Abstract
Next-generation sequencing of the transcriptome (RNA-Seq) is a powerful method that allows for the quantitative determination of absolute gene expression, and can be used to investigate how these levels change in response to an experimental manipulation or disease condition. The sensitivity of this method allows one to analyze transcript levels of all expressed genes, including low abundance transcripts that encode important regulatory molecules, providing valuable insights into the global effects of experimental manipulations. However, this increased sensitivity can also make it challenging to ascertain which expression changes are biologically significant. Here, we describe a novel set of filtering criteria - based on biological insights and computational approaches - that were applied to prioritize genes for further study from an extensive number of differentially expressed transcripts in lenses lacking Smad interacting protein 1 (Sip1) obtained via RNA-Seq by Manthey and colleagues in Mechanisms of Development (Manthey et al., 2014). Notably, this workflow allowed an original list of over 7,100 statistically significant differentially expressed genes (DEGs) to be winnowed down to 190 DEGs that likely play a biologically significant role in Sip1 function during lens development. Focusing on genes whose expression was upregulated or downregulated in a manner opposite to what normally occurs during lens development, we identified 78 genes that appear to be strongly dependent on Sip1 function. From these data (GEO accession number GSE49949), it appears that Sip1 regulates multiple genes in the lens that are generally distinct from those regulated by Sip1 in other cellular contexts, including genes whose expression is prominent in the early head ectoderm, from which the lens differentiates. Further, the analysis criteria outlined here represent a filtering scheme that can be used to prioritize genes in future RNA-Seq investigations performed at this stage of ocular lens development.