Full-length transcriptome sequencing reveals the molecular mechanism of potato seedlings responding to low-temperature

Abstract

Background: Potato (Solanum tuberosum L.) is one of the world's most important crops, the cultivated potato is frost-sensitive, and low-temperature severely influences potato production. However, the mechanism by which potato responds to low-temperature stress is unclear. In this research, we apply a combination of second-generation sequencing and third-generation sequencing technologies to sequence full-length transcriptomes in low-temperature-sensitive cultivars to identify the important genes and main pathways related to low-temperature resistance.

Results: In this study, we obtained 41,016 high-quality transcripts, which included 15,189 putative new transcripts. Amongst them, we identified 11,665 open reading frames, 6085 simple sequence repeats out of the potato dataset. We used public available genomic contigs to analyze the gene features, simple sequence repeat, and alternative splicing event of 24,658 non-redundant transcript sequences, predicted the coding sequence and identified the alternative polyadenylation. We performed cluster analysis, GO, and KEGG functional analysis of 4518 genes that were differentially expressed between the different low-temperature treatments. We examined 36 transcription factor families and identified 542 transcription factors in the differentially expressed genes, and 64 transcription factors were found in the AP2 transcription factor family which was the most. We measured the malondialdehyde, soluble sugar, and proline contents and the expression genes changed associated with low temperature resistance in the low-temperature treated leaves. We also tentatively speculate that StLPIN10369.5 and StCDPK16 may play a central coordinating role in the response of potatoes to low temperature stress.

Conclusions: Overall, this study provided the first large-scale full-length transcriptome sequencing of potato and will facilitate structure-function genetic and comparative genomics studies of this important crop.

Keywords: Full-length transcriptomes; Low-temperature stress; Second-generation sequencing technologies; Third-generation sequencing technologies; potato.

Fig. 1

The effect of low-temperature stress on the physiological metabolism of potato. A is the effect of different low temperatures on MDA content in potato seedlings; B is the effect of low temperatures on proline content in potato seedlings; C is the effect of low temperatires on soluble sugar content in potato seedlings; S 20 is the control group which was treated at 20 °C for hours; S 2 is the treatment group which was treated at 2 °C for 4 h; S -2 is the treatment group which was treated at -2 °C for 4 h

Fig. 2

Summary of PacBio RS II single-molecule real-time (SMRT) sequencing. A is the number and length distributions of 220,035 reads in potato; B is the proportion of different types of PacBio reads in potato; C is the consensus isoforms read length distribution of each size bins

Fig. 3

The Comparison of homologous species in Nr database

Fig. 4

Statistics of the number of alternative splicing events. Alternative 3'splice site: alternative transcription termination site; Alternative 5'splice site: alternative transcription start site; Exon skipping: exon skipping; Intron retention: intron retention; Mutually exclusive exon: available Change exons

Fig. 5

The distribution of different type of SSRs

Fig. 6

Predicted CDS-encoded protein length distribution map. A is the predicted best CDS-encoded protein length distribution map; B is the predicted complete CDS-encoded protein length distribution map

Fig. 7

Distributions of polyadenylation sites in potato gene. Abscissa: the number of polyadenylation sites; Ordinate: the number of genes

Fig. 8

Differentially expressed genes volcano map. Each point in the volcano map represents a gene. The abscissa represents the logarithm of the difference in expression of a certain gene in two samples; the ordinate represents the negative logarithm of the change in gene expression. The larger the absolute value of the abscissa, the greater the difference in expression between two samples; the larger the ordinate value, the more significant the difference and the more reliable the differentially expressed genes. In the figure, the green dots represent down-regulated differentially expressed genes, the red dots represent up- regulated differentially expressed genes, and the black dots represents non-differentially expressed genes. A is the differentially expressed transcript volcano map of S20 vs S2; B is the differentially expressed transcript volcano map of S20 vs S-2; C is the differentially expressed transcript volcano map of S2 vs S-2

Fig. 9

Heat map of DEGs during low-temperature stress in the potato. The color represents gene expression values (the red corresponds to genes with high expression and the blue corresponds to gene with low expression). S20, S2 and S-2 correspond to the libraries obtained in the temperature 20 °C, 2 °C and -2 °C respectively. A up-regulation at 20 °C but down-regulation at other 2 temperatures; B: down-regulation at 20 °C but up-regulation at other 2 temperatures; C: up-regulation at 2 °C but down-regulation at other 2 temperatures; D: down-regulation at 2 °C but up-regulation at other 2 temperatures; E: up-regulation at 2 °C but down-regulation at other 2 temperatures; F: up-regulation at -2 °C but down-regulation at other 2 temperatures

Fig. 10

GO enrichment analysis mapped to potato during low-temperature stress in the potato. A is the GO enrichment analysis between S20 vs S2; B is the GO enrichment analysis between S20 vs S-2; C is the GO enrichment analysis between S2 vs S-2

Fig. 11

COG annotation classification statistics of differentially expressed genes. The abscissa is the content of each COG classification, and the ordinate is the number of genes; A is the COG annotation classification statistics analysis between S20 vs S2; B is the COG annotation classification statistics between S20 vs S-2; C is the COG annotation classification statistics analysis between S2 vs S-2

Fig. 12

Scatter plot of enrichment of differentially expressed genes in the KEGG pathway. Each circle in the figure represents a KEGG pathway, the ordinate indicated the name of the pathway, and the abscissa is the enrichment factor, which represents the ratio of the proportion of genes annotated to a pathway in the differential gene to the proportion of genes annotated to the pathway in all genes. The larger the enrichment factor the more significant the enrichment level of differentially expressed genes in this pathway. The color of the circle represents the q-value, which is the P-value after multiple hypothesis testing corrections. The smaller the q-value, the more reliable the significance of the enrichment of differentially expressed genes in the pathway; the size of the circle indicates the number of enriched genes in the pathway, the larger the circle, the more genes. A is the KEGG enrichment analysis between S20 vs S2; B is the KEGG enrichment analysis between S20 vs S-2; C is the KEGG enrichment analysis between S2 vs S-2

Fig. 13

The qPCR validation of partial genes during low-temperature stress in the potato. Note: *P < 0.05; **P < 0.001; the number of biological replicates = 3