
==== Front
Hortic Res
Hortic Res
hr
Horticulture Research
2662-6810
2052-7276
Oxford University Press

10.1093/hr/uhae194
uhae194
Article
AcademicSubjects/SCI01210
AcademicSubjects/SCI01140
Genomic data provides insights into the evolutionary history and adaptive differentiation of two tetraploid strawberries
Lin Hanyang School of Advanced Study, Taizhou University, Taizhou 318000, China
Zhejiang Provincial Key Laboratory of Plant Evolutionary Ecology and Conservation, School of Life Sciences, Taizhou University, Taizhou 318000, China

Chen Luxi Zhejiang Provincial Key Laboratory of Plant Evolutionary Ecology and Conservation, School of Life Sciences, Taizhou University, Taizhou 318000, China

Cai Chaonan Zhejiang Provincial Key Laboratory of Plant Evolutionary Ecology and Conservation, School of Life Sciences, Taizhou University, Taizhou 318000, China

Ma Junxia Zhejiang Provincial Key Laboratory of Plant Evolutionary Ecology and Conservation, School of Life Sciences, Taizhou University, Taizhou 318000, China

https://orcid.org/0000-0001-8244-0461
Li Junmin School of Advanced Study, Taizhou University, Taizhou 318000, China
Zhejiang Provincial Key Laboratory of Plant Evolutionary Ecology and Conservation, School of Life Sciences, Taizhou University, Taizhou 318000, China

Ashman Tia-Lynn Department of Biological Sciences, University of Pittsburgh, Pittsburgh, PA 15260, USA

Liston Aaron Department of Botany and Plant Pathology, Oregon State University, Corvallis, OR 97331, USA

Dong Ming Key Laboratory of Hangzhou City for Ecosystem Protection and Restoration, College of Life and Environmental Sciences, Hangzhou Normal University, Hangzhou 311121, China

Corresponding author. E-mails: lijm@tzc.edu.cn; lijmtzc@126.com
9 2024
11 7 2024
11 7 2024
11 9 uhae19414 3 2024
05 7 2024
01 9 2024
© The Author(s) 2024. Published by Oxford University Press on behalf of Nanjing Agricultural University.
2024
https://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Over the decades, evolutionists and ecologists have shown intense interest in the role of polyploidization in plant evolution. Without clear knowledge of the diploid ancestor(s) of polyploids, we would not be able to answer fundamental ecological questions such as the evolution of niche differences between them or its underlying genetic basis. Here, we explored the evolutionary history of two Fragaria tetraploids, Fragaria corymbosa and Fragaria moupinensis. We de novo assembled five genomes including these two tetraploids and three diploid relatives. Based on multiple lines of evidence, we found no evidence of subgenomes in either of the two tetraploids, suggesting autopolyploid origins. We determined that Fragaria chinensis was the diploid ancestor of F. corymbosa while either an extinct species affinitive to F. chinensis or an unsampled population of F. chinensis could be the progenitor of F. moupinensis. Meanwhile, we found introgression signals between F. chinensis and Fragaria pentaphylla, leading to the genomic similarity between these two diploids. Compared to F. chinensis, gene families related to high ultraviolet (UV)-B and DNA repair were expanded, while those that responded towards abiotic and biotic stresses (such as salt stress, wounding, and various pathogens) were contracted in both tetraploids. Furthermore, the two tetraploids tended to down-regulate defense response genes but up-regulate UV-B response, DNA repairing, and cell division gene expression compared to F. chinensis. These findings may reflect adaptions toward high-altitude habitats. In summary, our work provides insights into the genome evolution of wild Fragaria tetraploids and opens up an avenue for future works to answer deeper evolutionary and ecological questions regarding the strawberry genus.
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pmcIntroduction

Polyploidization (also known as whole-genome duplication) refers to the possession of more than two copies of each chromosome [1]. Polyploidization is widespread across eukaryotes, especially in plants [2, 3]. For instance, all extant species of vascular plants have experienced two ancient polyploidization events (ζ and ε), while monocots and dicots have undergone the other two (τ and γ, respectively) after their divergence [4]. Therefore, polyploidization is acknowledged to be one of the key factors promoting the evolution of higher plant genomes, the generation of new species, and the emergence of adaptive evolution [2, 5, 6].

Historically, some researchers have argued that polyploidization may lead to ‘evolutionary dead-ends’ [7]. Shortly after the polyploidization events, polyploids would exhibit lower rates of speciation and higher rates of extinction compared to their diploid relatives, further losing evolutionary potential [8]. However, mounting evidence has shown that polyploid species show stronger evolutionary advantages in the long term [6, 9]. Compared to their diploid relatives, polyploids tend to show stronger adaptability and a broader ecological niche, especially with respect to harsh environments (such as drought and extreme temperature) [10–13]. Nevertheless, due to the biased research interests (mainly cultivated plants, e.g., cotton [14]; sugarcane [15]; banana [16]) and the lack of sufficient genomic data, diploid ancestors of many wild polyploids await discovery. In addition, whether and how polyploids show differential responses to extreme habitats compared to their diploid relatives remains an open but intriguing question.

