Abstract Black spot disease (BSD), caused by Alternaria alternata, is a devastating threat to the chrysanthemum industry, yet its genetic basis remains largely elusive. The present study aimed to decipher the genetic architecture of chrysanthemum BSD resistance and to discover genetic loci and candidate genes using genome-wide association studies (GWAS) in a biparental F1 population (n = 164). Phenotypic evaluations of BSD resistance were conducted using both multi-stage detached-leaf assays and seedling-stage in vivo inoculations. The disease severity index (DSI) exhibited wide coefficient of variation (CV: 26.21%–54.84%) and high broad-sense heritability (0.71–0.95), with significant transgressive segregation observed in the F1 progeny. 375 865 high-quality SNPs-based GWAS identified 220 quantitative trait nucleotides (QTNs) and 36 QTN-by-environment interactions (QEIs), explaining up to 7.39% and 3.46% of the phenotypic variance, respectively. Among 26 stable QTNs, 17 favorable alleles displayed significant additive effects and a clear dosage-pyramiding effect (P < 0.001). By integrating functional annotation with transcriptome profiling, 34 candidate genes involved in immune defense were identified within the candidate intervals. Notably, three key candidate genes, CmABF1, CmSINAT3, and CmLTPG1, were validated as positive regulators of BSD resistance through transient overexpression and silencing assays. The research findings provide crucial genetic resources for the molecular improvement of resistance to BSD in chrysanthemums.

Cliff habitats are characterized by limited and heterogeneous water availability, requiring plants to develop adaptive strategies to cope with drought stress. Opisthopappus longilobus, a cliff-endemic Asteraceae species restricted to the Taihang Mountains of northern China, has evolved under persistent water-limited conditions and represents a valuable model for investigating the molecular mechanisms underlying drought adaptation. However, the transcriptional regulatory networks involved in its drought response remain largely unexplored. In this study, we performed RNA sequencing of O. longilobus leaves under control and drought conditions to investigate drought-responsive regulatory networks. Six RNA-seq libraries were generated, and a total of 5260 differentially expressed genes (DEGs) were identified in response to drought stress. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses revealed that these DEGs were mainly associated with phytohormone signal transduction, stress-responsive regulation, defense responses, metabolic reprogramming, and transcriptional regulation. Notably, multiple transcription factor families, including MYB, ERF, and ABF, were enriched among drought-responsive genes, suggesting their involvement in drought adaptation. Furthermore, quantitative RT-PCR was used to validate the RNA-seq results. Among the drought-responsive transcription factors, an R2R3-MYB transcription factor, OlMYB35, was identified as a candidate regulator and was further demonstrated to play a positive role in drought response through transient transformation assays. Taken together, this study provides new insights into drought-responsive regulatory mechanisms in O. longilobus and identifies OlMYB35 as a promising candidate gene for further functional validation and potential application in stress-resilient chrysanthemum breeding.

Accurate classification of crop cultivars is a crucial technical support for germplasm resource research and targeted breeding. Chrysanthemum has ornamental, beverage, and medicinal values, with over 30,000 cultivars worldwide. The large scale of germplasm resources and the subtle differences in key morphological traits such as flower shape and petal type make traditional manual identification difficult and inefficient. General deep learning models can achieve high recognition accuracy in chrysanthemum cultivar classification; however, their relatively large parameter size and computational overhead limit their efficient deployment on mobile or edge devices in field scenarios. To address these problems, we first constructed a large-scale fine-grained chrysanthemum dataset, Chry-FG-151, containing 43,325 RGB images of 151 cultivars across six color series (white, yellow, orange, pink, purple, red), captured under natural light using various types of mobile devices. To reduce the influence of complex field backgrounds during training, we developed a Background Substitution Module (BSM) that combines explicit foreground extraction, morphological refinement, and neutral solid-color background reconstruction to generate foreground-focused augmented samples. To strengthen spatial responses to flower-related regions, we integrated a Spatial Semantic Calibration Module (SSCM), implemented as a lightweight pointwise-convolution spatial gate without spatial downsampling, to recalibrate feature maps for fine-grained cultivar discrimination. To meet the computational constraints of mobile deployment, we built a lightweight classification network, CCNet, consisting of a stem, six inverted residual bottleneck layers, a last expansion layer, two DropBlock2D layers placed before and after SSCM, and a lightweight classifier. CCNet achieved a test accuracy of 99.31 ± 0.24% on Chry-FG-151 under the full training pipeline. Under the BSM-only public-dataset protocol, it achieved test accuracies of 92.82 ± 0.84% and 86.18 ± 1.76% on Public Dataset I and Oxford 102 Flowers, respectively. The model contains 0.16 M parameters and requires 0.10 G FLOPs. Grad-CAM visualization and foreground–background attention analysis showed that CCNet allocated a slightly larger proportion of activation responses to flower foreground regions than MobileNetV3-small. Across seven backbone models and two public datasets, the BSM-only setting yielded higher mean test accuracy than the no-augmentation baseline. The compiled model size was 312.13 KB, and the single-image inference latency on the tested mobile CPU was 143 ms. These results support the feasibility of on-device inference under the evaluated hardware setting. This study presents a lightweight, deployment-oriented approach for intelligent chrysanthemum cultivar recognition.

