Combination of novel and public RNA-seq datasets to generate an mRNA expression atlas for the domestic chicken
In: BMC Genomics, Jg. 19 (2018), Heft 1, S. 1-19
Online
academicJournal
Zugriff:
Background 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. Results 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. Conclusion 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.
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Combination of novel and public RNA-seq datasets to generate an mRNA expression atlas for the domestic chicken
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Autor/in / Beteiligte Person: | Bush, Stephen J. ; Freem, Lucy ; MacCallum, Amanda J. ; O’Dell, Jenny ; Wu, Chunlei ; Afrasiabi, Cyrus ; Psifidi, Androniki ; Stevens, Mark P. ; Smith, Jacqueline ; Summers, Kim M. ; Hume, David A. |
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Zeitschrift: | BMC Genomics, Jg. 19 (2018), Heft 1, S. 1-19 |
Veröffentlichung: | BMC, 2018 |
Medientyp: | academicJournal |
ISSN: | 1471-2164 (print) |
DOI: | 10.1186/s12864-018-4972-7 |
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