Integration of conventional and advanced molecular tools to track footprints of heterosis in cotton
Abstract Background Heterosis, a multigenic complex trait extrapolated as sum total of many phenotypic features, is widely utilized phenomenon in agricultural crops for about a century. It is mainly focused on establishing vigorous cultivars with the fact that its deployment in crops necessitates th...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Zareen Sarfraz [verfasserIn] Muhammad Shahid Iqbal [verfasserIn] Zhaoe Pan [verfasserIn] Yinhua Jia [verfasserIn] Shoupu He [verfasserIn] Qinglian Wang [verfasserIn] Hongde Qin [verfasserIn] Jinhai Liu [verfasserIn] Hui Liu [verfasserIn] Jun Yang [verfasserIn] Zhiying Ma [verfasserIn] Dongyong Xu [verfasserIn] Jinlong Yang [verfasserIn] Jinbiao Zhang [verfasserIn] Wenfang Gong [verfasserIn] Xiaoli Geng [verfasserIn] Zhikun Li [verfasserIn] Zhongmin Cai [verfasserIn] Xuelin Zhang [verfasserIn] Xin Zhang [verfasserIn] Aifen Huang [verfasserIn] Xianda Yi [verfasserIn] Guanyin Zhou [verfasserIn] Lin Li [verfasserIn] Haiyong Zhu [verfasserIn] Yujie Qu [verfasserIn] Baoyin Pang [verfasserIn] Liru Wang [verfasserIn] Muhammad Sajid Iqbal [verfasserIn] Muhammad Jamshed [verfasserIn] Junling Sun [verfasserIn] Xiongming Du [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2018 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
In: BMC Genomics - BMC, 2003, 19(2018), 1, Seite 19 |
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| Übergeordnetes Werk: |
volume:19 ; year:2018 ; number:1 ; pages:19 |
| Links: |
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| DOI / URN: |
10.1186/s12864-018-5129-4 |
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| Katalog-ID: |
DOAJ029969700 |
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| 245 | 1 | 0 | |a Integration of conventional and advanced molecular tools to track footprints of heterosis in cotton |
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| 520 | |a Abstract Background Heterosis, a multigenic complex trait extrapolated as sum total of many phenotypic features, is widely utilized phenomenon in agricultural crops for about a century. It is mainly focused on establishing vigorous cultivars with the fact that its deployment in crops necessitates the perspective of genomic impressions on prior selection for metric traits. In spite of extensive investigations, the actual mysterious genetic basis of heterosis is yet to unravel. Contemporary crop breeding is aimed at enhanced crop production overcoming former achievements. Leading cotton improvement programs remained handicapped to attain significant accomplishments. Results In mentioned context, a comprehensive project was designed involving a large collection of cotton accessions including 284 lines, 5 testers along with their respective F1 hybrids derived from Line × Tester mating design were evaluated under 10 diverse environments. Heterosis, GCA and SCA were estimated from morphological and fiber quality traits by L × T analysis. For the exploration of elite marker alleles related to heterosis and to provide the material carrying such multiple alleles the mentioned three dependent variables along with trait phenotype values were executed for association study aided by microsatellites in mixed linear model based on population structure and linkage disequilibrium analysis. Highly significant 46 microsatellites were discovered in association with the fiber and yield related traits under study. It was observed that two-thirds of the highly significant associated microsatellites related to fiber quality were distributed on D sub-genome, including some with pleiotropic effect. Newly discovered 32 hQTLs related to fiber quality traits are one of prominent findings from current study. A set of 96 exclusively favorable alleles were discovered and C tester (A971Bt) posited a major contributor of these alleles primarily associated with fiber quality. Conclusions Hence, to uncover hidden facts lying within heterosis phenomenon, discovery of additional hQTLs is required to improve fibre quality. To grab prominent improvement in influenced fiber quality and yield traits, we suggest the A971 Bt cotton cultivar as fundamental element in advance breeding programs as a parent of choice. | ||
| 650 | 4 | |a Heterosis | |
| 650 | 4 | |a L × T | |
| 650 | 4 | |a GCA | |
| 650 | 4 | |a SCA | |
| 650 | 4 | |a Microsatellite markers | |
| 650 | 4 | |a hQTL | |
| 653 | 0 | |a Biotechnology | |
| 653 | 0 | |a Genetics | |
| 700 | 0 | |a Muhammad Shahid Iqbal |e verfasserin |4 aut | |
| 700 | 0 | |a Zhaoe Pan |e verfasserin |4 aut | |
| 700 | 0 | |a Yinhua Jia |e verfasserin |4 aut | |
| 700 | 0 | |a Shoupu He |e verfasserin |4 aut | |
| 700 | 0 | |a Qinglian Wang |e verfasserin |4 aut | |
| 700 | 0 | |a Hongde Qin |e verfasserin |4 aut | |
| 700 | 0 | |a Jinhai Liu |e verfasserin |4 aut | |
| 700 | 0 | |a Hui Liu |e verfasserin |4 aut | |
| 700 | 0 | |a Jun Yang |e verfasserin |4 aut | |
