Mining lycodine-type alkaloid biosynthetic genes and genetic markers from transcriptome of Lycopodiastrum casuarinoides / 中草药·英文版

ABSTRACT

Objective: Lycopodiastrum casuarinoides, a fern of the Lycopodiaceae family, is a traditional Chinese medicine, which has similar efficacy to that of Huperzia serrata in treating rheumatoid arthritis (RA). However, they are different in the contents and compositions of lycopodium alkaloids. In this study, the biosynthesis related genes of lycopodium alkaloids and genetic markers are discovered in L. casuarinoides transcriptome. Methods: The plant of L. casuarinoides was collected and was subjected to the RNA isolation, cDNA library construction, high throughput RNA sequencing and bioinformatics analysis. Results: Totally 124, 524 high-quality unigenes were assembled from RNA sequencing reads, with an average sequence length of 601 bp. Among the L. casuarinoides transcripts, 61,304 shared the significant similarity (E-value < 10−5) with existing protein sequences in the public databases. From 124,524 unigenes, 47,538 open reading frames (ORFs) were predicted. Based on the bioinformatics analysis, all possible enzyme genes involved in the lycodine-type alkaloids biosynthetic pathway of L. casuarinoides were identified, including lysine decarboxylase (LDC), primary amine oxidase (PAO), malonyl-CoA decarboxylase, etc. Sixty-four putative cytochrome p450 (CYP) and 827 putative transcription factors were selected from the transcriptome unigenes as the candidates of lycodine-type alkaloids biosynthesis modifiers. Furthermore, 13,352 simple sequence repeats (SSRs) were identified from 124,524 unigenes, of which dinucleotide motifs AG/CT were the most abundant (50.1%). Meanwhile, we confirmed the amplification effectiveness of 25 PCR primer pairs for randomly selected SSRs. Conclusion: We obtained the comprehensive transcriptomic information from the high throughput RNA sequencing and bioinformatics analysis, which provided a valuable resource of transcript sequences of L. casuarinoides in public databases.