Determination of dosage compensation of the mammalian X chromosome by RNA-seq is dependent on analytical approach

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Abstract

Background: An enduring question surrounding sex chromosome evolution is whether effective hemizygosity in the heterogametic sex leads inevitably to dosage compensation of sex-linked genes, and whether this compensation has been observed in a variety of organisms. Incongruence in the conclusions reached in some recent reports has been attributed to different high-throughput approaches to transcriptome analysis. However, recent reports each utilizing RNA-seq to gauge X-linked gene expression relative to autosomal gene expression also arrived at diametrically opposed conclusions regarding X chromosome dosage compensation in mammals.Results: Here we analyze RNA-seq data from X-monosomic female human and mouse tissues, which are uncomplicated by genes that escape X-inactivation, as well as published RNA-seq data to describe relative X expression (RXE). We find that the determination of RXE is highly dependent upon a variety of computational, statistical and biological assumptions underlying RNA-seq analysis. Parameters implemented in short-read mapping programs, choice of reference genome annotation, expression data distribution, tissue source for RNA and RNA-seq library construction method have profound effects on comparing expression levels across chromosomes.Conclusions: Our analysis shows that the high number of paralogous gene families on the mammalian X chromosome relative to autosomes contributes to the ambiguity in RXE calculations, RNA-seq analysis that takes into account that single- and multi-copy genes are compensated differently supports the conclusion that, in many somatic tissues, the mammalian X is up-regulated compared to the autosomes. © 2013 Jue et al.; licensee BioMed Central Ltd.

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Jue, N. K., Murphy, M. B., Kasowitz, S. D., Qureshi, S. M., Obergfell, C. J., Elsisi, S., … O’Neill, M. J. (2013). Determination of dosage compensation of the mammalian X chromosome by RNA-seq is dependent on analytical approach. BMC Genomics, 14(1). https://doi.org/10.1186/1471-2164-14-150

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