The process by which information encoded m an organism's DNA is used in the synthesis of functional cell products is known as gene expression. In recent years, sequencing of RNA (RNA-seq) has emerged as the preferred technology for the simultaneous measurement of transcript sequences and their abundance. The analysis of RNA-seq data presents novel challenges and many methods have been developed for the purpose of mapping reads to genomic features and expression quantification. In the first part of my thesis I developed an R based pipeline for pre-processing, expression estimation and data quality assessment of RNA-seq datasets, which formed the basis for my subsequent work on the evolution of gene expression regulation in mammals. Since changes in gene expression levels are thought to underlie many of the phenotypic differences between species, identifying and characterising the regulatory mechanisms responsible for these changes is an important goal of molecular biology. For this, I studied the regulatory divergence of liver gene expression and of isoform usage between mouse strains. I demonstrate that gene expression diverges extensively between the strains and propose that the regulatory mechanism underlying divergent expression between two closely related mammalian species is a combination of variants that arise in cis and in trans. Isoform usage diverges to a lesser extent and appears to display a larger contribution of trans acting regulatory elements to its regulation, suggesting that isoform usage may be under different evolutionary constraints. These observations have important implications for understanding mammalian gene expression divergence and for understanding how speciation occurs.