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...
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Autor*in:	Om Prakash Gupta [verfasserIn] Vanita Pandey [verfasserIn] Ritu Saini [verfasserIn] Sneh Narwal [verfasserIn] Vipin Kumar Malik [verfasserIn] Tushar Khandale [verfasserIn] Sewa Ram [verfasserIn] Gyanendra Pratap Singh [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2020

Schlagwörter:	Fe/Zn deficiency Hexaploid wheat Phytosiderophore Fe/Zn transporters Biofortification, Sand pot culture

Übergeordnetes Werk:	In: Data in Brief - Elsevier, 2015, 31(2020), Seite 105995-
Übergeordnetes Werk:	volume:31 ; year:2020 ; pages:105995-

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1016/j.dib.2020.105995

Katalog-ID:	DOAJ007508859

Internformat


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520			\|a 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 N50 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.
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allfields	10.1016/j.dib.2020.105995 doi (DE-627)DOAJ007508859 (DE-599)DOAJ17f677e99f144532b6f340c54616e288 DE-627 ger DE-627 rakwb eng R858-859.7 Q1-390 Om Prakash Gupta verfasserin aut Transcriptomic dataset reveals the molecular basis of genotypic variation in hexaploid wheat (T. aestivum L.) in response to Fe/Zn deficiency 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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 N50 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. Fe/Zn deficiency Hexaploid wheat Phytosiderophore Fe/Zn transporters Biofortification, Sand pot culture Computer applications to medicine. Medical informatics Science (General) Vanita Pandey verfasserin aut Ritu Saini verfasserin aut Sneh Narwal verfasserin aut Vipin Kumar Malik verfasserin aut Tushar Khandale verfasserin aut Sewa Ram verfasserin aut Gyanendra Pratap Singh verfasserin aut In Data in Brief Elsevier, 2015 31(2020), Seite 105995- (DE-627)797838937 (DE-600)2786545-9 23523409 nnns volume:31 year:2020 pages:105995- https://doi.org/10.1016/j.dib.2020.105995 kostenfrei https://doaj.org/article/17f677e99f144532b6f340c54616e288 kostenfrei http://www.sciencedirect.com/science/article/pii/S2352340920308891 kostenfrei https://doaj.org/toc/2352-3409 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 31 2020 105995-
spelling	10.1016/j.dib.2020.105995 doi (DE-627)DOAJ007508859 (DE-599)DOAJ17f677e99f144532b6f340c54616e288 DE-627 ger DE-627 rakwb eng R858-859.7 Q1-390 Om Prakash Gupta verfasserin aut Transcriptomic dataset reveals the molecular basis of genotypic variation in hexaploid wheat (T. aestivum L.) in response to Fe/Zn deficiency 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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 N50 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. Fe/Zn deficiency Hexaploid wheat Phytosiderophore Fe/Zn transporters Biofortification, Sand pot culture Computer applications to medicine. Medical informatics Science (General) Vanita Pandey verfasserin aut Ritu Saini verfasserin aut Sneh Narwal verfasserin aut Vipin Kumar Malik verfasserin aut Tushar Khandale verfasserin aut Sewa Ram verfasserin aut Gyanendra Pratap Singh verfasserin aut In Data in Brief Elsevier, 2015 31(2020), Seite 105995- (DE-627)797838937 (DE-600)2786545-9 23523409 nnns volume:31 year:2020 pages:105995- https://doi.org/10.1016/j.dib.2020.105995 kostenfrei https://doaj.org/article/17f677e99f144532b6f340c54616e288 kostenfrei http://www.sciencedirect.com/science/article/pii/S2352340920308891 kostenfrei https://doaj.org/toc/2352-3409 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 31 2020 105995-
