De novo transcriptome analysis of tobacco seedlings and identification of the early response gene network under low-potassium stress.

ABSTRACT

Tobacco is an economically important crop, and its potassium content can greatly affect the quality of tobacco leaves. However, the molecular mechanism involved in potassium starvation in tobacco has not been elucidated to date. In this study, Illumina (Solexa) sequencing technology was used to analyze the transcriptome of tobacco seedlings under low-potassium stress for 6, 12, and 24 h. After analysis, 107,824 assembled unigenes were categorized into 57 GO functional groups, and 31,379 unigenes (29.08%) were clustered into 25 COG categories. A total of 9945 genes were classified into 233 KEGG pathways, and 15,209 SSRs were found among the 107,824 unigenes. Between the two samples, 1034 genes were differentially expressed. Twelve randomly selected gene expression levels were analyzed by quantitative RT-PCR, and the results were highly consistent with those obtained by Solexa sequencing. Our results provide a comprehensive analysis of the gene-regulatory network of tobacco seedlings under low-potassium stress.