Investigation into the underlying regulatory mechanisms shaping inflorescence architecture in Chenopodium quinoa

Background Inflorescence architecture is denoted by the spatial arrangement of various lateral branches and florets formed on them, which is shaped by a complex of regulators. Unveiling of the regulatory mechanisms underlying inflorescence architecture is pivotal for improving crop yield potential. Quinoa (Chenopodium quinoa Willd), a pseudo cereal originated from Andean region of South America, has been widely recognized as a functional super food due to its excellent nutritional elements. Increasing worldwide consumption of this crop urgently calls for its yield improvement. However, dissection of the regulatory networks underlying quinoa inflorescence patterning is lacking. Results In this study, we performed RNA-seq analysis on quinoa inflorescence samples collected from six developmental stages, yielding a total of 138.8 GB data. We screened 21,610 differentially expressed genes (DEGs) among all the stages through comparative analysis. Weighted Gene Co-Expression Network Analysis (WGCNA) was performed to categorize the DEGs into ten different modules. Subsequently, we placed emphasis on investigating the modules associated with none branched and branched inflorescence samples. We manually refined the coexpression networks with stringent edge weight cutoffs, and generated core networks using transcription factors and key inflorescence architecture related genes as seed nodes. The core networks were visualized and analyzed by Cytoscape to obtain hub genes in each network. Our finding indicates that the specific occurrence of B3, TALE, WOX, LSH, LFY, GRAS, bHLH, EIL, DOF, G2-like and YABBY family members in early reproductive stage modules, and of TFL, ERF, bZIP, HD-ZIP, C2H2, LBD, NAC, C3H, Nin-like and FAR1 family members in late reproductive stage modules, as well as the several different MADS subfamily members identified in both stages may account for shaping quinoa inflorescence architecture. Conclusion In this study we carried out comparative transcriptome analysis of six different stages quinoa inflorescences, and using WGCNA we obtained the most highly potential central hubs for shaping inflorescence. The data obtained from this study will enhance our understanding of the gene network regulating quinoa inflorescence architecture, as well will supply with valuable genetic resources for high-yield elite breeding in the future. Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Wu, Qi [verfasserIn] Bai, Xue Zhao, Wei Shi, Xiaodong Xiang, Dabing Wan, Yan Wu, Xiaoyong Sun, Yanxia Zhao, Jianglin Peng, Lianxin Zhao, Gang

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2019

Schlagwörter:	Inflorescence architecture RNA-seq Transcriptome analysis Weighted gene co-expression network analysis

Anmerkung:	© The Author(s). 2019

Übergeordnetes Werk:	Enthalten in: BMC genomics - London : BioMed Central, 2000, 20(2019), 1 vom: 17. Aug.
Übergeordnetes Werk:	volume:20 ; year:2019 ; number:1 ; day:17 ; month:08

Links:	Volltext

DOI / URN:	10.1186/s12864-019-6027-0

Katalog-ID:	SPR027156788

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520			\|a Background Inflorescence architecture is denoted by the spatial arrangement of various lateral branches and florets formed on them, which is shaped by a complex of regulators. Unveiling of the regulatory mechanisms underlying inflorescence architecture is pivotal for improving crop yield potential. Quinoa (Chenopodium quinoa Willd), a pseudo cereal originated from Andean region of South America, has been widely recognized as a functional super food due to its excellent nutritional elements. Increasing worldwide consumption of this crop urgently calls for its yield improvement. However, dissection of the regulatory networks underlying quinoa inflorescence patterning is lacking. Results In this study, we performed RNA-seq analysis on quinoa inflorescence samples collected from six developmental stages, yielding a total of 138.8 GB data. We screened 21,610 differentially expressed genes (DEGs) among all the stages through comparative analysis. Weighted Gene Co-Expression Network Analysis (WGCNA) was performed to categorize the DEGs into ten different modules. Subsequently, we placed emphasis on investigating the modules associated with none branched and branched inflorescence samples. We manually refined the coexpression networks with stringent edge weight cutoffs, and generated core networks using transcription factors and key inflorescence architecture related genes as seed nodes. The core networks were visualized and analyzed by Cytoscape to obtain hub genes in each network. Our finding indicates that the specific occurrence of B3, TALE, WOX, LSH, LFY, GRAS, bHLH, EIL, DOF, G2-like and YABBY family members in early reproductive stage modules, and of TFL, ERF, bZIP, HD-ZIP, C2H2, LBD, NAC, C3H, Nin-like and FAR1 family members in late reproductive stage modules, as well as the several different MADS subfamily members identified in both stages may account for shaping quinoa inflorescence architecture. Conclusion In this study we carried out comparative transcriptome analysis of six different stages quinoa inflorescences, and using WGCNA we obtained the most highly potential central hubs for shaping inflorescence. The data obtained from this study will enhance our understanding of the gene network regulating quinoa inflorescence architecture, as well will supply with valuable genetic resources for high-yield elite breeding in the future.
