Combination of novel and public RNA-seq datasets to generate an mRNA expression atlas for the domestic chicken

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

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish
Article number594 (2018)
JournalBMC Genomics
Volume19
Issue number1
DOIs
Publication statusPublished - 7 Aug 2018

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