publication . Article . 2017

Monitoring transcription initiation activities in rat and dog

Lizio, Marina; Mukarram, Abdul Kadir; Ohno, Mizuho; Watanabe, Shoko; Itoh, Masayoshi; Hasegawa, Akira; Lassmann, Timo; Severin, Jessica; Harshbarger, Jayson; Abugessaisa, Imad; ...
Open Access English
  • Published: 01 Nov 2017 Journal: Scientific Data, volume 4 (eissn: 2052-4463, Copyright policy)
  • Publisher: Nature Publishing Group
Abstract
The promoter landscape of several non-human model organisms is far from complete. As a part of FANTOM5 data collection, we generated 13 profiles of transcription initiation activities in dog and rat aortic smooth muscle cells, mesenchymal stem cells and hepatocytes by employing CAGE (Cap Analysis of Gene Expression) technology combined with single molecule sequencing. Our analyses show that the CAGE profiles recapitulate known transcription start sites (TSSs) consistently, in addition to uncover novel TSSs. Our dataset can be thus used with high confidence to support gene annotation in dog and rat species. We identified 28,497 and 23,147 CAGE peaks, or promoter ...
Subjects
free text keywords: Computational platforms and environments, Research data, Data processing, Transcriptomics, Data Descriptor
47 references, page 1 of 4

1. Tomato Genome, C. The tomato genome sequence provides insights into fleshy fruit evolution. Nature 485, 635-641 (2012).

2. Zeng, X. et al. The draft genome of Tibetan hulless barley reveals adaptive patterns to the high stressful Tibetan Plateau. Proc Natl Acad Sci USA 112, 1095-1100 (2015).

3. Conesa, A. et al. A survey of best practices for RNA-seq data analysis. Genome Biol 17, 13 (2016).

4. Engstrom, P. G. et al. Systematic evaluation of spliced alignment programs for RNA-seq data. Nat Methods 10, 1185-1191 (2013).

5. Fang, Z. & Cui, X. Design and validation issues in RNA-seq experiments. Brief Bioinform 12, 280-287 (2011).

6. Robert, C. & Watson, M. Errors in RNA-Seq quantification affect genes of relevance to human disease. Genome Biol 16, 177 (2015).

7. Alfoldi, J. & Lindblad-Toh, K. Comparative genomics as a tool to understand evolution and disease. Genome Res 23, 1063-1068 (2013). [OpenAIRE]

8. Takahashi, H., Kato, S., Murata, M. & Carninci, P. CAGE (cap analysis of gene expression): a protocol for the detection of promoter and transcriptional networks. Methods Mol Biol 786, 181-200 (2012).

9. de Hoon, M., Shin, J. W. & Carninci, P. Paradigm shifts in genomics through the FANTOM projects. Mamm Genome 26, 391-402 (2015). [OpenAIRE]

10. Wang, Z., Gerstein, M. & Snyder, M. RNA-Seq: a revolutionary tool for transcriptomics. Nat Rev Genet 10, 57-63 (2009).

11. Andersson, R. et al. An atlas of active enhancers across human cell types and tissues. Nature 507, 455-461 (2014).

12. Hon, C. C. et al. An atlas of human long non-coding RNAs with accurate 5' ends. Nature 543, 199-204 (2017).

13. Carninci, P. et al. The transcriptional landscape of the mammalian genome. Science 309, 1559-1563 (2005).

14. Consortium, F.et al. The transcriptional network that controls growth arrest and differentiation in a human myeloid leukemia cell line. Nat Genet 41, 553-562 (2009).

15. Ravasi, T. et al. An atlas of combinatorial transcriptional regulation in mouse and man. Cell 140, 744-752 (2010). [OpenAIRE]

47 references, page 1 of 4
Abstract
The promoter landscape of several non-human model organisms is far from complete. As a part of FANTOM5 data collection, we generated 13 profiles of transcription initiation activities in dog and rat aortic smooth muscle cells, mesenchymal stem cells and hepatocytes by employing CAGE (Cap Analysis of Gene Expression) technology combined with single molecule sequencing. Our analyses show that the CAGE profiles recapitulate known transcription start sites (TSSs) consistently, in addition to uncover novel TSSs. Our dataset can be thus used with high confidence to support gene annotation in dog and rat species. We identified 28,497 and 23,147 CAGE peaks, or promoter ...
Subjects
free text keywords: Computational platforms and environments, Research data, Data processing, Transcriptomics, Data Descriptor
47 references, page 1 of 4

1. Tomato Genome, C. The tomato genome sequence provides insights into fleshy fruit evolution. Nature 485, 635-641 (2012).

2. Zeng, X. et al. The draft genome of Tibetan hulless barley reveals adaptive patterns to the high stressful Tibetan Plateau. Proc Natl Acad Sci USA 112, 1095-1100 (2015).

3. Conesa, A. et al. A survey of best practices for RNA-seq data analysis. Genome Biol 17, 13 (2016).

4. Engstrom, P. G. et al. Systematic evaluation of spliced alignment programs for RNA-seq data. Nat Methods 10, 1185-1191 (2013).

5. Fang, Z. & Cui, X. Design and validation issues in RNA-seq experiments. Brief Bioinform 12, 280-287 (2011).

6. Robert, C. & Watson, M. Errors in RNA-Seq quantification affect genes of relevance to human disease. Genome Biol 16, 177 (2015).

7. Alfoldi, J. & Lindblad-Toh, K. Comparative genomics as a tool to understand evolution and disease. Genome Res 23, 1063-1068 (2013). [OpenAIRE]

8. Takahashi, H., Kato, S., Murata, M. & Carninci, P. CAGE (cap analysis of gene expression): a protocol for the detection of promoter and transcriptional networks. Methods Mol Biol 786, 181-200 (2012).

9. de Hoon, M., Shin, J. W. & Carninci, P. Paradigm shifts in genomics through the FANTOM projects. Mamm Genome 26, 391-402 (2015). [OpenAIRE]

10. Wang, Z., Gerstein, M. & Snyder, M. RNA-Seq: a revolutionary tool for transcriptomics. Nat Rev Genet 10, 57-63 (2009).

11. Andersson, R. et al. An atlas of active enhancers across human cell types and tissues. Nature 507, 455-461 (2014).

12. Hon, C. C. et al. An atlas of human long non-coding RNAs with accurate 5' ends. Nature 543, 199-204 (2017).

13. Carninci, P. et al. The transcriptional landscape of the mammalian genome. Science 309, 1559-1563 (2005).

14. Consortium, F.et al. The transcriptional network that controls growth arrest and differentiation in a human myeloid leukemia cell line. Nat Genet 41, 553-562 (2009).

15. Ravasi, T. et al. An atlas of combinatorial transcriptional regulation in mouse and man. Cell 140, 744-752 (2010). [OpenAIRE]

47 references, page 1 of 4
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publication . Article . 2017

Monitoring transcription initiation activities in rat and dog

Lizio, Marina; Mukarram, Abdul Kadir; Ohno, Mizuho; Watanabe, Shoko; Itoh, Masayoshi; Hasegawa, Akira; Lassmann, Timo; Severin, Jessica; Harshbarger, Jayson; Abugessaisa, Imad; ...