Abstract
Recently, the Mouse ENCODE Consortium reported that comparative gene expression data from human and mouse tend to cluster more by species rather than by tissue. This observation was surprising, as it contradicted much of the comparative gene regulatory data collected previously, as well as the common notion that major developmental pathways are highly conserved across a wide range of species, in particular across mammals. Here we show that the Mouse ENCODE gene expression data were collected using a flawed study design, which confounded sequencing batch (namely, the assignment of samples to sequencing flowcells and lanes) with species. When we account for the batch effect, the corrected comparative gene expression data from human and mouse tend to cluster by tissue, not by species.
Highlights
The mouse ENCODE Consortium has collected multiple types of genomic and functional data in order to better understand the potential utility of the mouse as a model system for biomedical research
The previously published data consist of RNA sequencing from ENCODE, the Illumina Human BodyMap 2.0, and the Roadmap Epigenomics Mapping Consortium
In these previously collected data sets, human and mouse samples were analyzed by different labs at different times, such that there is a clear batch effect that is confounded with species
Summary
The mouse ENCODE Consortium has collected multiple types of genomic and functional data in order to better understand the potential utility of the mouse as a model system for biomedical research. To study gene expression levels, the Consortium collected RNA sequencing data from multiple tissues from human and mouse. Their comparative analysis revealed that gene expression patterns tend to support clustering of the data by species, rather than by tissue (Figure 2a in reference 1). This pattern was confirmed and discussed in greater detail in a companion paper by Lin et al.[2], which acknowledged that this observation is somewhat unexpected. Lin et al proposed that previous studies might have been biased in their focus on a few ‘specialized’ tissues that tend to express the largest number of ‘tissue-specific genes’, while the overall pattern supports less tissue specificity
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