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      Transcriptome Analysis of Litsea cubeba Floral Buds Reveals the Role of Hormones and Transcription Factors in the Differentiation Process

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          Litsea cubeba (Lour.) Pers. is an important economic plant that is rich in valuable essential oil. The essential oil is often used as a raw material for perfumes, food additives, insecticides and bacteriostats. Most of the essential oil is contained in the fruit, and the quantity and quality of fruit are dependent on the flowers. To explore the molecular mechanism of floral bud differentiation, high-throughput RNA sequencing was used to detect differences in the gene expression of L. cubeba female and male floral buds at three differentiation stages.


          This study obtained 160.88 Gbp of clean data that were assembled into 100,072 unigenes, and a total of 38,658 unigenes were annotated. A total of 27,521 simple sequence repeats (SSRs) were identified after scanning the assembled transcriptome, and the mono-nucleotide repeats were predominant, followed by di-nucleotide and tri-nucleotide repeats. A total of 12,559 differentially expressed genes (DEGs) were detected from the female (F) and male (M) floral bud comparisons. The gene ontology (GO) databases revealed that these DEGs were primarily contained in “metabolic processes”, “cellular processes”, and “single-organism processes”. The Kyoto Encyclopedia of Genes and Genomes (KEGG) databases suggested that the DEGs belonged to “plant hormone signal transduction” and accounted for a relatively large portion in all of these comparisons. We analyzed the expression level of plant hormone-related genes and detected the contents of several relevant plant hormones in different stages. The results revealed that the dynamic changes in each hormone content were almost consistent with the expression levels of relevant genes. The transcription factors selected from the DEGs were analyzed. Most DEGs of MADS-box were upregulated and most DEGs of bZIP were downregulated. The expression trends of the DEGs were nearly identical in female and male floral buds, and qRT-PCR analysis revealed consistency with the transcriptome data.


          We sequenced and assembled a high-quality L. cubeba floral bud transcriptome, and the data appeared to be well replicated (n = 3) over three developmental time points during flower development. Our study explored the changes in the contents of several plant hormones during floral bud differentiation using biochemical and molecular biology techniques, and the changes in expression levels of several flower development related transcription factors. These results revealed the role of these factors ( i.e., hormones and transcription factors) and may advance our understanding of their functions in flower development in L. cubeba.

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          Most cited references 51

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          Trinity: reconstructing a full-length transcriptome without a genome from RNA-Seq data

          Massively-parallel cDNA sequencing has opened the way to deep and efficient probing of transcriptomes. Current approaches for transcript reconstruction from such data often rely on aligning reads to a reference genome, and are thus unsuitable for samples with a partial or missing reference genome. Here, we present the Trinity methodology for de novo full-length transcriptome reconstruction, and evaluate it on samples from fission yeast, mouse, and whitefly – an insect whose genome has not yet been sequenced. Trinity fully reconstructs a large fraction of the transcripts present in the data, also reporting alternative splice isoforms and transcripts from recently duplicated genes. In all cases, Trinity performs better than other available de novo transcriptome assembly programs, and its sensitivity is comparable to methods relying on genome alignments. Our approach provides a unified and general solution for transcriptome reconstruction in any sample, especially in the complete absence of a reference genome.
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            TIGR Gene Indices clustering tools (TGICL): a software system for fast clustering of large EST datasets.

            TGICL is a pipeline for analysis of large Expressed Sequence Tags (EST) and mRNA databases in which the sequences are first clustered based on pairwise sequence similarity, and then assembled by individual clusters (optionally with quality values) to produce longer, more complete consensus sequences. The system can run on multi-CPU architectures including SMP and PVM.
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              FD, a bZIP protein mediating signals from the floral pathway integrator FT at the shoot apex.

              FLOWERING LOCUS T (FT) is a conserved promoter of flowering that acts downstream of various regulatory pathways, including one that mediates photoperiodic induction through CONSTANS (CO), and is expressed in the vasculature of cotyledons and leaves. A bZIP transcription factor, FD, preferentially expressed in the shoot apex is required for FT to promote flowering. FD and FT are interdependent partners through protein interaction and act at the shoot apex to promote floral transition and to initiate floral development through transcriptional activation of a floral meristem identity gene, APETALA1 (AP1). FT may represent a long-distance signal in flowering.

                Author and article information

                [* ]State Key Laboratory of Tree Genetics and Breeding, Chinese Academy of Forestry, Beijing, China
                []Research Institute of Subtropical Forestry, Chinese Academy of Forestry, Hangzhou, China
                []Fujian Academy of Forestry, the Key Laboratory of Timber Forest Breeding and Cultivation for Mountainous Areas in Southern China, the Key Laboratory of Forest Culture and Forest Product Processing Utilization of Fujian Province, Fuzhou, China
                Author notes

                These authors contributed equally to this work.

                [2 ]Corresponding Author: Room 606, Research Institute of Subtropical Forestry, Chinese Academy of Forestry, No.73 Daqiao Road, Hangzhou, Zhejiang province, P. R. China, 311400 Liwen Wu, wuliwenhappy@ ; Yangdong Wang, wyd11111@
                G3 (Bethesda)
                G3: Genes, Genomes, Genetics
                G3: Genes, Genomes, Genetics
                G3: Genes, Genomes, Genetics
                G3: Genes|Genomes|Genetics
                Genetics Society of America
                27 February 2018
                April 2018
                : 8
                : 4
                : 1103-1114
                Copyright © 2018 He et al.

                This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                Figures: 5, Tables: 8, Equations: 0, References: 53, Pages: 12
                Genome Reports


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