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700	1		\|a Zhao, Gang \|4 aut
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allfields	10.1186/s12864-019-6027-0 doi (DE-627)SPR027156788 (SPR)s12864-019-6027-0-e DE-627 ger DE-627 rakwb eng Wu, Qi verfasserin (orcid)0000-0001-5739-2381 aut Investigation into the underlying regulatory mechanisms shaping inflorescence architecture in Chenopodium quinoa 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2019 Background Inflorescence architecture is denoted by the spatial arrangement of various lateral branches and florets formed on them, which is shaped by a complex of regulators. Unveiling of the regulatory mechanisms underlying inflorescence architecture is pivotal for improving crop yield potential. Quinoa (Chenopodium quinoa Willd), a pseudo cereal originated from Andean region of South America, has been widely recognized as a functional super food due to its excellent nutritional elements. Increasing worldwide consumption of this crop urgently calls for its yield improvement. However, dissection of the regulatory networks underlying quinoa inflorescence patterning is lacking. Results In this study, we performed RNA-seq analysis on quinoa inflorescence samples collected from six developmental stages, yielding a total of 138.8 GB data. We screened 21,610 differentially expressed genes (DEGs) among all the stages through comparative analysis. Weighted Gene Co-Expression Network Analysis (WGCNA) was performed to categorize the DEGs into ten different modules. Subsequently, we placed emphasis on investigating the modules associated with none branched and branched inflorescence samples. We manually refined the coexpression networks with stringent edge weight cutoffs, and generated core networks using transcription factors and key inflorescence architecture related genes as seed nodes. The core networks were visualized and analyzed by Cytoscape to obtain hub genes in each network. Our finding indicates that the specific occurrence of B3, TALE, WOX, LSH, LFY, GRAS, bHLH, EIL, DOF, G2-like and YABBY family members in early reproductive stage modules, and of TFL, ERF, bZIP, HD-ZIP, C2H2, LBD, NAC, C3H, Nin-like and FAR1 family members in late reproductive stage modules, as well as the several different MADS subfamily members identified in both stages may account for shaping quinoa inflorescence architecture. Conclusion In this study we carried out comparative transcriptome analysis of six different stages quinoa inflorescences, and using WGCNA we obtained the most highly potential central hubs for shaping inflorescence. The data obtained from this study will enhance our understanding of the gene network regulating quinoa inflorescence architecture, as well will supply with valuable genetic resources for high-yield elite breeding in the future. Inflorescence architecture (dpeaa)DE-He213 RNA-seq (dpeaa)DE-He213 Transcriptome analysis (dpeaa)DE-He213 Weighted gene co-expression network analysis (dpeaa)DE-He213 Bai, Xue aut Zhao, Wei aut Shi, Xiaodong aut Xiang, Dabing aut Wan, Yan aut Wu, Xiaoyong aut Sun, Yanxia aut Zhao, Jianglin aut Peng, Lianxin aut Zhao, Gang aut Enthalten in BMC genomics London : BioMed Central, 2000 20(2019), 1 vom: 17. Aug. (DE-627)326644954 (DE-600)2041499-7 1471-2164 nnns volume:20 year:2019 number:1 day:17 month:08 https://dx.doi.org/10.1186/s12864-019-6027-0 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 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_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 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_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4338 GBV_ILN_4367 GBV_ILN_4700 AR 20 2019 1 17 08
spelling	10.1186/s12864-019-6027-0 doi (DE-627)SPR027156788 (SPR)s12864-019-6027-0-e DE-627 ger DE-627 rakwb eng Wu, Qi verfasserin (orcid)0000-0001-5739-2381 aut Investigation into the underlying regulatory mechanisms shaping inflorescence architecture in Chenopodium quinoa 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2019 Background Inflorescence architecture is denoted by the spatial arrangement of various lateral branches and florets formed on them, which is shaped by a complex of regulators. Unveiling of the regulatory mechanisms underlying inflorescence architecture is pivotal for improving crop yield potential. Quinoa (Chenopodium quinoa Willd), a pseudo cereal originated from Andean region of South America, has been widely recognized as a functional super food due to its excellent nutritional elements. Increasing worldwide consumption of this crop urgently calls for its yield improvement. However, dissection of the regulatory