| 700 | 0 | |a Zhiying Ma |e verfasserin |4 aut | |
| 700 | 0 | |a Dongyong Xu |e verfasserin |4 aut | |
| 700 | 0 | |a Jinlong Yang |e verfasserin |4 aut | |
| 700 | 0 | |a Jinbiao Zhang |e verfasserin |4 aut | |
| 700 | 0 | |a Wenfang Gong |e verfasserin |4 aut | |
| 700 | 0 | |a Xiaoli Geng |e verfasserin |4 aut | |
| 700 | 0 | |a Zhikun Li |e verfasserin |4 aut | |
| 700 | 0 | |a Zhongmin Cai |e verfasserin |4 aut | |
| 700 | 0 | |a Xuelin Zhang |e verfasserin |4 aut | |
| 700 | 0 | |a Xin Zhang |e verfasserin |4 aut | |
| 700 | 0 | |a Aifen Huang |e verfasserin |4 aut | |
| 700 | 0 | |a Xianda Yi |e verfasserin |4 aut | |
| 700 | 0 | |a Guanyin Zhou |e verfasserin |4 aut | |
| 700 | 0 | |a Lin Li |e verfasserin |4 aut | |
| 700 | 0 | |a Haiyong Zhu |e verfasserin |4 aut | |
| 700 | 0 | |a Yujie Qu |e verfasserin |4 aut | |
| 700 | 0 | |a Baoyin Pang |e verfasserin |4 aut | |
| 700 | 0 | |a Liru Wang |e verfasserin |4 aut | |
| 700 | 0 | |a Muhammad Sajid Iqbal |e verfasserin |4 aut | |
| 700 | 0 | |a Muhammad Jamshed |e verfasserin |4 aut | |
| 700 | 0 | |a Junling Sun |e verfasserin |4 aut | |
| 700 | 0 | |a Xiongming Du |e verfasserin |4 aut | |
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10.1186/s12864-018-5129-4 doi (DE-627)DOAJ029969700 (DE-599)DOAJd8704be69a7a461fb5248b400b89abeb DE-627 ger DE-627 rakwb eng TP248.13-248.65 QH426-470 Zareen Sarfraz verfasserin aut Integration of conventional and advanced molecular tools to track footprints of heterosis in cotton 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Background Heterosis, a multigenic complex trait extrapolated as sum total of many phenotypic features, is widely utilized phenomenon in agricultural crops for about a century. It is mainly focused on establishing vigorous cultivars with the fact that its deployment in crops necessitates the perspective of genomic impressions on prior selection for metric traits. In spite of extensive investigations, the actual mysterious genetic basis of heterosis is yet to unravel. Contemporary crop breeding is aimed at enhanced crop production overcoming former achievements. Leading cotton improvement programs remained handicapped to attain significant accomplishments. Results In mentioned context, a comprehensive project was designed involving a large collection of cotton accessions including 284 lines, 5 testers along with their respective F1 hybrids derived from Line × Tester mating design were evaluated under 10 diverse environments. Heterosis, GCA and SCA were estimated from morphological and fiber quality traits by L × T analysis. For the exploration of elite marker alleles related to heterosis and to provide the material carrying such multiple alleles the mentioned three dependent variables along with trait phenotype values were executed for association study aided by microsatellites in mixed linear model based on population structure and linkage disequilibrium analysis. Highly significant 46 microsatellites were discovered in association with the fiber and yield related traits under study. It was observed that two-thirds of the highly significant associated microsatellites related to fiber quality were distributed on D sub-genome, including some with pleiotropic effect. Newly discovered 32 hQTLs related to fiber quality traits are one of prominent findings from current study. A set of 96 exclusively favorable alleles were discovered and C tester (A971Bt) posited a major contributor of these alleles primarily associated with fiber quality. Conclusions Hence, to uncover hidden facts lying within heterosis phenomenon, discovery of additional hQTLs is required to improve fibre quality. To grab prominent improvement in influenced fiber quality and yield traits, we suggest the A971 Bt cotton cultivar as fundamental element in advance breeding programs as a parent of choice. Heterosis L × T GCA SCA Microsatellite markers hQTL Biotechnology Genetics Muhammad Shahid Iqbal verfasserin aut Zhaoe Pan verfasserin aut Yinhua Jia verfasserin aut Shoupu He verfasserin aut Qinglian Wang verfasserin aut Hongde Qin verfasserin aut Jinhai Liu verfasserin aut Hui Liu verfasserin aut Jun Yang verfasserin aut Zhiying Ma verfasserin aut Dongyong Xu verfasserin aut Jinlong Yang verfasserin aut Jinbiao Zhang verfasserin aut Wenfang Gong verfasserin aut Xiaoli Geng verfasserin aut Zhikun Li verfasserin aut Zhongmin Cai verfasserin aut Xuelin Zhang verfasserin aut Xin Zhang verfasserin aut Aifen Huang verfasserin aut Xianda Yi verfasserin aut Guanyin Zhou verfasserin aut Lin Li verfasserin aut Haiyong Zhu verfasserin aut Yujie Qu verfasserin aut Baoyin Pang verfasserin aut Liru Wang verfasserin aut Muhammad Sajid Iqbal verfasserin aut Muhammad Jamshed verfasserin aut Junling Sun verfasserin aut Xiongming Du verfasserin aut In BMC Genomics BMC, 2003 19(2018), 1, Seite 19 (DE-627)326644954 (DE-600)2041499-7 14712164 nnns volume:19 year:2018 number:1 pages:19 https://doi.org/10.1186/s12864-018-5129-4 kostenfrei https://doaj.org/article/d8704be69a7a461fb5248b400b89abeb kostenfrei http://link.springer.com/article/10.1186/s12864-018-5129-4 kostenfrei https://doaj.org/toc/1471-2164 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ 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 19 2018 1 19 |