Harboring about 25 species with diverse ploidy levels (ranging from diploid [2×], to tetraploid [4×] and above [5×, 6×, 8×, 10×]), strawberries (Fragaria L., Rosaceae) are not only important food plants but also serve as a promising system to study the above-mentioned issues [17, 18]. To date, the diploid ancestors of the octoploid cultivated strawberry (Fragaria × ananassa) have been intensively studied [19–26]. Lines of evidence indicate that one F. × ananassa subgenome is most closely related to the extant Fragaria vesca, one subgenome resembles Fragaria iinumae mostly, while the other two distinct subgenomes could be derived from extinct or unsampled species that are more affinitive to F. iinumae than F. vesca. Nevertheless, none of these works shed light on the niche evolution between polyploids and their potential diploid ancestors, leaving an evident knowledge gap that calls for deeper investigations. Meanwhile, much less attention has been paid to the evolutionary trajectory of wild tetraploid Fragaria species (such as Fragaria corymbosa and Fragaria moupinensis), and hence, their diploid ancestors remain ambiguous. The most comprehensive work was reported by Kamneva et al. [27]. Based on 257 low-copy nuclear markers of 20 diploid and polyploid Fragaria species, they used phylogenetic approaches to infer the evolutionary origins of polyploid strawberries. This study provided some evidence of the diploid ancestors of tetraploids, yet the robustness of the conclusion is relatively weak (the support probability did not exceed 50%), possibly owing to the widespread reticulate evolution in Fragaria (as shown by later works [28]) and the limitations of datasets. Despite the imperfections, the work of Kamneva et al. [27] provides us with valuable clues that Fragaria chinensis and Fragaria pentaphylla would be the likely ancestors of both F. corymbosa and F. moupinensis. Besides molecular analyses, morphological comparisons suggested that F. moupinensis most resembles Fragaria nubicola, and F. chinensis could be the ancestor of F. corymbosa [17, 29]. On the other hand, information on geographical distribution and earlier studies have suggested that these two Chinese endemic tetraploids (F. corymbosa and F. moupinensis) may have undergone climate niche evolution after the divergence from their diploid ancestors [30]. In general, F. corymbosa and F. moupinensis were prone to occupy higher altitude habitats with lower temperatures, compared to their diploid relatives [31]. Again, no solid conclusion should be drawn without a clear species phylogeny, and stronger genomic data are needed to decipher the evolutionary histories of the tetraploids and examine how their gene expression differs from the diploids in a manner that would facilitate niche differentiation.

Table 1 Plant information and genome characteristics of five sequenced Fragaria species.

Species	Collection locality	Latitude	Longitude	Evaluated genome size (Mb)	Assembly size (Mb)	Percentage of anchoring (%)	Contig N50 (Kb)	Scaffold N50 (Mb)	Repeats (%)	Number of predicted coding genes	Complete BUSCO (%)	
Fragaria corymbosa	Gansu, China	35.776	103.964	236.99 (1×)	875.99 (4×)	98.32	408.52	31.54	44.41	81 282	98.0	
Fragaria moupinensis	Sichuan, China	30.043	101.827	236.20 (1×)	980.12 (4×)	96.76	323.22	32.88	43.18	89 611	98.2	
Fragaria chinensis	Shaanxi, China	33.279	108.302	236.27 (1×)	254.62 (1×)	92.54	2290.75	32.42	44.95	30 300	95.4	
Fragaria pentaphylla	Sichuan, China	31.717	103.883	259.21 (1×)	253.27 (1×)	97.01	2365.18	34.20	43.56	33 501	96.2	
Fragaria daltoniana	Xizang, China	28.029	85.986	273.67 (1×)	270.50 (1×)	96.69	6955.13	34.83	45.91	31 385	98.6	

In the present study, we first used genomic data to determine the most likely diploid ancestors of F. corymbosa and F. moupinensis. Then, we tested whether and to what extent hybridization played a role in shaping the evolutionary history of the two tetraploids and their close relatives. Last, we investigated genes that show contrasting responses to the presumed climate niche divergence between pairs of ancestor–descendant species. By utilizing phylogenomic approaches, the current study sheds light on the evolutionary imprints of these wild Fragaria tetraploids with ecological significance.

