A powerful method for transcriptional profiling of specific cell types in eukaryotes: laser-assisted microdissection and RNA sequencing.

The acquisition of distinct cell fates is central to the development of multicellular organisms and is largely mediated by gene expression patterns specific to individual cells and tissues. A spatially and temporally resolved analysis of gene expression facilitates the elucidation of transcriptional...
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Gespeichert in:

Autor*in:	Marc W Schmid [verfasserIn] Anja Schmidt [verfasserIn] Ulrich C Klostermeier [verfasserIn] Matthias Barann [verfasserIn] Philip Rosenstiel [verfasserIn] Ueli Grossniklaus [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2012

Übergeordnetes Werk:	In: PLoS ONE - Public Library of Science (PLoS), 2007, 7(2012), 1, p e29685
Übergeordnetes Werk:	volume:7 ; year:2012 ; number:1, p e29685

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1371/journal.pone.0029685

Katalog-ID:	DOAJ062617931

Internformat


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520			\|a The acquisition of distinct cell fates is central to the development of multicellular organisms and is largely mediated by gene expression patterns specific to individual cells and tissues. A spatially and temporally resolved analysis of gene expression facilitates the elucidation of transcriptional networks linked to cellular identity and function. We present an approach that allows cell type-specific transcriptional profiling of distinct target cells, which are rare and difficult to access, with unprecedented sensitivity and resolution. We combined laser-assisted microdissection (LAM), linear amplification starting from <1 ng of total RNA, and RNA-sequencing (RNA-Seq). As a model we used the central cell of the Arabidopsis thaliana female gametophyte, one of the female gametes harbored in the reproductive organs of the flower. We estimated the number of expressed genes to be more than twice the number reported previously in a study using LAM and ATH1 microarrays, and identified several classes of genes that were systematically underrepresented in the transcriptome measured with the ATH1 microarray. Among them are many genes that are likely to be important for developmental processes and specific cellular functions. In addition, we identified several intergenic regions, which are likely to be transcribed, and describe a considerable fraction of reads mapping to introns and regions flanking annotated loci, which may represent alternative transcript isoforms. Finally, we performed a de novo assembly of the transcriptome and show that the method is suitable for studying individual cell types of organisms lacking reference sequence information, demonstrating that this approach can be applied to most eukaryotic organisms.
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publishDate	2012
allfields	10.1371/journal.pone.0029685 doi (DE-627)DOAJ062617931 (DE-599)DOAJ08c9b9f237244bc0a84388baf343ebe3 DE-627 ger DE-627 rakwb eng Marc W Schmid verfasserin aut A powerful method for transcriptional profiling of specific cell types in eukaryotes: laser-assisted microdissection and RNA sequencing. 2012 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The acquisition of distinct cell fates is central to the development of multicellular organisms and is largely mediated by gene expression patterns specific to individual cells and tissues. A spatially and temporally resolved analysis of gene expression facilitates the elucidation of transcriptional networks linked to cellular identity and function. We present an approach that allows cell type-specific transcriptional profiling of distinct target cells, which are rare and difficult to access, with unprecedented sensitivity and resolution. We combined laser-assisted microdissection (LAM), linear amplification starting from <1 ng of total RNA, and RNA-sequencing (RNA-Seq). As a model we used the central cell of the Arabidopsis thaliana female gametophyte, one of the female gametes harbored in the reproductive organs of the flower. We estimated the number of expressed genes to be more than twice the number reported previously in a study using LAM and ATH1 microarrays, and identified several classes of genes that were systematically underrepresented in the transcriptome measured with the ATH1 microarray. Among them are many genes that are likely to be important for developmental processes and specific cellular functions. In addition, we identified several intergenic regions, which are likely to be transcribed, and describe a considerable fraction of reads mapping to introns and regions flanking annotated loci, which may represent alternative transcript isoforms. Finally, we performed a de novo assembly of the transcriptome and show that the method is suitable for studying individual cell types of organisms lacking reference sequence information, demonstrating that this approach can be applied to most eukaryotic organisms. Medicine R Science Q Anja Schmidt verfasserin aut Ulrich C Klostermeier verfasserin