| spelling |
10.1186/s12864-018-5129-4 doi (DE-627)DOAJ029969700 (DE-599)DOAJd8704be69a7a461fb5248b400b89abeb DE-627 ger DE-627 rakwb eng TP248.13-248.65 QH426-470 Zareen Sarfraz verfasserin aut Integration of conventional and advanced molecular tools to track footprints of heterosis in cotton 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Background Heterosis, a multigenic complex trait extrapolated as sum total of many phenotypic features, is widely utilized phenomenon in agricultural crops for about a century. It is mainly focused on establishing vigorous cultivars with the fact that its deployment in crops necessitates the perspective of genomic impressions on prior selection for metric traits. In spite of extensive investigations, the actual mysterious genetic basis of heterosis is yet to unravel. Contemporary crop breeding is aimed at enhanced crop production overcoming former achievements. Leading cotton improvement programs remained handicapped to attain significant accomplishments. Results In mentioned context, a comprehensive project was designed involving a large collection of cotton accessions including 284 lines, 5 testers along with their respective F1 hybrids derived from Line × Tester mating design were evaluated under 10 diverse environments. Heterosis, GCA and SCA were estimated from morphological and fiber quality traits by L × T analysis. For the exploration of elite marker alleles related to heterosis and to provide the material carrying such multiple alleles the mentioned three dependent variables along with trait phenotype values were executed for association study aided by microsatellites in mixed linear model based on population structure and linkage disequilibrium analysis. Highly significant 46 microsatellites were discovered in association with the fiber and yield related traits under study. It was observed that two-thirds of the highly significant associated microsatellites related to fiber quality were distributed on D sub-genome, including some with pleiotropic effect. Newly discovered 32 hQTLs related to fiber quality traits are one of prominent findings from current study. A set of 96 exclusively favorable alleles were discovered and C tester (A971Bt) posited a major contributor of these alleles primarily associated with fiber quality. Conclusions Hence, to uncover hidden facts lying within heterosis phenomenon, discovery of additional hQTLs is required to improve fibre quality. To grab prominent improvement in influenced fiber quality and yield traits, we suggest the A971 Bt cotton cultivar as fundamental element in advance breeding programs as a parent of choice. Heterosis L × T GCA SCA Microsatellite markers hQTL Biotechnology Genetics Muhammad Shahid Iqbal verfasserin aut Zhaoe Pan verfasserin aut Yinhua Jia verfasserin aut Shoupu He verfasserin aut Qinglian Wang verfasserin aut Hongde Qin verfasserin aut Jinhai Liu verfasserin aut Hui Liu verfasserin aut Jun Yang verfasserin aut Zhiying Ma verfasserin aut Dongyong Xu verfasserin aut Jinlong Yang verfasserin aut Jinbiao Zhang verfasserin aut Wenfang Gong verfasserin aut Xiaoli Geng verfasserin aut Zhikun Li verfasserin aut Zhongmin Cai verfasserin aut Xuelin Zhang verfasserin aut Xin Zhang verfasserin aut Aifen Huang verfasserin aut Xianda Yi verfasserin aut Guanyin Zhou verfasserin aut Lin Li verfasserin aut Haiyong Zhu verfasserin aut Yujie Qu verfasserin aut Baoyin Pang verfasserin aut Liru Wang verfasserin aut Muhammad Sajid Iqbal verfasserin aut Muhammad Jamshed verfasserin aut Junling Sun verfasserin aut Xiongming Du verfasserin aut In BMC Genomics BMC, 2003 19(2018), 1, Seite 19 (DE-627)326644954 (DE-600)2041499-7 14712164 nnns volume:19 year:2018 number:1 pages:19 https://doi.org/10.1186/s12864-018-5129-4 kostenfrei https://doaj.org/article/d8704be69a7a461fb5248b400b89abeb kostenfrei http://link.springer.com/article/10.1186/s12864-018-5129-4 kostenfrei https://doaj.org/toc/1471-2164 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ 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 19 2018 1 19 |