Sympetaly (fused petals) is a key morphological innovation that has arisen multiple times during evolution. It occurs via one of two developmental pathways: late sympetaly (from initially separate petal primordia that later fuse) or early sympetaly (directly from a shared ring-like primordium). Nevertheless, the genetic basis of corolla tube formation in early-sympetalous lineages remains largely unknown. In Chrysanthemum morifolium, an early-sympetalous species, ray floret corolla tube formation depends specifically on dorsal petal elongation. Through integrated genome-wide association studies and RNA-seq analyses, we identified CmSAUR66 as a negative regulator of corolla tube fusion. Functional studies showed that CmSAUR66 knockdown enhances corolla tube fusion by promoting dorsal petal elongation. Mechanistically, CmSAUR66 acts by modulating the spatiotemporal expression of the dorsoventral asymmetry gene CmCYC2c; knocking down CmCYC2c in the amiR-CmSAUR66 background rescues the fusion phenotype. We found that sustained auxin treatment promotes corolla tube fusion while suppressing CmSAUR66 expression, and knocking down this gene alters auxin sensitivity. Importantly, we found that the auxin-induced transcription factor CmBES1 directly represses CmSAUR66 expression. Consistent with this, transient overexpression of CmSAUR66 in OX-CmBES1 plants significantly rescued the fusion phenotype. Our study thus unveils the CmBES1-CmSAUR66 regulatory module as a central component of auxin-mediated sympetalous development, providing insights into the hormonal control of floral morphological evolution.

Drought is one of the most serious abiotic stresses limiting plant productivity and becomes increasingly extreme worldwide due to the ongoing deterioration of the global climate. Chrysanthemum ( Chrysanthemum morifolium Ramat.), one of the four most popular cut flowers in the world, is sensitive to water-limited environment. However, the genetic basis and causal genes underlying drought tolerance (DT) remain largely unknown. In this research, multi-locus GWAS was employed to detect the genetic loci and candidate genes for DT in a diverse panel of 200 cut chrysanthemum accessions that were genotyped with 330,710 high-quality SNPs. As a result, 43 stable QTNs in single-environment analysis, 18 stable QTNs and 115 QEIs in multiple-environments analysis were identified via the 3VmrMLM method. Among the genes around stable QTNs and QEIs, eleven were homologous to known DT regulatory genes in other plants such as WRKY57 , MYB121 , GH3.6 . In addition, seven candidate genes were predicted to be associated with DT related traits by combing the functional annotation, transcriptomics data and quantitative real-time PCR. More importantly, four drought-tolerant cultivars harboring favorable alleles were identified as pre-bred material to improve tolerance of cultivated chrysanthemum. These findings provide robust insights into the genetic architecture of DT and offer valuable prospects for the molecular breeding of chrysanthemum.

