Background: Anthurium andraeanum is one of the most popular tropical flowers. In temperate and cold zones, a much greater risk of cold stress occurs in the supply of Anthurium plants. Unlike the freeze-tolerant model plants, Anthurium plants are particularly sensitive to low temperatures. Improvement of chilling tolerance in Anthurium may significantly increase its production and extend its shelf-life. To date, no previous genomic information has been reported in Anthurium plants. Results: Using Illumina sequencing technology, we generated over two billion base of high-quality sequence in Anthurium, and demonstrated de novo assembly and annotation of genes without prior genome information. These reads were assembled into 44,382 unigenes (mean length = 560 bp). Based on similarity search with known protein in the non-redundant (nr) protein database, 27396 unigenes (62%) were functionally annotated with a cut-off E-value of 10^-5. Further, DGE tags were mapped to the assembled transcriptome for gene expression analysis under cold stress. In total, 4363 differentially expressed genes were identified. Among these genes, 292, 805 and 708 genes were up-regulated after 1-h, 5-h and 24-h cold treatment, respectively. Then we mapped these cold-induced genes to the KEGG database. Specific enrichment was observed in photosynthesis pathway, metabolic pathways and oxidative phosphorylation pathway in 1-h cold-treated plants. After a 5-h cold treatment, the metabolic pathways and oxidative phosphorylation pathway were significantly identified as the top two pathways. After 24-h cold treatment, mRNA surveillance pathway, RNA transport pathway and plant-pathogen interaction pathway were significantly enriched. Together, a total of 39 cold-inducible transcription factors were identified, including subsets of AP2/ERF, Zinc figure, NAC, MYB and bZIP family members. Conclusion: Our study is the first to provide the transcriptome sequence resource for Anthurium plants, and demonstrate its digital gene expression profiling under cold conditions using the assembled transcriptome data for reference. These data provides a valuable resource for genetic and genomic studies under abiotic conditions for Anthurium plants.

The objective of this study was to identify the major volatile compounds and their relative concentrations in flowers of different chrysanthemum cultivars and their wild relatives. The volatile organic components of fresh flowers were analyzed using a headspace solid-phase microextraction coupled with gas chromatography-mass spectrometry. In total, 193 volatile organic components were detected; the major scent components were monoterpenoids and oxygenated monoterpenoids, which accounted for 68.59%–99.93% of the total volatiles in all tested materials except for Chrysanthemum indicum collected from Huangshan, in which they accounted for only 37.45% of total volatiles. The major volatile compounds were camphor, α-pinene, chrysanthenone, safranal, myrcene, eucalyptol, 2,4,5,6,7,7ab-hexahydro-1H-indene, verbenone, β-phellandrene and camphene. In a hierarchical cluster analysis, 39 accessions of Chrysanthemum and its relatives formed six clusters based on their floral volatile compounds. In a principal component analysis, only spider type flowers were located closely on the score plot. The results of this study provide a basis for breeding chrysanthemum cultivars which desirable floral scents.

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 F_ST 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.