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10.1186/s12864-018-5129-4 doi (DE-627)DOAJ029969700 (DE-599)DOAJd8704be69a7a461fb5248b400b89abeb DE-627 ger DE-627 rakwb eng TP248.13-248.65 QH426-470 Zareen Sarfraz verfasserin aut Integration of conventional and advanced molecular tools to track footprints of heterosis in cotton 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Background Heterosis, a multigenic complex trait extrapolated as sum total of many phenotypic features, is widely utilized phenomenon in agricultural crops for about a century. It is mainly focused on establishing vigorous cultivars with the fact that its deployment in crops necessitates the perspective of genomic impressions on prior selection for metric traits. In spite of extensive investigations, the actual mysterious genetic basis of heterosis is yet to unravel. Contemporary crop breeding is aimed at enhanced crop production overcoming former achievements. Leading cotton improvement programs remained handicapped to attain significant accomplishments. Results In mentioned context, a comprehensive project was designed involving a large collection of cotton accessions including 284 lines, 5 testers along with their respective F1 hybrids derived from Line × Tester mating design were evaluated under 10 diverse environments. Heterosis, GCA and SCA were estimated from morphological and fiber quality traits by L × T analysis. For the exploration of elite marker alleles related to heterosis and to provide the material carrying such multiple alleles the mentioned three dependent variables along with trait phenotype values were executed for association study aided by microsatellites in mixed linear model based on population structure and linkage disequilibrium analysis. Highly significant 46 microsatellites were discovered in association with the fiber and yield related traits under study. It was observed that two-thirds of the highly significant associated microsatellites related to fiber quality were distributed on D sub-genome, including some with pleiotropic effect. Newly discovered 32 hQTLs related to fiber quality traits are one of prominent findings from current study. A set of 96 exclusively favorable alleles were discovered and C tester (A971Bt) posited a major contributor of these alleles primarily associated with fiber quality. Conclusions Hence, to uncover hidden facts lying within heterosis phenomenon, discovery of additional hQTLs is required to improve fibre quality. To grab prominent improvement in influenced fiber quality and yield traits, we suggest the A971 Bt cotton cultivar as fundamental element in advance breeding programs as a parent of choice. Heterosis L × T GCA SCA Microsatellite markers hQTL Biotechnology Genetics Muhammad Shahid Iqbal verfasserin aut Zhaoe Pan verfasserin aut Yinhua Jia verfasserin aut Shoupu He verfasserin aut Qinglian Wang verfasserin aut Hongde Qin verfasserin aut Jinhai Liu verfasserin aut Hui Liu verfasserin aut Jun Yang verfasserin aut Zhiying Ma verfasserin aut Dongyong Xu verfasserin aut Jinlong Yang verfasserin aut Jinbiao Zhang verfasserin aut Wenfang Gong verfasserin aut Xiaoli Geng verfasserin aut Zhikun Li verfasserin aut Zhongmin Cai verfasserin aut Xuelin Zhang verfasserin aut Xin Zhang verfasserin aut Aifen Huang verfasserin aut Xianda Yi verfasserin aut Guanyin Zhou verfasserin aut Lin Li verfasserin aut Haiyong Zhu verfasserin aut Yujie Qu verfasserin aut Baoyin Pang verfasserin aut Liru Wang verfasserin aut Muhammad Sajid Iqbal verfasserin aut Muhammad Jamshed verfasserin aut Junling Sun verfasserin aut Xiongming Du verfasserin aut In BMC Genomics BMC, 2003 19(2018), 1, Seite 19 (DE-627)326644954 (DE-600)2041499-7 14712164 nnns volume:19 year:2018 number:1 pages:19 https://doi.org/10.1186/s12864-018-5129-4 kostenfrei https://doaj.org/article/d8704be69a7a461fb5248b400b89abeb kostenfrei http://link.springer.com/article/10.1186/s12864-018-5129-4 kostenfrei https://doaj.org/toc/1471-2164 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ 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 19 2018 1 19 |
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10.1186/s12864-018-5129-4 doi (DE-627)DOAJ029969700 (DE-599)DOAJd8704be69a7a461fb5248b400b89abeb DE-627 ger DE-627 rakwb eng TP248.13-248.65 QH426-470 Zareen Sarfraz verfasserin aut Integration of conventional and advanced molecular tools to track footprints of heterosis in cotton 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Background Heterosis, a multigenic complex trait extrapolated as sum total of many phenotypic features, is widely utilized phenomenon in agricultural crops for about a century. It is mainly focused on establishing vigorous cultivars with the fact that its deployment in crops necessitates the perspective of genomic impressions on prior selection for metric traits. In spite of extensive investigations, the actual mysterious genetic basis of heterosis is yet to unravel. Contemporary crop breeding is aimed at enhanced crop production overcoming former achievements. Leading cotton improvement programs remained handicapped to attain significant accomplishments. Results In mentioned context, a comprehensive project was designed involving a large collection of cotton accessions including 284 lines, 5 testers along with their respective F1 hybrids derived from Line × Tester mating design were evaluated under 10 diverse environments. Heterosis, GCA and SCA were estimated from morphological and fiber quality traits by L × T analysis. For the exploration of elite marker alleles related to heterosis and to provide the material carrying such multiple alleles the mentioned three dependent variables