allfields_unstemmed	10.1016/j.dib.2020.105995 doi (DE-627)DOAJ007508859 (DE-599)DOAJ17f677e99f144532b6f340c54616e288 DE-627 ger DE-627 rakwb eng R858-859.7 Q1-390 Om Prakash Gupta verfasserin aut Transcriptomic dataset reveals the molecular basis of genotypic variation in hexaploid wheat (T. aestivum L.) in response to Fe/Zn deficiency 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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 N50 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. Fe/Zn deficiency Hexaploid wheat Phytosiderophore Fe/Zn transporters Biofortification, Sand pot culture Computer applications to medicine. Medical informatics Science (General) Vanita Pandey verfasserin aut Ritu Saini verfasserin aut Sneh Narwal verfasserin aut Vipin Kumar Malik verfasserin aut Tushar Khandale verfasserin aut Sewa Ram verfasserin aut Gyanendra Pratap Singh verfasserin aut In Data in Brief Elsevier, 2015 31(2020), Seite 105995- (DE-627)797838937 (DE-600)2786545-9 23523409 nnns volume:31 year:2020 pages:105995- https://doi.org/10.1016/j.dib.2020.105995 kostenfrei https://doaj.org/article/17f677e99f144532b6f340c54616e288 kostenfrei http://www.sciencedirect.com/science/article/pii/S2352340920308891 kostenfrei https://doaj.org/toc/2352-3409 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 31 2020 105995-
allfieldsGer	10.1016/j.dib.2020.105995 doi (DE-627)DOAJ007508859 (DE-599)DOAJ17f677e99f144532b6f340c54616e288 DE-627 ger DE-627 rakwb eng R858-859.7 Q1-390 Om Prakash Gupta verfasserin aut Transcriptomic dataset reveals the molecular basis of genotypic variation in hexaploid wheat (T. aestivum L.) in response to Fe/Zn deficiency 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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 N50 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. Fe/Zn deficiency Hexaploid wheat Phytosiderophore Fe/Zn transporters Biofortification, Sand pot culture Computer applications to medicine. Medical informatics Science (General) Vanita Pandey verfasserin aut Ritu Saini verfasserin aut Sneh Narwal verfasserin aut Vipin Kumar Malik verfasserin aut Tushar Khandale verfasserin aut Sewa Ram verfasserin aut Gyanendra Pratap Singh verfasserin aut In Data in Brief Elsevier, 2015 31(2020), Seite 105995- (DE-627)797838937 (DE-600)2786545-9 23523409 nnns volume:31 year:2020 pages:105995- https://doi.org/10.1016/j.dib.2020.105995 kostenfrei https://doaj.org/article/17f677e99f144532b6f340c54616e288 kostenfrei http://www.sciencedirect.com/science/article/pii/S2352340920308891 kostenfrei https://doaj.org/toc/2352-3409 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 31 2020 105995-
allfieldsSound	10.1016/j.dib.2020.105995 doi (DE-627)DOAJ007508859 (DE-599)DOAJ17f677e99f144532b6f340c54616e288 DE-627 ger DE-627 rakwb eng R858-859.7 Q1-390 Om Prakash Gupta verfasserin aut Transcriptomic dataset reveals the molecular basis of genotypic variation in hexaploid wheat (T. aestivum L.) in response to Fe/Zn deficiency 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier 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 N50 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. Fe/Zn deficiency Hexaploid wheat Phytosiderophore Fe/Zn transporters Biofortification, Sand pot culture Computer applications to medicine. Medical informatics Science (General) Vanita Pandey verfasserin aut Ritu Saini verfasserin aut Sneh Narwal verfasserin aut Vipin Kumar Malik verfasserin aut Tushar Khandale verfasserin aut Sewa Ram verfasserin aut Gyanendra Pratap Singh verfasserin aut In Data in Brief Elsevier, 2015 31(2020), Seite 105995- (DE-627)797838937 (DE-600)2786545-9 23523409 nnns volume:31 year:2020 pages:105995- https://doi.org/10.1016/j.dib.2020.105995 kostenfrei https://doaj.org/article/17f677e99f144532b6f340c54616e288 kostenfrei http://www.sciencedirect.com/science/article/pii/S2352340920308891 kostenfrei https://doaj.org/toc/2352-3409 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2088 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 31 2020 105995-
language	English
source	In Data in Brief 31(2020), Seite 105995- volume:31 year:2020 pages:105995-
sourceStr	In Data in Brief 31(2020), Seite 105995- volume:31 year:2020 pages:105995-
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Fe/Zn deficiency Hexaploid wheat Phytosiderophore Fe/Zn transporters Biofortification, Sand pot culture Computer applications to medicine. Medical informatics Science (General)
