Analysis of Quasispecies of Avain Leukosis Virus Subgroup J Using Sanger and High-throughput Sequencing

Background Avian leukosis viruses subgroup J (ALV-J) exists as a complex mixture of different, but closely related genomes named quasispecies subjected to continuous change according to the Principles of Darwinian evolution. Method The present study seeks to compare conventional Sanger sequencing wi...
Ausführliche Beschreibung

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Autor*in:	Meng, Fanfeng [verfasserIn] Dong, Xuan Hu, Tao Liu, Yingnan Zhao, Yingjie Lv, Yanyan Chang, Shuang Zhao, Peng Cui, Zhizhong

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2016

Schlagwörter:	Quasispecies-Sanger sequencing-deep sequencing-simulation

Anmerkung:	© The Author(s). 2016

Übergeordnetes Werk:	Enthalten in: Virology journal - London : BioMed Central, 2004, 13(2016), 1 vom: 27. Juni
Übergeordnetes Werk:	volume:13 ; year:2016 ; number:1 ; day:27 ; month:06

Links:	Volltext

DOI / URN:	10.1186/s12985-016-0559-6

Katalog-ID:	SPR029263549

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520			\|a Background Avian leukosis viruses subgroup J (ALV-J) exists as a complex mixture of different, but closely related genomes named quasispecies subjected to continuous change according to the Principles of Darwinian evolution. Method The present study seeks to compare conventional Sanger sequencing with deep sequencing using MiSeq platform to study quasispecies dynamics of ALV-J. Results The accuracy and reproducibility of MiSeq sequencing was determined better than Sanger sequencing by running each experiment in duplicate. According to the mutational rate of single position and the ability to distinguish dominant quasispecies with two sequencing methods, conventional Sanger sequencing technique displayed high randomness due to few sequencing samples, while deep sequencing could reflect the composition of the quasispecies more accurately. In the mean time, the research of quasispecies via Sanger sequencing was simulated and analyzed with the aid of re-sampling strategy with replacement for 1000 times repeat from high-throughput sequencing data, which indicated that the higher antibody titer, the higher sequence entropy, the harder analyzing with the conventional Sanger sequencing, resulted in lower ratios of dominant variants. Conclusions In sum, deep sequencing is better suited for detecting rare variants comprehensively. The simulation of Sanger sequencing that we propose here will also help to standardize quasispecies researching under different selection pressure based on next-generation sequencing data.
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Indexfelder

