separates A. suecica from the ancestral species and the synthetic hybrid (Fig. 5a,b and Extended Data Fig. 8), suggesting that hybridization does not automatically result in large-scale transcriptional changes, and that gene expression changes in natural A. suecica have evolved over time. Given the limited time involved, and the fact that the genes that have changed expression are not random with respect to function (Fig. 5c), we suggest that the first principal component captures trans-regulated expression changes in A. suecica that are adaptive.

To further characterize expression changes in natural A. suecica, we analysed differentially expressed genes (DEGs) on each subgenome compared to the corresponding ancestral species. The total number of DEGs was 4,186 and 4,571 for the A. thaliana and A. arenosa subgenome, respectively (see Methods and Supplementary Data 2). These genes were clustered on the basis of the pattern of change across individuals (Fig. 5c,d) and GO enrichment analysis was performed for each cluster (Fig. 5e and Supplementary Table 2).

For the A. thaliana subgenome, we identified three clusters. Cluster 1 comprised 2,135 genes that showed decreased expression in A. suecica compared to A. thaliana. These genes are enriched for transcriptional regulation, which may be expected as we are examining DEGs between the species. Enrichments for circadian rhythm function and phototropism may be related to the ecology of A. suecica and its post-glacial migration to Fennoscandinavia (Fig. 1a).

Cluster 2 consisted of 468 genes that are upregulated in both natural and synthetic A. suecica relative to A. thaliana. These expression changes most likely are an immediate consequence of trans-regulation in hybrids. Genes in this cluster are enriched for mRNA transport and protein folding. Adjustment of protein homeostasis has been reported previously in experimentally evolved stable polyploid yeast120. Notably, the synthetic lines used in the expression analysis did not show signs of aneuploidy (Extended Data Fig. 9).

Cluster 3 consisted of 1,583 genes that are upregulated in A. suecica compared to A. thaliana, and several of the enriched GO categories, such as microtubule-based movement, cytokinesis, meiosis and cell division, suggest that the A. thaliana subgenome of A. suecica is adapting to polyploidy at a cellular level. Selection for this seems likely given that aneuploidy is frequent in synthetic A. suecica (Extended Data Fig. 9), while natural A. suecica has a stable conserved karyotype. Independent evidence for adaptation to polyploidy via modifications of the meiotic machinery in the other ancestor of A. suecica, A. arenosa, also exists23,121,122, although we see very little overlap in the genes involved (Extended Data Fig. 9). The nature of these changes in the A. thaliana subgenome of A. suecica will require further investigation, but we note the enrichment (see Methods and Supplementary Data 2) of MYB family transcription factor binding sites123 in cluster 3.

For the A. arenosa subgenome, we also found three clusters of DEGs (Fig. 5d) with GO enrichment for two clusters (Fig. 5e and Supplementary Table 2). Cluster 1 consisted of 1,278 genes that are upregulated in natural A. suecica compared to A. arenosa and synthetic A. suecica. We find enrichment for plastid-related functions that may be due to selection on the A. arenosa subgenome to restore communication with the maternally inherited plastids from A. thaliana. Twelve out of a total of 69 genes with structural evidence for direct plastid–nuclear interactions in A. thaliana overlap our genes in Cluster 1 using CyMIRA124 (P = 0.0072; one-sided Fisher’s exact test; Supplementary Data 2). Cluster 3 consists of 3,166 genes that are downregulated in A. suecica compared to A. arenosa and synthetic A. suecica. These genes were enriched for mRNA processing and epigenetic regulation of gene expression (Supplementary Table 2), and for positive regulation of transcription by RNA polymerase II, which suggests differences in the epigenetic regulation of expression between A. arenosa and A. suecica. Cluster 2 (127 genes), finally, did not have a GO overrepresentation and showed an intriguing pattern that will be discussed in the next section.