networks underlying quinoa inflorescence patterning is lacking. Results In this study, we performed RNA-seq analysis on quinoa inflorescence samples collected from six developmental stages, yielding a total of 138.8 GB data. We screened 21,610 differentially expressed genes (DEGs) among all the stages through comparative analysis. Weighted Gene Co-Expression Network Analysis (WGCNA) was performed to categorize the DEGs into ten different modules. Subsequently, we placed emphasis on investigating the modules associated with none branched and branched inflorescence samples. We manually refined the coexpression networks with stringent edge weight cutoffs, and generated core networks using transcription factors and key inflorescence architecture related genes as seed nodes. The core networks were visualized and analyzed by Cytoscape to obtain hub genes in each network. Our finding indicates that the specific occurrence of B3, TALE, WOX, LSH, LFY, GRAS, bHLH, EIL, DOF, G2-like and YABBY family members in early reproductive stage modules, and of TFL, ERF, bZIP, HD-ZIP, C2H2, LBD, NAC, C3H, Nin-like and FAR1 family members in late reproductive stage modules, as well as the several different MADS subfamily members identified in both stages may account for shaping quinoa inflorescence architecture. Conclusion In this study we carried out comparative transcriptome analysis of six different stages quinoa inflorescences, and using WGCNA we obtained the most highly potential central hubs for shaping inflorescence. The data obtained from this study will enhance our understanding of the gene network regulating quinoa inflorescence architecture, as well will supply with valuable genetic resources for high-yield elite breeding in the future. Inflorescence architecture (dpeaa)DE-He213 RNA-seq (dpeaa)DE-He213 Transcriptome analysis (dpeaa)DE-He213 Weighted gene co-expression network analysis (dpeaa)DE-He213 Bai, Xue aut Zhao, Wei aut Shi, Xiaodong aut Xiang, Dabing aut Wan, Yan aut Wu, Xiaoyong aut Sun, Yanxia aut Zhao, Jianglin aut Peng, Lianxin aut Zhao, Gang aut Enthalten in BMC genomics London : BioMed Central, 2000 20(2019), 1 vom: 17. Aug. (DE-627)326644954 (DE-600)2041499-7 1471-2164 nnns volume:20 year:2019 number:1 day:17 month:08 https://dx.doi.org/10.1186/s12864-019-6027-0 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 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_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 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_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4338 GBV_ILN_4367 GBV_ILN_4700 AR 20 2019 1 17 08
allfields_unstemmed	10.1186/s12864-019-6027-0 doi (DE-627)SPR027156788 (SPR)s12864-019-6027-0-e DE-627 ger DE-627 rakwb eng Wu, Qi verfasserin (orcid)0000-0001-5739-2381 aut Investigation into the underlying regulatory mechanisms shaping inflorescence architecture in Chenopodium quinoa 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2019 Background Inflorescence architecture is denoted by the spatial arrangement of various lateral branches and florets formed on them, which is shaped by a complex of regulators. Unveiling of the regulatory mechanisms underlying inflorescence architecture is pivotal for improving crop yield potential. Quinoa (Chenopodium quinoa Willd), a pseudo cereal originated from Andean region of South America, has been widely recognized as a functional super food due to its excellent nutritional elements. Increasing worldwide consumption of this crop urgently calls for its yield improvement. However, dissection of the regulatory networks underlying quinoa inflorescence patterning is lacking. Results In this study, we performed RNA-seq analysis on quinoa inflorescence samples collected from six developmental stages, yielding a total of 138.8 GB data. We screened 21,610 differentially expressed genes (DEGs) among all the stages through comparative analysis. Weighted Gene Co-Expression Network Analysis (WGCNA) was performed to categorize the DEGs into ten different modules. Subsequently, we placed emphasis on investigating the modules associated with none branched and branched inflorescence samples. We manually refined the coexpression networks with stringent edge weight cutoffs, and generated core networks using transcription factors and key inflorescence architecture related genes as seed nodes. The core networks were visualized and analyzed by Cytoscape to obtain hub genes in each network. Our finding indicates that the specific occurrence of B3, TALE, WOX, LSH, LFY, GRAS, bHLH, EIL, DOF, G2-like and YABBY family members in early reproductive stage modules, and of