Chromosome doubling mediates superior drought tolerance in Lycium ruthenicum via abscisic acid signaling

Abstract

Plants are continuously affected by unfavorable external stimuli, which influences their productivity and growth. Differences in gene composition and expression patterns lead homologous polyploid plants to exhibit different physiological phenomena, among which enhanced environmental adaptability is a powerful phenotype conferred by polyploidization. The mechanisms underlying the differences in stress tolerance between diploids and autotetraploids at the molecular level remain unclear. In this research, a full-length transcription profile obtained via the single-molecule real-time (SMRT) sequencing of high-quality single RNA molecules for use as background was combined with next-generation transcriptome and proteome technologies to probe the variation in the molecular mechanisms of autotetraploids. Tetraploids exhibited an increase in ABA content of 78.4% under natural conditions and a superior stress-resistance phenotype under severe drought stress compared with diploids. The substantial differences in the transcriptome profiles observed between diploids and autotetraploids under normal growth conditions were mainly related to ABA biosynthesis and signal transduction pathways, and 9-cis-epoxycarotenoid dioxygenase 1 (NCED1) and NCED2, which encode key synthetic enzymes, were significantly upregulated. The increased expression of the ABRE-binding factor 5-like (ABF5-like) gene was a pivotal factor in promoting the activation of the ABA signaling pathway and downstream target genes. In addition, ABA strongly induced the expression of osmotic proteins to increase the stress tolerance of the plants at the translational level. We consider the intrinsic mechanisms by which ABA affects drought resistance in tetraploids and diploids to understand the physiological and molecular mechanisms that enhance abiotic stress tolerance in polyploid plants.

Keywords: Abiotic; Polyploidy in plants.

Fig. 1. Target plants for the detection of ploidy by flow cytometry.

The upper part of the flow cytometry diagram shows the results for three diploid samples, and the bottom shows the results for tetraploids. The X and Y axes represent the ploidy and the number of cells, respectively

Fig. 2. Phenotypic status under stress and ABA content determination in L. ruthenicum of different ploidies.

a Phenotypes in L. ruthenicum of different ploidies grown in the greenhouse for 1 month. b Phenotypic status of L. ruthenicum seedlings under salt and drought stress. c Box plot of ABA contents. For each sample three replicates were performed. The two images on the left present the growth of diploids and tetraploids at 148 h under 350 mM salt treatment, and the two figures on the right show the growth of diploids and tetraploids after 15 days of drought. Duncan’s test was applied to determine significant differences between the different ploidies. Two asterisks on a column indicate a significant difference at p < 0.01

Fig. 3. Chlorophyll a, b, total chlorophyll and carotenoid contents after 0, 8, and 12 days of drought.

a Chlorophyll a after 0, 8, and 12 days of drought. b Chlorophyll b after 0, 8, and 12 days of drought. c Total chlorophyll content after 0, 8, and 12 days of drought. d Carotenoids after 0, 8, and 12 days of drought

Fig. 4. DAB determination in L. ruthenicum of different ploidies after 0 days and 12 days of drought.

Bars = 100 µm

Fig. 5. Annotation information for full-length transcripts in multiple databases.

a Annotation distribution of full-length transcripts in five databases: KOG, SwissProt, Go, NR, and eggNOG. b Consensus isoform sequence length distribution of full-length transcripts. c Functional classification of consensus isoform sequences in the COG database. d Homologous species distribution in the Nr database. e Functional classification of consensus isoform sequences in the GO database

Fig. 6. Summary of Illumina sequencing based on the full-length transcriptome.

a FPKM box plot of the second-generation transcriptome of each sample. b Correlation heat map of expression in two pairs of samples according to next-generation sequencing. c Summary of the DEGs according to the second-generation transcriptome. d Statistics of differentially expressed TFs in L. ruthenicum of different ploidies. e Investigation of the up- and downregulation of differentially expressed TFs

Fig. 7. Expression patterns of 12 candidate genes according to RNA-seq (white) and qRT-PCR (oblique line) for selected transcripts.

The data represent the mean ± SD of three independent experiments. The X-axis shows the selected gene ID, and the Y-axis shows the log₂ ratio

Fig. 8. Summary of proteomic results.

a SDS-PAGE of proteomics samples. b PCA of proteomics samples. c Venn diagram of differentially expressed proteins according to proteomic analysis. d Venn diagram of differentially expressed proteins according to proteomic analysis. e Hierarchical clustering of differentially expressed proteins according to proteomic analysis

Fig. 9. GO and KEGG classification and enrichment of DEGs and DEPs.

a GO classification of differentially expressed genes. b GO classification of differentially expressed proteins. c KEGG enrichment of DEGs. d KEGG enrichment of DEPs

Fig. 10. Model for the internal mechanisms of ABA-regulated stress resistance after chromosome doubling.

The white boxes contain the sample names (diploid 1, 2, 3 and tetraploid 1, 2, 3)