### Homeologous exchange contributes to variation in gene expression

The second principal component for gene expression identified three outlier accessions of A. suecica: two for the A. thaliana subgenome (Fig. 5a) and one for the A. arenosa subgenome (Fig. 5b). While closely examining the latter accession, AS530, we realized that it is responsible for the cluster of genes with distinct expression patterns but no GO enrichment (Fig. 5d, Cluster 2). Genes from this cluster were significantly downregulated on the A. arenosa subgenome (Fig. 6a) and upregulated on the A. thaliana subgenome (Fig. 6b)—for AS530 only. The observation that 104 of the 127 genes (Extended Data Fig. 10) in the cluster are located in close proximity in the genome pointed to a structural rearrangement. The lack of DNA-sequencing coverage on the A. arenosa subgenome around these 104 genes, and the doubled coverage for their homeologues on the A. thaliana subgenome, suggested a homeologous exchange (HE) event resulting in AS530 carrying four copies of the A. thaliana subgenome and zero copies of the A. arenosa subgenome for this approximately 2.5 Mb region of the genome (Fig. 6c). This was further supported by Hi-C data, which showed clear evidence for interchromosomal contacts between A. thaliana subgenome chromosome 1 and A. arenosa subgenome chromosome 6 around the break points of the putative HE in AS530 (Fig. 6d,e), and by multiple discordant paired-end reads at the break points between the homeologous chromosomes, which independently support the HE event (Extended Data Fig. 10).

We examined the two outlier A. suecica accessions for the A. thaliana subgenome (Fig. 5a; AS150 and ASÖ5) and found that they probably share a single HE event in the opposite direction (four copies of the A. arenosa subgenome and no copies of the A. thaliana subgenome for a region of around 1.2 Mb in size; see Extended Data Fig. 10). This demonstrates that HE occurs in A. suecica and contributes to the intraspecific variation in gene expression (Fig. 5a,b). HE in allopolyploids is a main source of diversity, causing extensive phenotypic changes9,125. However, the majority of HEs are probably deleterious as they will lead to gene loss: although the A. thaliana and A. arenosa genomes are largely syntenic, AS530 is missing 108 genes (Extended Data Fig. 10) that are only present on the A. arenosa subgenome segment that has been replaced by the homeologous segment from the A. thaliana subgenome, and AS150 and ASÖ5 are missing 53 genes that were only present on the A. thaliana subgenome.

## Discussion

This study has focused on the process of polyploidization in a natural allotetraploid species, A. suecica. Its ancestral species, A. thaliana and A. arenosa, differ substantially in genome size, chromosome number, ploidy, mating system and ecology.

Our main conclusion from this study is that the polyploid speciation leading to A. suecica appears to have been a gradual process rather than some kind of ‘event’. We confirmed previous results that genetic polymorphism is largely shared with the ancestral species, demonstrating that A. suecica did not originate through a single unique hybridization event, but rather through multiple crosses20. We also find no evidence for a ‘genome shock’, in the sense of major genomic changes linked to structural and functional alterations, which has often been suggested to accompany polyploidization and hybridization. Specifically, the genome has not been massively rearranged, transposable elements are not out of control and there is no subgenome dominance in expression. On the contrary, we find evidence of genetic adaptation to ‘stable’ life as a polyploid, in particular changes to the meiotic machinery and in interactions with the plastids. These findings made in natural (but not synthetic) A. suecica, together with the observation that experimentally generated A. suecica is often unviable and does exhibit evidence of genome rearrangements, similar to the young allopolyploid species in Tragopogon and monkeyflower, suggest that the most important bottleneck in polyploid speciation may be selective. If this is true, domesticated polyploids may not always be representative of natural polyploidization. Darwin famously argued that evolution is gradual126—we suggest that natural polyploids are no exception from this, but note that many more species will have to be studied before it is possible to draw general conclusions.

## Methods

### PacBio sequencing of A. suecica

We used genomic DNA from whole rosettes of one A. suecica (ASS3) accession to generate PacBio sequencing data. DNA was extracted using a modified PacBio protocol for preparing Arabidopsis genomic DNA for size-selected approximately 20-kb SMRTbell libraries. In brief, whole-genomic DNA was extracted from 32 g of 3–4-week-old plants, grown at 16 °C and subjected to a 2-day dark treatment. This generated 23 μg of purified genomic DNA with a fragment length of more than 40 kb for A. suecica. We assessed DNA quality with a Qubit fluorometer and a Nanodrop analysis and ran the DNA on a gel to visualize fragmentation. Genomic libraries and single-molecule real-time (SMRT) sequence data were generated at the Functional Genomics Center Zurich (FGCZ). The PacBio RSII instrument was used with P6-C4 chemistry and an average movie length of 6 hours. A total of 12 SMRT cells were processed, generating 16.3 Gb of DNA bases with an N50 read length of 20 kb and median read length of 14 kb. Using the same genomic library, an additional 3.3 Gb of data was generated by a PacBio Sequel instrument at the Vienna BioCenter Core Facilities (VBCF), with a median read length of 10 kbp.