TFL, ERF, bZIP, HD-ZIP, C2H2, LBD, NAC, C3H, Nin-like and FAR1 family members in late reproductive stage modules, as well as the several different MADS subfamily members identified in both stages may account for shaping quinoa inflorescence architecture. Conclusion In this study we carried out comparative transcriptome analysis of six different stages quinoa inflorescences, and using WGCNA we obtained the most highly potential central hubs for shaping inflorescence. The data obtained from this study will enhance our understanding of the gene network regulating quinoa inflorescence architecture, as well will supply with valuable genetic resources for high-yield elite breeding in the future. Inflorescence architecture (dpeaa)DE-He213 RNA-seq (dpeaa)DE-He213 Transcriptome analysis (dpeaa)DE-He213 Weighted gene co-expression network analysis (dpeaa)DE-He213 Bai, Xue aut Zhao, Wei aut Shi, Xiaodong aut Xiang, Dabing aut Wan, Yan aut Wu, Xiaoyong aut Sun, Yanxia aut Zhao, Jianglin aut Peng, Lianxin aut Zhao, Gang aut Enthalten in BMC genomics London : BioMed Central, 2000 20(2019), 1 vom: 17. Aug. (DE-627)326644954 (DE-600)2041499-7 1471-2164 nnns volume:20 year:2019 number:1 day:17 month:08 https://dx.doi.org/10.1186/s12864-019-6027-0 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 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_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 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_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4338 GBV_ILN_4367 GBV_ILN_4700 AR 20 2019 1 17 08
allfieldsGer	10.1186/s12864-019-6027-0 doi (DE-627)SPR027156788 (SPR)s12864-019-6027-0-e DE-627 ger DE-627 rakwb eng Wu, Qi verfasserin (orcid)0000-0001-5739-2381 aut Investigation into the underlying regulatory mechanisms shaping inflorescence architecture in Chenopodium quinoa 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2019 Background Inflorescence architecture is denoted by the spatial arrangement of various lateral branches and florets formed on them, which is shaped by a complex of regulators. Unveiling of the regulatory mechanisms underlying inflorescence architecture is pivotal for improving crop yield potential. Quinoa (Chenopodium quinoa Willd), a pseudo cereal originated from Andean region of South America, has been widely recognized as a functional super food due to its excellent nutritional elements. Increasing worldwide consumption of this crop urgently calls for its yield improvement. However, dissection of the regulatory networks underlying quinoa inflorescence patterning is lacking. Results In this study, we performed RNA-seq analysis on quinoa inflorescence samples collected from six developmental stages, yielding a total of 138.8 GB data. We screened 21,610 differentially expressed genes (DEGs) among all the stages through comparative analysis. Weighted Gene Co-Expression Network Analysis (WGCNA) was performed to categorize the DEGs into ten different modules. Subsequently, we placed emphasis on investigating the modules associated with none branched and branched inflorescence samples. We manually refined the coexpression networks with stringent edge weight cutoffs, and generated core networks using transcription factors and key inflorescence architecture related genes as seed nodes. The core networks were visualized and analyzed by Cytoscape to obtain hub genes in each network. Our finding indicates that the specific occurrence of B3, TALE, WOX, LSH, LFY, GRAS, bHLH, EIL, DOF, G2-like and YABBY family members in early reproductive stage modules, and of TFL, ERF, bZIP, HD-ZIP, C2H2, LBD, NAC, C3H, Nin-like and FAR1 family members in late reproductive stage modules, as well as the several different MADS subfamily members identified in both stages may account for shaping quinoa inflorescence architecture. Conclusion In this study we carried out comparative transcriptome analysis of six different stages quinoa inflorescences, and using WGCNA we obtained the most highly potential central hubs for shaping inflorescence. The data obtained from this study will enhance our understanding of the gene network regulating quinoa inflorescence architecture, as well will supply with valuable genetic resources for high-yield elite breeding in the future. Inflorescence architecture (dpeaa)DE-He213 RNA-seq (dpeaa)DE-He213 Transcriptome analysis (dpeaa)DE-He213 Weighted gene co-expression network analysis (dpeaa)DE-He213 Bai, Xue aut Zhao, Wei aut Shi, Xiaodong aut Xiang, Dabing aut Wan, Yan aut Wu, Xiaoyong aut Sun, Yanxia aut Zhao, Jianglin aut Peng, Lianxin aut Zhao, Gang aut Enthalten in BMC genomics London : BioMed Central, 2000 20(2019), 1 vom: 17. Aug. (DE-627)326644954 (DE-600)2041499-7 1471-2164 nnns volume:20 year:2019 number:1 day:17 month:08 https://dx.doi.org/10.1186/s12864-019-6027-0 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 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_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 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_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4338 GBV_ILN_4367 GBV_ILN_4700 AR 20 2019 1 17 08
