Dataset Information

Transcriptomic resources for an endemic Neotropical plant lineage (Gesneriaceae).

ABSTRACT: PREMISE OF THE STUDY:Despite the extensive phenotypic variation that characterizes the Gesneriaceae family, there is a lack of genomic resources to investigate the molecular basis of their diversity. We developed and compared the transcriptomes for two species of the Neotropical lineage of the Gesneriaceae. METHODS AND RESULTS:Illumina sequencing and de novo assembly of floral and leaf samples were used to generate multigene sequence data for Sinningia eumorpha and S. magnifica, two species endemic to the Brazilian Atlantic Forest. A total of 300 million reads were used to assemble the transcriptomes, with an average of 92,038 transcripts and 43,506 genes per species. The transcriptomes showed good quality metrics, with the presence of all eukaryotic core genes, and an equal representation of clusters of orthologous groups (COG) classifications between species. The orthologous search produced 8602 groups, with 15-20% of them annotated using BLAST tools. DISCUSSION:This study provides the first step toward a comprehensive multispecies transcriptome characterization of the Gesneriaceae family. These resources are the basis for comparative analyses in this species-rich Neotropical plant group; they will also allow the investigation of the evolutionary importance of multiple metabolic pathways and phenotypic diversity, as well as developmental programs in these nonmodel species.

SUBMITTER: Serrano-Serrano ML

PROVIDER: S-EPMC5400431 | biostudies-literature | 2017 Apr

REPOSITORIES: biostudies-literature

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Transcriptomic resources for an endemic Neotropical plant lineage (Gesneriaceae).

Serrano-Serrano Martha L ML Marcionetti Anna A Perret Mathieu M Salamin Nicolas N

Applications in plant sciences 20170412 4

<h4>Premise of the study</h4>Despite the extensive phenotypic variation that characterizes the Gesneriaceae family, there is a lack of genomic resources to investigate the molecular basis of their diversity. We developed and compared the transcriptomes for two species of the Neotropical lineage of the Gesneriaceae.<h4>Methods and results</h4>Illumina sequencing and de novo assembly of floral and leaf samples were used to generate multigene sequence data for <i>Sinningia eumorpha</i> and <i>S. ma ...[more]

PMID: 28439475

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Project description:The natural diversity of plant metabolism has long been a source for human medicines. One group of plant-derived compounds, the monoterpene indole alkaloids (MIAs), includes well-documented therapeutic agents used in the treatment of cancer (vinblastine, vincristine, camptothecin), hypertension (reserpine, ajmalicine), malaria (quinine), and as analgesics (7-hydroxymitragynine). Our understanding of the biochemical pathways that synthesize these commercially relevant compounds is incomplete due in part to a lack of molecular, genetic, and genomic resources for the identification of the genes involved in these specialized metabolic pathways. To address these limitations, we generated large-scale transcriptome sequence and expression profiles for three species of Asterids that produce medicinally important MIAs: Camptotheca acuminata, Catharanthus roseus, and Rauvolfia serpentina. Using next generation sequencing technology, we sampled the transcriptomes of these species across a diverse set of developmental tissues, and in the case of C. roseus, in cultured cells and roots following elicitor treatment. Through an iterative assembly process, we generated robust transcriptome assemblies for all three species with a substantial number of the assembled transcripts being full or near-full length. The majority of transcripts had a related sequence in either UniRef100, the Arabidopsis thaliana predicted proteome, or the Pfam protein domain database; however, we also identified transcripts that lacked similarity with entries in either database and thereby lack a known function. Representation of known genes within the MIA biosynthetic pathway was robust. As a diverse set of tissues and treatments were surveyed, expression abundances of transcripts in the three species could be estimated to reveal transcripts associated with development and response to elicitor treatment. Together, these transcriptomes and expression abundance matrices provide a rich resource for understanding plant specialized metabolism, and promotes realization of innovative production systems for plant-derived pharmaceuticals.

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Dataset Information

Transcriptomic resources for an endemic Neotropical plant lineage (Gesneriaceae).

Publications

Transcriptomic resources for an endemic Neotropical plant lineage (Gesneriaceae).

Similar Datasets

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