author_variant	f m fm x d xd t h th y l yl y z yz y l yl s c sc p z pz z c zc
matchkey_str	article:1743422X:2016----::nlssfusseisfviluoivrsugopuigagrnh
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allfields	10.1186/s12985-016-0559-6 doi (DE-627)SPR029263549 (SPR)s12985-016-0559-6-e DE-627 ger DE-627 rakwb eng Meng, Fanfeng verfasserin aut Analysis of Quasispecies of Avain Leukosis Virus Subgroup J Using Sanger and High-throughput Sequencing 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2016 Background Avian leukosis viruses subgroup J (ALV-J) exists as a complex mixture of different, but closely related genomes named quasispecies subjected to continuous change according to the Principles of Darwinian evolution. Method The present study seeks to compare conventional Sanger sequencing with deep sequencing using MiSeq platform to study quasispecies dynamics of ALV-J. Results The accuracy and reproducibility of MiSeq sequencing was determined better than Sanger sequencing by running each experiment in duplicate. According to the mutational rate of single position and the ability to distinguish dominant quasispecies with two sequencing methods, conventional Sanger sequencing technique displayed high randomness due to few sequencing samples, while deep sequencing could reflect the composition of the quasispecies more accurately. In the mean time, the research of quasispecies via Sanger sequencing was simulated and analyzed with the aid of re-sampling strategy with replacement for 1000 times repeat from high-throughput sequencing data, which indicated that the higher antibody titer, the higher sequence entropy, the harder analyzing with the conventional Sanger sequencing, resulted in lower ratios of dominant variants. Conclusions In sum, deep sequencing is better suited for detecting rare variants comprehensively. The simulation of Sanger sequencing that we propose here will also help to standardize quasispecies researching under different selection pressure based on next-generation sequencing data. Quasispecies-Sanger sequencing-deep sequencing-simulation (dpeaa)DE-He213 Dong, Xuan aut Hu, Tao aut Liu, Yingnan aut Zhao, Yingjie aut Lv, Yanyan aut Chang, Shuang aut Zhao, Peng aut Cui, Zhizhong aut Enthalten in Virology journal London : BioMed Central, 2004 13(2016), 1 vom: 27. Juni (DE-627)394165004 (DE-600)2160640-7 1743-422X nnns volume:13 year:2016 number:1 day:27 month:06 https://dx.doi.org/10.1186/s12985-016-0559-6 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_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 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 13 2016 1 27 06
spelling	10.1186/s12985-016-0559-6 doi (DE-627)SPR029263549 (SPR)s12985-016-0559-6-e DE-627 ger DE-627 rakwb eng Meng, Fanfeng verfasserin aut Analysis of Quasispecies of Avain Leukosis Virus Subgroup J Using Sanger and High-throughput Sequencing 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2016 Background Avian leukosis viruses subgroup J (ALV-J) exists as a complex mixture of different, but closely related genomes named quasispecies subjected to continuous change according to the Principles of Darwinian evolution. Method The present study seeks to compare conventional Sanger sequencing with deep sequencing using MiSeq platform to study quasispecies dynamics of ALV-J. Results The accuracy and reproducibility of MiSeq sequencing was determined better than Sanger sequencing by running each experiment in duplicate. According to the mutational rate of single position and the ability to distinguish dominant quasispecies with two sequencing methods, conventional Sanger sequencing technique displayed high randomness due to few sequencing samples, while deep sequencing could reflect the composition of the quasispecies more accurately. In the mean time, the research of quasispecies via Sanger sequencing was simulated and analyzed with the aid of re-sampling strategy with replacement for 1000 times repeat from high-throughput sequencing data, which indicated that the higher antibody titer, the higher sequence entropy, the harder analyzing with the conventional Sanger sequencing, resulted in lower ratios of dominant variants. Conclusions In sum, deep sequencing is better suited for detecting rare variants comprehensively. The simulation of Sanger sequencing that we propose here will also help to standardize quasispecies researching under different selection pressure based on next-generation sequencing data. Quasispecies-Sanger sequencing-deep sequencing-simulation (dpeaa)DE-He213 Dong, Xuan aut Hu, Tao aut Liu, Yingnan aut Zhao, Yingjie aut Lv, Yanyan aut Chang, Shuang aut Zhao, Peng aut Cui, Zhizhong aut Enthalten in Virology journal London : BioMed Central, 2004 13(2016), 1 vom: 27. Juni (DE-627)394165004 (DE-600)2160640-7 1743-422X nnns volume:13 year:2016 number:1 day:27 month:06 https://dx.doi.org/10.1186/s12985-016-0559-6 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_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 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 13 2016 1 27 06
