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Transcriptome profiling of Curcuma longa L. cv. Suvarna

Turmeric is an economically valued crop, because of its utility in the food, pharmaceutical industries and Ayurvedic medicine, attracts the attention in many areas of research work. In the present study, we executed resequencing through transcriptome assembly of the turmeric cultivar Suvarna (CL_Suv...

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Autores principales: Sahoo, Ambika, Kar, Basudeba, Sahoo, Suprava, Ray, Asit, Nayak, Sanghamitra
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5024144/
https://www.ncbi.nlm.nih.gov/pubmed/27668184
http://dx.doi.org/10.1016/j.gdata.2016.09.001
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author Sahoo, Ambika
Kar, Basudeba
Sahoo, Suprava
Ray, Asit
Nayak, Sanghamitra
author_facet Sahoo, Ambika
Kar, Basudeba
Sahoo, Suprava
Ray, Asit
Nayak, Sanghamitra
author_sort Sahoo, Ambika
collection PubMed
description Turmeric is an economically valued crop, because of its utility in the food, pharmaceutical industries and Ayurvedic medicine, attracts the attention in many areas of research work. In the present study, we executed resequencing through transcriptome assembly of the turmeric cultivar Suvarna (CL_Suv_10). Resequencing of Suvarna variety has generated 5 Gbases raw data with 75 bp paired-end sequence. The raw data has been submitted to SRA database of NCBI with accession number SRR4042181. Reads were assembled using Cufflinks-2.2.1 tool which ended up with 42994 numbers of transcripts. The length of transcripts ranged from 83 to15565, with a N50 value 1216 and median transcript length 773. The transcripts were annotated through number of databases. For the first time transcriptome profiling of cultivar Suvarna has been done, which could help towards identification of single nucleotide polymorphisms (SNPs) between Suvarna and other turmeric cultivars for its authentic identification.
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spelling pubmed-50241442016-09-23 Transcriptome profiling of Curcuma longa L. cv. Suvarna Sahoo, Ambika Kar, Basudeba Sahoo, Suprava Ray, Asit Nayak, Sanghamitra Genom Data Data in Brief Turmeric is an economically valued crop, because of its utility in the food, pharmaceutical industries and Ayurvedic medicine, attracts the attention in many areas of research work. In the present study, we executed resequencing through transcriptome assembly of the turmeric cultivar Suvarna (CL_Suv_10). Resequencing of Suvarna variety has generated 5 Gbases raw data with 75 bp paired-end sequence. The raw data has been submitted to SRA database of NCBI with accession number SRR4042181. Reads were assembled using Cufflinks-2.2.1 tool which ended up with 42994 numbers of transcripts. The length of transcripts ranged from 83 to15565, with a N50 value 1216 and median transcript length 773. The transcripts were annotated through number of databases. For the first time transcriptome profiling of cultivar Suvarna has been done, which could help towards identification of single nucleotide polymorphisms (SNPs) between Suvarna and other turmeric cultivars for its authentic identification. Elsevier 2016-09-09 /pmc/articles/PMC5024144/ /pubmed/27668184 http://dx.doi.org/10.1016/j.gdata.2016.09.001 Text en © 2016 Published by Elsevier Inc. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Data in Brief
Sahoo, Ambika
Kar, Basudeba
Sahoo, Suprava
Ray, Asit
Nayak, Sanghamitra
Transcriptome profiling of Curcuma longa L. cv. Suvarna
title Transcriptome profiling of Curcuma longa L. cv. Suvarna
title_full Transcriptome profiling of Curcuma longa L. cv. Suvarna
title_fullStr Transcriptome profiling of Curcuma longa L. cv. Suvarna
title_full_unstemmed Transcriptome profiling of Curcuma longa L. cv. Suvarna
title_short Transcriptome profiling of Curcuma longa L. cv. Suvarna
title_sort transcriptome profiling of curcuma longa l. cv. suvarna
topic Data in Brief
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5024144/
https://www.ncbi.nlm.nih.gov/pubmed/27668184
http://dx.doi.org/10.1016/j.gdata.2016.09.001
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