The epigenome underlying a novel and non-parental stress-adaptive phenotype created by transgressive segregation

doi:10.21203/rs.3.rs-5307002/v1

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The epigenome underlying a novel and non-parental stress-adaptive phenotype created by transgressive segregation

https://doi.org/10.21203/rs.3.rs-5307002/v1

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Transgressive segregation offers a non-reductionist strategy for breeding crops with novel mechanisms for complex adaptive traits through the omnigenic paradigm. While this phenomenon has been linked to complementation and epistatic effects, the contribution of the epigenome is unknown. We examined a well-characterized recombinant inbred population (F₉) of Oryza sativa (rice) derived from parents of wide genetic contrast (IR29/indica x Pokkali/aus) to understand the impact of mild genomic shock to the epigenomic and chromatin landscapes of a transgressive segregant with superior tolerance to hyper-salinity stress. Analysis of the genome, methylome, Topographically Associating Domain (TAD), and transcriptome across parents and recombinants revealed that the novelty of the outlier progeny is associated with peculiar features being an outcome of recombination between the longer chromatins of indica and shorter chromatins of aus. This is characterized by the downsizing of recombinant genome due to the shedding of transposon loci and other repetitive sequences. Transposon shedding was largely responsible for the most extreme hypomethylation of the transgressive epigenome in all of CG, CHG and CHH contexts but with the most peculiarity in the CHH context affecting both the intergenic and genic spaces. The consequence was a novel chromatin profile characterized by uniform segmentation of TADs in all affected chromosomes. This defining epigenomic profile of the transgressive segregant positively correlated with the reduction of stochastic variability in the salinity stress response transcriptome especially the genes affected by the non-parental TAD segmentation, many of which function in stress-related and growth-related responses.

Genomic Shock

Transgressive Segregation

Epigenome

DNA Methylation

Topologically Associating Domains

Transcriptome

Stochastic Gene Expression

Phenotypic Novelty

Adaptive Traits

Hyper-salinity Tolerance

Oryza sativa

The grand challenge to agriculture in the 20th century was to elevate the yield potential of staple food crops to evade the threats of widespread hunger and malnutrition due to poverty and population explosion in the developing world. The political response was science-based crop breeding to create ideal combinations of traits out of the genetic potentials of traditional landraces and unimproved varieties. The goal was to maximize the yield potential under environments where soil health, nutrients, water, and other environmental factors contributing to plant productivity were still ideal compared to what they are today [1]. The outcomes were the semi-dwarf, photoperiod-insensitive, early-maturing, and photosynthetically efficient modern varieties of rice, wheat, and maize with excellent harvest index under well-managed environments. This success story was made possible by the brilliant use of Mendelian genetics for idiotype breeding – the core paradigm of the Green Revolution [2, 3].

A much grander challenge in the 21st century is to preserve or even surpass the yield frontier achieved during the Green Revolution. The challenge is to mitigate the threats of climate change and deteriorating water and nutrient resources that continue to undermine the otherwise ideal interaction between the genetics of the Green Revolution ideotypes and their optimal environments. There is a growing appreciation of the need to reinvent a new genetic paradigm for creating ‘novel phenotypes’ beyond what is possible through Mendelian genetics, transgenic, and gene editing.

Evolutionary biology has long embraced the importance of the so called ‘genetic novelties’ as major drivers of adaptive speciation in plants [4–8]. A long-standing theory is that rare outlier individuals representing such novelties in natural populations are evolutionary innovations with higher likelihood to create new lineages when they successfully occupy their own ecological niche without much competition. These novelties would outcompete the great majority of the wider population under certain marginal environments because of their higher levels of fitness [9, 10]. This evolutionary theory must be embraced to enhance the innovative capacity of current crop breeding paradigms for resilience to marginal environments.

Two possible mechanisms have been pursued to understand the underpinnings of such novelties. First is the impact of macromutation and saltation speciation, resulting from changes in ploidy level created by rare hybridization between two distinct but closely related diploid strains or species. If the mating produces fertile progenies, the outcome of fixation would be an extensive gene duplication from polyploidization, which could lead to morphological, developmental or physiological innovations with adaptive functions, raising the individual’s fitness to a new environment [4, 6, 7, 11]. The second mechanism is also an outcome of rare natural hybridization between widely contrasting individuals but independent of saltation mutation. An example is the phenomenon of ‘transgressive segregation’ characterized by rare individuals across a biparental mating population whose phenotypes are beyond the parental range. Gain of novel phenotypes in transgressive segregants is similar to overdominance effect in heterotic F₁ hybrids (hybrid vigor), except that transgressive traits are trans-generationally stable while heterotic traits are not. Transgressive individuals are rare, but their likelihood is higher when the parents are of wider genetic distance [4, 12, 13].

Directed mating of widely contrasting parents (intraspecies or interspecies) is a core strategy in plant breeding, thus transgressive segregants are commonly observed in large populations where breeders select for desired trait combinations. While the exact mechanisms behind transgressive individuals remain an enigma, classical genetic studies have uncovered evidence that they can be created by complementation and epistatic interactions [4, 14]. These effects are highly possible through the vast permutations by which the contrasting parental alleles could be reshuffled by recombination to create the most novel and rarest combinations [15–17].

A largely unexplored mechanism that could create transgressive traits involves the potential impacts of genomic shock to the epigenomic landscape of recombinants [3]. Genomic shock occurs when two widely contrasting haploid chromosome sets with less-than-optimal homologies are brought together in the same nucleus and undergo synaptic pairing during meiosis [18–20]. An important theory is that genomic shock is a perturbation of optimal synapsis and crossing-over, which may then disturb the intrinsic control of dormant transposons. Such disturbance is believed to have drastic impacts to the epigenomic landscape and chromatin architecture by altering the patterns of DNA methylation and histone organization [21, 22]. Extreme cytogenetic consequences of genomic shock could also lead to hybrid sterility or zygotic abortion [23, 24].

In this study, we examined the potential contributions of the epigenome to a transgressive trait. We addressed the question of whether genomic shock could stably alter the epigenome, and whether such alteration could create the phenotypic novelties of a transgressive segregant. We investigated a well-phenotyped recombinant inbred population of rice (IR29 x Pokkali F₉) derived from the mating of parents from distinct evolutionary clades of Oryza sativa, where the hyper-salinity-sensitive IR29 represents the indica clade and the hyper-salinity-tolerant Pokkali represents the aus clade [25–29]. Indica and aus represent an adequately wide genetic contrast to expect some sort of genomic shock during recombination as evidenced from anecdotal reports of partial hybrid sterility [30, 31]. We identified a rare transgressive segregant with super-tolerance to hyper-salinity that cannot be fully explained by the major QTL SalTol [28, 32]. We describe the peculiar epigenomic landscape of this transgressive segregant in terms of transposon composition, DNA methylation, and heterochromatin profile.