allfields_unstemmed	10.1186/s12985-016-0559-6 doi (DE-627)SPR029263549 (SPR)s12985-016-0559-6-e DE-627 ger DE-627 rakwb eng Meng, Fanfeng verfasserin aut Analysis of Quasispecies of Avain Leukosis Virus Subgroup J Using Sanger and High-throughput Sequencing 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2016 Background Avian leukosis viruses subgroup J (ALV-J) exists as a complex mixture of different, but closely related genomes named quasispecies subjected to continuous change according to the Principles of Darwinian evolution. Method The present study seeks to compare conventional Sanger sequencing with deep sequencing using MiSeq platform to study quasispecies dynamics of ALV-J. Results The accuracy and reproducibility of MiSeq sequencing was determined better than Sanger sequencing by running each experiment in duplicate. According to the mutational rate of single position and the ability to distinguish dominant quasispecies with two sequencing methods, conventional Sanger sequencing technique displayed high randomness due to few sequencing samples, while deep sequencing could reflect the composition of the quasispecies more accurately. In the mean time, the research of quasispecies via Sanger sequencing was simulated and analyzed with the aid of re-sampling strategy with replacement for 1000 times repeat from high-throughput sequencing data, which indicated that the higher antibody titer, the higher sequence entropy, the harder analyzing with the conventional Sanger sequencing, resulted in lower ratios of dominant variants. Conclusions In sum, deep sequencing is better suited for detecting rare variants comprehensively. The simulation of Sanger sequencing that we propose here will also help to standardize quasispecies researching under different selection pressure based on next-generation sequencing data. Quasispecies-Sanger sequencing-deep sequencing-simulation (dpeaa)DE-He213 Dong, Xuan aut Hu, Tao aut Liu, Yingnan aut Zhao, Yingjie aut Lv, Yanyan aut Chang, Shuang aut Zhao, Peng aut Cui, Zhizhong aut Enthalten in Virology journal London : BioMed Central, 2004 13(2016), 1 vom: 27. Juni (DE-627)394165004 (DE-600)2160640-7 1743-422X nnns volume:13 year:2016 number:1 day:27 month:06 https://dx.doi.org/10.1186/s12985-016-0559-6 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_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 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 13 2016 1 27 06
allfieldsGer	10.1186/s12985-016-0559-6 doi (DE-627)SPR029263549 (SPR)s12985-016-0559-6-e DE-627 ger DE-627 rakwb eng Meng, Fanfeng verfasserin aut Analysis of Quasispecies of Avain Leukosis Virus Subgroup J Using Sanger and High-throughput Sequencing 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2016 Background Avian leukosis viruses subgroup J (ALV-J) exists as a complex mixture of different, but closely related genomes named quasispecies subjected to continuous change according to the Principles of Darwinian evolution. Method The present study seeks to compare conventional Sanger sequencing with deep sequencing using MiSeq platform to study quasispecies dynamics of ALV-J. Results The accuracy and reproducibility of MiSeq sequencing was determined better than Sanger sequencing by running each experiment in duplicate. According to the mutational rate of single position and the ability to distinguish dominant quasispecies with two sequencing methods, conventional Sanger sequencing technique displayed high randomness due to few sequencing samples, while deep sequencing could reflect the composition of the quasispecies more accurately. In the mean time, the research of quasispecies via Sanger sequencing was simulated and analyzed with the aid of re-sampling strategy with replacement for 1000 times repeat from high-throughput sequencing data, which indicated that the higher antibody titer, the higher sequence entropy, the harder analyzing with the conventional Sanger sequencing, resulted in lower ratios of dominant variants. Conclusions In sum, deep sequencing is better suited for detecting rare variants comprehensively. The simulation of Sanger sequencing that we propose here will also help to standardize quasispecies researching under different selection pressure based on next-generation sequencing data. Quasispecies-Sanger sequencing-deep sequencing-simulation (dpeaa)DE-He213 Dong, Xuan aut Hu, Tao aut Liu, Yingnan aut Zhao, Yingjie aut Lv, Yanyan aut Chang, Shuang aut Zhao, Peng aut Cui, Zhizhong aut Enthalten in Virology journal London : BioMed Central, 2004 13(2016), 1 vom: 27. Juni (DE-627)394165004 (DE-600)2160640-7 1743-422X nnns volume:13 year:2016 number:1 day:27 month:06 https://dx.doi.org/10.1186/s12985-016-0559-6 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_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 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 13 2016 1 27 06