Chrysanthemum & times;morifolium Ramat., a polyploid ornamental plant of the genus Chrysanthemum in the family Asteraceae, possesses ornamental, medicinal and economic values. As segmental allopolyploid hexaploids, cultivated Chrysanthemum s possess an enormous and highly heterozygous genome, which has long been a major obstacle to genetic dissection and targeted varietal improvement. Benefiting from the rapid evolution of next-generation sequencing and long-read sequencing technologies, multi-omics research on the genus Chrysanthemum has witnessed tremendous progress over recent years. The rapid breakthroughs in genomics technologies have propelled Chrysanthemum research into the era of molecular precision, with remarkable achievements made in genome sequencing, functional gene mining, gene editing and molecular marker development. To date, high-quality chromosome-scale genome assemblies have been completed for a wide range of Chrysanthemum species, including diploid wild relatives, aromatic varieties, medicinal germplasms and commercial hexaploid cultivars. These genomic resources reveal the evolutionary characteristics of polyploidization, genome expansion and structural variation within the genus, and lay a fundamental framework for functional gene mining and molecular mechanism analysis. Integrated multi-omics strategies combining transcriptomics, metabolomics, proteomics, epigenomics and single-cell transcriptomics have been widely adopted to dissect complex agronomic traits. A large number of core genes and regulatory modules related to flower color, flower shape, flowering time, plant architecture, biotic and abiotic stress tolerance, postharvest senescence and biosynthesis of active ingredients have been identified and functionally verified. These findings clarify the molecular regulatory networks of key traits and provide abundant candidate genes for precise genetic improvement. Currently, a comprehensive molecular breeding system has been established for Chrysanthemum. Transgenic technology enables directional modification of important traits such as ornamental and stress-related traits by regulating critical metabolic and signaling pathways. Optimized CRISPR/Cas and epigenetic editing systems support accurate manipulation of endogenous genes, overcoming the limitations of conventional breeding methods. Meanwhile, a full range of molecular markers, from traditional PCR-based markers to high-throughput SNP, InDel and SV markers, have been widely applied in germplasm identification, genetic map construction, QTL mapping and genome-wide association studies. Genomic selection has also shown prominent application value in predicting complex quantitative traits such as plant height and flowering time, displaying broad application potential in practical breeding programs in Chrysanthemum. Despite substantial progress, multiple bottlenecks still restrict the large-scale application of Chrysanthemum molecular breeding. The complex polyploid genetic background leads to widespread gene redundancy and functional differentiation of homologous genes. Additionally, genotype-dependent transformation systems, ambiguous allelic dosage effects and high costs of high-throughput genotyping remain major obstacles. To address these issues, future research will prioritize constructing high-quality pan-genomes and haplotype maps, developing efficient multi-gene editing tools and novel genotype-independent delivery systems. It is also essential to build low-cost high-throughput genotyping platforms and intelligent multi-omics databases for data sharing and deep mining. Collectively, these technological advancements will fully promote the transformation of Chrysanthemum breeding from conventional breeding to modern precise and intelligent molecular design breeding in the future.

Global climate change and human activities are posing substantial threats to biodiversity. The genus Opisthopappus (O. taihangensis and O. longilobus), endemic to Taihang Mountains in china, possesses great ornamental and medicinal value. However, it is confronted with the compounding pressures of habitat fragmentation and escalating climate change. Here, we present the first haplotype-resolved, chromosome-scale genome assembly of O. longilobus (~2.95 Gb, ~58,000 protein-coding genes per haplotype) and re-sequence 115 individuals across its range. Comparative analyses show Opisthopappus is sister to Artemisia-Chrysanthemum, with Opisthopappus and Chrysanthemum diverging at 5.15-5.18 million years ago. A profound genetic divergence is evident between O. taihangensis and O. longilobus, resulting in two distinct lineages within each species, driven by geography and climate. Our analyses indicate restricted gene flow, low diversity, and recurrent demographic bottlenecks collectively contribute to their endangerment. By integrating population genomics and environmental variables, we identified 4,620 core adaptive loci and 4,437 core adaptive genes linked to water deprivation, hormone regulation, and metabolism. Genomic offset predicts higher maladaptation risk in populations under drastic climate change. Furthermore, metabolomic and experimental data demonstrate that diverged promoters of two O-methyltransferase genes, OMT250 and OMT310, account for the differential acacetin/linarin accumulation between C. morifolium and O. longilobus. These findings advance understanding of evolution and climate vulnerability of Opisthopappus, offering a model for genomics-guided biodiversity conservation. ### Competing Interest Statement The authors have declared no competing interest. National Key Research and Development Program of China, 2021YFD1200200

