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      The root transcriptome for North American ginseng assembled and profiled across seasonal development

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          Abstract

          Background

          Ginseng including North American ginseng ( Panax quinquefolius L.) is one of the most widely used medicinal plants. Its success is thought to be due to a diverse collection of ginsenosides that serve as its major bioactive compounds. However, few genomic resources exist and the details concerning its various biosynthetic pathways remain poorly understood. As the root is the primary tissue harvested commercially for ginsenosides, next generation sequencing was applied to the characterization and assembly of the root transcriptome throughout seasonal development. Transcripts showing homology to ginsenoside biosynthesis enzymes were profiled in greater detail.

          Results

          RNA extracts from root samples from seven development stages of North American ginseng were subjected to 454 sequencing, filtered for quality and used in the de novo assembly of a collective root reference transcriptome consisting of 41,623 transcripts. Annotation efforts using a number of public databases resulted in detailed annotation information for 34,801 (84%) transcripts. In addition, 3,955 genes were assigned to metabolic pathways using the Kyoto Encyclopedia of Genes and Genomes. Among our results, we found all of the known enzymes involved in the ginsenoside backbone biosynthesis and used co-expression analysis to identify a number of candidate sequences involved in the latter stages ginsenoside biosynthesis pathway. Transcript profiles suggest ginsenoside biosynthesis occurs at distinct stages of development.

          Conclusions

          The assembly generated provides a comprehensive annotated reference for future transcriptomic study of North American ginseng. A collection of putative ginsenoside biosynthesis genes were identified and candidate genes predicted from the lesser understood downstream stages of biosynthesis. Transcript expression profiles across seasonal development suggest a primary dammarane-type ginsenoside biosynthesis occurs just prior to plant senescence, with secondary ginsenoside production occurring throughout development. Data from the study provide a valuable resource for conducting future ginsenoside biosynthesis research in this important medicinal plant.

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          Most cited references33

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          Hidden Markov model speed heuristic and iterative HMM search procedure

          Background Profile hidden Markov models (profile-HMMs) are sensitive tools for remote protein homology detection, but the main scoring algorithms, Viterbi or Forward, require considerable time to search large sequence databases. Results We have designed a series of database filtering steps, HMMERHEAD, that are applied prior to the scoring algorithms, as implemented in the HMMER package, in an effort to reduce search time. Using this heuristic, we obtain a 20-fold decrease in Forward and a 6-fold decrease in Viterbi search time with a minimal loss in sensitivity relative to the unfiltered approaches. We then implemented an iterative profile-HMM search method, JackHMMER, which employs the HMMERHEAD heuristic. Due to our search heuristic, we eliminated the subdatabase creation that is common in current iterative profile-HMM approaches. On our benchmark, JackHMMER detects 14% more remote protein homologs than SAM's iterative method T2K. Conclusions Our search heuristic, HMMERHEAD, significantly reduces the time needed to score a profile-HMM against large sequence databases. This search heuristic allowed us to implement an iterative profile-HMM search method, JackHMMER, which detects significantly more remote protein homologs than SAM's T2K and NCBI's PSI-BLAST.
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            Next-generation transcriptome assembly.

            Transcriptomics studies often rely on partial reference transcriptomes that fail to capture the full catalogue of transcripts and their variations. Recent advances in sequencing technologies and assembly algorithms have facilitated the reconstruction of the entire transcriptome by deep RNA sequencing (RNA-seq), even without a reference genome. However, transcriptome assembly from billions of RNA-seq reads, which are often very short, poses a significant informatics challenge. This Review summarizes the recent developments in transcriptome assembly approaches - reference-based, de novo and combined strategies - along with some perspectives on transcriptome assembly in the near future.
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              RNA-seq: from technology to biology

              Next-generation sequencing technologies are now being exploited not only to analyse static genomes, but also dynamic transcriptomes in an approach termed RNA-seq. Although these powerful and rapidly evolving technologies have only been available for a couple of years, they are already making substantial contributions to our understanding of genome expression and regulation. Here, we briefly describe technical issues accompanying RNA-seq data generation and analysis, highlighting differences to array-based approaches. We then review recent biological insight gained from applying RNA-seq and related approaches to deeply sample transcriptomes in different cell types or physiological conditions. These approaches are providing fascinating information about transcriptional and post-transcriptional gene regulation, and they are also giving unique insight into the richness of transcript structures and processing on a global scale and at unprecedented resolution.
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                Author and article information

                Contributors
                Journal
                BMC Genomics
                BMC Genomics
                BMC Genomics
                BioMed Central
                1471-2164
                2013
                19 August 2013
                : 14
                : 564
                Affiliations
                [1 ]Western University, 1151 Richmond St, London, ON, Canada
                [2 ]Agriculture and Agri-Food Canada, 1391 Sandford Street, London, ON, Canada
                [3 ]Canadian Centre for Agri-food Research in Health and Medicine (CCARM), St. Boniface Hospital, 351 Taché Avenue, Winnipeg, MN, Canada
                Article
                1471-2164-14-564
                10.1186/1471-2164-14-564
                3751939
                23957709
                3c5f9067-d9f2-4b2b-b2b9-c4648d1928dc
                Copyright © 2013 Wu et al.; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 17 April 2013
                : 6 August 2013
                Categories
                Research Article

                Genetics
                north american ginseng,transcriptome,next generation sequencing,ginsenoside
                Genetics
                north american ginseng, transcriptome, next generation sequencing, ginsenoside

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