allfieldsSound	10.1186/s12985-016-0559-6 doi (DE-627)SPR029263549 (SPR)s12985-016-0559-6-e DE-627 ger DE-627 rakwb eng Meng, Fanfeng verfasserin aut Analysis of Quasispecies of Avain Leukosis Virus Subgroup J Using Sanger and High-throughput Sequencing 2016 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Author(s). 2016 Background Avian leukosis viruses subgroup J (ALV-J) exists as a complex mixture of different, but closely related genomes named quasispecies subjected to continuous change according to the Principles of Darwinian evolution. Method The present study seeks to compare conventional Sanger sequencing with deep sequencing using MiSeq platform to study quasispecies dynamics of ALV-J. Results The accuracy and reproducibility of MiSeq sequencing was determined better than Sanger sequencing by running each experiment in duplicate. According to the mutational rate of single position and the ability to distinguish dominant quasispecies with two sequencing methods, conventional Sanger sequencing technique displayed high randomness due to few sequencing samples, while deep sequencing could reflect the composition of the quasispecies more accurately. In the mean time, the research of quasispecies via Sanger sequencing was simulated and analyzed with the aid of re-sampling strategy with replacement for 1000 times repeat from high-throughput sequencing data, which indicated that the higher antibody titer, the higher sequence entropy, the harder analyzing with the conventional Sanger sequencing, resulted in lower ratios of dominant variants. Conclusions In sum, deep sequencing is better suited for detecting rare variants comprehensively. The simulation of Sanger sequencing that we propose here will also help to standardize quasispecies researching under different selection pressure based on next-generation sequencing data. Quasispecies-Sanger sequencing-deep sequencing-simulation (dpeaa)DE-He213 Dong, Xuan aut Hu, Tao aut Liu, Yingnan aut Zhao, Yingjie aut Lv, Yanyan aut Chang, Shuang aut Zhao, Peng aut Cui, Zhizhong aut Enthalten in Virology journal London : BioMed Central, 2004 13(2016), 1 vom: 27. Juni (DE-627)394165004 (DE-600)2160640-7 1743-422X nnns volume:13 year:2016 number:1 day:27 month:06 https://dx.doi.org/10.1186/s12985-016-0559-6 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_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 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 13 2016 1 27 06
language	English
source	Enthalten in Virology journal 13(2016), 1 vom: 27. Juni volume:13 year:2016 number:1 day:27 month:06
sourceStr	Enthalten in Virology journal 13(2016), 1 vom: 27. Juni volume:13 year:2016 number:1 day:27 month:06
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author	Meng, Fanfeng
spellingShingle	Meng, Fanfeng misc Quasispecies-Sanger sequencing-deep sequencing-simulation Analysis of Quasispecies of Avain Leukosis Virus Subgroup J Using Sanger and High-throughput Sequencing
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topic_title	Analysis of Quasispecies of Avain Leukosis Virus Subgroup J Using Sanger and High-throughput Sequencing Quasispecies-Sanger sequencing-deep sequencing-simulation (dpeaa)DE-He213
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title	Analysis of Quasispecies of Avain Leukosis Virus Subgroup J Using Sanger and High-throughput Sequencing
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title_full	Analysis of Quasispecies of Avain Leukosis Virus Subgroup J Using Sanger and High-throughput Sequencing
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author_browse	Meng, Fanfeng Dong, Xuan Hu, Tao Liu, Yingnan Zhao, Yingjie Lv, Yanyan Chang, Shuang Zhao, Peng Cui, Zhizhong
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title_sort	analysis of quasispecies of avain leukosis virus subgroup j using sanger and high-throughput sequencing
title_auth	Analysis of Quasispecies of Avain Leukosis Virus Subgroup J Using Sanger and High-throughput Sequencing
abstract	Background Avian leukosis viruses subgroup J (ALV-J) exists as a complex mixture of different, but closely related genomes named quasispecies subjected to continuous change according to the Principles of Darwinian evolution. Method The present study seeks to compare conventional Sanger sequencing with deep sequencing using MiSeq platform to study quasispecies dynamics of ALV-J. Results The accuracy and reproducibility of MiSeq sequencing was determined better than Sanger sequencing by running each experiment in duplicate. According to the mutational rate of single position and the ability to distinguish dominant quasispecies with two sequencing methods, conventional Sanger sequencing technique displayed high randomness due to few sequencing samples, while deep sequencing could reflect the composition of the quasispecies more accurately. In the mean time, the research of quasispecies via Sanger sequencing was simulated and analyzed with the aid of re-sampling strategy with replacement for 1000 times repeat from high-throughput sequencing data, which indicated that the higher antibody titer, the higher sequence entropy, the harder analyzing with the conventional Sanger sequencing, resulted in lower ratios of dominant variants. Conclusions In sum, deep sequencing is better suited for detecting rare variants comprehensively. The simulation of Sanger sequencing that we propose here will also help to standardize quasispecies researching under different selection pressure based on next-generation sequencing data. © The Author(s). 2016