aut Matthias Barann verfasserin aut Philip Rosenstiel verfasserin aut Ueli Grossniklaus verfasserin aut In PLoS ONE Public Library of Science (PLoS), 2007 7(2012), 1, p e29685 (DE-627)523574592 (DE-600)2267670-3 19326203 nnns volume:7 year:2012 number:1, p e29685 https://doi.org/10.1371/journal.pone.0029685 kostenfrei https://doaj.org/article/08c9b9f237244bc0a84388baf343ebe3 kostenfrei https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22291893/?tool=EBI kostenfrei https://doaj.org/toc/1932-6203 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_34 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_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_235 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 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_2522 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_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 7 2012 1, p e29685
spelling	10.1371/journal.pone.0029685 doi (DE-627)DOAJ062617931 (DE-599)DOAJ08c9b9f237244bc0a84388baf343ebe3 DE-627 ger DE-627 rakwb eng Marc W Schmid verfasserin aut A powerful method for transcriptional profiling of specific cell types in eukaryotes: laser-assisted microdissection and RNA sequencing. 2012 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The acquisition of distinct cell fates is central to the development of multicellular organisms and is largely mediated by gene expression patterns specific to individual cells and tissues. A spatially and temporally resolved analysis of gene expression facilitates the elucidation of transcriptional networks linked to cellular identity and function. We present an approach that allows cell type-specific transcriptional profiling of distinct target cells, which are rare and difficult to access, with unprecedented sensitivity and resolution. We combined laser-assisted microdissection (LAM), linear amplification starting from <1 ng of total RNA, and RNA-sequencing (RNA-Seq). As a model we used the central cell of the Arabidopsis thaliana female gametophyte, one of the female gametes harbored in the reproductive organs of the flower. We estimated the number of expressed genes to be more than twice the number reported previously in a study using LAM and ATH1 microarrays, and identified several classes of genes that were systematically underrepresented in the transcriptome measured with the ATH1 microarray. Among them are many genes that are likely to be important for developmental processes and specific cellular functions. In addition, we identified several intergenic regions, which are likely to be transcribed, and describe a considerable fraction of reads mapping to introns and regions flanking annotated loci, which may represent alternative transcript isoforms. Finally, we performed a de novo assembly of the transcriptome and show that the method is suitable for studying individual cell types of organisms lacking reference sequence information, demonstrating that this approach can be applied to most eukaryotic organisms. Medicine R Science Q Anja Schmidt verfasserin aut Ulrich C Klostermeier verfasserin aut Matthias Barann verfasserin aut Philip Rosenstiel verfasserin aut Ueli Grossniklaus verfasserin aut In PLoS ONE Public Library of Science (PLoS), 2007 7(2012), 1, p e29685 (DE-627)523574592 (DE-600)2267670-3 19326203 nnns volume:7 year:2012 number:1, p e29685 https://doi.org/10.1371/journal.pone.0029685 kostenfrei https://doaj.org/article/08c9b9f237244bc0a84388baf343ebe3 kostenfrei https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22291893/?tool=EBI kostenfrei https://doaj.org/toc/1932-6203 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_34 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_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_235 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 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_2522 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_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 7 2012 1, p e29685
allfields_unstemmed	10.1371/journal.pone.0029685 doi (DE-627)DOAJ062617931 (DE-599)DOAJ08c9b9f237244bc0a84388baf343ebe3 DE-627 ger DE-627 rakwb eng Marc W Schmid verfasserin aut A powerful method for transcriptional profiling of specific cell types in eukaryotes: laser-assisted microdissection and RNA sequencing. 2012 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The acquisition of distinct cell fates is central to the development of multicellular organisms and is largely mediated by gene expression patterns specific to individual cells and tissues. A spatially and temporally resolved analysis of gene expression facilitates the elucidation of transcriptional networks linked to cellular identity and function. We present an approach that allows cell type-specific transcriptional profiling of distinct target cells, which are rare and difficult to access, with unprecedented sensitivity and resolution. We combined laser-assisted microdissection (LAM), linear amplification starting from <1 ng of total RNA, and RNA-sequencing (RNA-Seq). As a model we used the central