Garden chrysanthemums (Chrysanthemum x morifolium Ramat.) are widely appreciated for their rich diversity in color, form, and blooming period. However, traditional evaluations of ornamental traits rely on subjective and labor-intensive methods, limiting efficiency and consistency. To address this, we developed an UAV-based phenotyping framework to objectively assess ornamental traits in chrysanthemums. Using the UAV-based RGB imaging platform, we evaluated forty cultivars and extracted eleven ornamental traits, including plant height, canopy orthophoto area, canopy roundness, clump cohesion, ornamental duration, flowering rarity grade, flowering efficiency index, visual uniformity, flower color coverage, color saturation, and color value. Principal component analysis (PCA) reduced trait dimensionality, with four principal components explaining 77.94 % of total variance. K-means clustering grouped cultivars into three performance categories (excellent, moderate, poor), supported by hierarchical clustering. Color group analysis showed that pink-purple cultivars exhibited the greatest color diversity, while red cultivars were more uniform. Traits associated with color and texture (e.g., color coverage, saturation, visual uniformity) and floral duration (e.g., efficiency index, ornamental duration) were most influential in cultivar differentiation. Twelve cultivars, such as 'Jinling Guili', were identified as excellent based on their visual appeal and landscape suitability. Our results demonstrate that UAV-based phenotyping provides an efficient, objective, and scalable method for cultivar evaluation. The proposed framework identifies color-texture and floral duration as core drivers and offers valuable tools for chrysanthemum breeding and landscape application. More broadly, this study demonstrates the potential of integrating remote sensing and multivariate analysis to modernize ornamental plant evaluation across diverse germplasm resources.

The role of ethylene as an initial signaling molecule in waterlogging stress is well-established. However, the complex molecular mechanisms underlying ethylene biosynthesis and its functional significance in chrysanthemums under waterlogging conditions have remained unclear. In this study, we observed an increase in the expression of 1-aminocyclopropane-1-carboxylate synthase 6 (CmACS6), which encodes a key enzyme responsible for ethylene biosynthesis, in response to waterlogging. This elevation increases ethylene production, induces leaf chlorosis, and enhances the chrysanthemum's sensitivity to waterlogging stress. Moreover, our analysis of upstream regulators revealed that the expression of CmACS6, in response to waterlogging, is directly upregulated by CmHRE2-like (Hypoxia Responsive ERF-like, CmHRE2L), an ethylene response factor. Notably, CmHRE2-L binds directly to the GCC-like motif in the promoter region of CmACS6. Genetic validation assays demonstrated that CmHRE2L was induced by waterlogging and contributed to ethylene production, consequently reducing waterlogging tolerance in a partially CmACS6-dependent manner. This study identified the regulatory module involving CmHRE2L and CmACS6, which governs ethylene biosynthesis in response to waterlogging stress.

Chrysanthemum, a globally renowned economic crop, primarily relies on vegetative propagation methods such as cutting for commercial cultivation. However, certain varieties with exceptional ornamental qualities often encounter difficulties in widespread adoption due to poor rooting ability and suboptimal root quality. The genetic underpinnings of rooting ability in chrysanthemum cuttings have remained largely unexplored. This study marks a significant advancement in this field. By evaluating 11 rooting traits across a diverse panel of 188 chrysanthemum genotypes, we found that spray cut chrysanthemums exhibit superior rooting ability compared to other cultivated types and wild species. Selective sweep analysis identified 534 selected genomic regions potentially linked to rooting traits during the domestication and improvement of chrysanthemums. Genome-wide association studies (GWAS) conducted on four key rooting traits - total root length, root surface area, average root diameter, and number of roots, using multiple models discovered 71 significant SNPs and 98 candidate genes, including 21 differentially expressed genes identified via transcriptomic sequencing. A weighted gene co-expression network analysis further revealed two key modules (yellow and lightyellow) related to rooting traits. By integrating GWAS, transcriptomic data, and functional verification, we pinpointed the candidate gene CmNRAMP3 as a negative regulator of rooting ability. These findings substantially enrich our understanding of the genetic mechanisms underlying rooting ability in chrysanthemum cuttings and provide a promising gene pool for improving rooting traits in future breeding programs.