Analysis of transgressive segregation for hyper-salinity tolerance in the IR29 (indica) x Pokkali (aus) recombinant inbred population (F₉) under greenhouse conditions was described earlier [28, 32, 33]. Phenotyping of 139 recombinant inbred lines revealed major phenotypic categories and their contributing morpho-physiological traits. FL478 is equally tolerant as its parent Pokkali, which is the origin of the SalTol QTL. FL454 is equally sensitive as its parent IR29. FL510 is superior to both FL478 and Pokkali, and while all three genotypes contain the SalTol allele from Pokkali, FL510 is transgressive super-tolerant. FL499 is inferior to both IR29 and FL454 hence transgressive super-sensitive.

Agronomic superiority of the transgressive progeny

To confirm the transgressive nature of FL510 as established under EC = 9 to 12 dSm^− 1 in the greenhouse, we tested the population in the field at the International Rice Research Institute (IRRI), Philippines during the wet season of 2023–2024. Tests were performed under Artificial Salinity Field at IRRI headquarters in Los Banos, Laguna, where field plots were irrigated with artificial saltwater, and under Natural Salinity Field in the coastal town of Infanta, Quezon (Philippine Sea) with seawater irrigation. The population was subjected to moderate (EC = 9 dSm^− 1), severe (EC = 10 to 12 dSm^− 1) and lethal (EC = 14 to 16 dSm^− 1) levels of hyper-salinity. Results reiterated the transgressive nature of FL510, which is the only progeny that survived under lethal hyper-salinity (Fig. 1). Agronomic performance indicated the outlier nature of FL510.

Non-parental genomic novelties created by recombination

IR29 is a typical short-duration indica released as a high-yielding variety from multi-parent hybrid selections during the Green Revolution. Pokkali is a photoperiod-sensitive landrace historically grown in the marshlands and river basins of South Asia affected by brackish water runoffs [34]. Pan-genome analysis showed that the typical indica subspecies has a generally larger genome ranging from 376Mb to 380Mb compared to the typical japonica subspecies which range from 386Mb to 393Mb. The aus subgroup where Pokkali is classified under is a clade between indica and japonica with a typically smaller genome than indica, e.g., 383Mb for cv Natel Boro [35] (Additional Files 1 to 5).

Genome size prediction based on k-mer analysis showed that IR29 is similar to the indica reference from 425 to 445Mbp, and Pokkali is comparable to the japonica reference at from 415 to 425Mbp (Fig. 2A). While the overall gene content were similar between IR29 and Pokkali, the two genomes were widely contrasting due to the contraction-expansion of repetitive sequences and transposon loci (Fig. 2B). These differences are suggestive of variation in chromatin length between the indica and aus. Chromatin length variation due to expansion-contraction of non-coding regions contributes to imperfect synapsis of homologous chromosomes during prophase-1, an event that is often associated with genomic shock [24, 30, 31].

We observed a general trend of genome downsizing in the recombinants of IR29 x Pokkali characterized by the shrinkage of repetitive and transposon loci (Figs. 2A, 2B). Most notably, the transgressive super-tolerant FL510 had the smallest genome and highest magnitude of downsizing. K-mer analysis also confirmed the homozygosity of recombinants, consistent with the expectation of fixed and stable recombinant genomes after eight generations of selfing (Fig. 2C). Homozygosity eliminates the possibility that the outlier nature of FL510 could be due to overdominance effects.

We assembled the IR29 and Pokkali genomes using the most closely related genotypes IR8 and N22 as respective references [36] (Additional Files 6 to 8). IR29 and Pokkali genomes were compared to each other to establish locus synteny across the entire genome. From this comparison, we observed that the differences were not only due to the contraction-expansion of repetitive and transposon loci but also because of microsynteny disruptions driven by rearrangements and expansion-contraction (Additional Files 9 to 11).

We performed a locus-by-locus genotyping-by-sequencing of the recombinant genomes by sequence identity to assign the parental origins of genomic loci based on sequence homology and synteny. Genotypic profiles indicate that the two tolerant recombinants (FL478, FL510) are more similar to each other than to their sensitive siblings (FL499, FL454) as shown by similarity dendgrams in each chromosome (Fig. 2B). Notably, FL510 had the highest allelic contribution from Pokkali at 26,083 loci in comparison to only 23,910 loci from IR29 (Fig. 3A). FL499 and FL454 had the highest contributions from IR29 at 25,808 and 27987 loci, respectively.

IR29 is a longer genome due to expanded repeat and retrotransposon loci, while Pokkali is a shorter genome due to contracted repeat and retrotransposon loci (Fig. 2A). While considerable genome downsizing was evident in all recombinants, there were also significant rearrangements in many loci across all chromosomes. A locus was considered ‘conserved’ when allele-called at high certainty (threshold of ≥ 90% recovery of parental loci) to the parents. A locus was considered ‘IR29-type’ or ‘Pokkali-type’ when the similarity to one parent is 5% higher than the other. ‘Non-parental’ and ‘Unmapped’ loci are attributed largely to size contraction and structural rearrangements that caused extensive disruptions in microsynteny to the point that the loci can no longer be reliably allele-called to either parent (Fig. 3A). It appears that the difference in chromatin sizes between indica and aus may have caused a mild genomic shock that led to downsizing and microsynteny disruption in the recombinant progenies.

We observed a bias in the transmission of shorter loci from either parent to the recombinants. There is a high propensity for the contracted loci from either indica (IR29) or aus (Pokkali) genome to be preferentially passed on to recombinants. This bias is most pronounced in FL510, having the smallest genome of all the recombinants (Fig. 3B). The highest frequency of recombination is also evident in FL510 (Fig. 3C; Additional File 12). The highest magnitude of genome downsizing in FL510 due to repeat and transposable element loci contraction and microsynteny disruption is an outcome of higher recombination frequency and genomic shock effects.

Shedding from the repetitive and retrotransposon loci in recombinants

We scrutinized the loci that were most frequently shed in the recombinant genomes by examining the types of transposons and other sequence motifs that were affected by locus contraction (Figs. 2A, 2C). We mapped the transposons from the IR29 and Pokkali genomes into the recombinant genomes to predict genome exchanges by recombination (Figs. 2B, 3A). Results showed the predominance of copia and gypsy LTR-retrotransposons along with other unclassified subclasses of LTRs and nested retrotransposons in the genomes of both parents and recombinants (Additional File 13). It is also evident that copia and gypsy heavily populated the shed regions. The shedding of copia and gypsy loci are most pronounced in the most downsized genome of transgressive FL510, which is about 10Mb smaller than the genome of Pokkali. Taking that into account, shedding of retrotransposon regions explains about 50% of the downsizing of recombinant genomes, with FL510 having the highest cumulative shedding (Fig. 4B).

In-depth scrutiny of the enrichment of repetitive elements in the shed regions by permutation test showed different magnitudes of losses and retention of parental elements in the recombinant genomes (Fig. 4C). LINEs appeared to be retained across all recombinants while copia from IR29 appeared to be shed at the highest magnitude in FL510. Shedding of gypsy from Pokkali contributed largely to the downsized genome of FL510. Unclassified LTR-type retrotransposons (RLX) had parent-specific pattern of retention, while SINEs are very well retained regardless of parental origin. For DNA transposons, cacta is shed heavily while harbinger/mutator have higher propensity to be retained.

