{'fraction_non_alphanumeric': 0.03686868686868687, 'fraction_numerical': 0.00909090909090909, 'mean_word_length': 5.8075601374570445, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
An organ‐specific transcriptomic atlas of the medicinal plant Bletilla striata: Protein‐coding genes, microRNAs, and regulatory networks

As one of the important species belonging to the Bletilla genus of Orchidaceae, Bletilla striata (Thunb.) Rchb. f., possesses both ornamental and medicinal values. Its dried tubers are used as a traditional Chinese medicine, and several secondary metabolites have been indicated to be the active ingredients. However, the molecular mechanisms related to the regulation of secondary metabolism have not been characterized in B. striata. In this study, integrated analysis of RNA sequencing (RNA‐seq), small RNA sequencing (sRNA‐seq), and degradome sequencing (degradome‐seq) data from three organs (leaf, root, and tuber) of B. striata provided us with a comprehensive view of the microRNA (miRNA)‐mediated regulatory network. Firstly, based on the RNA‐seq data, the organ‐specific expression patterns of the protein‐coding genes, especially for those related to secondary metabolism, were investigated. Secondly, 342 conserved miRNA candidates were identified from B. striata. These miRNAs were assigned to 88 families, some of which were selected for expression pattern analysis. Additionally, 31 hairpin‐structured precursors encoding 23 novel miRNAs were uncovered from the transcriptome assembly. Thirdly, based on the degradome signatures, 1,142 validated miRNA–target pairs (involving 167 conserved miRNAs and six novel miRNAs and 51 target genes) were included in the regulatory network. Organ‐specific expression level comparison between the miRNAs and their targets revealed some interesting miRNA–target pairs. Fourthly, some valuable subnetworks were extracted for further functional studies. Additionally, some regulatory pathways were indicated to be monocot specific. Summarily, our results lay a solid basis for in‐depth studies on the regulatory mechanisms underlying the production of the medicinal ingredients in B. striata.