Chrysanthemum is rich in active compounds such as flavonoids and phenolic acids,and its dried head flowers are commonly used for tea and medicinal purposes.However,the genetic determinism underlying chrysanthemum active compounds remains elusive.In this study,we evaluated a panel of 137 chrysanthemum accessions for total flavonoids,chlorogenic acid,luteolin,and isochlorogenic acid A across two consecutive years.The four active compounds exhibited considerable variation,with a coefficient of variation ranging from 44.96％to 76.30％.Significant differences were observed in genotype and environments,and the broad-sense heritability was estimated at 0.5-0.63 for all examined traits.Significant pair-wise correlation was found between the four active compounds.Several accessions showing the highest active compounds were figured out for breeding use by integrating the membership function and hierarchical cluster analysis methods.Based on the 327 042 high-quality SNPs,a genome-wide association study(GWAS)captured 59 significant SNPs for the four active compounds,of which 24 elite alleles exhibited pyramiding effects.A total of 18 potential candidate genes were mined,among which evm.model.scaffold_1149.273(QUA1)has one linkage disequilibrium(LD)block corresponding to Hap4 with the highest luteolin content.The findings are beneficial to understanding the genetic basis of the active compounds and provide parental materials and valuable markers for the genetic improvement of active com-pounds in chrysanthemums.

Black spot disease (BSD), induced by Alternaria alternata, constitutes a significant menace to chrysanthemum. Identifying resistant germplasm resources underscores its critical importance in chrysanthemum breeding. To elucidate the genetic basis and candidate genes underpinning chrysanthemum BSD resistance, we conducted a multi-locus genome-wide association study (GWAS) using a panel of 152 accessions and 351 555 single nucleotide polymorphisms (SNPs) via the 3VmrMLM method. We observed extensive phenotypic variation for the disease severity index (DSI) of BSD, with coefficients of variation ranging from 70.79% to 85.00%, and the broad-sense heritability was calculated at 74.36%. GWAS result detected seventy-one quantitative trait nucleotides (QTNs) and seven QTN-by-environment interactions (QEIs), accounting for 1.53%-7.06% and 0.68%-3.16% of the phenotypic variation, respectively. Eighteen stable QTNs were identified in more than two methods, from which eight highly favorable SNP alleles were extracted for BSD resistance. Furthermore, we observed a significant dosage-pyramiding effect (P < 0.001) among the favorable alleles. Among the genes surrounding the QTNs and QEIs, 12 were homologous to known disease-resistance genes in Arabidopsis, and 14 candidate genes were mined by combining the functional annotation and transcriptomics data, respectively. Our results help better understand the genetic architecture of BSD resistance, and the identified significant SNPs and candidate genes pave the way for future molecular breeding of chrysanthemums with enhanced BSD resistance.

Waterlogging is a major stress that impacts the chrysanthemum industry. Large-scale germplasm screening for identifying waterlogging-tolerant resources in a quick and accurate manner is essential for developing new cultivars with improved waterlogging tolerance. To overcome this phenotyping bottleneck, consumer-grade digital cameras have been used to acquire the red-green-blue (RGB) images of 180 chrysanthemum cultivars and their wild relatives under waterlogging stress and well-watered conditions. A total of 103 image-based digital traits (i-traits), including 10 morphological i-traits and 93 texture i-traits, were extracted and systematically analyzed. Most of these i-traits presented high coefficients of variation (CVs) and broad-sense heritability (H 2 ), with an average CV of 34.04 ​% and an average H 2 of 0.93. We identified several novel texture i-traits associated with the hue (H) component, which strongly correlated with the traditional waterlogging tolerance index, the membership function value of waterlogging (MFVW) (R ​= ​0.63-0.77). We further employed the random forest (RF) and gradient boosting tree (GBT) machine learning algorithms to predict aboveground biomass and MFVW on the basis of different i-trait datasets. The RF model achieved superior predictive performance, with a coefficient of determination (R 2 ) of up to 0.88 for shoot weight and 0.86 for MFVW. Moreover, a subset of the top 13 most important i-traits could accurately predict MFVW (R 2  ​> ​0.80) via the cross-validation method. A total of 10 highly tolerant resources were selected by traditional and RGB-based evaluation, and 50 ​% belonged to Artemisia. Our findings confirmed that RGB-based technology provides a promising novel approach for quantifying waterlogging response that contributes to future breeding programs and genetic dissection for waterlogging tolerance.