By permutation test, we also examined the enrichment of repetitive elements within the loci that are unique to the recombinants as consequences of new insertion and duplication events. In Fig. 4D, positive values indicate the association with the regions that are unique to the recombinant genomes while negative values indicate that these loci are not contributing to the disturbance of parental substrates in recombinants. LINEs have the propensity to be retained in the recombinant genomes. Interestingly, copia appeared to have high retention in the transgressive FL510, and this is largely contributing to its overall uniqueness relative to its other recombinant siblings. Gypsy is very similar in all recombinants except FL510.

Shedding from transposon loci led to genome-wide hypomethylation

Methylation of cytosine residues is an evolutionarily conserved property of eukaryotic genomes as the primary mechanism for taming the resident transposons. On average, indica genome is about 38% transposons while aus genome is about 46% transposons [36, 37]. DNA methylation is fluid in nature where C-methylation from non-coding and repetitive regions could spread to the periphery or into the body of genic spaces [38, 39]. Cytosine methylation in plants occur in three context, i.e., CG, CHG, CHH, where CG and CHG methylation are predominant in the repetitive/transposon, intergenic, centromeric, and telomeric regions, while CHH is more predominant in the facultatively heterochromatic genic spaces [38]. Having established that recombination between indica and aus led to the shrinkage of non-coding and transposon loci, we addressed the question of whether genome downsizing has significant impacts to DNA methylation.

Bisulfite-seq assembly indicated that the indica-type genome of IR29 and the aus-type genome of Pokkali have widely divergent methylome landscapes in all contexts. Differences in the overall sizes of genomes and their transposon contents translate to significant variation in DNA methylation (Fig. 3A; Additional File 13). There is a general trend of significant hypomethylation in the recombinant genomes in all contexts, with the transgressive FL510 exhibiting the highest magnitude of overall hypomethylation (Fig. 5A). Each recombinant genome has a unique pattern of hypomethylation with FL510 being the most extreme. FL499 had the most similar hypomethylation to FL510, particularly in CG and CHG contexts as indicated by the similarity dendrograms across many chromosomes (Fig. 5A). Notably, FL510 is a clade of its own in CHH context, indicating its unique CG and CHG hypomethylation profiles (Fig. 5B). The loci affected by CHH-hypomethylation were distinct between FL510 and FL499. The unique CHH-hypomethylation profile of FL510 is highly correlated with its most highly recombinant nature. Much of CHH-hypomethylated loci in FL510 also co-localized with non-parental variant loci (Figs. 5B, 5C).

Variation in hypomethylation across the sibling recombinants was lowest in CG context and highest in CHH context. This implies that the hypomethylation signatures of each distinct recombinant have important implications to gene functions by virtue of CHH-methylation polymorphism in genic regions. For instance, when the genic space methylation profiles were compared with respect to all protein-coding genes, transcription factor-encoding genes, and genes in the SalTol QTL, the unique CHH-hypomethylation of FL510 stands out across the upstream regions, gene bodies and downstream regions (Fig. 5D). The most CHH-hypomethylated group of genes in FL510 was enriched with biological processes associated with the regulation of growth and development.

We also compared the small RNA (sRNA) profiles of the leaf transcriptomes to understand the potential significance of sRNA expression to the observed hypomethylation of recombinant epigenomes. Normalized abundances indicate that 24-nt sRNAs are the most predominantly expressed class (Fig. 6A, top panel). This class plays a key role in RNA-directed DNA methylation (RdDM) of the non-coding and retrotransposon-rich regions [39, 40]. Evidently, expression of 24-nt sRNAs was significantly higher in the parents compared to their hypomethylated recombinant progenies. Notably, the transgressive super-sensitive FL499 exhibited the lowest expression. Based on occurrence of CG/CHG/CHH motif in the sRNA sequences, it appears that the 24-nt sRNAs that were most abundantly expressed in the parents are being targeted to genomic regions where CHH-methylation sites are also very high (Fig. 6A, bottom panel). This trend is further reiterated by the lower range of mapped 24-nt sRNA on the CHH-hypomethylated and CHH-hypermethylated loci of FL510. The proportion of genomic loci with reduced 24-nt sRNA and CHH-hypomethylation was highest in FL510 (23%) and most consistent in the most CHH-hypomethylated loci in FL510, indicative of uncoupling to RdDM (Fig. 6B).

Novel chromatin landscapes predicted from Topologically Associating Domains

Methylation and demethylation of cytosine residues have a profound influence on localized interactions along the DNA. The Topologically Associating Domains (TADs) formed by localized chromatin folding are important components of the third dimension of the genome. DNA sequences within a TAD interact more frequently with each other than with other sequences outside of TAD boundaries. TADs also tend to overlap with the units of recombination. Formation of chromatin loops affect the accessibility of cis-regulatory components of transcriptional initiation (enhancers, silencers, insulators) to trans-acting factors (activators, repressors) in both positive and negative manner [41, 42]. In vertebrates, TAD variation has been implicated with developmental innovations [43, 44].

With the observed genome-wide extreme hypomethylation in in the transgressive hyper-salinity super-tolerant FL510, we investigated its potential higher-order consequences by modeling the chromatin configuration with respect to TAD distribution across the twelve chromosomes. We examined the TAD profiles using normalized Hi-C linkages with a common threshold to identify the relative saturation of domains. Results indicate that the TAD profiles of recombinants cannot be attributed directly to the contributions of parental chromatin profiles. Rather, the recombinant epigenomes exhibited various types of uniquely non-parental TAD profiles (Fig. 7A, top panel). The most notable was the extreme and distinctively uniform segmentation of TADs in the transgressive FL510. This distinctive TAD characteristic of FL510 is evident across all twelve chromosomes (Additional Figures Files 14 to 37). Despite the differences in the degree of segmentation, the overall structure of chromatin as measured by the profiles of A/B compartments were quite conserved, implying that TAD segmentation is site-specific (Fig. 7A, bottom panel).

To ensure an effective noise reduction in Hi-C-based TAD prediction, we carried out our inter-genotypic comparison through a ‘four-reference-approach’ instead of just using either IR29 or Pokkali genome as direct references. We used IR29 genome to detect TADs in IR29 and in the other five genotypes, i.e., IR8-parent. In parallel, we used Pokkali to detect TADs in Pokkali and in the other five genotypes, i.e., N22-parent. Moreover, we assembled working references for each of the four recombinants relative to IR29, i.e., IR29-native and Pokkali, i.e., Pokkali-native, and then used them as references to detect TADs in individual genotypes to account for the Hi-C mapping in non-parental segments (Fig. 7B).

Results of this prediction further reiterated the most uniquely segmented nature of TAD profile in FL510, both in terms of relative number and size of TADs (Fig. 7B). More segmentation translates to smaller TADs while less segmentation translates to larger TADs. Higher segmentation of TADs brings higher possibility for uncoupling with insulators, which could mean positive effects to transcription initiation. The two sensitive recombinants FL454 and FL499 had significantly lower levels of segmentation while the tolerant recombinant FL478 is in between (Figs. 7A, 7B). To address the possibility that the extreme TAD segmentation in FL510 was a consequence of the global loss of DNA methylation, we investigated the degree of methylated and unmethylated cytosines around 500-kb windows surrounding the TAD triangles in all of CG, CHG, and CHH contexts (Fig. 7A). Results indicate that the extreme CHH-methylation in FL510 contributed to its highest degree of TAD segmentation (Fig. 7B).

