To compare gene expression among bovine tissues, large bovine RNA-seq datasets were used, comprising 280 samples from 10 different bovine tissues (uterine endometrium, granulosa cells, theca cells, cervix, embryos, leucocytes, liver, hypothalamus, pituitary, muscle) and generating 260 Gbases of data. Twin approaches were used: an information-theoretic analysis of the existing annotated transcriptome to identify the most tissue-specific genes and a de-novo transcriptome annotation to evaluate general features of the transcription landscape. Expression was detected for 97% of the Ensembl transcriptome with at least one read in one sample and between 28% and 66% at a level of 10 tags per million (TPM) or greater in individual tissues. Over 95% of genes exhibited some level of tissue-specific gene expression. This was mostly due to different levels of expression in different tissues rather than exclusive expression in a single tissue. Less than 1% of annotated genes exhibited a highly restricted tissue-specific expression profile and approximately 2% exhibited classic housekeeping profiles. In conclusion, it is the combined effects of the variable expression of large numbers of genes (73%-93% of the genome) and the specific expression of a small number of genes (<1% of the transcriptome) that contribute to determining the outcome of the function of individual tissues.