along with trait phenotype values were executed for association study aided by microsatellites in mixed linear model based on population structure and linkage disequilibrium analysis. Highly significant 46 microsatellites were discovered in association with the fiber and yield related traits under study. It was observed that two-thirds of the highly significant associated microsatellites related to fiber quality were distributed on D sub-genome, including some with pleiotropic effect. Newly discovered 32 hQTLs related to fiber quality traits are one of prominent findings from current study. A set of 96 exclusively favorable alleles were discovered and C tester (A971Bt) posited a major contributor of these alleles primarily associated with fiber quality. Conclusions Hence, to uncover hidden facts lying within heterosis phenomenon, discovery of additional hQTLs is required to improve fibre quality. To grab prominent improvement in influenced fiber quality and yield traits, we suggest the A971 Bt cotton cultivar as fundamental element in advance breeding programs as a parent of choice. Heterosis L × T GCA SCA Microsatellite markers hQTL Biotechnology Genetics Muhammad Shahid Iqbal verfasserin aut Zhaoe Pan verfasserin aut Yinhua Jia verfasserin aut Shoupu He verfasserin aut Qinglian Wang verfasserin aut Hongde Qin verfasserin aut Jinhai Liu verfasserin aut Hui Liu verfasserin aut Jun Yang verfasserin aut Zhiying Ma verfasserin aut Dongyong Xu verfasserin aut Jinlong Yang verfasserin aut Jinbiao Zhang verfasserin aut Wenfang Gong verfasserin aut Xiaoli Geng verfasserin aut Zhikun Li verfasserin aut Zhongmin Cai verfasserin aut Xuelin Zhang verfasserin aut Xin Zhang verfasserin aut Aifen Huang verfasserin aut Xianda Yi verfasserin aut Guanyin Zhou verfasserin aut Lin Li verfasserin aut Haiyong Zhu verfasserin aut Yujie Qu verfasserin aut Baoyin Pang verfasserin aut Liru Wang verfasserin aut Muhammad Sajid Iqbal verfasserin aut Muhammad Jamshed verfasserin aut Junling Sun verfasserin aut Xiongming Du verfasserin aut In BMC Genomics BMC, 2003 19(2018), 1, Seite 19 (DE-627)326644954 (DE-600)2041499-7 14712164 nnns volume:19 year:2018 number:1 pages:19 https://doi.org/10.1186/s12864-018-5129-4 kostenfrei https://doaj.org/article/d8704be69a7a461fb5248b400b89abeb kostenfrei http://link.springer.com/article/10.1186/s12864-018-5129-4 kostenfrei https://doaj.org/toc/1471-2164 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ 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 19 2018 1 19 |
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10.1186/s12864-018-5129-4 doi (DE-627)DOAJ029969700 (DE-599)DOAJd8704be69a7a461fb5248b400b89abeb DE-627 ger DE-627 rakwb eng TP248.13-248.65 QH426-470 Zareen Sarfraz verfasserin aut Integration of conventional and advanced molecular tools to track footprints of heterosis in cotton 2018 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Background Heterosis, a multigenic complex trait extrapolated as sum total of many phenotypic features, is widely utilized phenomenon in agricultural crops for about a century. It is mainly focused on establishing vigorous cultivars with the fact that its deployment in crops necessitates the perspective of genomic impressions on prior selection for metric traits. In spite of extensive investigations, the actual mysterious genetic basis of heterosis is yet to unravel. Contemporary crop breeding is aimed at enhanced crop production overcoming former achievements. Leading cotton improvement programs remained handicapped to attain significant accomplishments. Results In mentioned context, a comprehensive project was designed involving a large collection of cotton accessions including 284 lines, 5 testers along with their respective F1 hybrids derived from Line × Tester mating design were evaluated under 10 diverse environments. Heterosis, GCA and SCA were estimated from morphological and fiber quality traits by L × T analysis. For the exploration of elite marker alleles related to heterosis and to provide the material carrying such multiple alleles the mentioned three dependent variables along with trait phenotype values were executed for association study aided by microsatellites in mixed linear model based on population structure and linkage disequilibrium analysis. Highly significant 46 microsatellites were discovered in association with the fiber and yield related traits under study. It was observed that two-thirds of the highly significant associated microsatellites related to fiber quality were distributed on D sub-genome, including some with pleiotropic effect. Newly discovered 32 hQTLs related to fiber quality traits are one of prominent findings from current study. A set of 96 exclusively favorable alleles were discovered and C tester (A971Bt) posited a major contributor of these alleles primarily associated with fiber quality. Conclusions Hence, to uncover hidden facts lying within heterosis phenomenon, discovery of additional hQTLs is required to improve fibre