allfieldsSound	10.1186/s12864-019-6027-0 doi (DE-627)SPR027156788 (SPR)s12864-019-6027-0-e DE-627 ger DE-627 rakwb eng Wu, Qi verfasserin (orcid)0000-0001-5739-2381 aut Investigation into the underlying regulatory mechanisms shaping inflorescence architecture in Chenopodium quinoa 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2019 Background Inflorescence architecture is denoted by the spatial arrangement of various lateral branches and florets formed on them, which is shaped by a complex of regulators. Unveiling of the regulatory mechanisms underlying inflorescence architecture is pivotal for improving crop yield potential. Quinoa (Chenopodium quinoa Willd), a pseudo cereal originated from Andean region of South America, has been widely recognized as a functional super food due to its excellent nutritional elements. Increasing worldwide consumption of this crop urgently calls for its yield improvement. However, dissection of the regulatory networks underlying quinoa inflorescence patterning is lacking. Results In this study, we performed RNA-seq analysis on quinoa inflorescence samples collected from six developmental stages, yielding a total of 138.8 GB data. We screened 21,610 differentially expressed genes (DEGs) among all the stages through comparative analysis. Weighted Gene Co-Expression Network Analysis (WGCNA) was performed to categorize the DEGs into ten different modules. Subsequently, we placed emphasis on investigating the modules associated with none branched and branched inflorescence samples. We manually refined the coexpression networks with stringent edge weight cutoffs, and generated core networks using transcription factors and key inflorescence architecture related genes as seed nodes. The core networks were visualized and analyzed by Cytoscape to obtain hub genes in each network. Our finding indicates that the specific occurrence of B3, TALE, WOX, LSH, LFY, GRAS, bHLH, EIL, DOF, G2-like and YABBY family members in early reproductive stage modules, and of TFL, ERF, bZIP, HD-ZIP, C2H2, LBD, NAC, C3H, Nin-like and FAR1 family members in late reproductive stage modules, as well as the several different MADS subfamily members identified in both stages may account for shaping quinoa inflorescence architecture. Conclusion In this study we carried out comparative transcriptome analysis of six different stages quinoa inflorescences, and using WGCNA we obtained the most highly potential central hubs for shaping inflorescence. The data obtained from this study will enhance our understanding of the gene network regulating quinoa inflorescence architecture, as well will supply with valuable genetic resources for high-yield elite breeding in the future. Inflorescence architecture (dpeaa)DE-He213 RNA-seq (dpeaa)DE-He213 Transcriptome analysis (dpeaa)DE-He213 Weighted gene co-expression network analysis (dpeaa)DE-He213 Bai, Xue aut Zhao, Wei aut Shi, Xiaodong aut Xiang, Dabing aut Wan, Yan aut Wu, Xiaoyong aut Sun, Yanxia aut Zhao, Jianglin aut Peng, Lianxin aut Zhao, Gang aut Enthalten in BMC genomics London : BioMed Central, 2000 20(2019), 1 vom: 17. Aug. (DE-627)326644954 (DE-600)2041499-7 1471-2164 nnns volume:20 year:2019 number:1 day:17 month:08 https://dx.doi.org/10.1186/s12864-019-6027-0 kostenfrei Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 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_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 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_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4338 GBV_ILN_4367 GBV_ILN_4700 AR 20 2019 1 17 08
language	English
source	Enthalten in BMC genomics 20(2019), 1 vom: 17. Aug. volume:20 year:2019 number:1 day:17 month:08
sourceStr	Enthalten in BMC genomics 20(2019), 1 vom: 17. Aug. volume:20 year:2019 number:1 day:17 month:08
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Inflorescence architecture RNA-seq Transcriptome analysis Weighted gene co-expression network analysis
isfreeaccess_bool	true
container_title	BMC genomics
authorswithroles_txt_mv	Wu, Qi @@aut@@ Bai, Xue @@aut@@ Zhao, Wei @@aut@@ Shi, Xiaodong @@aut@@ Xiang, Dabing @@aut@@ Wan, Yan @@aut@@ Wu, Xiaoyong @@aut@@ Sun, Yanxia @@aut@@ Zhao, Jianglin @@aut@@ Peng, Lianxin @@aut@@ Zhao, Gang @@aut@@
