Title |
Combination of novel and public RNA-seq datasets to generate an mRNA expression atlas for the domestic chicken
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Published in |
BMC Genomics, August 2018
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DOI | 10.1186/s12864-018-4972-7 |
Pubmed ID | |
Authors |
Stephen J. Bush, Lucy Freem, Amanda J. MacCallum, Jenny O’Dell, Chunlei Wu, Cyrus Afrasiabi, Androniki Psifidi, Mark P. Stevens, Jacqueline Smith, Kim M. Summers, David A. Hume |
Abstract |
The domestic chicken (Gallus gallus) is widely used as a model in developmental biology and is also an important livestock species. We describe a novel approach to data integration to generate an mRNA expression atlas for the chicken spanning major tissue types and developmental stages, using a diverse range of publicly-archived RNA-seq datasets and new data derived from immune cells and tissues. Randomly down-sampling RNA-seq datasets to a common depth and quantifying expression against a reference transcriptome using the mRNA quantitation tool Kallisto ensured that disparate datasets explored comparable transcriptomic space. The network analysis tool Graphia was used to extract clusters of co-expressed genes from the resulting expression atlas, many of which were tissue or cell-type restricted, contained transcription factors that have previously been implicated in their regulation, or were otherwise associated with biological processes, such as the cell cycle. The atlas provides a resource for the functional annotation of genes that currently have only a locus ID. We cross-referenced the RNA-seq atlas to a publicly available embryonic Cap Analysis of Gene Expression (CAGE) dataset to infer the developmental time course of organ systems, and to identify a signature of the expansion of tissue macrophage populations during development. Expression profiles obtained from public RNA-seq datasets - despite being generated by different laboratories using different methodologies - can be made comparable to each other. This meta-analytic approach to RNA-seq can be extended with new datasets from novel tissues, and is applicable to any species. |
X Demographics
Geographical breakdown
Country | Count | As % |
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United Kingdom | 5 | 42% |
United States | 1 | 8% |
Unknown | 6 | 50% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 6 | 50% |
Scientists | 6 | 50% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 41 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 8 | 20% |
Researcher | 6 | 15% |
Student > Bachelor | 5 | 12% |
Student > Master | 4 | 10% |
Student > Postgraduate | 2 | 5% |
Other | 5 | 12% |
Unknown | 11 | 27% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 12 | 29% |
Biochemistry, Genetics and Molecular Biology | 10 | 24% |
Computer Science | 2 | 5% |
Medicine and Dentistry | 2 | 5% |
Veterinary Science and Veterinary Medicine | 1 | 2% |
Other | 4 | 10% |
Unknown | 10 | 24% |