cell of the Arabidopsis thaliana female gametophyte, one of the female gametes harbored in the reproductive organs of the flower. We estimated the number of expressed genes to be more than twice the number reported previously in a study using LAM and ATH1 microarrays, and identified several classes of genes that were systematically underrepresented in the transcriptome measured with the ATH1 microarray. Among them are many genes that are likely to be important for developmental processes and specific cellular functions. In addition, we identified several intergenic regions, which are likely to be transcribed, and describe a considerable fraction of reads mapping to introns and regions flanking annotated loci, which may represent alternative transcript isoforms. Finally, we performed a de novo assembly of the transcriptome and show that the method is suitable for studying individual cell types of organisms lacking reference sequence information, demonstrating that this approach can be applied to most eukaryotic organisms. Medicine R Science Q Anja Schmidt verfasserin aut Ulrich C Klostermeier verfasserin aut Matthias Barann verfasserin aut Philip Rosenstiel verfasserin aut Ueli Grossniklaus verfasserin aut In PLoS ONE Public Library of Science (PLoS), 2007 7(2012), 1, p e29685 (DE-627)523574592 (DE-600)2267670-3 19326203 nnns volume:7 year:2012 number:1, p e29685 https://doi.org/10.1371/journal.pone.0029685 kostenfrei https://doaj.org/article/08c9b9f237244bc0a84388baf343ebe3 kostenfrei https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22291893/?tool=EBI kostenfrei https://doaj.org/toc/1932-6203 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_34 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_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_235 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 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_2522 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_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 7 2012 1, p e29685
allfieldsGer	10.1371/journal.pone.0029685 doi (DE-627)DOAJ062617931 (DE-599)DOAJ08c9b9f237244bc0a84388baf343ebe3 DE-627 ger DE-627 rakwb eng Marc W Schmid verfasserin aut A powerful method for transcriptional profiling of specific cell types in eukaryotes: laser-assisted microdissection and RNA sequencing. 2012 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The acquisition of distinct cell fates is central to the development of multicellular organisms and is largely mediated by gene expression patterns specific to individual cells and tissues. A spatially and temporally resolved analysis of gene expression facilitates the elucidation of transcriptional networks linked to cellular identity and function. We present an approach that allows cell type-specific transcriptional profiling of distinct target cells, which are rare and difficult to access, with unprecedented sensitivity and resolution. We combined laser-assisted microdissection (LAM), linear amplification starting from <1 ng of total RNA, and RNA-sequencing (RNA-Seq). As a model we used the central cell of the Arabidopsis thaliana female gametophyte, one of the female gametes harbored in the reproductive organs of the flower. We estimated the number of expressed genes to be more than twice the number reported previously in a study using LAM and ATH1 microarrays, and identified several classes of genes that were systematically underrepresented in the transcriptome measured with the ATH1 microarray. Among them are many genes that are likely to be important for developmental processes and specific cellular functions. In addition, we identified several intergenic regions, which are likely to be transcribed, and describe a considerable fraction of reads mapping to introns and regions flanking annotated loci, which may represent alternative transcript isoforms. Finally, we performed a de novo assembly of the transcriptome and show that the method is suitable for studying individual cell types of organisms lacking reference sequence information, demonstrating that this approach can be applied to most eukaryotic organisms. Medicine R Science Q Anja Schmidt verfasserin aut Ulrich C Klostermeier verfasserin aut Matthias Barann verfasserin aut Philip Rosenstiel verfasserin aut Ueli Grossniklaus verfasserin aut In PLoS ONE Public Library of Science (PLoS), 2007 7(2012), 1, p e29685 (DE-627)523574592 (DE-600)2267670-3 19326203 nnns volume:7 year:2012 number:1, p e29685 https://doi.org/10.1371/journal.pone.0029685 kostenfrei https://doaj.org/article/08c9b9f237244bc0a84388baf343ebe3 kostenfrei https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22291893/?tool=EBI kostenfrei https://doaj.org/toc/1932-6203 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_34 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_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_235 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 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_2522 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_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 7 2012 1, p e29685