publishDateDaySort_date	2019-08-17T00:00:00Z
hierarchy_top_id	326644954
id	SPR027156788
language_de	englisch
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Unveiling of the regulatory mechanisms underlying inflorescence architecture is pivotal for improving crop yield potential. Quinoa (Chenopodium quinoa Willd), a pseudo cereal originated from Andean region of South America, has been widely recognized as a functional super food due to its excellent nutritional elements. Increasing worldwide consumption of this crop urgently calls for its yield improvement. However, dissection of the regulatory networks underlying quinoa inflorescence patterning is lacking. Results In this study, we performed RNA-seq analysis on quinoa inflorescence samples collected from six developmental stages, yielding a total of 138.8 GB data. We screened 21,610 differentially expressed genes (DEGs) among all the stages through comparative analysis. Weighted Gene Co-Expression Network Analysis (WGCNA) was performed to categorize the DEGs into ten different modules. Subsequently, we placed emphasis on investigating the modules associated with none branched and branched inflorescence samples. We manually refined the coexpression networks with stringent edge weight cutoffs, and generated core networks using transcription factors and key inflorescence architecture related genes as seed nodes. The core networks were visualized and analyzed by Cytoscape to obtain hub genes in each network. Our finding indicates that the specific occurrence of B3, TALE, WOX, LSH, LFY, GRAS, bHLH, EIL, DOF, G2-like and YABBY family members in early reproductive stage modules, and of TFL, ERF, bZIP, HD-ZIP, C2H2, LBD, NAC, C3H, Nin-like and FAR1 family members in late reproductive stage modules, as well as the several different MADS subfamily members identified in both stages may account for shaping quinoa inflorescence architecture. Conclusion In this study we carried out comparative transcriptome analysis of six different stages quinoa inflorescences, and using WGCNA we obtained the most highly potential central hubs for shaping inflorescence. 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author	Wu, Qi
spellingShingle	Wu, Qi misc Inflorescence architecture misc RNA-seq misc Transcriptome analysis misc Weighted gene co-expression network analysis Investigation into the underlying regulatory mechanisms shaping inflorescence architecture in Chenopodium quinoa
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topic_title	Investigation into the underlying regulatory mechanisms shaping inflorescence architecture in Chenopodium quinoa Inflorescence architecture (dpeaa)DE-He213 RNA-seq (dpeaa)DE-He213 Transcriptome analysis (dpeaa)DE-He213 Weighted gene co-expression network analysis (dpeaa)DE-He213
topic	misc Inflorescence architecture misc RNA-seq misc Transcriptome analysis misc Weighted gene co-expression network analysis
topic_unstemmed	misc Inflorescence architecture misc RNA-seq misc Transcriptome analysis misc Weighted gene co-expression network analysis
topic_browse	misc Inflorescence architecture misc RNA-seq misc Transcriptome analysis misc Weighted gene co-expression network analysis
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title	Investigation into the underlying regulatory mechanisms shaping inflorescence architecture in Chenopodium quinoa
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title_full	Investigation into the underlying regulatory mechanisms shaping inflorescence architecture in Chenopodium quinoa
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author_browse	Wu, Qi Bai, Xue Zhao, Wei Shi, Xiaodong Xiang, Dabing Wan, Yan Wu, Xiaoyong Sun, Yanxia Zhao, Jianglin Peng, Lianxin Zhao, Gang
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title_sort	investigation into the underlying regulatory mechanisms shaping inflorescence architecture in chenopodium quinoa
title_auth	Investigation into the underlying regulatory mechanisms shaping inflorescence architecture in Chenopodium quinoa