Results

The characteristics of five assembled Fragaria genomes

The chromosome squashes confirmed the tetraploidy of both sequenced F. corymbosa and F. moupinensis individuals (Fig. S1, see online supplementary material). Through the de novo assembly pipeline, we achieved initial genome assemblies that captured 875.99, 980.12, 254.62, 253.27, and 270.50 Mb in 2956, 6692, 382, 221, and 185 contigs for F. corymbosa, F. moupinensis, F. chinensis, F. pentaphylla, and Fragaria daltoniana genomes, with contig N50 of 408.52, 323.22, 2290.75, 2365.18, and 6955.13 Kb, respectively (Table 1). The assembled genome sizes are largely consistent with estimated values from the genome survey. Using the Hi-C assisted scaffolding pipeline, 861.25 Mb which accounted for 98.32% of the assembled F. corymbosa genome, 948.39 Mb which accounted for 96.76% of the assembled F. moupinensis genome, 235.62 Mb which accounted for 92.54% of the assembled F. chinensis genome, 245.70 Mb which accounted for 97.01% of the assembled F. pentaphylla genome, and 261.56 Mb which accounted for 96.69% of the assembled F. daltoniana genome were anchored on 28 (for the two tetraploids) or seven (for the three diploids) pseudo-chromosomes (Table 1; Fig. S2, see online supplementary material). The BUSCO evaluation suggested that these genomes were well-assembled (complete BUSCOs >95%; Table 1). With the hybrid annotation procedure, we predicted 81 282, 89 611, 30 300, 33 501, and 31 385 coding genes in the F. corymbosa genome, the F. moupinensis genome, the F. chinensis genome, the F. pentaphylla genome, and the F. daltoniana genome, respectively (Table 1). The size of repeat sequences contributed to 44.41% of the F. corymbosa genome, 43.18% of the F. moupinensis genome, 44.95% of the F. chinensis genome, 43.56% of the F. pentaphylla genome, and 45.91% of the F. daltoniana genome. For the two tetraploids, we found no presence of subgenomes based on the gene synteny analysis, the k-mer spectrums, and the principal components analysis (PCA) results of the transposable elements (TE) profiles (Fig. 1). Specifically, we observed a higher proportion of aaab than aabb in both genomes of F. corymbosa (1.34% vs. 0.468%) and F. moupinensis (1.57% vs. 0.484%) and two major peaks in the k-mer distribution with 1/4 coverage ratio, indicating that these two species are autotetraploids.

Figure 1 An overview of five sequenced Fragaria species. (a) The sampling localities and photographs of sequenced Fragaria individuals showing the overall morphological features and reproductive organs. Photo credits: the authors. (b) The genome features of Fragaria corymbosa and Fragaria moupinensis showing (i) gene synteny blocks; (ii) the labels of pseudo-chromosomes; (iii) sequence positions; (iv) GC contents; and (v) gene densities. (c) The k-mer spectra and fitted models of F. corymbosa and F. moupinensis genomes. (d) The distribution of TE profiles along the first and second axes of principal components.

Figure 2 Identification of the most likely diploid ancestors of the two Fragaria tetraploids. (a) The consensus ML tree based on the concatenated sequences of 6054 single-copy orthologous genes. The bootstrap values are shown near nodes. The numbers of expanded (red) or contracted (blue) gene families of each Fragaria species are shown on the right of the tip labels. (b) The ASTRAL species tree regarding the two tetraploids and their close relatives summarized from 6054 ML gene trees. The values of local posterior probability are shown. (c) Reads mapping rates of Fragaria corymbosa and Fragaria moupinensis individuals to the composite genome constituted by nine Fragaria diploids shown by the sppIDer analysis.

The diploid progenitor of two tetraploids

With the inclusion of 19 studied species, we obtained 27 (present in all 25 haplotypes), 520 (≥13 haplotypes), and 2587 (≥4 haplotypes) single-copy orthologous genes (OGs) based on different thresholds of haplotype coverages. Both the consensus ML tree based on the concatenated sequences and the ASTRAL species tree strongly suggested the monophyly of the Fragaria genus, and close evolutionary relationships among Rosa chinensis, Rubus occidentalis, and Fragaria species [Fig. S3, see online supplementary material; bootstrap (BS) value = 100, local posterior probability (LPP) = 1.00]. Subsequently, we identified 851 (present at all 19 haplotypes), 4045 (≥10 haplotypes), and 6054 (≥4 haplotypes) single-copy OGs among Fragaria, R. chinensis, and R. occidentalis with three haplotype coverages. The reconstructed phylogeny based on these three OG datasets and both the concatenation and the coalescent-based methods were highly congruent, and strongly supported the monophyly (BS value = 100, LPP = 1.00) of the clade comprising F. corymbosa, F. chinensis, F. moupinensis, F. pentaphylla, and F. nubicola (Fig. 2a and b; Fig. S4, see online supplementary material). Within this clade, F. nubicola represented the first diverged species; then F. pentaphylla diverged and F. moupinensis showed a sister relationship with the F. chinensis–F. corymbosa species pair (Fig. 2a and b; BS value = 100, LPP = 1.00). Also, all haplotypes within F. corymbosa and F. moupinensis showed strong monophyly (BS value = 100, LPP = 1.00), implying the absence of subgenomes.