### A. suecica genome assembly

To generate the A. suecica assembly we first used FALCON127 (v.0.3.0) with a length cut-off for seed reads set to 1 kb in size. The assembly produced 828 contigs with an N50 of 5.81 Mb and a total assembly size of 271 Mb. In addition, we generated a Canu128 (v.1.3.0) assembly using default settings, which resulted in 260 contigs with an N50 of 6.65 Mb and a total assembly size of 267 Mb. Then we merged the two assemblies using the software quickmerge129. The resulting merged assembly consisted of 929 contigs with an N50 of 9.02 Mb and a total draft assembly size of 276 Mb. We polished the assembly using Arrow130 (smrtlink release 5.0.0.6792) and Pilon (v.1.22). For Pilon131, 100 bp (with PCR duplicates removed), and a second PCR-free 250 bp, Illumina paired-end reads were used that had been generated from the reference A. suecica accession ASS3.

### PacBio sequencing of A. arenosa

A natural Swedish autotetraploid A. arenosa accession, Aa4, was inbred in a lab for two generations to reduce heterozygosity. We extracted whole-genomic DNA from 64 g of 3-week-old plants in the same way as described for A. suecica, generating 50 μg of purified genomic DNA with fragment sizes longer than 40 kb in length. The A. arenosa genomic libraries and SMRT sequence data were generated at the VBCF. A PacBio Sequel instrument was used to generate a total of 22 Gb of data from five SMRT cells, with an N50 of 13 kb and median read length of 10 kb. In addition, two runs of Oxford Nanopore sequencing were carried out at the VBCF, producing 750 Mb in 180,000 reads (median 5 kb and 2.6 kb; N50 8.7 and 6.7 kb, respectively).

### Assembly of autotetraploid A. arenosa

We assembled a draft contig assembly for the autotetraploid A. arenosa accession Aa4 using FALCON (v.0.3.0) as for A. suecica. The assembly produced 3,629 contigs with an N50 of 331 kb, a maximum contig size of 2.5 Mb and a total assembly size of 461 Mb. The assembly size is greater than the calculated haploid size of 330 Mb using fluorescence-activated cell sorting (FACS) (see Extended Data Fig. 1), probably because of the high levels of heterozygosity in A. arenosa. The resulting assembly was polished as described for A. suecica.

### Hi-C tissue fixation and library preparation

To generate physical scaffolds for the A. suecica assembly we generated proximity-ligation Hi-C sequencing data. We collected approximately 0.5 g of tissue from 3-week-old seedlings of the same reference A. suecica accession. Freshly collected plant tissue was fixed in 1% formaldehyde. Cross-linking was stopped by the addition of 0.15 M glycine. The fixed tissue was ground to a powder in liquid nitrogen and suspended in 10 ml nuclei isolation buffer. Nuclei were digested by adding 50 U DpnII and the digested chromatin was blunt-ended by incubation with 25 μl of 0.4 mM biotin–14-dCTP and 40 U of Klenow enzyme. T4 DNA ligase (20 U) was then added to start proximity ligation. The extracted DNA was sheared by sonication with a Covaris S220 to produce 250–500-bp fragments. This was followed by size fractionation using AMPure XP beads. Biotin was then removed from unligated ends. DNA fragments were blunt-end-repaired and adaptors were ligated to the DNA products following the NEBNext Ultra II RNA Library Prep Kit for Illumina.

To analyse structural rearrangements, we collected tissue for one other natural A. suecica (AS530), one A. thaliana accession (6978), one A. arenosa (Aa6) and one synthetic A. suecica (F3). Each sample had two replicates. We collected tissue and prepared libraries in the same manner as described above. Illumina reads (125-bp paired-end) were mapped using HiCUP132 (v.0.6.1).

### Reference-guided scaffolding of the A. suecica genome with LACHESIS

We sequenced 207 million pairs of 125-bp paired-end Illumina reads from the Hi-C library of the reference accession ASS3. We mapped reads using HiCUP (v.0.6.1) to the draft A. suecica contig assembly. This resulted in around 137 million read pairs with a unique alignment.

Setting an assembly threshold of ≥1 kb in size, contigs of the draft A. suecica assembly were first assigned to the A. thaliana or A. arenosa subgenome. To do this, we used nucmer from the software MUMmer133 (v.3.23) to perform whole-genome alignments. We aligned the draft A. suecica assembly to the A. thaliana TAIR10 reference and to our A. arenosa draft contig assembly, simultaneously. We used the MUMer command dnadiff to produce 1-to-1 alignments. As the subgenomes are only around 86% identical, the majority of contigs could be conclusively assigned to either subgenome by examining how similar the alignments were. Contigs that could not be assigned to a subgenome on the basis of percentage identity were examined manually, and the length of the alignment was used to determine subgenome assignment.