allfieldsSound	10.1371/journal.pone.0029685 doi (DE-627)DOAJ062617931 (DE-599)DOAJ08c9b9f237244bc0a84388baf343ebe3 DE-627 ger DE-627 rakwb eng Marc W Schmid verfasserin aut A powerful method for transcriptional profiling of specific cell types in eukaryotes: laser-assisted microdissection and RNA sequencing. 2012 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The acquisition of distinct cell fates is central to the development of multicellular organisms and is largely mediated by gene expression patterns specific to individual cells and tissues. A spatially and temporally resolved analysis of gene expression facilitates the elucidation of transcriptional networks linked to cellular identity and function. We present an approach that allows cell type-specific transcriptional profiling of distinct target cells, which are rare and difficult to access, with unprecedented sensitivity and resolution. We combined laser-assisted microdissection (LAM), linear amplification starting from <1 ng of total RNA, and RNA-sequencing (RNA-Seq). As a model we used the central cell of the Arabidopsis thaliana female gametophyte, one of the female gametes harbored in the reproductive organs of the flower. We estimated the number of expressed genes to be more than twice the number reported previously in a study using LAM and ATH1 microarrays, and identified several classes of genes that were systematically underrepresented in the transcriptome measured with the ATH1 microarray. Among them are many genes that are likely to be important for developmental processes and specific cellular functions. In addition, we identified several intergenic regions, which are likely to be transcribed, and describe a considerable fraction of reads mapping to introns and regions flanking annotated loci, which may represent alternative transcript isoforms. Finally, we performed a de novo assembly of the transcriptome and show that the method is suitable for studying individual cell types of organisms lacking reference sequence information, demonstrating that this approach can be applied to most eukaryotic organisms. Medicine R Science Q Anja Schmidt verfasserin aut Ulrich C Klostermeier verfasserin aut Matthias Barann verfasserin aut Philip Rosenstiel verfasserin aut Ueli Grossniklaus verfasserin aut In PLoS ONE Public Library of Science (PLoS), 2007 7(2012), 1, p e29685 (DE-627)523574592 (DE-600)2267670-3 19326203 nnns volume:7 year:2012 number:1, p e29685 https://doi.org/10.1371/journal.pone.0029685 kostenfrei https://doaj.org/article/08c9b9f237244bc0a84388baf343ebe3 kostenfrei https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22291893/?tool=EBI kostenfrei https://doaj.org/toc/1932-6203 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_34 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_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_235 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 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_2522 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_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 7 2012 1, p e29685
language	English
source	In PLoS ONE 7(2012), 1, p e29685 volume:7 year:2012 number:1, p e29685
sourceStr	In PLoS ONE 7(2012), 1, p e29685 volume:7 year:2012 number:1, p e29685
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container_title	PLoS ONE
authorswithroles_txt_mv	Marc W Schmid @@aut@@ Anja Schmidt @@aut@@ Ulrich C Klostermeier @@aut@@ Matthias Barann @@aut@@ Philip Rosenstiel @@aut@@ Ueli Grossniklaus @@aut@@
publishDateDaySort_date	2012-01-01T00:00:00Z
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id	DOAJ062617931
language_de	englisch
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author	Marc W Schmid
spellingShingle	Marc W Schmid misc Medicine misc R misc Science misc Q A powerful method for transcriptional profiling of specific cell types in eukaryotes: laser-assisted microdissection and RNA sequencing.
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topic_title	A powerful method for transcriptional profiling of specific cell types in eukaryotes: laser-assisted microdissection and RNA sequencing
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title	A powerful method for transcriptional profiling of specific cell types in eukaryotes: laser-assisted microdissection and RNA sequencing.
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title_full	A powerful method for transcriptional profiling of specific cell types in eukaryotes: laser-assisted microdissection and RNA sequencing
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author_browse	Marc W Schmid Anja Schmidt Ulrich C Klostermeier Matthias Barann Philip Rosenstiel Ueli Grossniklaus
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title_sort	powerful method for transcriptional profiling of specific cell types in eukaryotes: laser-assisted microdissection and rna sequencing
title_auth	A powerful method for transcriptional profiling of specific cell types in eukaryotes: laser-assisted microdissection and RNA sequencing.