quality. To grab prominent improvement in influenced fiber quality and yield traits, we suggest the A971 Bt cotton cultivar as fundamental element in advance breeding programs as a parent of choice. Heterosis L × T GCA SCA Microsatellite markers hQTL Biotechnology Genetics Muhammad Shahid Iqbal verfasserin aut Zhaoe Pan verfasserin aut Yinhua Jia verfasserin aut Shoupu He verfasserin aut Qinglian Wang verfasserin aut Hongde Qin verfasserin aut Jinhai Liu verfasserin aut Hui Liu verfasserin aut Jun Yang verfasserin aut Zhiying Ma verfasserin aut Dongyong Xu verfasserin aut Jinlong Yang verfasserin aut Jinbiao Zhang verfasserin aut Wenfang Gong verfasserin aut Xiaoli Geng verfasserin aut Zhikun Li verfasserin aut Zhongmin Cai verfasserin aut Xuelin Zhang verfasserin aut Xin Zhang verfasserin aut Aifen Huang verfasserin aut Xianda Yi verfasserin aut Guanyin Zhou verfasserin aut Lin Li verfasserin aut Haiyong Zhu verfasserin aut Yujie Qu verfasserin aut Baoyin Pang verfasserin aut Liru Wang verfasserin aut Muhammad Sajid Iqbal verfasserin aut Muhammad Jamshed verfasserin aut Junling Sun verfasserin aut Xiongming Du verfasserin aut In BMC Genomics BMC, 2003 19(2018), 1, Seite 19 (DE-627)326644954 (DE-600)2041499-7 14712164 nnns volume:19 year:2018 number:1 pages:19 https://doi.org/10.1186/s12864-018-5129-4 kostenfrei https://doaj.org/article/d8704be69a7a461fb5248b400b89abeb kostenfrei http://link.springer.com/article/10.1186/s12864-018-5129-4 kostenfrei https://doaj.org/toc/1471-2164 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ 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 19 2018 1 19 |
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Zareen Sarfraz @@aut@@ Muhammad Shahid Iqbal @@aut@@ Zhaoe Pan @@aut@@ Yinhua Jia @@aut@@ Shoupu He @@aut@@ Qinglian Wang @@aut@@ Hongde Qin @@aut@@ Jinhai Liu @@aut@@ Hui Liu @@aut@@ Jun Yang @@aut@@ Zhiying Ma @@aut@@ Dongyong Xu @@aut@@ Jinlong Yang @@aut@@ Jinbiao Zhang @@aut@@ Wenfang Gong @@aut@@ Xiaoli Geng @@aut@@ Zhikun Li @@aut@@ Zhongmin Cai @@aut@@ Xuelin Zhang @@aut@@ Xin Zhang @@aut@@ Aifen Huang @@aut@@ Xianda Yi @@aut@@ Guanyin Zhou @@aut@@ Lin Li @@aut@@ Haiyong Zhu @@aut@@ Yujie Qu @@aut@@ Baoyin Pang @@aut@@ Liru Wang @@aut@@ Muhammad Sajid Iqbal @@aut@@ Muhammad Jamshed @@aut@@ Junling Sun @@aut@@ Xiongming Du @@aut@@ |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">DOAJ029969700</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230503005019.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">230226s2018 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1186/s12864-018-5129-4</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)DOAJ029969700</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)DOAJd8704be69a7a461fb5248b400b89abeb</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="050" ind1=" " ind2="0"><subfield code="a">TP248.13-248.65</subfield></datafield><datafield tag="050" ind1=" " ind2="0"><subfield code="a">QH426-470</subfield></datafield><datafield tag="100" ind1="0" ind2=" "><subfield code="a">Zareen Sarfraz</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Integration of conventional and advanced molecular tools to track footprints of heterosis in cotton</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2018</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract Background Heterosis, a multigenic complex trait extrapolated as sum total of many phenotypic features, is widely utilized phenomenon in agricultural crops for about a century. It is mainly focused on establishing vigorous cultivars with the fact that its deployment in crops necessitates the perspective of genomic impressions on prior selection for metric traits. In spite of extensive investigations, the actual mysterious genetic basis of heterosis is yet to unravel. Contemporary crop breeding is aimed at enhanced crop production overcoming former achievements. Leading cotton improvement programs remained handicapped to attain significant accomplishments. Results In mentioned context, a comprehensive project was designed involving a large collection of cotton accessions including 284 lines, 5 testers along with their respective F1 hybrids derived from Line × Tester mating design were evaluated under 10 diverse environments. Heterosis, GCA and SCA were estimated from morphological and fiber quality traits by L × T analysis. For the exploration of elite marker alleles related to heterosis and to provide the material carrying such multiple alleles the mentioned three dependent variables along with trait phenotype values were executed for association study aided by microsatellites in mixed linear model based on population structure and linkage disequilibrium analysis. Highly significant 46 microsatellites were discovered in association with the fiber and yield related traits under study. It was observed that two-thirds of the highly significant associated microsatellites related to fiber quality were distributed on D sub-genome, including some with pleiotropic effect. Newly discovered 32 hQTLs related to fiber quality traits are one of prominent findings from current study. A set of 96 exclusively favorable alleles were discovered and C tester (A971Bt) posited a major contributor of these alleles primarily associated with fiber quality. Conclusions Hence, to uncover hidden facts lying within heterosis phenomenon, discovery of additional hQTLs is required to improve fibre quality. 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Zareen Sarfraz misc TP248.13-248.65 misc QH426-470 misc Heterosis misc L × T misc GCA misc SCA misc Microsatellite markers misc hQTL misc Biotechnology misc Genetics Integration of conventional and advanced molecular tools to track footprints of heterosis in cotton |