Finally, we used the software LACHESIS134 (v.1.0.0) to scaffold our draft assembly, using the reference genomes of A. thaliana and A. lyrata as a guide to assist with scaffolding the contigs (we used A. lyrata here instead of our draft A. arenosa contig assembly, as A. lyrata is a chromosome-level assembly). This produced a 13-scaffold chromosome-level assembly for A. suecica.

### Construction of the A. suecica genetic map

We crossed the natural A. suecica accession AS150 with the reference accession ASS3. The cross was uni-directional with AS150 as the maternal and ASS3 as the paternal plant. A total of 192 F2 plants were collected. We multiplexed the samples on 96-well plates using 75-bp paired-end reads and generated data of 1–2× coverage per sample. Samples were mapped to the repeat-masked scaffolds of the reference A. suecica genome using BWA-MEM135 (v.0.7.15). SAMtools136 (v.0.1.19) was used to filter reads for proper pairs and a minimum mapping quality of 5 (-F 256 -f 3 -q 5). We called variants directly from SAMtools mpileup giving a total of 590,537 SNPs. We required sites to have non-zero coverage in a minimum of 20 individuals and filtered SNPs to have frequency between 0.45-0.55 in our F2 population. We removed F2 individuals that did not have genotype calls for more than 90% of the data. This resulted in 183 individuals with genotype calls for 334,257 SNPs.

We applied a hidden Markov model implemented in the R package HMM137 to classify SNPs as homozygous or heterozygous for each of our F2 lines. We then divided the genome into 500-kb non-overlapping windows, and classified each window as homozygous or heterozygous. This was done per chromosome and the resulting file for each chromosome and their markers were processed in the R package qtl138, to generate a genetic map. Markers genotyped in fewer than 100 F2 individuals were excluded from the analysis. Linkage groups were assigned with a minimum log of the odds (LOD) score of 8 and a maximum recombination fraction of 0.35. We defined the final marker order by the best LOD score and the lowest number of crossover events.

We corrected the erroneous placement of a contig at the beginning of chromosome 1 of the A. arenosa subgenome. The misplaced contig was relocated from chromosome 1 to the pericentromeric region of chromosome 2 of the A. arenosa subgenome in A. suecica. Chromosome 2 of the A. thaliana subgenome of A. suecica was previously shown to be largely devoid of intraspecific variation, resulting in few markers for this chromosome. Therefore, this chromosome-scale scaffold was assembled by the manual inspection of 3D-proximity information based on our Hi-C sequencing using the software Juicebox139.

### Gene prediction and annotation of the A. suecica genome

We combined de novo and evidence-based approaches to predict protein-coding genes. For de novo prediction, we trained AUGUSTUS140 on the set of conserved single-copy genes using BUSCO141 separately on A. thaliana and A. arenosa subgenomes of A. suecica. The evidence-based approach included both homology to the protein sequences of the ancestral species and the transcriptome of A. suecica. We aligned the peptide sequences from the TAIR10 A. thaliana assembly to the A. thaliana subgenome of A. suecica, while the peptides from A. lyrata annotation142 (Alyrata_384_v2.1) were aligned to the A. arenosa subgenome of A. suecica using GenomeThreader143 (v.1.7.0). We mapped the RNA-seq reads from the reference accession of A. suecica (ASS3) from the rosettes and flower bud tissues to the reference genome using TopHat144 and generated intron hints from the split reads using the bam2hints extension of AUGUSTUS. We split the alignment into A. thaliana and A. arenosa subgenomes and assembled the transcriptome of A. suecica for each subgenome separately in the genome-guided mode with Trinity145 (v.2.6.6). Separately for each of the subgenomes, we filtered the assembled transcripts using a transcripts per million (TPM) cut-off set to 1, collapsed similar transcripts using CD-HIT146,147 with sequence identity set to 90%, and chose the longest open reading frame from the six-frame translation. We then aligned the proteins from A. thaliana and A. arenosa parts of A. suecica to the corresponding subgenomes using GenomeThreader (v.1.7.0). We ran AUGUSTUS using retrained parameters from BUSCO and merged hints from all three sources, these being: (1) intron hints from A. suecica RNA-seq; (2) homology hints from ancestral proteins; and (3) hints from A. suecica proteins.