The sppIDer analysis generated similar results with the ‘tree-based’ methods as shown above (Fig. 2c). Both the two tetraploids showed greater genomic similarity with F. chinensis, F. pentaphylla, and F. nubicola compared to other Fragaria diploids (Fig. 2c; Table S1, see online supplementary material). After mapping genomic sequences of F. corymbosa to the composite genome, we found that the largest proportion of the reads (with an average of 47.8%, hereafter) showed similarity with the F. chinensis genome (df = 8, F = 371.4, ANOVA P-value <0.001, Tukey’s HSD P-value <0.001), followed by F. pentaphylla (23.2%) and F. nubicola (16.4%). For F. moupinensis, we found that most of the reads (with an average of 38.0%) also mapped to the F. chinensis genome (df = 8, F = 1308, ANOVA P-value <0.001, Tukey’s HSD P-value <0.001), followed by F. pentaphylla (26.4%) and F. nubicola (22.5%). Therefore, we cautiously deduced that the ancestor–descendant relationship between F. chinensis and F. corymbosa was robust, and the most likely diploid ancestor of F. moupinensis could be an extinct species closely related to F. chinensis or an unsampled F. chinensis population.

Introgression between F. chinensis and F. pentaphylla

Using the ‘sequence-based’ method, we found that the genomic sequences of F. chinensis most resembled the F. corymbosa genome (30.7%; df = 9, F = 238.4, ANOVA P-value <0.001, Tukey’s HSD P-value <0.001) and followed by the F. pentaphylla genome (21.1%) (Fig. 3a; Table S1, see online supplementary material).

Figure 3 Genetic admixtures among the two tetraploids and their close relatives revealed by genome-resequencing data. (a) Reads mapping rates of Fragaria chinensis individuals to the composite genome constituted by ten Fragaria species shown by the sppIDer analysis. Fco = Fragaria corymbosa, Fpe = Fragaria pentaphylla, Fmo = Fragaria moupinensis, Fnu = Fragaria nubicola, Fda = Fragaria daltoniana, Fni = Fragaria nilgerrensis, Fvi = Fragaria viridis, Fii = Fragaria iinumae, Fma = Fragaria mandshurica, Fve = Fragaria vesca. (b) The D-statistics among these species. F. nilgerrensis was designated as the outgroup consistently. A warmer color indicates a greater D-statistic hence a stronger signal of introgression. Only significant D-statistics (Z-score > 3) are shown.

Figure 4 Enriched GO terms of genes that exclusively expanded (the left panel, red) or contracted (the right panel, blue) in Fragaria corymbosa (Fco) and Fragaria moupinensis (Fmo) compared to Fragaria chinensis. The heatmap corresponds to the p-value of Fisher’s exact test (with Benjamini and Hochberg FDR correction). The dot size corresponds to the gene ratio.

After the mapping and filtering processes, we retained 285 066 single-nucleotide polymorphism (SNP) loci to infer the D-statistics among focal species. With F. corymbosa being the species X, we found excess allele sharing between F. chinensis and F. pentaphylla (D-statistic = 0.0733, Z-score = 9.959), suggesting introgression between these two diploid species (Fig. 3b; Table S2, see online supplementary material). With F. moupinensis being the species X, we observed excess allele sharing among F. chinensis, F. pentaphylla, and F. corymbosa. With F. pentaphylla being the species X, a high magnitude of allele sharing was suggested between F. chinensis and F. corymbosa. With F. nubicola being the species X, signals of introgression were shown in all species pairs, which is intuitive as the results of phylogenic analysis have shown that F. nubicola was relatively phylogenetically distant from the remaining Fragaria species (Fig. 2a). In this case, the strongest introgression signal was found between F. pentaphylla and F. chinensis (D-statistic = 0.1889, Z-score = 24.128; Fig. 3b; Table S2, see online supplementary material). To summarize, multiple lines of evidence suggest the presence of genomic introgression between F. chinensis and F. pentaphylla.

Gene families with expansion or contraction in the tetraploids

The K = 2 model was determined to be the best model of gene family evolutionary rates in CAFE analysis based on the final likelihood (Table S3, see online supplementary material). We found that 1349 gene families expanded in size while 4690 gene families contracted in size in the F. corymbosa genome (Fig. 2a). Among those, 1335 gene families exclusively expanded and 4374 gene families exclusively contracted in F. corymbosa compared to F. chinensis (Fig. S5, see online supplementary material). Meanwhile, 1795 gene families expanded in size while 3730 gene families contracted in size in the F. moupinensis genome, among which 1624 expanded gene families and 3479 contracted gene families were not found in F. chinensis (Fig. S5, see online supplementary material).

