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Transcriptomic dataset reveals the molecular basis of genotypic variation in hexaploid wheat (T. aestivum L.) in response to Fe/Zn deficiency
The datasets depicted in the paper are related to the original article entitled “Identifying transcripts associated with efficient transport and accumulation of Fe and Zn in hexaploid wheat (T. aestivum L.)” [1]. Four wheat genotypes i.e. Sonora 64, CRP 1660, Vinata, and DBW 17 were selected for RNA...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Elsevier
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7358265/ https://www.ncbi.nlm.nih.gov/pubmed/32685638 http://dx.doi.org/10.1016/j.dib.2020.105995 |
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author | Gupta, Om Prakash Pandey, Vanita Saini, Ritu Narwal, Sneh Malik, Vipin Kumar Khandale, Tushar Ram, Sewa Singh, Gyanendra Pratap |
author_facet | Gupta, Om Prakash Pandey, Vanita Saini, Ritu Narwal, Sneh Malik, Vipin Kumar Khandale, Tushar Ram, Sewa Singh, Gyanendra Pratap |
author_sort | Gupta, Om Prakash |
collection | PubMed |
description | The datasets depicted in the paper are related to the original article entitled “Identifying transcripts associated with efficient transport and accumulation of Fe and Zn in hexaploid wheat (T. aestivum L.)” [1]. Four wheat genotypes i.e. Sonora 64, CRP 1660, Vinata, and DBW 17 were selected for RNA sequencing using Illumina HiSeq4000 platform. These genotypes were grown in Fe/Zn sufficient and deficient conditions in sand pot culture with intermittent administration of Hoagland solution. Pooled assembly was carried out for all of the four varieties subsequent to discarding low-quality reads, adaptor sequences and contamination resulting in approximately 315,904 clean transcripts of around 937 bp lengths and N(50) of 1,294 bp. For the functional annotation of the identified transcripts databases like Pfam, KEGG pathway, Uniprot, PlnTFDB and wheat proteins were utilized. Differential expression calculation of transcripts was carried out by DESeq, an R package and real-time PCR study of 12 Fe/Zn metabolic pathway related transcripts was utilized for further revalidation of data. Elemental analysis of grain Fe and Zn was performed using Flame Atomic Absorption Spectrometry (FAAS). The RNA-seq data of all the four wheat genotypes was uploaded on Sequence Read Archive (SRA: SUB6961770 and BioProject: PRJNA605909), enabling easy access to the researchers worldwide. |
format | Online Article Text |
id | pubmed-7358265 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-73582652020-07-17 Transcriptomic dataset reveals the molecular basis of genotypic variation in hexaploid wheat (T. aestivum L.) in response to Fe/Zn deficiency Gupta, Om Prakash Pandey, Vanita Saini, Ritu Narwal, Sneh Malik, Vipin Kumar Khandale, Tushar Ram, Sewa Singh, Gyanendra Pratap Data Brief Agricultural and Biological Science The datasets depicted in the paper are related to the original article entitled “Identifying transcripts associated with efficient transport and accumulation of Fe and Zn in hexaploid wheat (T. aestivum L.)” [1]. Four wheat genotypes i.e. Sonora 64, CRP 1660, Vinata, and DBW 17 were selected for RNA sequencing using Illumina HiSeq4000 platform. These genotypes were grown in Fe/Zn sufficient and deficient conditions in sand pot culture with intermittent administration of Hoagland solution. Pooled assembly was carried out for all of the four varieties subsequent to discarding low-quality reads, adaptor sequences and contamination resulting in approximately 315,904 clean transcripts of around 937 bp lengths and N(50) of 1,294 bp. For the functional annotation of the identified transcripts databases like Pfam, KEGG pathway, Uniprot, PlnTFDB and wheat proteins were utilized. Differential expression calculation of transcripts was carried out by DESeq, an R package and real-time PCR study of 12 Fe/Zn metabolic pathway related transcripts was utilized for further revalidation of data. Elemental analysis of grain Fe and Zn was performed using Flame Atomic Absorption Spectrometry (FAAS). The RNA-seq data of all the four wheat genotypes was uploaded on Sequence Read Archive (SRA: SUB6961770 and BioProject: PRJNA605909), enabling easy access to the researchers worldwide. Elsevier 2020-07-05 /pmc/articles/PMC7358265/ /pubmed/32685638 http://dx.doi.org/10.1016/j.dib.2020.105995 Text en © 2020 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 | Agricultural and Biological Science Gupta, Om Prakash Pandey, Vanita Saini, Ritu Narwal, Sneh Malik, Vipin Kumar Khandale, Tushar Ram, Sewa Singh, Gyanendra Pratap Transcriptomic dataset reveals the molecular basis of genotypic variation in hexaploid wheat (T. aestivum L.) in response to Fe/Zn deficiency |
title | Transcriptomic dataset reveals the molecular basis of genotypic variation in hexaploid wheat (T. aestivum L.) in response to Fe/Zn deficiency |
title_full | Transcriptomic dataset reveals the molecular basis of genotypic variation in hexaploid wheat (T. aestivum L.) in response to Fe/Zn deficiency |
title_fullStr | Transcriptomic dataset reveals the molecular basis of genotypic variation in hexaploid wheat (T. aestivum L.) in response to Fe/Zn deficiency |
title_full_unstemmed | Transcriptomic dataset reveals the molecular basis of genotypic variation in hexaploid wheat (T. aestivum L.) in response to Fe/Zn deficiency |
title_short | Transcriptomic dataset reveals the molecular basis of genotypic variation in hexaploid wheat (T. aestivum L.) in response to Fe/Zn deficiency |
title_sort | transcriptomic dataset reveals the molecular basis of genotypic variation in hexaploid wheat (t. aestivum l.) in response to fe/zn deficiency |
topic | Agricultural and Biological Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7358265/ https://www.ncbi.nlm.nih.gov/pubmed/32685638 http://dx.doi.org/10.1016/j.dib.2020.105995 |
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