RepeatModeler148 (v.1.0.11) was used to build a de novo TE consensus library for A. suecica and identify repetitive elements based on the genome sequence. Genome locations for the identified TE repeats were determined by using RepeatMasker149 (v.4.0.7) and filtered for full-length matches using a code described previously150. Helitrons are the most abundant TE family in both subgenomes.

### Synthetic A. suecica lines

To generate synthetic A. suecica we crossed a natural tetraploid A. thaliana accession (6978, also known as Wa-1) to a natural Swedish autotetraploid A. arenosa (Aa4) accession. Similar to the natural A. suecica, A. thaliana was the maternal and A. arenosa was the paternal plant in this cross. Crosses in the opposite direction were unsuccessful. We managed to obtain very few F1 hybrid plants, which after one round of selfing set higher levels of seed. The resulting synthetic line was able to self-fertilize. F2 seeds were descended from a common F1 and were similar to natural A. suecica in appearance. We further continued the synthetic line to F3 (selfed third generation).

### Synteny analysis

We performed an all-against-all BLASTP search using CDS sequences for the reference A. suecica genome and the ancestral genomes, A. thaliana and A. lyrata. We used the SynMap tool151 from the online CoGe portal152. We examined synteny using the default parameters for DAGChainer (maximum distance between two matches = 20 genes; minimum number of aligned pairs = 5 genes).

### Estimating the copy number of rDNA repeats using short DNA reads

To measure the copy number of 45S rRNA repeats in our populations of different species, we aligned short DNA reads to a single reference 45S consensus sequence of A. thaliana153. An A. arenosa 45S rRNA consensus sequence was constructed by finding the best hit using BLAST in our draft A. arenosa contig assembly. This hit matched position 1571–8232 bp of the A. thaliana consensus sequence, was 6,647 bp in length and is 97% identical to the A. thaliana 45S rRNA consensus sequence. The aligned regions of these two 45S rRNA consensus sequences, determined by BLAST, were used in copy number estimates, to ensure that the sizes of the sequences were equal. The relative increase in sequence coverage of these loci, when compared to the mean coverage for the reference genome, was used to estimate copy number.

### Plant material for RNA-seq

Transcriptomic data generated in this study included 15 accessions of A. suecica, 16 accessions of A. thaliana, 4 accessions of A. arenosa and 2 generations of an artificial A. suecica line (the second and third selfed generation). The sibling of a paternal A. arenosa parent (Aa4) and the maternal tetraploid A. thaliana parent (6978, or Wa-1) of our artificial A. suecica line were included as part of our samples (Supplementary Data 1). Each accession was replicated three times. Seeds were stratified in the dark for 4 days at 4 °C in 1 ml of sterilized water. Seeds were then transferred to pots in a controlled growth chamber at 21 °C. Humidity was kept constant at 60%. Pots were thinned to two to three seedlings after one week. Pots were re-randomized each week in their trays. Whole rosettes were collected when plants reached the seven-to-nine true-leaf stage of development. Samples were collected between 14:00 and 17:00 and flash-frozen in liquid nitrogen.

### RNA extraction and library preparation

For each accession, two to three whole rosettes in each pot were pooled and total RNA was extracted using the ZR Plant RNA MiniPrep kit. We treated the samples with DNAse and performed purification of mRNA and polyA selection using the AMPure XP magnetic beads and the Poly(A) RNA Selection Kit from Lexogen. RNA quality and degradation were assessed using the RNA Fragment Analyzer (DNF-471 stranded sensitivity RNA analysis kit, 15 nt). The concentration of RNA per sample was measured using the Qubit fluorometer. Library preparation was carried out following the NEBNext Ultra II RNA Library Prep Kit for Illumina. Barcoded adaptors were ligated using NEBNext Multiplex Oligos for Illumina (Index Primers Set 1 and 2). The libraries were PCR-amplified for seven cycles, and 125-bp paired-end sequencing was carried out at the VBCF on Illumina (HiSeq 2500) using multiplexing.

### RNA-seq mapping and gene expression analysis

We mapped 125-bp paired-end reads to the de-novo-assembled A. suecica reference using STAR154 (v.2.7), and we filtered for primary and uniquely aligned reads using the parameters–outfilterMultimapNmax 1–outSamprimaryFlag OneBestScore. We quantified reads mapped to genes using–quantMode GeneCounts.

To reduce signals that are the result of cross-mapping between the subgenomes of A. suecica we used A. thaliana and A. arenosa as a control. For each gene in the A. thaliana subgenome we compared the log fold change of gene counts in our A. thaliana population to those in our A. arenosa population. We filtered for genes with a log2(A. thaliana/A. arenosa) below 0. We applied the same filters for genes on the A. arenosa subgenome. This reduced the number of genes analysed from 22,383 to 21,737 on the A. thaliana subgenome, and from 23,353 to 23,221 on the A. arenosa subgenome.