The gene enrichment analysis showed that 61 and 62 Gene Ontology (GO) terms were enriched in the expanded gene families of F. corymbosa and F. moupinensis, respectively (Fig. 4; Table S4, see online supplementary material). Among those, GO terms related to the response to high ultraviolet (UV)-B, DNA repair, the abscisic acid-activated signaling pathway, and the glutathione metabolic process were both enriched in F. corymbosa and F. moupinensis. On the other hand, 96 and 83 GO terms were enriched in the contracted gene families of F. corymbosa and F. moupinensis, respectively (Fig. 4; Table S4, see online supplementary material). We found that many of the shared GO terms were related to the responses to abiotic and biotic stresses, such as response to wounding, response to salt stress, response to heat, defense response to fungus, defense response to bacterium, and defense response to oomycetes (Fig. 4; Table S4, see online supplementary material). These shared GO terms between F. corymbosa and F. moupinensis enriched from both the expanded and the contracted gene families may be relevant to the high-altitude habitat of these two tetraploids compared to their closest diploid ancestor.

Up- and down-regulated genes between the tetraploids and their closest diploid relative

We identified 920 differentially expressed genes (DEGs) between the transcripts of F. corymbosa and F. chinensis, among which 643 DEGs were up-regulated and 277 DEGs were down-regulated in F. corymbosa (Fig. S6, see online supplementary material). Meanwhile, 1327 DEGs were found between the transcripts of F. moupinensis and F. chinensis, among which 793 DEGs were up-regulated and 534 DEGs were down-regulated in F. moupinensis (Fig. S6, see online supplementary material).

These up-regulated genes were enriched to 19 GO terms in total (Fig. 5; Table S5, see online supplementary material). Some GO terms were related to the processes of the cell division, such as telomere maintenance, meiotic cell cycle, DNA-templated DNA replication, and meristem maintenance, which may secure cell functions under UV-B damages. These down-regulated genes were enriched to 48 GO terms (Fig. 5; Table S5, see online supplementary material), many of which were related to the regulation of defense response and systemic acquired resistance. In general, the results of gene enrichment analysis of DEGs partly coincided with those of expanded or contracted genes (Figs 4 and 5).

Figure 5 Enriched GO terms of genes that up-regulated (the left panel, red) or down-regulated (the right panel, blue) in Fragaria corymbosa (Fco) and Fragaria moupinensis (Fmo) compared to Fragaria chinensis. The heatmap corresponds to the p-value of Fisher’s exact test (with Benjamini and Hochberg FDR correction). The dot size corresponds to the gene ratio.

Discussion

By taking advantage of rapidly developing DNA sequencing technologies, we are now able to trace the evolutionary histories of these two tetraploids with whole-genome data. The reconstructed Fragaria phylogeny here is consistent with the work of Qiao et al. [32], which supported that F. chinensis, F. pentaphylla, and F. nubicola showed close evolutionary affinities and formed a monophyletic clade. With the inclusion of the two tetraploids, our phylogenomic analysis revealed a strongly supported clade that consists of F. corymbosa, F. chinensis, F. moupinensis, F. pentaphylla, and F. nubicola (Fig. 2a). Within this clade, F. nubicola and F. pentaphylla diverged sequentially; then the subclade was comprised of F. moupinensis and the F. corymbosa–F. chinensis pair. This result is also partly supported by Kamneva et al. [27] and morphological similarities among these species [17, 29]. Early studies have disputed whether F. corymbosa and F. moupinensis were autotetraploids or allotetraploids [33, 34]. In the paper of Kamneva et al. [27], they claimed that the hybridization events between F. chinensis and F. pentaphylla gave rise to the speciation of both F. corymbosa and F. moupinensis. However, this inference was weakly supported (the level of support was at most 20%). If the hypothesized scenario of Kamneva et al. [27] was true, then both the two tetraploids would at least show some signs of subgenomes that were supported by neither the present study (Figs 1 and 2) nor recent work [35].

By integrating lines of evidence from both the ‘tree-based’ method and the ‘sequence-based’ method [21], we deduce that F. chinensis is the sole diploid ancestor of F. corymbosa and is the closest diploid relative of F. moupinensis, though the genuine ancestor of F. moupinensis could be an extinct species affinitive to F. chinensis or an unsampled F. chinensis population (Fig. 2). The introgression between F. chinensis and F. pentaphylla could account for the reason why F. chinensis showed greater genomic similarities with F. pentaphylla than with F. moupinensis (Fig. 3). In the sense of biogeography, both F. chinensis and F. pentaphylla and their tetraploids relatives can be found in the flora surrounding the Qinghai-Tibet Plateau (QTP), where interspecific hybridization is prevailing (Fig. 1a; see Review in [36]). Therefore, the hybridization between F. chinensis and F. pentaphylla is feasible and has also been implicitly suggested by Feng et al. [28]. More recently, Qiao et al. [35] also found the presence of genetic admixtures between F. chinensis and F. pentaphylla and claimed the evolutionary affinity between F. chinensis, F. pentaphylla, and F. corymbosa. Here, we sequenced the genome of both tetraploids along with the comparisons between the expression levels of genes, which generates additional insights into the ancestor–descendant relationship of diploid-tetraploid species.