Studies in vertebrates have shown that CTCF-binding sites are highly enriched in TAD borders, and differential binding of trans-acting factors to these sites are methylation-sensitive [45]. Although the CTCF ortholog in plant is not established, CTCF-binding motifs functioning as insulators are predicted to be enriched with gypsy retrotransposons in Arabidopsis [46]. In this context, we examined if the characteristic shedding of gypsy may have contributed to the extreme hypomethylation and TAD segmentation of the FL510 epigenome. Figure 7D shows the propensity for gypsy elements to be enriched in the TAD borders and this trend is consistent with the unique TAD profiles. For example, TAD borders of FL510 are enriched in O. rufipogon-type gypsy from IR29 and O. nivara-type gypsy from Pokkali. TAD borders of FL499 are enriched in O. punctata-type gypsy from IR29 and O. barthii-type gypsy from Pokkali, all of which suggest a direct link of TAD formation to the shedding of retrotransposons in recombinant epigenomes.

Impact of novel TAD signatures to the transcriptome

We classified the different categories of parent-to-progeny modifications in TAD profile. We identified the most predominant TAD categories using both the indica (IR29) and aus (Pokkali) references. The major categories of TAD included: a) ‘Retained’ in which > 90% of parental TAD is identified in the same locus as in the recombinants, which is most enriched in the transgressive FL510; b) ‘Segmented’ in which one parental TAD is associated with multiple TADs in recombinants, which is most enriched in FL510; c) ‘Merged’ is the opposite of segmented and most enriched in FL499; d) ‘Lost’ is a parental TAD that is no longer traceable in recombinants, which is most enriched in FL499; and e) ‘New’ in which the inter-TAD regions in parent are associated with a new TAD in recombinants, most enriched in FL510 (Fig. 8A).

Chromatin state has profound effects to the plasticity and stochasticity of gene expression by virtue of the openness or availability of transcriptional landing pads to trans-acting factors influencing enhancer-gene interactions. While rapid changes in gene activity may contribute to adaptation to various conditions, instability due to hyper-induction could compromise the modulation and economy of steady-state transcription. Under hyper-induction, a significant proportion of the transcriptome is dedicated towards non-coding RNA for post-transcriptional and translational regulation, which is critical to the maintenance of steady-state and homeostatic conditions [47–49].

To understand the impact of TAD modification to the relative stability of transcript abundances in the recombinants, we first identified the gene loci under each TAD category (Additional Files 38, 39). We examined the temporal fluctuation in transcript abundances from one time-point to the next across a series as a measure of relative stability of expression (stochasticity) during a period of 144 hours before and during exposure to hyper-salinity stress (0, 24, 48, 72, 144 hr). FL510 along with FL499 had the most stable and robust transcription profiles (i.e., least fluctuation from one time-point to the next, hence lowest stochastic variability). This is shown by the low relative coefficient of variation for temporal transcript abundance fluctuation for a specific TAD category (Fig. 8B).

Venn diagrams show the shared and unique genes with low stochasticity across recombinants for each TAD category (Fig. 8C). FL510 and FL499 had the highest number of genes with uniquely low stochastic variability. FL510 exhibited the highest proportion of genes with uniquely low stochastic variability (i.e., 76–78% of stable genes are unique to FL510) for the ‘Segmented’ TAD category, which represents its most defining chromatin state at 21% overall enrichment relative to the 16%, 3%, and 3% enrichment in its siblings FL478, FL499, and FL454, respectively (Fig. 8A, 8B).

The other TAD categories that were most predominant in FL510 include the ‘Retained’ and ‘New’ categories at 7% and 4%, respectively (Fig. 8A). The total number of uniquely stable genes was also highest in FL510 for these TAD categories at 76–78% and 44–65%, respectively (Fig. 8C). In contrast to FL510, the ‘Merged’ and ‘Lost’ categories defined FL499 the most at 56% and 7% enrichment, respectively (Fig. 8A). FL499 is the second genotype with the least stochastic variability after FL510 (Fig. 8B). Consistent with these trends, the ‘Merged’ and ‘Lost’ TADs also had the highest percentages of stable genes that are unique to FL499 at 54–55% and 44–74%, respectively (Fig. 8C). Integrated analysis of TAD profile and transcriptome datasets showed a strong positive correlation between TAD enrichment across categories, low stochastic variability of gene expression, and genotype-dependence of the number of uniquely stable genes under the TAD.

Physiological implications of TAD-effects to the transcriptome

Robust gene expression associated by the signature TAD modification in FL510 are generally enriched with functions associated with the regulation of stress-related and growth and development-related responses (Fig. 8D; Additional File 39). These robustly expressed genes are consistent with the observed phenotypic novelty of FL510 [28, 32]. For instance, gene ontologies associated with the regulation of cell cycle, mitosis, and cell wall organization, and the establishment of building blocks for secondary cell walls are significantly enriched in the genomic regions where the signature segmented TAD of FL510 chromatin are also most enriched. Examples include attributes related to plant architecture such as cyclin-related genes (GO:0000079 and GO:0016592), expansins (GO:0009664) and xyloglucan fucosyltransferases (GO:0008107). It appears that the stable expression of these genes under hyper-salinity stress are important contributors to the novel ideotype of FL510, which imparted its novel stress-adaptive morphology and resilience of growth and development under prolonged periods of hyper-salinity stress [28, 32]. The characteristic segmented TAD of FL510 is also enriched with gene ontologies associated with stomatal regulation (GO:0010119; plectin-related genes). We have reported earlier that low stomatal conductance was a defining characteristic of FL510 thereby allowing its ability to efficiently regulate water loss and transpiration [32].

Gene ontologies associated with processes involved in the mitigation of cellular ionic toxicity effects are also significantly enriched in the genomic regions under the segmented TADs of FL510 chromatin (Fig. 8D). These include regulatory genes involved in calcium signaling (GO:0005516; calmodulins), ethylene-mediated stress signaling (GO:0051740), and stress-related kinases (GO:0048544; S-domain receptor kinases). Furthermore, the enrichment of genes associated with urea transport (GO:0071705 and GO:0015204) are also relevant to cellular damage repair mechanisms by virtue of their direct roles in polyamine and proline biosynthesis and maintenance of foliar chlorophyll stability [50, 51]. As expected, genes involved in potassium transport (GO:0015079, high-affinity K⁺ transporters) are also among those that were enriched in the segmented TAD regions of FL510 chromatin. Taken together, the enrichment of relevant gene ontologies under the characteristic segmented TAD of FL510 chromatin are consistent with the ideotype and physiological novelties of FL510 as previously reported [28, 32, 33].