Expression analysis was then further restricted to 1:1 unique homeologous gene pairs between the subgenomes of A. suecica (17,881 gene pairs). Gene counts were normalized for gene size by calculating the TPM. The effective library sizes were calculated by computing a scaling factor based on the trimmed mean of M-values (TMM) in edgeR155, separately for each subgenome. Genes expressed at a low level were removed from the analysis by keeping genes that were expressed in at least three individuals of A. thaliana and A. suecica, at least one individual of A. arenosa and at least one individual of synthetic A. suecica. A total of 14,041 homeologous gene pairs satisfied our expression criteria. As A. suecica is expressing both subgenomes, to correctly normalize the effective library size in A. suecica accessions, the effective library size was calculated as a mean of TPM counts for both subgenomes. The effective library size of A. thaliana accessions was calculated for TPM counts using the A. thaliana subgenome of the reference genome, as genes from this subgenome will be expressed in A. thaliana, and the effective library size of A. arenosa lines was calculated using the A. arenosa subgenome of the reference A. suecica genome. Gene counts were transformed to counts per million (CPM) with a prior count of 1 and were log2-transformed. We used the mean of replicates per accession for downstream analyses.

To compare homeologous genes between the subgenomes in A. suecica we computed a log fold change using log2(A. arenosa homeologue/A. thaliana homeologue). For tissue-specific genes we took genes that showed a log fold change ≥ 2 in expression between two tissues.

For comparing homologous genes between the (sub-)genomes of A. suecica and the ancestral species A. thaliana and A. arenosa, we performed a Wilcoxon test independently for each of the 14,041 homeologous gene pairs. Using the normalized CPM values, we compared the relative expression level of a gene on the A. thaliana subgenome between our populations of A. thaliana and A. suecica. We performed the same test on the A. arenosa subgenome comparing the relative expression of a gene between our populations of A. arenosa and A. suecica. We filtered for genes with an adjusted P value of less than 0.05 (using false discovery rate (FDR) correction). This amounted to 4,186 and 4,571 DEGs for the A. thaliana and the A. arenosa subgenomes, respectively.

Cross-mapping of short RNA reads between the subgenomes of A. suecica was measured by mixing the RNA reads between A. thaliana and A. arenosa individuals to generate ‘in-silico’ A. suecica individuals. We mapped reads from 10 in-silico A. suecica individuals to the A. suecica genome. We compared different RNA-seq pipelines to determine cross-mapping error rates. We mapped reads using STAR154 (v.2.7), HISAT2156 (v.2.1) and EAGLE157. Around 1% of A. thaliana reads map to the A. arenosa subgenome and around 6% of the A. arenosa reads map to the A. thaliana subgenome, regardless of mapping strategy or pipeline (see Extended Data Fig. 6).

### Expression analysis of rRNA

RNA reads were mapped in a similar manner to DNA reads for the analysis of rDNA copy number. Expression analysis was performed in a similar manner to protein-coding genes, in edgeR. We defined the exclusive expression of a particular 45S rRNA gene by taking a cut-off of 15 for log2(CPM) as this was the maximum level of cross-mapping we observed for the ancestral species (see Extended Data Fig. 3).

### Expression analysis of transposable elements

To analyse the expression of transposable elements between species, the annotated TE consensus sequences in A. suecica were aligned using BLAST all vs all. Highly similar TE sequences (more than 85% similar for more than 85% of the TE sequence length), were removed, leaving 813 TE families out of 1,213. Filtered A. suecica TEs were aligned to annotated A. thaliana (TAIR10) and A. arenosa (the PacBio contig assembly presented in this study) TE sequences to assign each family to an ancestral species using BLAST. A total of 208 TE families were assigned to the A. thaliana parent and 171 TE families were assigned to the A. arenosa parent.

RNA reads were mapped to TE sequences using a similar approach as for gene expression analysis using edgeR. TEs that showed expression using a cut-off of log2(CPM) > 2 were kept. A total of 121 A. thaliana TE sequences and 93 A. arenosa TE sequences passed this threshold. We took the mean of replicates per accession for further downstream analyses.