The climatic niche differentiation between Fragaria diploids and tetraploids has been explored and confirmed [30, 31], but insight into how tetraploid genomes are differentiated across these environments has not previously been explored. By comparing the functions of genes with expansion or contraction and determining the differentially expressed genes between the tetraploids and their closest diploid relative, we found that both F. corymbosa and F. moupinensis showed less expression of defense responses towards biotic stresses (such as defense response to fungus and bacterium) but in contrast has stronger expression in UV-B response, DNA repairing, and the processes of cell division (Figs 4 and 5). These trade-offs can be explained by the habitat preference of these two tetraploids [31]. The environments in high-altitude floras near QTP are characterized by freezing temperatures, high UV radiation, and hypoxia, thus plants have to evolve suites of morphologic and genetic adaptations to ensure their survival and reproduction (e.g. [37, 38]). Despite hostile environments, the biotic stresses such as herbivory or pathogen infections are much reduced in high altitudes compared to that in low-altitude habitats [39–42]. A study focusing on high-altitude adaptations showed disease-resistance genes were contracted and UV radiation-related genes were expanded in alpine plants than their low-altitude relatives, which is similar to what is found in the present study [43]. In the future, we recommend deeper research harnessing the power of genome-wide association studies (GWAS) or the determination of quantitative trait loci (QTL) to better link specific adaptation-related traits to their genetic basis.

To sum up, though introgressions may occur between diploid relatives, our results firmly support the ancestor–descendant relationship between F. chinensis and F. corymbosa, and the close evolutionary affinity between F. chinensis and F. moupinensis. The two tetraploids show similar genetic responses in high-altitude environments compared to their diploid ancestor, providing evidence of niche differentiation between polyploids and their diploid relatives in the genetic aspect.

Materials and methods

Plant material, genome sequencing, assembly, and annotation

To gain insights into the evolution of F. corymbosa and F. moupinensis, we sequenced and de novo assembled the genomes of the two tetraploids along with three Fragaria diploids (F. chinensis, F. pentaphylla, and F. daltoniana) (Table 1 and Fig. 1a). The seeds of these plants were collected from the wild (Table 1) and then germinated in a walk-in growth chamber with conditions of 22°C during 16 h of daytime and 15°C during 8 h of nighttime, with a relative humidity of 90%. After the seed germination, the seedlings were grown in a greenhouse with a temperature of 20–25°C at Taizhou University (Zhejiang, China). For the two tetraploids, we counted the chromosome number following Nathewet et al. [44] to confirm the ploidy of plant materials prior to genome sequencing. About 2 cm root tips were harvested around 10 a.m. and pretreated with 2 mM 8-hydroxyquinoline at 22°C for 1 h and then kept at 4°C for over 15 h. After being cleaned with distilled water, the root tips were fixed in the Farmer’s solution (absolute ethanol:glacial acetic acid = 3:1) for 2 h. Then, the root tips were soaked in 1 N HCl at 22°C for 1 h, and macerated in 1 N HCl at 60°C for 11 min. Later, the root tip was moved onto a glass slide with one drop of carbol-fuchsin staining solution and stood for 15 min. After the root tips were broken into invisible particles, the chromosomes were observed using a Motic BA310 light microscope at 100× magnification.

We assembled the genomes using PacBio SMRT long reads (20-kb fragment size) (>150×; with an average of 189×), 150-bp paired-end Illumina short reads (>100×; with an average of 244×), and Hi-C library data (>100×; with an average of 144×) (Table S6, see online supplementary material). Detailed information on DNA isolation, RNA extraction, and sequencing procedure is available in the supplementary material. We conducted a genome survey by analysing the k-mer frequency [45]. High-quality pair-end Illumina reads were used to generate 17-mer frequency information. The genomes were initially de novo assembled using the PacBio SMRT long reads with FALCON (for diploids) and FALCON-Unzip (for tetraploids) [46]. Then, the primary contigs were self-corrected with the long reads using Quiver (a toolkit in FALCON) and subsequently corrected with the Illumina short reads using NextPolish (v. 1.3.1) [47]. The Hi-C sequencing data were aligned to the draft genome using Bowtie 2 (v. 2.4.5) [48]. Then, the chromosome scaffolding was conducted with the ALLHiC (v. 0.9.8) pipeline (pruning, partitioning, rescuing, optimization, and building; —minREs 50 —maxlinkdensity 3 —NonInformativeRabio 2) [49]. For the tetraploids, four sets of pseudo-chromosomes were anchored to explore the genomic features, and one set of pseudo-chromosomes was anchored for the three diploids following the literature [26, 28, 32, 35]. Later, the chromosome-level assembly was manually corrected using Juicebox (v. 1.5) [50]. The completeness of the assembled genome was evaluated using the Benchmarking Universal Single-Copy Orthologs (BUSCO; v. 4.1.2) [51]. Finally, we annotated these genomes (including repeats, genes, and non-coding RNA genes) via a combination of homology-based inference, de novo prediction, and transcripts from the RNA sequencing of different tissues (leaf, root, stolon, and stem; Table S6, see online supplementary material). The detailed procedures of RNA sequencing and genome annotation are reported in the supplementary material.