The transgressive super-sensitive FL499 also exhibited a drastic TAD modification relative to its parents with significant enrichment for the ‘Merged’ category, which is the opposite of the signature ‘Segmented’ TAD of FL510. Genomic regions associated with the ‘Merged’ TADs of FL499 were enriched with gene ontologies associated with trehalose biosynthesis (GO:0005992), response to DNA damage (GO:0006974), response to photo-oxidative damage (GO:0080183), and genes associated with cellular dehydration response including dehydrins (GO:0009627 and GO:0009415). Genes involved in Na⁺ toxicity response such as K⁺ transporters (GO:0006813; shaker/shaker-like K⁺ channels; total of 13 genes) were also enriched (Fig. 8D). While the expression of these genes may imply significance to defense, components related to growth and development that define the adaptive morphology of FL510 appeared to be uncoupled to the defense response components in FL499.

The gene-centric paradigm promises to create superior traits through targeted modification of cellular functions in elite genotypes by transgenic supplementation, complementation, or gene editing [3]. While this paradigm offers a one-shot strategy similar to conventional introgression breeding, its reductionist view underestimates the inherent complexity of organismal-level physiology. This paradigm does not fully embrace the cumulative effects of the entire genome and epigenome, and their intricate synergies [3, 52, 53].

We previously reported several lines of evidence supporting that the full expression of a complex adaptive trait (tolerance to hyper-salinity) in the IR29 x Pokkali recombinant inbred population cannot be fully explained by the effects of major QTL alone [28, 32]. Instead, the phenotypic range across the population could be explained by the synergy of many ‘core’ loci with measurable effects and a multitude of ‘peripheral’ loci distributed throughout the entire genome with immeasurable but additive effects, consistent with the recently proposed Omnigenic Theory [54, 55]. The question left hanging was how to explain the rare phenotypic outliers, which are the transgressive individuals that are either superior or inferior to parents. While often observed in plant breeding populations, phenotypic novelties do occur in natural populations as outcomes of rare wide hybridization events. These novelties are believed to drive adaptive speciation as they provide a substrate for new evolutionary lineages that can successfully occupy their own ecological niches [5, 56–59]. We further hypothesized that the novelty of transgressive segregants is above and beyond the Omnigenic Theory due to the nuanced effects of the epigenome that further elevate the phenotype to another level beyond the inherent effects of genetics.

Epigenomic novelties are outcomes of recombination under mild genomic shock

In plant breeding where F₁ hybrids across wide genetic distance are routinely attempted, partial hybrid sterility in varying magnitudes are not uncommon. Uniparental segregation bias and distortion are the typical consequences in subsequent generations of meiosis. In rice, partial hybrid sterility between indica and japonica and between indica and aus (including those with Pokkali) and skewed segregation are not uncommon based on anecdotal reports from breeders. This phenomenon has been attributed to the effects of mild genomic shock [60–62]. During intra-species hybridization of parents with wide genetic contrasts such as indica and aus, the occurrence of mild genomic shock may be attributed to less than perfect synapsis of homologous chromosomes with significant variation in chromatin length during prophase-1. Imperfect synapsis of homologous indica (IR29) and aus (Pokkali) chromosomes may have been due to significant variation in length in the non-coding and transposon-rich loci. This may have triggered imbalanced cross-overs as indicated by the numerous expansion-contraction loci as well as microsynteny disruption in the recombinants, especially in the non-coding and transposon regions.

Recent studies in Arabidopsis have shown that when two diverse haploid parental genomes are combined in the same nucleus, their DNA methylation profiles are reconfigured after meiotic recombination resulting to hybrid individuals (and their subsequent segregants) with distinctly non-parental methylation profiles [22]. In the IR29 x Pokkali recombinant inbred population, which is the outcome of eight generations of meiosis from the initial F₁ hybrid, we observed a wide range of extreme deviation from parental methylome profiles. Of these deviations, the most peculiar profile appeared to have created a rare phenotypic outlier – the transgressive hyper-salinity super-tolerant progeny FL510. Therefore, a logical conclusion to explain the implications of our observations is that recombination under mild genomic shock during eight generations of meiosis created the extremely downsized genome and extremely hypomethylated epigenome of the transgressive segregant FL510 at F₉ generation.

We uncovered several lines of evidence in support of this conclusion. Differences in the size of homologous chromosomes of IR29 (longer) and Pokkali (shorter) are due mainly to the expansion-contraction of repetitive element-rich regions, especially retrotransposons. Drastic differences in the length of these regions have been shown to influence the fidelity of homologous chromosome pairing (synapsis), affecting the genomic boundaries of crossing-over [63–65]. We also observed indicators of disturbance in normal cross-over between homologous chromosomes as shown by genomic regions with disrupted micro-synteny, and other types of structural rearrangements, which were most peculiar in the transgressive segregant FL510.

It appears that shuffling of the genomes of IR29 and Pokkali during meiotic recombination occurred with an unusually higher than normal rates of unequal cross-overs due to significant size differences of IR29 and Pokkali chromatins. Since the transgressive FL510 was clearly the outcome of the highest frequency of recombination, the rate of unequal cross-over in this recombinant was also the highest. Products of unequal cross-over are the rarest in the population and often escape the resolution of traditional marker-assisted genotyping [66–68]. High recombination frequency as revealed by long-read sequence and TAD segmentation analyses appeared to have triggered the most pronounced genome downsizing effect in the transgressive FL510. Genome downsizing was caused primarily by the shrinkage of repetitive element loci or by the preferential inheritance of shorter repetitive element and transposon alleles from either parent.

DNA methylation is the primary mechanism for taming the resident transposons in the genome. Shedding of repetitive elements and transposons in the recombinants of IR29 x Pokkali positively correlated with the small genome size and novel methylome landscape of FL510, which had the most extreme hypomethylation in all of CG, CHG, and CHH contexts but with the most peculiarity in the CHH context including the genic spaces. The novelty of the FL510 epigenome also directly correlated with its uniqueness at the chromatin-level as evident from the most extreme patterns of TAD segmentation across all hypomethylated chromosomes. This is consistent with earlier observations that CHH-hypomethylation contributes significantly to chromatin TAD border segmentation in tomato ddm1 mutants [42]. Restructuring of TADs causes the uncoupling of enhancers, and consequently, the stability of expression of affected genes could also change [69]. The extreme TAD segmentation observed in FL510 further translated into drastic effects to the transcriptome as manifested by the reduced temporal stochasticity among the genes affected by TAD [70].

Random epigenomic effects contribute to phenotypic novelty

Recombination occurs at random across the genome. It then follows that the modification of the epigenomic landscapes due to recombination is also of random nature where certain recombinants would be rare. A major consequence of the epigenomic novelties of the transgressive FL510 was an effective maintenance of an optimally stable transcriptome with much reduced trade-offs to the inherent control of crucial genes that impart positive morphological and physiological advantages. The hyper-salinity super-tolerant FL510 represents a rare but most ideal epigenomic configuration across the population. Its novel epigenomic signature is a nuanced effect of recombination that created a rare impact to physiology, growth, and development.