abstractGer	Background Avian leukosis viruses subgroup J (ALV-J) exists as a complex mixture of different, but closely related genomes named quasispecies subjected to continuous change according to the Principles of Darwinian evolution. Method The present study seeks to compare conventional Sanger sequencing with deep sequencing using MiSeq platform to study quasispecies dynamics of ALV-J. Results The accuracy and reproducibility of MiSeq sequencing was determined better than Sanger sequencing by running each experiment in duplicate. According to the mutational rate of single position and the ability to distinguish dominant quasispecies with two sequencing methods, conventional Sanger sequencing technique displayed high randomness due to few sequencing samples, while deep sequencing could reflect the composition of the quasispecies more accurately. In the mean time, the research of quasispecies via Sanger sequencing was simulated and analyzed with the aid of re-sampling strategy with replacement for 1000 times repeat from high-throughput sequencing data, which indicated that the higher antibody titer, the higher sequence entropy, the harder analyzing with the conventional Sanger sequencing, resulted in lower ratios of dominant variants. Conclusions In sum, deep sequencing is better suited for detecting rare variants comprehensively. The simulation of Sanger sequencing that we propose here will also help to standardize quasispecies researching under different selection pressure based on next-generation sequencing data. © The Author(s). 2016
abstract_unstemmed	Background Avian leukosis viruses subgroup J (ALV-J) exists as a complex mixture of different, but closely related genomes named quasispecies subjected to continuous change according to the Principles of Darwinian evolution. Method The present study seeks to compare conventional Sanger sequencing with deep sequencing using MiSeq platform to study quasispecies dynamics of ALV-J. Results The accuracy and reproducibility of MiSeq sequencing was determined better than Sanger sequencing by running each experiment in duplicate. According to the mutational rate of single position and the ability to distinguish dominant quasispecies with two sequencing methods, conventional Sanger sequencing technique displayed high randomness due to few sequencing samples, while deep sequencing could reflect the composition of the quasispecies more accurately. In the mean time, the research of quasispecies via Sanger sequencing was simulated and analyzed with the aid of re-sampling strategy with replacement for 1000 times repeat from high-throughput sequencing data, which indicated that the higher antibody titer, the higher sequence entropy, the harder analyzing with the conventional Sanger sequencing, resulted in lower ratios of dominant variants. Conclusions In sum, deep sequencing is better suited for detecting rare variants comprehensively. The simulation of Sanger sequencing that we propose here will also help to standardize quasispecies researching under different selection pressure based on next-generation sequencing data. © The Author(s). 2016
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title_short	Analysis of Quasispecies of Avain Leukosis Virus Subgroup J Using Sanger and High-throughput Sequencing
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Method The present study seeks to compare conventional Sanger sequencing with deep sequencing using MiSeq platform to study quasispecies dynamics of ALV-J. Results The accuracy and reproducibility of MiSeq sequencing was determined better than Sanger sequencing by running each experiment in duplicate. According to the mutational rate of single position and the ability to distinguish dominant quasispecies with two sequencing methods, conventional Sanger sequencing technique displayed high randomness due to few sequencing samples, while deep sequencing could reflect the composition of the quasispecies more accurately. In the mean time, the research of quasispecies via Sanger sequencing was simulated and analyzed with the aid of re-sampling strategy with replacement for 1000 times repeat from high-throughput sequencing data, which indicated that the higher antibody titer, the higher sequence entropy, the harder analyzing with the conventional Sanger sequencing, resulted in lower ratios of dominant variants. Conclusions In sum, deep sequencing is better suited for detecting rare variants comprehensively. The simulation of Sanger sequencing that we propose here will also help to standardize quasispecies researching under different selection pressure based on next-generation sequencing data.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Quasispecies-Sanger sequencing-deep sequencing-simulation</subfield><subfield code="7">(dpeaa)DE-He213</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Dong, Xuan</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Hu, Tao</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Liu, Yingnan</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Zhao, Yingjie</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Lv, Yanyan</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Chang, Shuang</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Zhao, Peng</subfield><subfield code="4">aut</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Cui, Zhizhong</subfield><subfield code="4">aut</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Virology journal</subfield><subfield code="d">London : BioMed Central, 2004</subfield><subfield code="g">13(2016), 1 vom: 27. 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Analysis of Quasispecies of Avain Leukosis Virus Subgroup J Using Sanger and High-throughput Sequencing

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