Drought stress is a major environmental constraint that severely impacts plant production. However, the genetic basis is primarily misunderstood in chrysanthemum species. The objectives of this study are to examine the genetic variation of drought tolerance in reciprocal F1 progenies of Chrysanthemum dichrum (drought-tolerant) and Chrysanthemum nankingense (drought-sensitive) and identify candidate genes by integrating linkage mapping, genome-wide association study (GWAS), and RNA-seq analysis. The results revealed extensive variation for the investigated traits in response to drought stress and notable genetic divergence in drought tolerance between the reciprocal crosses. This confirms that the hybridization direction influenced drought tolerance phenotypes. A high-resolution genetic map containing 6677 nonredundant bin markers spanning 1859.31 cM across nine linkage groups (LGs), achieving an average marker density of 0.28 cM, was developed with a genotyping-by-sequencing (GBS) approach. The inclusive composite interval mapping (ICIM) detected 89 significant quantitative trait loci (QTLs), and GWAS identified 1360 significant quantitative trait nucleotides (QTNs) in Single_Env, 394 QTNs, and 114 quantitative epistatic interactions (QEIs) in the Multi_Env algorithm, as well as six pairs of epistatic loci (QEs) related to drought tolerance. Besides the additive effects, we observed considerable adverse dominant and epistatic effects for the significant loci, explaining why drought tolerance exhibits negative heterosis in reciprocal crosses. The integration of QTL mapping and GWAS revealed 38 colocalized loci harboring 10 known and 15 novel candidate genes, eight validated through RNA-seq and qRT-PCR analyses. Moreover, we identified elite haplotypes yielding higher drought tolerance within the candidate gene Cn1062070. The findings help elucidate the genetic architecture of drought tolerance in chrysanthemum species and provide valuable genetic resources for the development of drought-tolerant cultivars.

Plant height (PH) is a crucial trait determining plant architecture in chrysanthemum. To better understand the genetic basis of PH, we investigated the variations of PH, internode number (IN), internode length (IL), and stem diameter (SD) in a panel of 200 cut chrysanthemum accessions. Based on 330 710 high-quality SNPs generated by genotyping by sequencing, a total of 42 associations were identified via a genome-wide association study (GWAS), and 16 genomic regions covering 2.57 Mb of the whole genome were detected through selective sweep analysis. In addition, two SNPs, Chr1_339370594 and Chr18_230810045, respectively associated with PH and SD, overlapped with the selective sweep regions from FST and π ratios. Moreover, candidate genes involved in hormones, growth, transcriptional regulation, and metabolic processes were highlighted based on the annotation of homologous genes in Arabidopsis and transcriptomes in chrysanthemum. Finally, genomic selection for four PH-related traits was performed using a ridge regression best linear unbiased predictor model (rrBLUP) and six marker sets. The marker set constituting the top 1000 most significant SNPs identified via GWAS showed higher predictabilities for the four PH-related traits, ranging from 0.94 to 0.97. These findings improve our knowledge of the genetic basis of PH and provide valuable markers that could be applied in chrysanthemum genomic selection breeding programs.

Ethylene-responsive factors (ERF) play an important role in plant responses to waterlogging stress. However, the function and mechanism of action of ERFVIII in response to waterlogging stress remain poorly understood. In this study, we found that expression of the ERF VIIIa gene CmERF4 in chrysanthemum was induced by waterlogging stress. CmERF4 localized to the nucleus when expressed in tobacco leaves. Yeast two-hybrid and luciferase assays showed that CmERF4 is a transcriptional inhibitor. CmERF4 overexpression in chrysanthemum reduced plant waterlogging tolerance, whereas overexpression of the chimeric activator CmERF4-VP64 reversed its transcriptional activity, promoting higher waterlogging tolerance than that observed in wild-type plants, indicating that CmERF4 negatively regulates waterlogging tolerance. Transcriptome profiling showed that energy metabolism and reactive oxygen species (ROS) pathway-associated genes were differentially expressed between CmERF4-VP64 and wild-type plants. RT-qPCR analysis of selected energy metabolism and reactive oxygen species-related genes showed that the gene expression patterns were consistent with the expression levels obtained from RNA-seq analysis. Overall, we identified new functions of CmERF4 in negatively regulating chrysanthemum waterlogging tolerance by modulating energy metabolism and ROS pathway genes. CmERF4 contributes to the waterlogging susceptibility in chrysanthemum by modulating energy metabolism and ROS pathway genes.