Maintenance of homeostasis with minimal trade-offs to growth and development is paramount to robust defense and survival mechanisms [71]. As a critical component of cellular response mechanisms to stress, transcriptional activation and subsequent de novo protein synthesis require higher energy costs at the expense of growth and development-related responses [72]. Effective maintenance and balance of all components of stress response require minimal disturbances and costs to cellular homeostasis (i.e., cellular economy). By virtue of its novel genomic and epigenomic landscapes, the transgressive super-tolerant FL510 had the most robust steady-state transcriptome, and this characteristic is indicative of its fine-tuned and economical stress response mechanism. This is evidently the impact of its uniquely hypomethylated genome that created a novel chromatin landscape that ensured the spatial and temporal availability of genes with crucial roles in defense-related and growth-related responses for de novo transcription initiation.

The stochastic nature of transcriptional activation and repression is costly to cellular energy balance as de novo initiation and termination requires continuous expenditure of enzymes and biosynthetic reagents. Stochasticity of the transcriptional machinery is exacerbated under stress conditions, which translates to greater energy consumption because of further diversion of enzymes and other macromolecules away from the requirements of baseline cellular processes necessary for growth and development. In the transgressive FL510, the stochasticity of the stress response transcriptome is much reduced as a consequence of more uniform chromatin state. This translates to a well-modulated transcriptional machinery where the rate of initiation and termination (hence transcript abundances in time and space) do not fluctuate at extreme levels. This ensures a quick but finely regulated stress response mechanism with significantly reduced trade-offs to energy balance and homeostasis. This is consistent with the observed superiority of FL510 in terms of defense and growth [32].

The importance of a more stable transcriptome in balancing growth and development with stress-related responses has been observed previously in elite breeding lines and heterotic hybrids [73, 74]. Similarly, the importance of the epigenome in enhancing agronomic performance under stressful conditions has also been observed. For example, seed priming and acclimation has been shown to create new epigenetic marks that enhance tolerance to hyper-salinity stress that can persist through generations[75, 76]. Priming prepares the necessary gene expression cascades for quick but tightly regulated activation under stress through DNA and histone modifications [77].

Trans-generational stability of the epigenome of a transgressive segregant

By default, the methylation profiles of progenies would be expected to be within the parental range[78–80]. However, we have uncovered evidence of drastic deviation of recombinant progeny methylation profile as a product of eight generations of meiosis from the original heterozygous F₁ hybrid of the genetically diverse indica and aus parents. The epigenome of the transgressive FL510 had the most extreme hypomethylation compared to parental epigenomes. Our findings are consistent with reports that the epigenomes of genetically distant parents confront each other to create a novel profile. This may occur either through RNA-directed DNA methylation (RdDM) or independent of such mechanism [22]. The recombinant genome of the transgressive FL510 is an extreme mosaic of genomic segments from the widely contrasting indica and aus parents. Hypomethylation and its consequential TAD segmentation are evidently the outcomes of significant shedding of repetitive elements and retrotransposons, as well as other structural rearrangements in the genome. Earlier studies have shown that shedding of repetitive elements and transposons through unequal cross-overs significantly reduce the magnitude of genomic cytosine methylation in all contexts [81].

We have multi-generational data both from laboratory and field experiments (F₉ to F₁₁) indicating that the transgressive phenotype of FL510 is trans-generationally stable. Until we have the trans-generational methylome and Hi-C/TAD modeling data at least from F₉ to F₁₁, we propose several hypotheses. Given that the transgressive FL510 is a recombinant inbred line with virtually negligible level of heterozygosity (hence, a fixed true-breeding line), we predict that its novel epigenomic landscape should be maintained largely unaltered through subsequent meiotic events, because recombination is between two identical epi-haplotypes.

If FL510 is to be hybridized with another homozygous but widely genetically contrasting genotype, new recombination events will erase and will not necessarily reinstate the original epigenomic profile of FL510 in its new recombinant genomic background. This new recombinant will now carry a new mosaic of genomic contributions from FL510 and the other new parent. In other words, the epigenomic landscape of FL510 would be stable as long as it is non-segregating, being a fixed true-breeding line in the F₉ generation. While the baseline DNA methylation especially in the CH and CHG contexts are maintained by maintenance DNA methyltransferase and RNA-directed DNA methylation [40], segregation from a heterozygous genome should drastically affect the overall methylation profiles of individual segregants until homozygosity when the global methylation profile will also be fixed. Therefore, the epigenomic novelty of the homozygous FL510 is evidently fixed and should breed-through in subsequent generations.

Potential applications of epigenomic novelties to plant breeding

It appears that during selection for yield potential and stability across multiple trials and diverse environments, breeders may have unknowingly favored the most optimal configuration of the epigenome that further enhanced the inherent effects of the elite genetics that was directly selected. Harnessing the potential power of epigenomic variation (epi-loci and epi-alleles) to incorporate phenotypic novelties into the crop breeding pipelines especially for complex adaptive traits such as stress tolerance is a new frontier in plant genetics. New cultivars created out of traditional breeding pipelines are typically elite selections from bi-parental or multi-parental recombinant inbred populations and near-isogenic populations, hence mosaic of genomic contributions of diverse origins. These types of genomic backgrounds are typically supplemented with parasexually added traits either from transgene(s) or gene-edited allele(s), a process called genetic fortification by stacking new genes on a true-breeding genomic background [82].

New inter-genotype recombination will alter the inherent organization of the epigenome of a homozygous recombinant individual because of the confrontation effects of diverse epigenomes. Since the epigenomic novelties of homozygous recombinants that confer novel traits would be expected to be trans-generationally unstable with further inter-genotype sexual hybridization, as a way to preserve such epigenomic profile, any elite homozygous selections from the breeding pipeline with a stable epigenome may be further improved without meiotic recombination events. This is possible by stacking single monogenic traits one at a time through transgene insertion or targeted gene editing. This approach will prevent the disruption of the stable epigenomic landscape especially in the non-coding space of the genome that may be caused by the reintroduction of heterozygosity and their segregation through subsequent meiotic events. This strategy could potentially offer new ways to utilize the stable epigenomic novelties of homozygous recombinants derived from wide intra-species or inter-species hybridization in plant breeding. The key is that complex traits in stable epigenomic variants will remain trans-generationally stable in the absence of any environmental effects as long they remain in homozygous condition.

We uncovered a new foundation of the molecular basis of transgressive segregation with far-reaching impacts to crop breeding beyond gene-based and genomic selection. Non-parental phenotypic novelties which are important tools of adaptive evolution are beyond the inherent effects of genetics alone, and a significant portion of the full potential of a genetic donor is hidden beyond the direct effects of the genome to the phenotype. Rather, deviation from parental phenotypic range is driven to a significant extent by the alteration of the epigenome when two widely contrasting genomic architectures recombine under genomic shock to create non-parental methylome and chromatin landscapes. Novel methylome and chromatin landscapes are due to the contraction-expansion of transposon loci and other types of repetitive elements, leading to novel patterns of gene expression and phenotypic novelties. The results of this investigation should inspire a paradigm shift in plant breeding that epigenomic changes can cause drastic deviations from parental phenotypic range, which are stable through generations.