### GO enrichment analysis

We used the R package TopGO158 to conduct GO enrichment analysis. We used the ‘weight01’ algorithm when running TopGO, which accounts for the hierarchical structure of GO terms and thus implicitly corrects for multiple testing. GO annotations were based on the A. thaliana orthologue of A. suecica genes. Gene annotations for A. thaliana were obtained using the R package biomaRt159 from Ensembl ‘biomaRt::useMart(biomart = ’plants_mart’, dataset = ’athaliana_eg_gene’, host = 'plants.ensembl.org').

### Genome size measurements

We measured genome size for the reference A. suecica accession ASS3 and the A. arenosa accession used for PacBio (Aa4), using Solanum lycopersicum cv. Stupicke (2C = 1.96 pg DNA) as the standard. The reference A. lyrata accession MN47 and the A. thaliana accession CVI were used as additional controls. Each sample had two replicates.

In brief, the leaves from three-week-old fresh tissue were chopped using a razor blade in 500 µl of UV Precise P extraction buffer with 10 µl mercaptoethanol per ml (kit PARTEC CyStain PI Absolute P no. 05- 5022) to isolate nuclei. Instead of the Partec UV Precise P staining buffer, however, 1 ml of a 5 mg DAPI solution was used, as DAPI provides DNA content histograms with high resolution. The suspension was then passed through a 30-µm filter (Partec CellTrics no. 04-0042-2316) and incubated for 15 minutes on ice before FACS.

Genome size was measured using flow cytometry and a FACS Aria III sorter with near UV 375-nm laser for DAPI. Debris was excluded by selecting peaks when plotting DAPI-W against DAPI-A for 20,000 events.

The data were analysed using the flowCore160 package in R. Genome size was estimated by comparing the mean G1 of the standard Solanum lycopersicum to that of each sample to calculate the 2C DNA content of that sample using the equation:

$$\begin{array}{l}{\rm{Sample}}\,{\rm{2C}}\,{\rm{DNA}}\,{\rm{content}} = [({\rm{sample}}\,{\rm{G1}}\,{\rm{peak}}\,{\rm{mean}})/({v\;\rm{standard}}\,{\rm{G1}}\,{\rm{peak}}\,{\rm{mean}})]\\ \times \ {{\rm{standard}}\,{\rm{2C}}\,{\rm{DNA}}\,{\rm{content}}}\end{array}$$

We also measured genome size for the reference A. suecica accession ASS3 using the software jellyfish161 and findGSE162 using k-mers (21mers). The genome size estimated was 312 Mb, compared to the 305 Mb estimated using FACS (see Extended Data Fig. 1).

### Mapping of TE insertions

We used PoPoolationTE2100 (v.v1.10.04) to identify TE insertions. The advantage of this TE-calling software to others is that it avoids a reference bias by treating all TEs as de novo insertions. In brief, it works by using discordant read pairs to calculate the location and abundance of a TE in the genome for an accession of interest.

We mapped 100-bp Illumina DNA reads from previous studies20,76,163, in addition to our newly generated synthetic A. suecica using BWA-MEM135 (v.0.7.15) to a repeat-masked version of the A. suecica reference genome, concatenated with our annotated repeat sequences (see ‘Gene prediction and annotation of the A. suecica genome’), as this is the data format required by PoPoolationTE2. Reads were given an increased penalty of 15 for being unpaired. Reads were de-duplicated using SAMtools136 rmdup (v.1.9). The resulting bam files were then provided to PoPoolationTE2 to identify TE insertions in the genome of each of our A. suecica, A. thaliana and A. arenosa accessions. We used a mapping quality of 10 for the read in the discordant read pair mapping to the genome. We used the ‘separate’ mode in the ‘identify TE signatures’ step and a ‘–min-distance −200–max-distance 500’ in the ‘pairupsignatures’ step of the pipeline. TE counts within each accession were merged if they fell within 400 bp of each other and if they mapped to the same TE sequence. All TE counts (that is, the processed TE counts for each accession) were then combined to produce a population-wide count estimate. Population-wide TE insertions were merged if they mapped to the same TE sequence and fell within 400 bp of each other. Coverage of each TE insertion in the population was also calculated for each accession. The final file was a list of TE insertions present in the population and the presence or absence (or ‘NA’ if there was no coverage to support the presence or absence of a TE insertion) in each accession analysed (Supplementary Data 1).