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TP248.13-248.65 QH426-470 Integration of conventional and advanced molecular tools to track footprints of heterosis in cotton Heterosis L × T GCA SCA Microsatellite markers hQTL |
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Zareen Sarfraz Muhammad Shahid Iqbal Zhaoe Pan Yinhua Jia Shoupu He Qinglian Wang Hongde Qin Jinhai Liu Hui Liu Jun Yang Zhiying Ma Dongyong Xu Jinlong Yang Jinbiao Zhang Wenfang Gong Xiaoli Geng Zhikun Li Zhongmin Cai Xuelin Zhang Xin Zhang Aifen Huang Xianda Yi Guanyin Zhou Lin Li Haiyong Zhu Yujie Qu Baoyin Pang Liru Wang Muhammad Sajid Iqbal Muhammad Jamshed Junling Sun Xiongming Du |
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Integration of conventional and advanced molecular tools to track footprints of heterosis in cotton |
| abstract |
Abstract Background Heterosis, a multigenic complex trait extrapolated as sum total of many phenotypic features, is widely utilized phenomenon in agricultural crops for about a century. It is mainly focused on establishing vigorous cultivars with the fact that its deployment in crops necessitates the perspective of genomic impressions on prior selection for metric traits. In spite of extensive investigations, the actual mysterious genetic basis of heterosis is yet to unravel. Contemporary crop breeding is aimed at enhanced crop production overcoming former achievements. Leading cotton improvement programs remained handicapped to attain significant accomplishments. Results In mentioned context, a comprehensive project was designed involving a large collection of cotton accessions including 284 lines, 5 testers along with their respective F1 hybrids derived from Line × Tester mating design were evaluated under 10 diverse environments. Heterosis, GCA and SCA were estimated from morphological and fiber quality traits by L × T analysis. For the exploration of elite marker alleles related to heterosis and to provide the material carrying such multiple alleles the mentioned three dependent variables along with trait phenotype values were executed for association study aided by microsatellites in mixed linear model based on population structure and linkage disequilibrium analysis. Highly significant 46 microsatellites were discovered in association with the fiber and yield related traits under study. It was observed that two-thirds of the highly significant associated microsatellites related to fiber quality were distributed on D sub-genome, including some with pleiotropic effect. Newly discovered 32 hQTLs related to fiber quality traits are one of prominent findings from current study. A set of 96 exclusively favorable alleles were discovered and C tester (A971Bt) posited a major contributor of these alleles primarily associated with fiber quality. Conclusions Hence, to uncover hidden facts lying within heterosis phenomenon, discovery of additional hQTLs is required to improve fibre quality. To grab prominent improvement in influenced fiber quality and yield traits, we suggest the A971 Bt cotton cultivar as fundamental element in advance breeding programs as a parent of choice. |
| abstractGer |
Abstract Background Heterosis, a multigenic complex trait extrapolated as sum total of many phenotypic features, is widely utilized phenomenon in agricultural crops for about a century. It is mainly focused on establishing vigorous cultivars with the fact that its deployment in crops necessitates the perspective of genomic impressions on prior selection for metric traits. In spite of extensive investigations, the actual mysterious genetic basis of heterosis is yet to unravel. Contemporary crop breeding is aimed at enhanced crop production overcoming former achievements. Leading cotton improvement programs remained handicapped to attain significant accomplishments. Results In mentioned context, a comprehensive project was designed involving a large collection of cotton accessions including 284 lines, 5 testers along with their respective F1 hybrids derived from Line × Tester mating design were evaluated under 10 diverse environments. Heterosis, GCA and SCA were estimated from morphological and fiber quality traits by L × T analysis. For the exploration of elite marker alleles related