Plant materials and hyper-salinity stress experiments in the field

The study population was a selection of 45 recombinant inbred lines at F₉ generation (RILs) along with their salt-sensitive indica parent (IR29) and salt-tolerant aus parent (Pokkali). This subset was a selection from the original F₈ population of 139 RILs that span the spectrum of tolerance at seedling and pre-flowering stages based on earlier greenhouse tests at EC = 9 to 12 dSm^− 1 [28, 32, 83]. Phenotypic evaluation was performed during the wet season of 2023–2024 under Artificial Salinity Field (ASF) at the International Rice Research Institute (IRRI) headquarters in Los Banos, Laguna, Philippines (4.1699° N, 121.2441° E, 1,095 m above sea level) and hotspot Natural Salinity Field (NSF) in Infanta, Quezon, Philippines (15° 5' N, 119° 5' E, elevation 11.6 m above sea level), 200 meters from the coast of the Philippine Sea.

The ASF experiments were according to IRRI’s standard salinity protocol [84]. Stress was induced 45 to 50 days after seeding by manually applying sea salt granules. Tests were performed at EC = 9 to 12dSm^− 1 and EC = 15 to 17 dSm^− 1, 60 to 100 days after seeding. In the NSF experiment, mini-plots with built-in water channels were directly irrigated with seawater 21 days after transplanting. Salinity was maintained at EC = 15 to 20 dSm^− 1 throughout the growth duration [84].

Genome-seq, RNA-seq, bisulfite-seq, and Hi-C-seq libraries

For genome-seq, bisulfite-seq, and Hi-C-seq, total genomic DNA was isolated from leaves at tillering stage (V₄ to V₁₂) in three replicates through the standard CTAB method. The hyper-salinity stress experiment in the greenhouse for RNA sampling was described earlier [28, 32]. Total RNA was isolated in three replicates under control/0hr (EC = 2 dSm^− 1) and hyper-salinity conditions (120mM NaCl; EC = 12 dSm^− 1) after 24, 48, 72, and 144 hr. RNA isolation was through the mirVana™ miRNA Isolation Kit (ThermoFisher Scientific, AM1560) according to manufacturer’s instructions. Hi-C-seq libraries were constructed from fresh leaves using the DpnII (Dovetail Genomics, Santa Cruz, California, USA). Genome-seq (32x), RNA-seq and Hi-C-seq libraries were sequenced at 150-bp paired-end reads on HiSeq2500 (Oklahoma Medical Research Foundation, Norman, Oklahoma, USA). Bisulfite treatment and sequencing was conducted by MrDNA (Shallowater, Texas, USA). Adapter and low-quality bases at Q30 were trimmed with sickle v1.33 with minimum length of 100-bp.

Genome assembly and reference-guided genotyping-by-sequencing

Assemblies of parental and recombinant genomes were based on publicly available references that are most closely related to the indica parent IR29 (IR8, GCA_001889745.1) and aus parent Pokkali (N22, GCA_001952365.3) along with the platinum standard japonica (Nipponbare Os-Nipponbare-Reference-IRGSP-1.0) and aus (Kasalath) references. All reference datasets were obtained from the National Center for Biotechnology Information (NCBI) and the Rice Annotation Project (RAP).

Preprocessed sequence reads were mapped with bwa (mem -M -R options) [85]. Inconsistent mapping within pairs was first detected and removed by Picard v1.68 (FixMateInformation.jar and GenomeAnalysisTK.jar). SNPs and indels were identified by GenomeAnalysisTK.jar and filtered in the end [86]. The extracted coordinates of genomic variants were used to assign genotypes in 100-kb bins by comparing the proportion of parentally unique variants commonly found in the recombinant genomes. Parental SNPs were identified by the mapping of reads from IR29 and Pokkali parents to references in the same manner as recombinant genotyping. Bins of 100-kb without 100 SNPs in either parent were considered as gaps, which represented the differences between the parental genomes that are not captured in the presence of SNPs.

Genotyping of syntenic regions

The preprocessed reads were assembled into contigs through Platanus v1.2.4 with a minimum contig size of 300-bp [87]. Contigs of parents IR29 and Pokkali were assigned to the chromosomes of references IR8 and N22, respectively. Scaffolding was conducted with RagTag v2.1.0 with the parameter (scaffold -r -u -f 300 with minimap2-2.14) to construct IR29 from IR8 and Pokkali from N22 [88]. The IR29 and Pokkali references were used to scaffold the recombinant contigs in the biparental references. Given the relatively shorter contigs, the working assemblies of parental genomes were considered to represent the relative size and positions of the genic regions but not the entirety of the repetitive regions.

Pairs of homologous IR29 and Pokkali chromosomes were aligned to each other using minimap2 (-ax asm5 –eqx) and coordinates were processed with syri (--seed 123 --unic 500 --unip 0.3 -F B -b 600) and plotsr (-s 500) [89–91]. The code SYNAL and SYN with length more than 1000bp were extracted (excluding code SNP, DEL, INS, NOTAL events) to identify homologous regions that represent the exchange of blocks during recombination. Established syntenic pairs (57,044) based on homology between parents with average length 4,356bp (4,384bp in IR29-counterpart and 4,328bp in Pokkali-counterpart) and those in-between the syntenic regions (non-syntenic blocks) were used for genotyping. Recombinant scaffolds built on IR29 and Pokkali were aligned to parental genome to calculate the proportion of parental genome inherited. For a given syntenic pair, if the recombinant scaffold had more than 90% of IR29 and Pokkali genomes, the pair was considered ‘conserved’. Otherwise, if the recombinant showed the IR29 parental substrate 5% higher than that of Pokkali, the segment was considered as ‘IR29-derived’ and vice versa for Pokkali. Segments were considered ‘non-parental’ if there was no alignment or if ‘unmapped’. The length of segment that was genotyped was further explored by intersecting the difference in parental length and inheritance. Genome annotation was through the IRGSP protein sequences (IRGSP_2024-07-12) anchored to the genome by metaeuk v5-34c21f2 [92]. Functional annotation was through interproscan v5.40-77.0 [93].

Genome-wide prediction of recombination sites

Genomic long-read libraries were subsampled for 5,000 sequences 15-times per genotype (with seed value 100 to 1,500 at 100-increments). These reads were mapped to biparental reference (IR29 and Pokkali combined) using SVIM v1.4.1 with aligner ngmlr, --min_mapq 10 [94]. This process identified long reads with alignment spanning the IR29 and Pokkali genomes (candidate class, BND). The possible recombination sites corresponded to those where the long read switches from one parent to the other.

The initial BND mapping was filtered further by removing the sites that occur in the parental background. Those that occurred within 1-kb bins are considered to correspond to one recombination event. Those spanning the non-homologous chromosomes of parents or those suggesting possible recombination of 10-Mb distance within a homologous pair were also removed. The resulting recombination occurring within the same chromosome pairs (i.e., chr01 of IR29 and Pokkali) with recombination not involving the distal segment of chromosome were normalized with z-score.