Testing the presence of subgenomes

Given that we lacked clear knowledge on whether sequenced accessions of F. corymbosa and F. moupinensis were autotetraploids or not, we tested the presence of subgenomes by detecting gene synteny, analysing k-mer spectrum, and analysing TE profiles. Gene synteny within the genomes of the two tetraploids was analysed using blastp (v. 2.13.0+; −evalue 1e−5 −num_alignments 20) and MCScanX [52] with default settings. Using GenomeScope (v. 2.0) [53], we explored how k-mer frequencies were distributed in the two tetraploid genomes with genome-survey data (Table S6, see online supplementary material). For autotetraploid, we would expect a high proportion of aaab and a low proportion of aabb [53]. Also, it is well-accepted that TE profiles can vary between homoeologous chromosomes when subgenomes are present (e.g. [54]). Hence, we built a summary matrix of the copy number of each TE family among pseudo-chromosomes and then performed a PCA using R package stats (v. 4.1.2) [55]. Furthermore, the results of the phylogenetic analysis could provide additional evidence for the presence or absence of subgenomes (see below).

Identifying the diploid ancestors

We inferred the potential diploid ancestors of the two Fragaria tetraploids using two complementary methods: the ‘tree-based’ method and the ‘sequence-based’ method [21].

The ‘tree-based’ method

To explore the affinity between the two tetraploids and their relatives, we inferred the phylogenetic tree based on the protein sequence data of 19 species (including 11 Fragaria spp.; 25 haplotypes in total) whose whole-genome information is available. Besides the five sequenced species in the present study, we included six Fragaria species, i.e., F. iinumae [20], Fragaria mandshurica [32], Fragaria nilgerrensis [32], F. nubicola [21], F. vesca [26], and Fragaria viridis [32], seven Rosaceae species, i.e., R. chinensis [56], R. occidentalis [57], Gillenia trifoliata [58], Malus domestica [59], Prunus mume [60], Prunus persica [61], Pyrus communis [62], and Arabidopsis thaliana (v. Araport11, as the outgroup [63]) in phylogenetic analysis. We searched OGs among these taxa using OrthoFinder (v. 2.5.4) [64] with the DIAMOND search program [65]. Additionally, we searched OGs among Fragaria species and the two closest Rosaceae species (R. chinensis and R. occidentalis; see Results) to include more OGs for phylogenetic inferences.

To compare the robustness of reconstructed phylogeny, we generated six single-copy OG datasets with the inclusion of different species: (i) 19 species (25 haplotypes) and (ii) 13 species (19 haplotypes), and different haplotypes coverages: (i) present at no less than four haplotypes, maximizing phylogenetic information; (ii) present at more than half of the haplotypes; and (iii) present at all haplotypes. For each OG dataset, we inferred the phylogenetic tree using both the concatenation method and the coalescent-based method. The protein sequences of each OG were aligned using MAFFT (v. 7.508; —auto) [66] and then being trimmed using trimAl (v. 1.4; −automated1) [67]. For the concatenation method, the consensus maximum likelihood (ML) phylogenetic tree was inferred using IQ-TREE (v. 2.2.0.3) with 1000 ultra-fast bootstrap replicates [68, 69]. The concatenated sequences were partitioned according to OG positions. The best-fit protein substitution model was determined automatically with ModelFinder as supported by IQ-TREE (−m MFP) [70]. For the coalescent-based method, the consensus ML tree of each OG was inferred with the identical approach as described above. Then, we summarized the species tree based on gene ML trees and calculated the LPP of each node using ASTRAL (v. 5.7.8) with default settings [71].

The ‘sequence-based’ method

As a complementary method to identify the ancestors of the two tetraploids, we applied the sppIDer approach which maps short-read sequencing data to a mixed reference genome constructed from potential ancestors to determine their contributions to hybrid genomes [72]. Here, we mapped whole-genome resequencing data of 20 tetraploid plant individuals (ten of F. corymbosa and F. moupinensis each; Table S7, see online supplementary material) to a composite genome constituted by nine Fragaria diploids, i.e., F. chinensis, F. pentaphylla, F. daltoniana, F. iinumae, F. mandshurica, F. nilgerrensis, F. nubicola, F. vesca, and F. viridis. The genome resequencing data were compiled from both the newly sequenced accessions (the same sequencing methods of the genome survey described above) and the NCBI SRA database. The raw reads downloaded from the SRA database were filtered into clean data using fastp (v. 0.23.4) with default settings [73]. The chromosome-level genome sequences of these diploids were obtained from the same sources of the protein sequences as described in the ‘tree-based’ method part. Then, we applied one-way ANOVA and post-hoc analysis (Tukey’s HSD) using the R package stats to test the significance of the difference in genome contribution among species. Further, we tested the contribution of hybrid genomes to the genome of F. chinensis with a similar method (see Results; Table S7, see online supplementary material).