abstract	Background Inflorescence architecture is denoted by the spatial arrangement of various lateral branches and florets formed on them, which is shaped by a complex of regulators. Unveiling of the regulatory mechanisms underlying inflorescence architecture is pivotal for improving crop yield potential. Quinoa (Chenopodium quinoa Willd), a pseudo cereal originated from Andean region of South America, has been widely recognized as a functional super food due to its excellent nutritional elements. Increasing worldwide consumption of this crop urgently calls for its yield improvement. However, dissection of the regulatory networks underlying quinoa inflorescence patterning is lacking. Results In this study, we performed RNA-seq analysis on quinoa inflorescence samples collected from six developmental stages, yielding a total of 138.8 GB data. We screened 21,610 differentially expressed genes (DEGs) among all the stages through comparative analysis. Weighted Gene Co-Expression Network Analysis (WGCNA) was performed to categorize the DEGs into ten different modules. Subsequently, we placed emphasis on investigating the modules associated with none branched and branched inflorescence samples. We manually refined the coexpression networks with stringent edge weight cutoffs, and generated core networks using transcription factors and key inflorescence architecture related genes as seed nodes. The core networks were visualized and analyzed by Cytoscape to obtain hub genes in each network. Our finding indicates that the specific occurrence of B3, TALE, WOX, LSH, LFY, GRAS, bHLH, EIL, DOF, G2-like and YABBY family members in early reproductive stage modules, and of TFL, ERF, bZIP, HD-ZIP, C2H2, LBD, NAC, C3H, Nin-like and FAR1 family members in late reproductive stage modules, as well as the several different MADS subfamily members identified in both stages may account for shaping quinoa inflorescence architecture. Conclusion In this study we carried out comparative transcriptome analysis of six different stages quinoa inflorescences, and using WGCNA we obtained the most highly potential central hubs for shaping inflorescence. The data obtained from this study will enhance our understanding of the gene network regulating quinoa inflorescence architecture, as well will supply with valuable genetic resources for high-yield elite breeding in the future. © The Author(s). 2019
abstractGer	Background Inflorescence architecture is denoted by the spatial arrangement of various lateral branches and florets formed on them, which is shaped by a complex of regulators. Unveiling of the regulatory mechanisms underlying inflorescence architecture is pivotal for improving crop yield potential. Quinoa (Chenopodium quinoa Willd), a pseudo cereal originated from Andean region of South America, has been widely recognized as a functional super food due to its excellent nutritional elements. Increasing worldwide consumption of this crop urgently calls for its yield improvement. However, dissection of the regulatory networks underlying quinoa inflorescence patterning is lacking. Results In this study, we performed RNA-seq analysis on quinoa inflorescence samples collected from six developmental stages, yielding a total of 138.8 GB data. We screened 21,610 differentially expressed genes (DEGs) among all the stages through comparative analysis. Weighted Gene Co-Expression Network Analysis (WGCNA) was performed to categorize the DEGs into ten different modules. Subsequently, we placed emphasis on investigating the modules associated with none branched and branched inflorescence samples. We manually refined the coexpression networks with stringent edge weight cutoffs, and generated core networks using transcription factors and key inflorescence architecture related genes as seed nodes. The core networks were visualized and analyzed by Cytoscape to obtain hub genes in each network. Our finding indicates that the specific occurrence of B3, TALE, WOX, LSH, LFY, GRAS, bHLH, EIL, DOF, G2-like and YABBY family members in early reproductive stage modules, and of TFL, ERF, bZIP, HD-ZIP, C2H2, LBD, NAC, C3H, Nin-like and FAR1 family members in late reproductive stage modules, as well as the several different MADS subfamily members identified in both stages may account for shaping quinoa inflorescence architecture. Conclusion In this study we carried out comparative transcriptome analysis of six different stages quinoa inflorescences, and using WGCNA we obtained the most highly potential central hubs for shaping inflorescence. The data obtained from this study will enhance our understanding of the gene network regulating quinoa inflorescence architecture, as well will supply with valuable genetic resources for high-yield elite breeding in the future. © The Author(s). 2019
