Transcriptome profiling of Set5 and Set1 methyltransferases: Tools for visualization of gene expression

Abstract

Cells regulate transcription by coordinating the activities of multiple histone modifying complexes. We recently identified the yeast histone H4 methyltransferase Set5 and discovered functional overlap with the histone H3 methyltransferase Set1 in gene expression. Specifically, using next-generation RNA sequencing (RNA-Seq), we found that Set5 and Set1 function synergistically to regulate specific transcriptional programs at subtelomeres and transposable elements. Here we provide a comprehensive description of the methodology and analysis tools corresponding to the data deposited in NCBI's Gene Expression Omnibus (GEO) under the accession number GSE52086. This data complements the experimental methods described in Mas Martín G et al. (2014) and provides the means to explore the cooperative functions of histone H3 and H4 methyltransferases in the regulation of transcription. Furthermore, a fully annotated R code is included to enable researchers to use the following computational tools: comparison of significant differential expression (SDE) profiles; gene ontology enrichment of SDE; and enrichment of SDE relative to chromosomal features, such as centromeres, telomeres, and transposable elements. Overall, we present a bioinformatics platform that can be generally implemented for similar analyses with different datasets and in different organisms.

Keywords

• Set5
• Set1
• Methyltransferase
• Gene expression
• RNA-Seq