### Assigning ancestry to TE sequences

To examine TE consensus sequences that have mobilized between the subgenomes of A. suecica, we first examined which of our TE consensus sequences (n = 1,152) have at least the potential to mobilize (that is, have full-length TE copies in the genome of A. suecica). We filtered for TE consensus sequences that had TE copies in the genome of A. suecica that are more than 80% similar in identity for more than 80% of the consensus sequence length (n = 936). Of these, 188 consensus sequences were private to the A. thaliana subgenome, 460 were private to the A. arenosa subgenome and 288 TE consensus sequences were present in both subgenomes of A. suecica. To determine whether TEs have jumped from the A. thaliana subgenome to the A. arenosa subgenome and vice versa we next needed to assign ancestry to these 288 TE consensus sequences. To do this we used BLAST to search for these consensus sequences in the ancestral genomes of A. suecica, using the TAIR10 A. thaliana reference and our A. arenosa PacBio contig assembly. Using the same 80%-80% rule we assigned 55 TEs to A. arenosa and 15 TEs to A. thaliana ancestry.

### Read mapping and SNP calling

To call biallelic SNPs we mapped reads to the A. suecica reference genome using the same filtering parameters described in ‘Mapping of TE insertions’. Biallelic SNPs were called using HaplotypeCaller from GATK164 (v.3.8) using default quality thresholds. SNPs were annotated using SnpEff165. Biallelic SNPs on the A. thaliana subgenome were polarized using 38 diploid A. lyrata lines76 and biallelic SNPS on the A. arenosa subgenome were polarized using 30 A. thaliana accessions163 closely related to A. suecica20.

### Chromosome preparation and FISH

Whole inflorescences of A. arenosa, A. suecica and A. thaliana were fixed in freshly prepared ethanol:acetic acid fixative (3:1) overnight, transferred into 70% ethanol and stored at −20 °C until use. Selected inflorescences were rinsed in distilled water and citrate buffer (10 mM sodium citrate, pH 4.8), and digested by a 0.3% mix of pectolytic enzymes (cellulase, cytohelicase, pectolyase; all from Sigma-Aldrich) in citrate buffer for around 3 h. Mitotic chromosome spreads were prepared from pistils as previously described166 and suitable slides were pretreated by RNase (100 µg ml−1, AppliChem) and pepsin (0.1 mg ml−1, Sigma-Aldrich).

For identification of A. thaliana and A. arenosa subgenomes in the allotetraploid genome of A. suecica, FISH probes were made from plasmids pARR20–1 or pAaCEN containing 180 bp of A. thaliana (pAL) or around 250 bp of A. arenosa (pAa) pericentromeric repeats, respectively. The A. thaliana BAC clone T15P10 (AF167571) bearing 45S rRNA gene repeats was used for in situ localization of nucleolar organizer regions (NORs). Individual probes were labelled with biotin–dUTP, digoxigenin–dUTP and Cy3–dUTP by nick translation, pooled, precipitated and resuspended in 20 µl of hybridization mixture (50% formamide and 10% dextran sulfate in 2× saline sodium citrate (2× SSC)) per slide as previously described96.

Probes and chromosomes were denatured together on a hot plate at 80 °C for 2 min and incubated in a moist chamber at 37 °C overnight. Post-hybridization washing was performed in 20% formamide in 2× SSC at 42 °C. Fluorescent detection was as follows: biotin–dUTP was detected by avidin–Texas Red (Vector Laboratories) and amplified by goat anti-avidin–biotin (Vector Laboratories) and avidin–Texas Red; digoxigenin–dUTP was detected by mouse anti-digoxigenin (Jackson ImmunoResearch) and goat anti-mouse Alexa Fluor 488 (Molecular Probes). Chromosomes were counterstained with DAPI (4’,6-diamidino-2-phenylindole; 2 μg ml−1) in Vectashield (Vector Laboratories). Fluorescent signals were analysed and photographed using a Zeiss Axioimager epifluorescence microscope and a CoolCube camera (MetaSystems). Images were acquired separately for the four fluorochromes using appropriate excitation and emission filters (AHF Analysentechnik). The monochromatic images were pseudo-coloured and merged using Adobe Photoshop CS6 software (Adobe Systems).

### DAP-seq enrichment analysis for transcription factor target genes

We downloaded the target genes of transcription factors from the plant cistrome database (http://neomorph.salk.edu/dap_web/pages/index.php), which is a collection of transcription-factor-binding sites and their target genes, in A. thaliana, based on DAP-seq167. To test for enrichment of a gene set (for example, the genes in A. thaliana cluster 2 on Fig. 5) for target genes of a particular transcription factor, we performed a hyper-geometric test in R. As a background we used the total 14,041 genes used in our gene expression analysis. We then performed FDR correction for multiple testing to calculate an accurate P value of the enrichment.

### Reporting Summary

Further information on research design is available in the Nature Research Reporting Summary linked to this article.