abstract_unstemmed	Background Inflorescence architecture is denoted by the spatial arrangement of various lateral branches and florets formed on them, which is shaped by a complex of regulators. Unveiling of the regulatory mechanisms underlying inflorescence architecture is pivotal for improving crop yield potential. Quinoa (Chenopodium quinoa Willd), a pseudo cereal originated from Andean region of South America, has been widely recognized as a functional super food due to its excellent nutritional elements. Increasing worldwide consumption of this crop urgently calls for its yield improvement. However, dissection of the regulatory networks underlying quinoa inflorescence patterning is lacking. Results In this study, we performed RNA-seq analysis on quinoa inflorescence samples collected from six developmental stages, yielding a total of 138.8 GB data. We screened 21,610 differentially expressed genes (DEGs) among all the stages through comparative analysis. Weighted Gene Co-Expression Network Analysis (WGCNA) was performed to categorize the DEGs into ten different modules. Subsequently, we placed emphasis on investigating the modules associated with none branched and branched inflorescence samples. We manually refined the coexpression networks with stringent edge weight cutoffs, and generated core networks using transcription factors and key inflorescence architecture related genes as seed nodes. The core networks were visualized and analyzed by Cytoscape to obtain hub genes in each network. Our finding indicates that the specific occurrence of B3, TALE, WOX, LSH, LFY, GRAS, bHLH, EIL, DOF, G2-like and YABBY family members in early reproductive stage modules, and of TFL, ERF, bZIP, HD-ZIP, C2H2, LBD, NAC, C3H, Nin-like and FAR1 family members in late reproductive stage modules, as well as the several different MADS subfamily members identified in both stages may account for shaping quinoa inflorescence architecture. Conclusion In this study we carried out comparative transcriptome analysis of six different stages quinoa inflorescences, and using WGCNA we obtained the most highly potential central hubs for shaping inflorescence. The data obtained from this study will enhance our understanding of the gene network regulating quinoa inflorescence architecture, as well will supply with valuable genetic resources for high-yield elite breeding in the future. © The Author(s). 2019
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title_short	Investigation into the underlying regulatory mechanisms shaping inflorescence architecture in Chenopodium quinoa
url	https://dx.doi.org/10.1186/s12864-019-6027-0
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author2	Bai, Xue Zhao, Wei Shi, Xiaodong Xiang, Dabing Wan, Yan Wu, Xiaoyong Sun, Yanxia Zhao, Jianglin Peng, Lianxin Zhao, Gang
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Unveiling of the regulatory mechanisms underlying inflorescence architecture is pivotal for improving crop yield potential. Quinoa (Chenopodium quinoa Willd), a pseudo cereal originated from Andean region of South America, has been widely recognized as a functional super food due to its excellent nutritional elements. Increasing worldwide consumption of this crop urgently calls for its yield improvement. However, dissection of the regulatory networks underlying quinoa inflorescence patterning is lacking. Results In this study, we performed RNA-seq analysis on quinoa inflorescence samples collected from six developmental stages, yielding a total of 138.8 GB data. We screened 21,610 differentially expressed genes (DEGs) among all the stages through comparative analysis. Weighted Gene Co-Expression Network Analysis (WGCNA) was performed to categorize the DEGs into ten different modules. Subsequently, we placed emphasis on investigating the modules associated with none branched and branched inflorescence samples. We manually refined the coexpression networks with stringent edge weight cutoffs, and generated core networks using transcription factors and key inflorescence architecture related genes as seed nodes. The core networks were visualized and analyzed by Cytoscape to obtain hub genes in each network. Our finding indicates that the specific occurrence of B3, TALE, WOX, LSH, LFY, GRAS, bHLH, EIL, DOF, G2-like and YABBY family members in early reproductive stage modules, and of TFL, ERF, bZIP, HD-ZIP, C2H2, LBD, NAC, C3H, Nin-like and FAR1 family members in late reproductive stage modules, as well as the several different MADS subfamily members identified in both stages may account for shaping quinoa inflorescence architecture. Conclusion In this study we carried out comparative transcriptome analysis of six different stages quinoa inflorescences, and using WGCNA we obtained the most highly potential central hubs for shaping inflorescence. 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Investigation into the underlying regulatory mechanisms shaping inflorescence architecture in Chenopodium quinoa

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