to heterosis and to provide the material carrying such multiple alleles the mentioned three dependent variables along with trait phenotype values were executed for association study aided by microsatellites in mixed linear model based on population structure and linkage disequilibrium analysis. Highly significant 46 microsatellites were discovered in association with the fiber and yield related traits under study. It was observed that two-thirds of the highly significant associated microsatellites related to fiber quality were distributed on D sub-genome, including some with pleiotropic effect. Newly discovered 32 hQTLs related to fiber quality traits are one of prominent findings from current study. A set of 96 exclusively favorable alleles were discovered and C tester (A971Bt) posited a major contributor of these alleles primarily associated with fiber quality. Conclusions Hence, to uncover hidden facts lying within heterosis phenomenon, discovery of additional hQTLs is required to improve fibre quality. To grab prominent improvement in influenced fiber quality and yield traits, we suggest the A971 Bt cotton cultivar as fundamental element in advance breeding programs as a parent of choice. |
| abstract_unstemmed |
Abstract Background Heterosis, a multigenic complex trait extrapolated as sum total of many phenotypic features, is widely utilized phenomenon in agricultural crops for about a century. It is mainly focused on establishing vigorous cultivars with the fact that its deployment in crops necessitates the perspective of genomic impressions on prior selection for metric traits. In spite of extensive investigations, the actual mysterious genetic basis of heterosis is yet to unravel. Contemporary crop breeding is aimed at enhanced crop production overcoming former achievements. Leading cotton improvement programs remained handicapped to attain significant accomplishments. Results In mentioned context, a comprehensive project was designed involving a large collection of cotton accessions including 284 lines, 5 testers along with their respective F1 hybrids derived from Line × Tester mating design were evaluated under 10 diverse environments. Heterosis, GCA and SCA were estimated from morphological and fiber quality traits by L × T analysis. For the exploration of elite marker alleles related to heterosis and to provide the material carrying such multiple alleles the mentioned three dependent variables along with trait phenotype values were executed for association study aided by microsatellites in mixed linear model based on population structure and linkage disequilibrium analysis. Highly significant 46 microsatellites were discovered in association with the fiber and yield related traits under study. It was observed that two-thirds of the highly significant associated microsatellites related to fiber quality were distributed on D sub-genome, including some with pleiotropic effect. Newly discovered 32 hQTLs related to fiber quality traits are one of prominent findings from current study. A set of 96 exclusively favorable alleles were discovered and C tester (A971Bt) posited a major contributor of these alleles primarily associated with fiber quality. Conclusions Hence, to uncover hidden facts lying within heterosis phenomenon, discovery of additional hQTLs is required to improve fibre quality. To grab prominent improvement in influenced fiber quality and yield traits, we suggest the A971 Bt cotton cultivar as fundamental element in advance breeding programs as a parent of choice. |
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Integration of conventional and advanced molecular tools to track footprints of heterosis in cotton |
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https://doi.org/10.1186/s12864-018-5129-4 https://doaj.org/article/d8704be69a7a461fb5248b400b89abeb http://link.springer.com/article/10.1186/s12864-018-5129-4 https://doaj.org/toc/1471-2164 |
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Muhammad Shahid Iqbal Zhaoe Pan Yinhua Jia Shoupu He Qinglian Wang Hongde Qin Jinhai Liu Hui Liu Jun Yang Zhiying Ma Dongyong Xu Jinlong Yang Jinbiao Zhang Wenfang Gong Xiaoli Geng Zhikun Li Zhongmin Cai Xuelin Zhang Xin Zhang Aifen Huang Xianda Yi Guanyin Zhou Lin Li Haiyong Zhu Yujie Qu Baoyin Pang Liru Wang Muhammad Sajid Iqbal Muhammad Jamshed Junling Sun Xiongming Du |
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Muhammad Shahid Iqbal Zhaoe Pan Yinhua Jia Shoupu He Qinglian Wang Hongde Qin Jinhai Liu Hui Liu Jun Yang Zhiying Ma Dongyong Xu Jinlong Yang Jinbiao Zhang Wenfang Gong Xiaoli Geng Zhikun Li Zhongmin Cai Xuelin Zhang Xin Zhang Aifen Huang Xianda Yi Guanyin Zhou Lin Li Haiyong Zhu Yujie Qu Baoyin Pang Liru Wang Muhammad Sajid Iqbal Muhammad Jamshed Junling Sun Xiongming Du |
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10.1186/s12864-018-5129-4 |
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2024-07-04T01:06:33.149Z |
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