isfreeaccess_bool	true
container_title	Data in Brief
authorswithroles_txt_mv	Om Prakash Gupta @@aut@@ Vanita Pandey @@aut@@ Ritu Saini @@aut@@ Sneh Narwal @@aut@@ Vipin Kumar Malik @@aut@@ Tushar Khandale @@aut@@ Sewa Ram @@aut@@ Gyanendra Pratap Singh @@aut@@
publishDateDaySort_date	2020-01-01T00:00:00Z
hierarchy_top_id	797838937
id	DOAJ007508859
language_de	englisch
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callnumber-first	R - Medicine
author	Om Prakash Gupta
spellingShingle	Om Prakash Gupta misc R858-859.7 misc Q1-390 misc Fe/Zn deficiency misc Hexaploid wheat misc Phytosiderophore misc Fe/Zn transporters misc Biofortification, Sand pot culture misc Computer applications to medicine. Medical informatics misc Science (General) Transcriptomic dataset reveals the molecular basis of genotypic variation in hexaploid wheat (T. aestivum L.) in response to Fe/Zn deficiency
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topic_title	R858-859.7 Q1-390 Transcriptomic dataset reveals the molecular basis of genotypic variation in hexaploid wheat (T. aestivum L.) in response to Fe/Zn deficiency Fe/Zn deficiency Hexaploid wheat Phytosiderophore Fe/Zn transporters Biofortification, Sand pot culture
topic	misc R858-859.7 misc Q1-390 misc Fe/Zn deficiency misc Hexaploid wheat misc Phytosiderophore misc Fe/Zn transporters misc Biofortification, Sand pot culture misc Computer applications to medicine. Medical informatics misc Science (General)
topic_unstemmed	misc R858-859.7 misc Q1-390 misc Fe/Zn deficiency misc Hexaploid wheat misc Phytosiderophore misc Fe/Zn transporters misc Biofortification, Sand pot culture misc Computer applications to medicine. Medical informatics misc Science (General)
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title	Transcriptomic dataset reveals the molecular basis of genotypic variation in hexaploid wheat (T. aestivum L.) in response to Fe/Zn deficiency
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title_full	Transcriptomic dataset reveals the molecular basis of genotypic variation in hexaploid wheat (T. aestivum L.) in response to Fe/Zn deficiency
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author_browse	Om Prakash Gupta Vanita Pandey Ritu Saini Sneh Narwal Vipin Kumar Malik Tushar Khandale Sewa Ram Gyanendra Pratap Singh
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title_sort	transcriptomic dataset reveals the molecular basis of genotypic variation in hexaploid wheat (t. aestivum l.) in response to fe/zn deficiency
callnumber	R858-859.7
title_auth	Transcriptomic dataset reveals the molecular basis of genotypic variation in hexaploid wheat (T. aestivum L.) in response to Fe/Zn deficiency
abstract	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 N50 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.
abstractGer	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 N50 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.
abstract_unstemmed	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 N50 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.
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title_short	Transcriptomic dataset reveals the molecular basis of genotypic variation in hexaploid wheat (T. aestivum L.) in response to Fe/Zn deficiency
url	https://doi.org/10.1016/j.dib.2020.105995 https://doaj.org/article/17f677e99f144532b6f340c54616e288 http://www.sciencedirect.com/science/article/pii/S2352340920308891 https://doaj.org/toc/2352-3409
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up_date	2024-07-04T01:50:24.434Z
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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 N50 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). 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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

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