De novo estimation of genome size, repetitive loci, and heterozygosity

To account for k-mer diversity across genotypes, a range of k-mer sampling size of 19 to 34 was used for the sub-sampled 35-million raw reads in each genotype. The k-mer was counted with jellyfish v2.2.10 and genome size was estimated with genomescope v1 [95, 96]. Total genome size is made up of unique and repetitive portions and the consistency of the unique regions across the panel was considered indicative of adequate sampling and depth.

Analysis of shed genomic loci and their repetitive sequence content

To identify the genomic regions affected by downsizing in the recombinants especially in the non-coding loci, repetitive sequences from RiTE database were mapped to IR29 and Pokkali references using RepeatMasker v 4.0.7 [97, 98]. In order to identify specific repeats that were affected by shedding, the genotyped regions affected by deletion (code DEL and NOTAL), NOTAL were considered as potentially shed repeats. In other words, deletion events in IR29 were disregarded if the genomic segments were genotyped as Pokkali-derived or vice versa. To explore the role of relatively large repeats in downsizing, the copia, gypsy and unclassified LTR were mapped to genome in each recombinant. Analysis of enrichment of other classes of repetitive sequences or retroelements in the shed regions relative to the background was through the permutation test of R-package regioneR (code DEL and NOTAL when mapping RIL genomes to parental genomes) and unique region (code DEL and NOTAL when mapping parental genomes to RIL genomes) [99].

Methylome analysis

Bisulfite sequences were mapped to IR29 and Pokkali genomes by BSMAP v2.90 [100]. Methylation ratio was calculated for CG, CHG, and CHH contexts. The genotyping results were reflected in the recombinant genomes, where IR29-based mapping was used to calculate methylation ratio if the segment was IR29-derived and Pokkali-based mapping if the segment was Pokkali-derived. For parental genome, IR29-mapping was used for IR29 and Pokkali-mapping for Pokkali. Relative methylation was taken per segment to normalize the centromeric/genic/pericentromeric regions. Relative methylation was visualized with rideogram and compared across syntenic/non-syntenic regions and by genotype classes (IR29-derived, Pokkali-derived, conserved, non-parental and shed). Genic regions were extracted for total genes, transcription factors, and genes within Saltol QTL with metaeuk-annotation.

Transcriptome analysis

RNA-seq libraries of each genotype across the hyper-salinity stress time-points (0, 24, 48, 72,144 hr) were mapped to IR29 and Pokkali references using hisat v2.1.0, and processed with featurecounts v1.5.2 [101]. Differential gene test and TMM-normalization were performed with EdgeR v3.28.1 at the cutoff value FDR < 0.05 with upregulation logFC > 1.8 and downregulation at logFC < -1.8 [102]. Stably expressed genes were extracted where TMM values for all the time-points showed a coefficient of variation of < 10%.

For the small RNA-seq analysis, the adaptors and reads with N-bases were removed, and reads of 15 to 34 bp after preprocessing was extracted as small RNAs. Abundance was normalized per input reads to estimate the proportion of small RNA expression. The frequency of cytosines in CG/CHG/CHH contexts were counted and normalized per context and number of bases. For functional annotation of small RNA, equal number of reads were subsampled from each genotype, i.e., 350,000 reads for 19nt, 70,000 reads for 21nt, and 800,000 reads for 24nt and 32nt. The 19nt, 24nt, and 32nt reads were mapped to IR29 and Pokkali genomes and regions with differential accumulation of siRNA and differentially methylated region (CHH methylation is not equal between parents and recombinants) were extracted to examine RdDM in differentially methylated regions.

TAD prediction and modeling from Hi-C data

Prediction and visualization of Topographically Associating Domains (TAD) were through the HiCExplorer package v3.7.2 [103]. The preprocessed Hi-C reads were normalized by subsampling 34-million reads with seqtk v1.3-r106 seed 100, and then mapping to IR29 and Pokkali working references with bwa mem v0.7.17-r1188, with -A1 -B4 -E50 -L0 options. Matrix was constructed using hicBuildMatrix (--binSize 1000, restriction sites GATC) and corrected with method ICE using the calculated threshold. Matrix bins were merged with hicPlotMatrix (-nb 10) per chromosome and visualized with thresholdComparisons 0.05 and delta 0.01. TAD profiles were compared between parents and recombinants according to five classes, i.e., parental TADs were ‘retained/segmented/merged’ in the RIL or ‘not overlapping’, ‘lost or new from the parents’, where parental TADs in IR29 are represented by IR29-TADs and that of Pokkali is represented by Pokkali-TADs. Specific threshold in bedtools were: -a parent and -b RIL -f 0.9 -F 0.9 for ‘retained; -a parent and -b RIL -F 0.9 then c > 0 (after excluding retained TADs) for ‘segmented’; merged: -a RIL and -b RIL -F 0.9 then c > 0 (after excluding retained TADs) for ‘merged’, -a parent -b RIL -v for ‘new’, and -a RIL -b parent -v for ‘lost’ [104].

Data availability

Sequence reads and other datasets are available under project PRJNA378253 at the National Center for Biotechnology Information at https://www.ncbi.nlm.nih.gov/sra. Custom scripts and gene galleries used in this study are deposited at https://github.com/akitazumi/scripts_transgressive.rice.git.

Author Contributions

AK, IP, KC and BR designed the experiments. IP and KC conducted the physiological evaluation. AK and YK analyzed the genomic, transcriptome and epigenomic data. RS generated the RIL population. WH and JR conducted field trials. BR conceptualized and directed the whole project and wrote the manuscript with contributions from AK. All authors contributed and approved the submission.

Acknowledgements

This work was funded by the National Science Foundation (Grant 1602494) and USDA-NIFA-AFRI (Grant 2023-67013-39541) with additional support from the Bayer CropScience Regents Endowed Chair Funding to BR. The recombinant inbred population was developed at the International Rice Research Institute, Philippines. Computations were performed through the supercomputing facilities of the National Institute of Genetics, Japan, and High-Performance Computing Center (HPCC) of Texas Tech University, USA.

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No competing interests reported.

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The epigenome underlying a novel and non-parental stress-adaptive phenotype created by transgressive segregation

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Abstract

Figures

Background

Results

Agronomic superiority of the transgressive progeny

Non-parental genomic novelties created by recombination

Shedding from the repetitive and retrotransposon loci in recombinants

Shedding from transposon loci led to genome-wide hypomethylation

Novel chromatin landscapes predicted from Topologically Associating Domains

Impact of novel TAD signatures to the transcriptome

Physiological implications of TAD-effects to the transcriptome

Discussion

Epigenomic novelties are outcomes of recombination under mild genomic shock

Random epigenomic effects contribute to phenotypic novelty

Trans-generational stability of the epigenome of a transgressive segregant

Potential applications of epigenomic novelties to plant breeding

Conclusions

Methods

Plant materials and hyper-salinity stress experiments in the field

Genome-seq, RNA-seq, bisulfite-seq, and Hi-C-seq libraries

Genome assembly and reference-guided genotyping-by-sequencing

Genotyping of syntenic regions

Genome-wide prediction of recombination sites

Analysis of shed genomic loci and their repetitive sequence content

Methylome analysis

Transcriptome analysis

TAD prediction and modeling from Hi-C data

Declarations

References

Additional Declarations

Supplementary Files

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