abstract	The acquisition of distinct cell fates is central to the development of multicellular organisms and is largely mediated by gene expression patterns specific to individual cells and tissues. A spatially and temporally resolved analysis of gene expression facilitates the elucidation of transcriptional networks linked to cellular identity and function. We present an approach that allows cell type-specific transcriptional profiling of distinct target cells, which are rare and difficult to access, with unprecedented sensitivity and resolution. We combined laser-assisted microdissection (LAM), linear amplification starting from <1 ng of total RNA, and RNA-sequencing (RNA-Seq). As a model we used the central cell of the Arabidopsis thaliana female gametophyte, one of the female gametes harbored in the reproductive organs of the flower. We estimated the number of expressed genes to be more than twice the number reported previously in a study using LAM and ATH1 microarrays, and identified several classes of genes that were systematically underrepresented in the transcriptome measured with the ATH1 microarray. Among them are many genes that are likely to be important for developmental processes and specific cellular functions. In addition, we identified several intergenic regions, which are likely to be transcribed, and describe a considerable fraction of reads mapping to introns and regions flanking annotated loci, which may represent alternative transcript isoforms. Finally, we performed a de novo assembly of the transcriptome and show that the method is suitable for studying individual cell types of organisms lacking reference sequence information, demonstrating that this approach can be applied to most eukaryotic organisms.
abstractGer	The acquisition of distinct cell fates is central to the development of multicellular organisms and is largely mediated by gene expression patterns specific to individual cells and tissues. A spatially and temporally resolved analysis of gene expression facilitates the elucidation of transcriptional networks linked to cellular identity and function. We present an approach that allows cell type-specific transcriptional profiling of distinct target cells, which are rare and difficult to access, with unprecedented sensitivity and resolution. We combined laser-assisted microdissection (LAM), linear amplification starting from <1 ng of total RNA, and RNA-sequencing (RNA-Seq). As a model we used the central cell of the Arabidopsis thaliana female gametophyte, one of the female gametes harbored in the reproductive organs of the flower. We estimated the number of expressed genes to be more than twice the number reported previously in a study using LAM and ATH1 microarrays, and identified several classes of genes that were systematically underrepresented in the transcriptome measured with the ATH1 microarray. Among them are many genes that are likely to be important for developmental processes and specific cellular functions. In addition, we identified several intergenic regions, which are likely to be transcribed, and describe a considerable fraction of reads mapping to introns and regions flanking annotated loci, which may represent alternative transcript isoforms. Finally, we performed a de novo assembly of the transcriptome and show that the method is suitable for studying individual cell types of organisms lacking reference sequence information, demonstrating that this approach can be applied to most eukaryotic organisms.
abstract_unstemmed	The acquisition of distinct cell fates is central to the development of multicellular organisms and is largely mediated by gene expression patterns specific to individual cells and tissues. A spatially and temporally resolved analysis of gene expression facilitates the elucidation of transcriptional networks linked to cellular identity and function. We present an approach that allows cell type-specific transcriptional profiling of distinct target cells, which are rare and difficult to access, with unprecedented sensitivity and resolution. We combined laser-assisted microdissection (LAM), linear amplification starting from <1 ng of total RNA, and RNA-sequencing (RNA-Seq). As a model we used the central cell of the Arabidopsis thaliana female gametophyte, one of the female gametes harbored in the reproductive organs of the flower. We estimated the number of expressed genes to be more than twice the number reported previously in a study using LAM and ATH1 microarrays, and identified several classes of genes that were systematically underrepresented in the transcriptome measured with the ATH1 microarray. Among them are many genes that are likely to be important for developmental processes and specific cellular functions. In addition, we identified several intergenic regions, which are likely to be transcribed, and describe a considerable fraction of reads mapping to introns and regions flanking annotated loci, which may represent alternative transcript isoforms. Finally, we performed a de novo assembly of the transcriptome and show that the method is suitable for studying individual cell types of organisms lacking reference sequence information, demonstrating that this approach can be applied to most eukaryotic organisms.
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title_short	A powerful method for transcriptional profiling of specific cell types in eukaryotes: laser-assisted microdissection and RNA sequencing.
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A powerful method for transcriptional profiling of specific cell types in eukaryotes: laser-assisted microdissection and RNA sequencing.

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