Genetic admixtures

To further explore introgressions among the two tetraploids and their close relatives (six species, 49 individuals; Table S7, see online supplementary material), we adopted the D-statistics (also known as ABBA-BABA tests) as implemented in AdmixTools (v. 7.0.2) [74]. Assuming W, X, Y, and Z are four species with a certain phylogeny (((W,X),Y),Z), W and X being the focal species, Y being the tested species potentially introgressing with W or X, and Z being the outgroup used to polarize variants (here, F. nilgerrensis). If W and X share equal amounts of alleles with Y, the D-statistic will be zero, or at least the absolute Z-score will be no greater than three. If the D-statistic is positive and Z-score >3, W and Y would show excess allele sharing than expected, thus implying the presence of introgression [74]. We generated SNP data as the input of AdmixTools analysis with the following steps. First, we mapped and aligned clean reads to the reference genome using BWA (v. 0.7.17-r1188) [75] and samtools (v. 1.9) [76]. Then, we performed variant calling with bcftools (v. 1.16) [76, 77]. The variants were first hard-filtered with advised parameters to remove low-quality loci and to reduce calling bias (−e 'QUAL < 20 || DP > 250 || MQBZ < −3 || RPBZ < −3 || RPBZ >3 || SCBZ >6′; https://www.htslib.org/workflow/filter.html). Then, soft-filtering was performed using vcftools (v. 0.1.16) [78]. Finally, only bi-allelic SNP loci that are present in more than 60% of individuals were retained (—max-missing 0.6 —max-alleles 2 —min-alleles 2).

Gene family expansion and contraction

To explore genes that responded strongly during polyploidization, we inferred the changes in the gene family size of OGs (identified from the OrthoFinder analysis as described above) along the evolutionary time using CAFE (v. 5.0 [79]). The ultrametric tree was inferred based on the consensus ML tree using r8s (v. 1.81; smoothing = 0.01, divtime method = PL, algorithm = TN) [80]. The crown age of the genus Fragaria was set to 6.37 million years ago (mya) following Feng et al. [21, 28]. To account for the rate variation among OG families, we compared the likelihood through a discrete gamma distribution (K = 2 to K = 6) and then chose the best model. Later, we extracted protein sequences of OGs that exclusively expanded or contracted observed in the two tetraploids rather than in their closest diploid relatives using SeqKit (v. 2.4.0) [81]. Subsequently, we annotated these genes by querying against A. thaliana and then enriched them to test whether these genes were statistically strongly associated with the GO terms. The annotation and enrichment analysis were conducted using KOBAS-i [82]. The GO terms under the ‘biological process’ category were focused and only those with Fisher’s exact test (with Benjamini and Hochberg FDR correction) p-value <0.05 were kept (hereafter).

Differentially expressed genes between tetraploids and their relatives

To explore whether the pattern of DEGs was partly correlated with gene family expansions or contractions between the tetraploids and their relatives, we used RNA sequencing data generated in aiding genome annotation (four tissues; Table S6, see online supplementary material) to investigate DEGs between F. corymbosa and F. chinensis, and between F. moupinensis and F. chinensis. Clean reads were mapped to the primary haplotype of each tetraploid respectively using HISAT2 (v. 2.2.1) [83]. Then, we analysed the expression levels of genes using StringTie (v. 2.2.1) [84]. The read count information was extracted using the prepDE.py script available in StringTie. Next, the DEGs were identified using the R package DESeq2 (v. 1.34.0) [85] based on the criteria of |log2FC| > 1 and padj < 0.05. Subsequently, these putative DEGs were annotated and enriched against A. thaliana using KOBAS-i. The GO terms under the ‘biological process’ category were focused.

Supplementary Material

Web_Material_uhae194

Acknowledgements

This work was funded by the National Natural Science Foundation of China (No. 31261120580 to M.D. and J.L.) and the National Science Foundation (DEB 12410006 to T.-L.A.; DEB 1241217 to A.L.). The authors thank Lingsong Chen, Minghua Song, Tong Chen, Xiaoyan Wang, Beifen Yang, Jinzhi Li, and Zhaokui Du for the collection of samples.

Author contributions

M.D., J.L., T.-L.A., and A.L. initiated the project. H.L. and J.L. wrote and finalized the manuscript. H.L., L.C., C.C., and J.M. designed and performed most of the experiments. T.-L.A., A.L., and M.D. provided assistance and suggestions. All authors discussed the results and commented on the manuscript.

Data availability

The assembled genome sequences and annotation files are available from the figshare repository (https://doi.org/10.6084/m9.figshare.25999996).

Conflict of interest statement

The authors declare no competing interests.

Supplementary data

Supplementary data is available at Horticulture Research online.
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