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Comprehensive proteomics data on whole rice grain of selected pigmented and non-pigmented rice varieties using SWATH-MS approach
The proteome data of whole rice grain is considerably limited particularly for rice with pigmentations such as black and red rice. Hence, we performed proteome analysis of two black rice varieties (BALI and Pulut Hitam 9), two red rice varieties (MRM16 and MRQ100) and two white rice varieties (MR297...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7334386/ https://www.ncbi.nlm.nih.gov/pubmed/32642524 http://dx.doi.org/10.1016/j.dib.2020.105927 |
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author | Sew, Yun Shin Aizat, Wan Mohd Razak, Mohd Shahril Firdaus Ab Zainal-Abidin, Rabiatul-Adawiah Simoh, Sanimah Abu-Bakar, Norliza |
author_facet | Sew, Yun Shin Aizat, Wan Mohd Razak, Mohd Shahril Firdaus Ab Zainal-Abidin, Rabiatul-Adawiah Simoh, Sanimah Abu-Bakar, Norliza |
author_sort | Sew, Yun Shin |
collection | PubMed |
description | The proteome data of whole rice grain is considerably limited particularly for rice with pigmentations such as black and red rice. Hence, we performed proteome analysis of two black rice varieties (BALI and Pulut Hitam 9), two red rice varieties (MRM16 and MRQ100) and two white rice varieties (MR297 and MRQ76) using label-free liquid chromatography Triple TOF 6600 tandem mass spectrometry (LC-MS/MS). Our aim was to profile and identify proteins related to nutritional (i.e. antioxidant, folate and low glycaemic index) and quality (i.e. aromatic) traits based on peptide-centric scoring from the Sequential Window Acquisition of All Theoretical Mass Spectra (SWATH-MS) approach. Both information dependent acquisition (IDA) and SWATH-MS run were performed in this analysis. Raw data was then processed using ProteinPilot software to identify and compare proteins from the six different varieties. In future, this proteomics data will be integrated with previously obtained genomics [1] and transcriptomics [2] data focusing on the above nutritional and quality traits, with an ultimate aim to develop a panel of functional biomarkers related to those traits for future rice breeding programme. The raw MS data of the pigmented and non-pigmented rice varieties have been deposited to ProteomeXchange database with accession number PXD018338. |
format | Online Article Text |
id | pubmed-7334386 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-73343862020-07-07 Comprehensive proteomics data on whole rice grain of selected pigmented and non-pigmented rice varieties using SWATH-MS approach Sew, Yun Shin Aizat, Wan Mohd Razak, Mohd Shahril Firdaus Ab Zainal-Abidin, Rabiatul-Adawiah Simoh, Sanimah Abu-Bakar, Norliza Data Brief Agricultural and Biological Science The proteome data of whole rice grain is considerably limited particularly for rice with pigmentations such as black and red rice. Hence, we performed proteome analysis of two black rice varieties (BALI and Pulut Hitam 9), two red rice varieties (MRM16 and MRQ100) and two white rice varieties (MR297 and MRQ76) using label-free liquid chromatography Triple TOF 6600 tandem mass spectrometry (LC-MS/MS). Our aim was to profile and identify proteins related to nutritional (i.e. antioxidant, folate and low glycaemic index) and quality (i.e. aromatic) traits based on peptide-centric scoring from the Sequential Window Acquisition of All Theoretical Mass Spectra (SWATH-MS) approach. Both information dependent acquisition (IDA) and SWATH-MS run were performed in this analysis. Raw data was then processed using ProteinPilot software to identify and compare proteins from the six different varieties. In future, this proteomics data will be integrated with previously obtained genomics [1] and transcriptomics [2] data focusing on the above nutritional and quality traits, with an ultimate aim to develop a panel of functional biomarkers related to those traits for future rice breeding programme. The raw MS data of the pigmented and non-pigmented rice varieties have been deposited to ProteomeXchange database with accession number PXD018338. Elsevier 2020-06-26 /pmc/articles/PMC7334386/ /pubmed/32642524 http://dx.doi.org/10.1016/j.dib.2020.105927 Text en © 2020 The Author(s) http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Agricultural and Biological Science Sew, Yun Shin Aizat, Wan Mohd Razak, Mohd Shahril Firdaus Ab Zainal-Abidin, Rabiatul-Adawiah Simoh, Sanimah Abu-Bakar, Norliza Comprehensive proteomics data on whole rice grain of selected pigmented and non-pigmented rice varieties using SWATH-MS approach |
title | Comprehensive proteomics data on whole rice grain of selected pigmented and non-pigmented rice varieties using SWATH-MS approach |
title_full | Comprehensive proteomics data on whole rice grain of selected pigmented and non-pigmented rice varieties using SWATH-MS approach |
title_fullStr | Comprehensive proteomics data on whole rice grain of selected pigmented and non-pigmented rice varieties using SWATH-MS approach |
title_full_unstemmed | Comprehensive proteomics data on whole rice grain of selected pigmented and non-pigmented rice varieties using SWATH-MS approach |
title_short | Comprehensive proteomics data on whole rice grain of selected pigmented and non-pigmented rice varieties using SWATH-MS approach |
title_sort | comprehensive proteomics data on whole rice grain of selected pigmented and non-pigmented rice varieties using swath-ms approach |
topic | Agricultural and Biological Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7334386/ https://www.ncbi.nlm.nih.gov/pubmed/32642524 http://dx.doi.org/10.1016/j.dib.2020.105927 |
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