High-density genetic maps are a valuable tool for quantitative trait locus (QTL) mapping and gene discovery for important traits in plants. However, such work in chrysanthemum remains largely unexplored, primarily owing to its large genome and complex genetic background. In this study, a high-density map containing 11,941 SNP bins spanning a total of 2,967.76 cM in 27 linkage groups (LGs) with an average intermarker distance of 0.26 cM was developed with a genotyping by sequencing (GBS) approach. A total of 34 QTL clusters for waterlogging tolerance (WAT) were detected via multiple-QTL mapping (MQM) algorithms. A total of 186 candidate genes within these QTL clusters were mined in combination with transcriptome data. One key candidate gene within the QTL cluster cWAT6.1, which belongs to group VII ethylene response factors (CmWAT6.1), was proven to be a positive regulator of WAT in chrysanthemum. Furthermore, transcriptomic assays of transgenic and wild-type chrysanthemums under normal conditions as well as further experiments provided evidence that CmWAT6.1 regulated WAT by promoting cell wall formation and lignin biosynthesis and coordinating oligosaccharide metabolic processes. This study represents important progress in gene mining through forward genetics, provides valuable genetic resources for further WAT improvement and provides new insight into the molecular mechanism of WAT in chrysanthemum.

The dynamic genetic architecture of flowering time in chrysanthemum was elucidated by GWAS. Thirty-six known genes and 14 candidate genes were identified around the stable QTNs and QEIs, among which ERF-1 was highlighted. Flowering time (FT) adaptation is one of the major breeding goals in chrysanthemum, a multipurpose ornamental plant. In order to reveal the dynamic genetic architecture of FT in chrysanthemum, phenotype investigation of ten FT-related traits was conducted on 169 entries in 2 environments. The broad-sense heritability of five non-conditional FT traits, i.e., budding (FBD), visible coloring (VC), early opening (EO), full-bloom (OF) and decay period (DP), ranged from 56.93 to 84.26

Background Heterosis breeding is one of the most important breeding methods for chrysanthemum. To date, the genetic mechanisms of heterosis for waterlogging tolerance in chrysanthemum are still unclear. This study aims to analyze the expression profiles and potential heterosis-related genes of two hybrid lines and their parents with extreme differences in waterlogging tolerance under control and waterlogging stress conditions by RNA-seq. Results A population of 140 F1 progeny derived from Chrysanthemum indicum (Nanchang) (waterlogging-tolerant) and Chrysanthemum indicum (Nanjing) (waterlogging-sensitive) was used to characterize the extent of genetic variation in terms of seven waterlogging tolerance-related traits across two years. Lines 98 and 95, respectively displaying positive and negative overdominance heterosis for the waterlogging tolerance traits together with their parents under control and waterlogging stress conditions, were used for RNA-seq. In consequence, the maximal number of differentially expressed genes (DEGs) occurred in line 98. Gene ontology (GO) enrichment analysis revealed multiple stress-related biological processes for the common up-regulated genes. Line 98 had a significant increase in non-additive genes under waterlogging stress, with transgressive up-regulation and paternal-expression dominant patterns being the major gene expression profiles. Further, GO analysis identified 55 and 95 transgressive up-regulation genes that overlapped with the up-regulated genes shared by two parents in terms of responses to stress and stimulus, respectively. 6,640 genes in total displaying maternal-expression dominance patterns were observed in line 95. In addition, 16 key candidate genes, including SAP12, DOX1, and ERF017 which might be of significant importance for the formation of waterlogging tolerance heterosis in line 98, were highlighted. Conclusion The current study provides a comprehensive overview of the root transcriptomes among F1 hybrids and their parents under waterlogging stress. These findings lay the foundation for further studies on molecular mechanisms underlying chrysanthemum heterosis on waterlogging tolerance.