Comprehensive transcriptome analysis reveals novel genes involved in cardiac glycoside biosynthesis and mlncRNAs associated with secondary metabolism and stress response in Digitalis purpurea

Abstract

BackgroundDigitalis purpurea is an important ornamental and medicinal plant. There is considerable interest in exploring its transcriptome.ResultsThrough high-throughput 454 sequencing and subsequent assembly, we obtained 23532 genes, of which 15626 encode conserved proteins. We determined 140 unigenes to be candidates involved in cardiac glycoside biosynthesis. It could be grouped into 30 families, of which 29 were identified for the first time in D. purpurea. We identified 2660 mRNA-like npcRNA (mlncRNA) candidates, an emerging class of regulators, using a computational mlncRNA identification pipeline and 13 microRNA-producing unigenes based on sequence conservation and hairpin structure-forming capability. Twenty five protein-coding unigenes were predicted to be targets of these microRNAs. Among the mlncRNA candidates, only 320 could be grouped into 140 families with at least two members in a family. The majority of D. purpurea mlncRNAs were species-specific and many of them showed tissue-specific expression and responded to cold and dehydration stresses. We identified 417 protein-coding genes with regions significantly homologous or complementary to 375 mlncRNAs. It includes five genes involved in secondary metabolism. A positive correlation was found in gene expression between protein-coding genes and the homologous mlncRNAs in response to cold and dehydration stresses, while the correlation was negative when protein-coding genes and mlncRNAs were complementary to each other.ConclusionsThrough comprehensive transcriptome analysis, we not only identified 29 novel gene families potentially involved in the biosynthesis of cardiac glycosides but also characterized a large number of mlncRNAs. Our results suggest the importance of mlncRNAs in secondary metabolism and stress response in D. purpurea.

Identification and characterization of mRNA-like noncoding RNAs in Salvia miltiorrhiza

“…2). Although we cannot rule out the possibility that some of the mlncRNA candidates, particularly the shorter ones, were fragments of protein-coding transcripts, the longer mlncRNA candidates, such as those with length over 900 bp (Table 3), are very likely to be authentic (Wu et al 2012a). …”

“…Members of a gene family can be derived from the same ancestors and exhibit similarity on structures and functions (Wu et al 2012a;Zhang et al 2014a). To obtain the first clue to the function of mlncRNAs, we classified the identified 5,444 S. miltiorrhiza mlnRNAs (two pri-miRNAs excluded) based on the sequence homology.…”

“…Compared with miRNA, mlncRNAs are less studied, and owing to their homology to known genes, some mlncRNAs, such as natural antisense transcripts, are often discarded in computational screens (Rymarquis et al 2008). The majority of currently known plant mlncRNAs were identified from Arabidopsis thaliana (Maclntosh et al 2001;Ben Amor et al 2009), Medicago truncatula (Wen et al 2007), wheat (Xin et al 2011), Panax ginseng , Digitalis purpurea (Wu et al 2012a) and Zea mays (Boerner and McGinnis 2012). A few were obtained from cucumber, soybean and other plants species (Rohrig et al 2002;Sugiyama et al 2003;Cho et al 2005;Ma et al 2008).…”

SSR Development and Utilization with Rehmannia glutinosa Transcriptome

“…Transcripts without any annotation in the Nr, GO, or KEGG database were mapped into R. glutinosa miRNA precursor generated in previous study (Li et al 2013), Rfam 10.0 (rfam.sanger.ac.uk/), NONCODE V3.0 (http://www.noncode.org/), and Repbase 20.0 (http://www.girinst.org/repbase/) databases using BlastN with an E-value cutoff of 10-5. Sequences recognized as long non-coding RNAs (lncRNA) in the Rfam and NONCODE databases were further distinguished from transcript-coding proteins (Wu et al, 2012). SSR primer design.…”

T-DNA Tagging: A Promising Tool for Functional Genomics in Medicinal Plants

“…EST sequencing is a rapid and relatively economic tool for transcriptome analysis. Through EST sequencing and subsequent computational analysis, some key enzyme genes involved in the biosynthesis of secondary metabolites have been identified and characterized in various medicinal plants, such as Glycyrrhiza uralensis [2], American ginseng [3], Ginkgo biloba [4], Digitalis purpurea [5], Panax notoginseng [6], Euphorbia fischeriana [7], Bupleurum chinense [8], Camptotheca acuminate [9], P. ginseng [10], Salvia miltiorrhiza [11,12], and Taxus cuspidate [13]. Whole-genome sequencing is the other effective tool for functional genomics.…”