Transcriptome Analysis Reveals That FvPAP1 Genes Are Related to the Prolongation of Red-Leaf Period in Ficus virens.

Ficus virens is a deciduous tree that is highly valuable both economically and medicinally. Like other plants with 'red young leaves', the red-leaf period of most F. virens trees lasts only a few days, and the red leaves have little ornamental value. However, in recent years, some lines of F. virens with bright red young leaves and a prolonged red-leaf period have been utilized for urban greening. To explore the mechanism of the different lengths of the duration of F. virens leaves, we analyzed the physiology and changes in gene expression during the development of two varieties of leaves. The detection of anthocyanin in different developmental stages of the F. virens leaves showed that the changes in color of the red leaves of F. virens were primarily caused by the change in anthocyanin content. A transcriptome analysis showed that the expression of genes related to the biosynthesis of anthocyanin changed significantly during the development of leaves. A MYB gene FvPAP1, which was consistent with the change in anthocyanin content, was identified. A real-time quantitative reverse transcription PCR analysis and heterologous expression transgenic studies showed that FvPAP1 promoted the biosynthesis of anthocyanins. The difference in the expression of FvPAP1 in time and intensity in the young leaves may be the reason for the difference in the duration of the red-leaf period in different lines of F. virens. A sequence analysis showed that the cDNA sequence of FvPAP1 was polymorphic, and possible reasons were discussed. These results can provide insight for similar studies on the mechanism of the formation of red coloring in other woody plant leaves and provide molecular targets to breed new materials with more prolonged red-leaf periods in F. virens.

Integrated transcriptome and proteome analysis provides insights into CpFPA1 for floral induction in Chimonanthus praecox (Magnoliidae) without FLC in genome.

KEY MESSAGE: We used transcriptomic and proteomic association analysis to reveal the critical genes/proteins at three key flower bud differentiation stages and overexpression of CpFPA1 in Arabidopsis resulted in earlier flowering. Wintersweet (Chimonanthus praecox), a rare winter-flowering woody plant, is well known for its unique blooming time, fragrance and long flowering period. However, the molecular mechanism of flowering in C. praecox remains poorly unclear. In this study, we used transcriptomic and proteomic association analysis to reveal the critical genes/proteins at three key flower bud (FB) differentiation stages (FB.Apr, FB.May and FB.Nov) in C. praecox. The results showed that a total of 952 differential expressed genes (DEGs) and 40 differential expressed proteins (DEPs) were identified. Gene ontology (GO) enrichment revealed that DEGs in FB.Apr/FB.May comparison group were mainly involved in metabolic of biological process, cell and cell part of cellular component and catalytic activity of molecular function. In the EuKaryotic Orthologous Groups (KOG) functional classification, DEPs were predicted mainly in the function of general function prediction only (KOG0118), post-translational modification, protein turnover and chaperones. The autonomous pathway genes play an essential role in the floral induction. Based on transcriptome and proteome correlation analysis, six candidate genes associated with the autonomous pathway were identified, including FPA1, FPA2a, FPA2b, FCA, FLK, FY. Furthermore, CpFPA1 was isolated and functionally characterized, and ectopic expression of CpFPA1 in Arabidopsis Columbia (Col-0) resulted in earlier flowering. These data could contribute to understand the function of CpFPA1 for floral induction and provide information for further research on the molecular mechanisms of flowering in wintersweet.

Establishment of Novel Simple Sequence Repeat (SSR) Markers from Chimonanthus praecox Transcriptome Data and Their Application in the Identification of Varieties.

Chimonanthus praecox, a member of the Calycanthaceae family, is a unique, traditional, and famous flowering economic tree species in China. Despite the existence of several varieties, only a few cultivars have been formally named. Currently, expression sequence tag-simple sequence repeat (EST-SSR) markers are extensively used to identify different species and varieties; a large number of microsatellites can be identified from transcriptome databases. A total of 162,638 unigenes were assembled using RNA-seq; 82,778 unigenes were annotated using the Nr, Nt, Swiss-Prot, Pfam, GO, KOG, and KEGG databases. In total, 13,556 SSR loci were detected from 11,691 unigenes, with trinucleotide repeat motifs being the most abundant among the six repeat motifs. To develop the markers, 64,440 pairs of SSR primers with polymorphism potential were designed, and 75 pairs of primers were randomly selected for amplification. Among these markers, seven pairs produced amplified fragments of the expected size with high polymorphism. Using these markers, 12 C. praecox varieties were clustered into two monophyletic clades. Microsatellites in the transcriptome of C. praecox exhibit rich types, strong specificity, and great polymorphism potential. These EST-SSR markers serve as molecular technical methods for identifying different varieties of C. praecox and facilitate the exploration of a large number of candidate genes associated with important traits.

Optimizing DUS testing for Chimonanthus praecox using feature selection based on a genetic algorithm.

Chimonanthus praecox is a famous traditional flower in China with high ornamental value. It has numerous varieties, yet its classification is highly disorganized. The distinctness, uniformity, and stability (DUS) test enables the classification and nomenclature of various species; thus, it can be used to classify the Chimonanthus varieties. In this study, flower traits were quantified using an automatic system based on pattern recognition instead of traditional manual measurement to improve the efficiency of DUS testing. A total of 42 features were quantified, including 28 features in the DUS guidelines and 14 new features proposed in this study. Eight algorithms were used to classify wintersweet, and the random forest (RF) algorithm performed the best when all features were used. The classification accuracy of the outer perianth was the highest when the features of the different parts were used for classification. A genetic algorithm was used as the feature selection algorithm to select a set of 22 reduced core features and improve the accuracy and efficiency of the classification. Using the core feature set, the classification accuracy of the RF model improved to 99.13%. Finally, K-means was used to construct a pedigree cluster tree of 23 varieties of wintersweet; evidently, wintersweet was clustered into a single class, which can be the basis for further study of genetic relationships among varieties. This study provides a novel method for DUS detection, variety identification, and pedigree analysis.