Transcriptomic resources for the medicinal legume Mucuna pruriens: de novo transcriptome assembly, annotation, identification and validation of EST-SSR markers
Authors
N Sathyanarayana
Department of Botany, Sikkim University, 6th Mile, Tadong-737102, Gangtok, Sikkim India
Ranjith Pittala
Department of Botany, Sikkim University, 6th Mile, Tadong-737102, Gangtok, Sikkim India
Pankaj Tripathi
Department of Botany, Sikkim University, 6th Mile, Tadong-737102, Gangtok, Sikkim India
Ratan Chopra
United States Department of Agriculture, Agriculture Research Service, 3810 4th St., Lubbock, TX 79415 USA
Heikham Singh
Department of Plant Science, McGill University, Raymond Building, 21111 Lakeshore Road, Ste. Anne de Bellevue, Quebec, H9X 3V9 Canada
Vikas Belamkar
Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE 68583 USA
Pardeep Bhardwaj
Institute of Bioresources and Sustainable Development, ikkim Centre, Tadong-737102, Gangtok, Sikkim India
Jeff Doyle
Section of Plant Breeding and Genetics, School of Integrative Plant Science, Cornell University, 412 Mann Library, Ithaca, NY 14853 USA
Ashley Egan
Department of Botany, Smithsonian Institution, National Museum of Natural History, US National Herbarium, 10th and Constitution Ave NW, Washington, DC 20013 USA
The medicinal legume Mucuna pruriens (L.) DC. has attracted attention worldwide as a source of the anti-Parkinson’s drug L-Dopa. It is also a popular green manure cover crop that offers many agronomic benefits including high protein content, nitrogen fixation and soil nutrients. The plant currently lacks genomic resources and there is limited knowledge on gene expression, metabolic pathways, and genetics of secondary metabolite production. Here, we present transcriptomic resources for M. pruriens, including a de novo transcriptome assembly and annotation, as well as differential transcript expression analyses between root, leaf, and pod tissues. We also develop microsatellite markers and analyze genetic diversity and population structure within a set of Indian germplasm accessions.
Results
One-hundred ninety-one million two hundred thirty-three thousand two hundred forty-two bp cleaned reads were assembled into 67,561 transcripts with mean length of 626 bp and N50 of 987 bp. Assembled sequences were annotated using BLASTX against public databases with over 80% of transcripts annotated. We identified 7,493 simple sequence repeat (SSR) motifs, including 787 polymorphic repeats between the parents of a mapping population. 134 SSRs from expressed sequenced tags (ESTs) were screened against 23 M. pruriens accessions from India, with 52 EST-SSRs retained after quality control. Population structure analysis using a Bayesian framework implemented in fastSTRUCTURE showed nearly similar groupings as with distance-based (neighbor-joining) and principal component analyses, with most of the accessions clustering per geographical origins. Pair-wise comparison of transcript expression in leaves, roots and pods identified 4,387 differentially expressed transcripts with the highest number occurring between roots and leaves. Differentially expressed transcripts were enriched with transcription factors and transcripts annotated as belonging to secondary metabolite pathways.
Conclusions
The M. pruriens transcriptomic resources generated in this study provide foundational resources for gene discovery and development of molecular markers. Polymorphic SSRs identified can be used for genetic diversity, marker-trait analyses, and development of functional markers for crop improvement. The results of differential expression studies can be used to investigate genes involved in L-Dopa synthesis and other key metabolic pathways in M. pruriens.
Electronic supplementary material
The online version of this article (doi:10.1186/s12864-017-3780-9) contains supplementary material, which is available to authorized users.
Keywords: Velvet bean, Mucuna pruriens, Transcriptomics, Differential gene expression, EST-SSRs, Population structure, Leguminosae, Fabaceae
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