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RNA-seq analysis of Rubus idaeus cv. Nova: transcriptome sequencing and de novo assembly for subsequent functional genomics approaches

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Using Illumina sequencing technology, we have generated the large-scale transcriptome sequencing data containing abundant information on genes involved in the metabolic pathways in R. idaeus cv. Nova fruits.

Abstract

Rubus idaeus (Red raspberry) is one of the important economical crops that possess numerous nutrients, micronutrients and phytochemicals with essential health benefits to human. The molecular mechanism underlying the ripening process and phytochemical biosynthesis in red raspberry is attributed to the changes in gene expression, but very limited transcriptomic and genomic information in public databases is available. To address this issue, we generated more than 51 million sequencing reads from R. idaeus cv. Nova fruit using Illumina RNA-Seq technology. After de novo assembly, we obtained 42,604 unigenes with an average length of 812 bp. At the protein level, Nova fruit transcriptome showed 77 and 68 % sequence similarities with Rubus coreanus and Fragaria versa, respectively, indicating the evolutionary relationship between them. In addition, 69 % of assembled unigenes were annotated using public databases including NCBI non-redundant, Cluster of Orthologous Groups and Gene ontology database, suggesting that our transcriptome dataset provides a valuable resource for investigating metabolic processes in red raspberry. To analyze the relationship between several novel transcripts and the amounts of metabolites such as γ-aminobutyric acid and anthocyanins, real-time PCR and target metabolite analysis were performed on two different ripening stages of Nova. This is the first attempt using Illumina sequencing platform for RNA sequencing and de novo assembly of Nova fruit without reference genome. Our data provide the most comprehensive transcriptome resource available for Rubus fruits, and will be useful for understanding the ripening process and for breeding R. idaeus cultivars with improved fruit quality.

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Acknowledgments

We thank Dr. Pill-Jae Park (Gochang Black Raspberry Research Institute) for supporting plant materials. This work was supported by Science and Technology and a Grant from the Next-Generation BioGreen 21 Program (SSAC Grant PJ009495; PJ00952004), Rural Development Administration, Republic of Korea.

Conflict of interest

The authors declare that they have no conflict of interest.

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Authors and Affiliations

  1. Division of Applied Life Science (BK21plus/WCU Program), Plant Molecular Biology and Biotechnology Research Center, Gyeongsang National University, Jinju, 660-701, Republic of Korea

    Tae Kyung Hyun, Dhinesh Kumar, Yeonggil Rim, Ritesh Kumar, Sang Yeol Lee & Jae-Yean Kim

  2. Division of Bioscience and Biotechnology, Konkuk University, Seoul, 143-701, Republic of Korea

    Sarah Lee & Choong Hwan Lee

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  1. Tae Kyung Hyun
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  2. Sarah Lee
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  3. Dhinesh Kumar
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  4. Yeonggil Rim
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  6. Sang Yeol Lee
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Corresponding authors

Correspondence to Choong Hwan Lee or Jae-Yean Kim.

Additional information

Communicated by Prakash Lakshmanan.

T. K. Hyun and S. Lee have contributed equally to this work.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Length distribution of assembled contigs and unigenes (TIFF 1178 kb)

299_2014_1641_MOESM2_ESM.tif

Gene ontology classification of assembled unigenes. The results are summarized in three main categories: Biological process, Cellular component and Molecular function (TIFF 1240 kb)

299_2014_1641_MOESM3_ESM.tif

Histogram presentation of clusters of orthologous groups (COG) classification. All unigenes were aligned to COG database to predict and classify possible functions. (TIFF 1941 kb)

Primer sequences for qRT-PCR analysis (DOC 52 kb)

299_2014_1641_MOESM5_ESM.xls

Top BLAST hits from NCBI nr database. BLAST results against the NCBI nr database for all the distinct sequences (XLS 8580 kb)

Pathway assignment based on KEGG (XLS 39 kb)

Anthocyanins identification of R. idaeus cv. Nova using UPLC–Q-TOF–MS and LC–IT–MS/MS (DOC 31 kb)

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Hyun, T.K., Lee, S., Kumar, D. et al. RNA-seq analysis of Rubus idaeus cv. Nova: transcriptome sequencing and de novo assembly for subsequent functional genomics approaches. Plant Cell Rep 33, 1617–1628 (2014). https://doi.org/10.1007/s00299-014-1641-4

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  • DOI: https://doi.org/10.1007/s00299-014-1641-4

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